WorldWideScience

Sample records for multi-satellite precipitation analysis

  1. Impact of Missing Passive Microwave Sensors on Multi-Satellite Precipitation Retrieval Algorithm

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    Bin Yong

    2015-01-01

    Full Text Available The impact of one or two missing passive microwave (PMW input sensors on the end product of multi-satellite precipitation products is an interesting but obscure issue for both algorithm developers and data users. On 28 January 2013, the Version-7 TRMM Multi-satellite Precipitation Analysis (TMPA products were reproduced and re-released by National Aeronautics and Space Administration (NASA Goddard Space Flight Center because the Advanced Microwave Sounding Unit-B (AMSU-B and the Special Sensor Microwave Imager-Sounder-F16 (SSMIS-F16 input data were unintentionally disregarded in the prior retrieval. Thus, this study investigates the sensitivity of TMPA algorithm results to missing PMW sensors by intercomparing the “early” and “late” Version-7 TMPA real-time (TMPA-RT precipitation estimates (i.e., without and with AMSU-B, SSMIS-F16 sensors with an independent high-density gauge network of 200 tipping-bucket rain gauges over the Chinese Jinghe river basin (45,421 km2. The retrieval counts and retrieval frequency of various PMW and Infrared (IR sensors incorporated into the TMPA system were also analyzed to identify and diagnose the impacts of sensor availability on the TMPA-RT retrieval accuracy. Results show that the incorporation of AMSU-B and SSMIS-F16 has substantially reduced systematic errors. The improvement exhibits rather strong seasonal and topographic dependencies. Our analyses suggest that one or two single PMW sensors might play a key role in affecting the end product of current combined microwave-infrared precipitation estimates. This finding supports algorithm developers’ current endeavor in spatiotemporally incorporating as many PMW sensors as possible in the multi-satellite precipitation retrieval system called Integrated Multi-satellitE Retrievals for Global Precipitation Measurement mission (IMERG. This study also recommends users of satellite precipitation products to switch to the newest Version-7 TMPA datasets and

  2. Satellite-Based Precipitation Datasets

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    Munchak, S. J.; Huffman, G. J.

    2017-12-01

    Of the possible sources of precipitation data, those based on satellites provide the greatest spatial coverage. There is a wide selection of datasets, algorithms, and versions from which to choose, which can be confusing to non-specialists wishing to use the data. The International Precipitation Working Group (IPWG) maintains tables of the major publicly available, long-term, quasi-global precipitation data sets (http://www.isac.cnr.it/ ipwg/data/datasets.html), and this talk briefly reviews the various categories. As examples, NASA provides two sets of quasi-global precipitation data sets: the older Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and current Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG). Both provide near-real-time and post-real-time products that are uniformly gridded in space and time. The TMPA products are 3-hourly 0.25°x0.25° on the latitude band 50°N-S for about 16 years, while the IMERG products are half-hourly 0.1°x0.1° on 60°N-S for over 3 years (with plans to go to 16+ years in Spring 2018). In addition to the precipitation estimates, each data set provides fields of other variables, such as the satellite sensor providing estimates and estimated random error. The discussion concludes with advice about determining suitability for use, the necessity of being clear about product names and versions, and the need for continued support for satellite- and surface-based observation.

  3. Hydrological Utility and Uncertainty of Multi-Satellite Precipitation Products in the Mountainous Region of South Korea

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    Jong Pil Kim

    2016-07-01

    Full Text Available Satellite-derived precipitation can be a potential source of forcing data for assessing water availability and managing water supply in mountainous regions of East Asia. This study investigates the hydrological utility of satellite-derived precipitation and uncertainties attributed to error propagation of satellite products in hydrological modeling. To this end, four satellite precipitation products (tropical rainfall measuring mission (TRMM multi-satellite precipitation analysis (TMPA version 6 (TMPAv6 and version 7 (TMPAv7, the global satellite mapping of precipitation (GSMaP, and the climate prediction center (CPC morphing technique (CMORPH were integrated into a physically-based hydrologic model for the mountainous region of South Korea. The satellite precipitation products displayed different levels of accuracy when compared to the intra- and inter-annual variations of ground-gauged precipitation. As compared to the GSMaP and CMORPH products, superior performances were seen when the TMPA products were used within streamflow simulations. Significant dry (negative biases in the GSMaP and CMORPH products led to large underestimates of streamflow during wet-summer seasons. Although the TMPA products displayed a good level of performance for hydrologic modeling, there were some over/underestimates of precipitation by satellites during the winter season that were induced by snow accumulation and snowmelt processes. These differences resulted in streamflow simulation uncertainties during the winter and spring seasons. This study highlights the crucial need to understand hydrological uncertainties from satellite-derived precipitation for improved water resource management and planning in mountainous basins. Furthermore, it is suggested that a reliable snowfall detection algorithm is necessary for the new global precipitation measurement (GPM mission.

  4. Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

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    Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

    2011-01-01

    In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to

  5. Connecting Satellite-Based Precipitation Estimates to Users

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    Huffman, George J.; Bolvin, David T.; Nelkin, Eric

    2018-01-01

    Beginning in 1997, the Merged Precipitation Group at NASA Goddard has distributed gridded global precipitation products built by combining satellite and surface gauge data. This started with the Global Precipitation Climatology Project (GPCP), then the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), and recently the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG). This 20+-year (and on-going) activity has yielded an important set of insights and lessons learned for making state-of-the-art precipitation data accessible to the diverse communities of users. Merged-data products critically depend on the input sensors and the retrieval algorithms providing accurate, reliable estimates, but it is also important to provide ancillary information that helps users determine suitability for their application. We typically provide fields of estimated random error, and recently reintroduced the quality index concept at user request. Also at user request we have added a (diagnostic) field of estimated precipitation phase. Over time, increasingly more ancillary fields have been introduced for intermediate products that give expert users insight into the detailed performance of the combination algorithm, such as individual merged microwave and microwave-calibrated infrared estimates, the contributing microwave sensor types, and the relative influence of the infrared estimate.

  6. Incorporating Satellite Precipitation Estimates into a Radar-Gauge Multi-Sensor Precipitation Estimation Algorithm

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    Yuxiang He

    2018-01-01

    Full Text Available This paper presents a new and enhanced fusion module for the Multi-Sensor Precipitation Estimator (MPE that would objectively blend real-time satellite quantitative precipitation estimates (SQPE with radar and gauge estimates. This module consists of a preprocessor that mitigates systematic bias in SQPE, and a two-way blending routine that statistically fuses adjusted SQPE with radar estimates. The preprocessor not only corrects systematic bias in SQPE, but also improves the spatial distribution of precipitation based on SQPE and makes it closely resemble that of radar-based observations. It uses a more sophisticated radar-satellite merging technique to blend preprocessed datasets, and provides a better overall QPE product. The performance of the new satellite-radar-gauge blending module is assessed using independent rain gauge data over a five-year period between 2003–2007, and the assessment evaluates the accuracy of newly developed satellite-radar-gauge (SRG blended products versus that of radar-gauge products (which represents MPE algorithm currently used in the NWS (National Weather Service operations over two regions: (I Inside radar effective coverage and (II immediately outside radar coverage. The outcomes of the evaluation indicate (a ingest of SQPE over areas within effective radar coverage improve the quality of QPE by mitigating the errors in radar estimates in region I; and (b blending of radar, gauge, and satellite estimates over region II leads to reduction of errors relative to bias-corrected SQPE. In addition, the new module alleviates the discontinuities along the boundaries of radar effective coverage otherwise seen when SQPE is used directly to fill the areas outside of effective radar coverage.

  7. Assessment of GPM and TRMM Multi-Satellite Precipitation Products in Streamflow Simulations in a Data-Sparse Mountainous Watershed in Myanmar

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    Fei Yuan

    2017-03-01

    Full Text Available Satellite precipitation products from the Global Precipitation Measurement (GPM mission and its predecessor the Tropical Rainfall Measuring Mission (TRMM are a critical data source for hydrological applications in ungauged basins. This study conducted an initial and early evaluation of the performance of the Integrated Multi-satellite Retrievals for GPM (IMERG final run and the TRMM Multi-satellite Precipitation Analysis 3B42V7 precipitation products, and their feasibility in streamflow simulations in the Chindwin River basin, Myanmar, from April 2014 to December 2015 was also assessed. Results show that, although IMERG and 3B42V7 can potentially capture the spatiotemporal patterns of historical precipitation, the two products contain considerable errors. Compared with 3B42V7, no significant improvements were found in IMERG. Moreover, 3B42V7 outperformed IMERG at daily and monthly scales and in heavy rain detections at four out of five gauges. The large errors in IMERG and 3B42V7 distinctly propagated to streamflow simulations via the Xinanjiang hydrological model, with a significant underestimation of total runoff and high flows. The bias correction of the satellite precipitation effectively improved the streamflow simulations. The 3B42V7-based streamflow simulations performed better than the gauge-based simulations. In general, IMERG and 3B42V7 are feasible for use in streamflow simulations in the study area, although 3B42V7 is better suited than IMERG.

  8. Data Analysis of GPM Constellation Satellites-IMERG and ERA-Interim precipitation products over West of Iran

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    Sharifi, Ehsan; Steinacker, Reinhold; Saghafian, Bahram

    2016-04-01

    Precipitation is a critical component of the Earth's hydrological cycle. The primary requirement in precipitation measurement is to know where and how much precipitation is falling at any given time. Especially in data sparse regions with insufficient radar coverage, satellite information can provide a spatial and temporal context. Nonetheless, evaluation of satellite precipitation is essential prior to operational use. This is why many previous studies are devoted to the validation of satellite estimation. Accurate quantitative precipitation estimation over mountainous basins is of great importance because of their susceptibility to hazards. In situ observations over mountainous areas are mostly limited, but currently available satellite precipitation products can potentially provide the precipitation estimation needed for meteorological and hydrological applications. One of the newest and blended methods that use multi-satellites and multi-sensors has been developed for estimating global precipitation. The considered data set known as Integrated Multi-satellitE Retrievals (IMERG) for GPM (Global Precipitation Measurement) is routinely produced by the GPM constellation satellites. Moreover, recent efforts have been put into the improvement of the precipitation products derived from reanalysis systems, which has led to significant progress. One of the best and a worldwide used model is developed by the European Centre for Medium Range Weather Forecasts (ECMWF). They have produced global reanalysis daily precipitation, known as ERA-Interim. This study has evaluated one year of precipitation data from the GPM-IMERG and ERA-Interim reanalysis daily time series over West of Iran. IMERG and ERA-Interim yield underestimate the observed values while IMERG underestimated slightly and performed better when precipitation is greater than 10mm. Furthermore, with respect to evaluation of probability of detection (POD), threat score (TS), false alarm ratio (FAR) and probability

  9. Object-Based Assessment of Satellite Precipitation Products

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    Jingjing Li

    2016-06-01

    Full Text Available An object-based verification approach is employed to assess the performance of the commonly used high-resolution satellite precipitation products: Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, Climate Prediction center MORPHing technique (CMORPH, and Tropical Rainfall Measurement Mission (TRMM Multi-Satellite Precipitation Analysis (TMPA 3B42RT. The evaluation of the satellite precipitation products focuses on the skill of depicting the geometric features of the localized precipitation areas. Seasonal variability of the performances of these products against the ground observations is investigated through the examples of warm and cold seasons. It is found that PERSIANN is capable of depicting the orientation of the localized precipitation areas in both seasons. CMORPH has the ability to capture the sizes of the localized precipitation areas and performs the best in the overall assessment for both seasons. 3B42RT is capable of depicting the location of the precipitation areas for both seasons. In addition, all of the products perform better on capturing the sizes and centroids of precipitation areas in the warm season than in the cold season, while they perform better on depicting the intersection area and orientation in the cold season than in the warm season. These products are more skillful on correctly detecting the localized precipitation areas against the observations in the warm season than in the cold season.

  10. JPSS Preparations at the Satellite Proving Ground for Marine, Precipitation, and Satellite Analysis

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    Folmer, Michael J.; Berndt, E.; Clark, J.; Orrison, A.; Kibler, J.; Sienkiewicz, J.; Nelson, J.; Goldberg, M.; Sjoberg, W.

    2016-01-01

    The ocean prediction center at the national hurricane center's tropical analysis and forecast Branch, the Weather Prediction center and the Satellite analysis branch of NESDIS make up the Satellite Proving Ground for Marine, Precipitation and Satellite Analysis. These centers had early exposure to JPSS products using the S-NPP Satellite that was launched in 2011. Forecasters continue to evaluate new products in anticipation for the launch of JPSS-1 sometime in 2017.

  11. Assessment of satellite-based precipitation estimates over Paraguay

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    Oreggioni Weiberlen, Fiorella; Báez Benítez, Julián

    2018-04-01

    Satellite-based precipitation estimates represent a potential alternative source of input data in a plethora of meteorological and hydrological applications, especially in regions characterized by a low density of rain gauge stations. Paraguay provides a good example of a case where the use of satellite-based precipitation could be advantageous. This study aims to evaluate the version 7 of the Tropical Rainfall Measurement Mission Multi-Satellite Precipitation Analysis (TMPA V7; 3B42 V7) and the version 1.0 of the purely satellite-based product of the Climate Prediction Center Morphing Technique (CMORPH RAW) through their comparison with daily in situ precipitation measurements from 1998 to 2012 over Paraguay. The statistical assessment is conducted with several commonly used indexes. Specifically, to evaluate the accuracy of daily precipitation amounts, mean error (ME), root mean square error (RMSE), BIAS, and coefficient of determination (R 2) are used, and to analyze the capability to correctly detect different precipitation intensities, false alarm ratio (FAR), frequency bias index (FBI), and probability of detection (POD) are applied to various rainfall rates (0, 0.1, 0.5, 1, 2, 5, 10, 20, 40, 60, and 80 mm/day). Results indicate that TMPA V7 has a better performance than CMORPH RAW over Paraguay. TMPA V7 has higher accuracy in the estimation of daily rainfall volumes and greater precision in the detection of wet days (> 0 mm/day). However, both satellite products show a lower ability to appropriately detect high intensity precipitation events.

  12. Precipitation Analysis at Fine Time Scales Using Multiple Satellites: Real-time and Research Products and Applications

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    Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric; Curtis, Scott; Pierce, Harold

    2004-01-01

    Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) in 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25" latitude-longitude resolution over the latitude range from 5O"N-5O0S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, including: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.

  13. Access NASA Satellite Global Precipitation Data Visualization on YouTube

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    Liu, Z.; Su, J.; Acker, J. G.; Huffman, G. J.; Vollmer, B.; Wei, J.; Meyer, D. J.

    2017-12-01

    Since the satellite era began, NASA has collected a large volume of Earth science observations for research and applications around the world. Satellite data at 12 NASA data centers can also be used for STEM activities such as disaster events, climate change, etc. However, accessing satellite data can be a daunting task for non-professional users such as teachers and students because of unfamiliarity of terminology, disciplines, data formats, data structures, computing resources, processing software, programing languages, etc. Over the years, many efforts have been developed to improve satellite data access, but barriers still exist for non-professionals. In this presentation, we will present our latest activity that uses the popular online video sharing web site, YouTube, to access visualization of global precipitation datasets at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC). With YouTube, users can access and visualize a large volume of satellite data without necessity to learn new software or download data. The dataset in this activity is the 3-hourly TRMM (Tropical Rainfall Measuring Mission) Multi-satellite Precipitation Analysis (TMPA). The video consists of over 50,000 data files collected since 1998 onwards, covering a zone between 50°N-S. The YouTube video will last 36 minutes for the entire dataset record (over 19 years). Since the time stamp is on each frame of the video, users can begin at any time by dragging the time progress bar. This precipitation animation will allow viewing precipitation events and processes (e.g., hurricanes, fronts, atmospheric rivers, etc.) on a global scale. The next plan is to develop a similar animation for the GPM (Global Precipitation Measurement) Integrated Multi-satellitE Retrievals for GPM (IMERG). The IMERG provides precipitation on a near-global (60°N-S) coverage at half-hourly time interval, showing more details on precipitation processes and development, compared to the 3

  14. Precipitation Characteristics in West and East Africa from Satellite and in Situ Observations

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    Dezfuli, Amin K.; Ichoku, Charles M.; Mohr, Karen I.; Huffman, George J.

    2017-01-01

    Using in situ data, three precipitation classes are identified for rainy seasons of West and East Africa: weak convective rainfall (WCR), strong convective rainfall (SCR), and mesoscale convective systems (MCSs).Nearly 75% of the total seasonal precipitation is produced by the SCR and MCSs, even though they represent only 8% of the rain events. Rain events in East Africa tend to have a longer duration and lower intensity than in West Africa, reflecting different characteristics of the SCR and MCS events in these two regions. Surface heating seems to be the primary convection trigger for the SCR, particularly in East Africa, whereas the WCR requires a dynamical trigger such as low-level convergence. The data are used to evaluate the performance of the recently launched Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG)project. The IMERG-based precipitation shows significant improvement over its predecessor, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), particularly in capturing the MCSs, due to its improved temporal resolution.

  15. Assessment of global precipitation measurement satellite products over Saudi Arabia

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    Mahmoud, Mohammed T.; Al-Zahrani, Muhammad A.; Sharif, Hatim O.

    2018-04-01

    Most hydrological analysis and modeling studies require reliable and accurate precipitation data for successful simulations. However, precipitation measurements should be more representative of the true precipitation distribution. Many approaches and techniques are used to collect precipitation data. Recently, hydrometeorological and climatological applications of satellite precipitation products have experienced a significant improvement with the emergence of the latest satellite products, namely, the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) products, which can be utilized to estimate and analyze precipitation data. This study focuses on the validation of the IMERG early, late and final run rainfall products using ground-based rain gauge observations throughout Saudi Arabia for the period from October 2015 to April 2016. The accuracy of each IMERG product is assessed using six statistical performance measures to conduct three main evaluations, namely, regional, event-based and station-based evaluations. The results indicate that the early run product performed well in the middle and eastern parts as well as some of the western parts of the country; meanwhile, the satellite estimates for the other parts fluctuated between an overestimation and an underestimation. The late run product showed an improved accuracy over the southern and western parts; however, over the northern and middle parts, it showed relatively high errors. The final run product revealed significantly improved precipitation estimations and successfully obtained higher accuracies over most parts of the country. This study provides an early assessment of the performance of the GPM satellite products over the Middle East. The study findings can be used as a beneficial reference for the future development of the IMERG algorithms.

  16. Evaluation of Satellite and Model Precipitation Products Over Turkey

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    Yilmaz, M. T.; Amjad, M.

    2017-12-01

    Satellite-based remote sensing, gauge stations, and models are the three major platforms to acquire precipitation dataset. Among them satellites and models have the advantage of retrieving spatially and temporally continuous and consistent datasets, while the uncertainty estimates of these retrievals are often required for many hydrological studies to understand the source and the magnitude of the uncertainty in hydrological response parameters. In this study, satellite and model precipitation data products are validated over various temporal scales (daily, 3-daily, 7-daily, 10-daily and monthly) using in-situ measured precipitation observations from a network of 733 gauges from all over the Turkey. Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 version 7 and European Center of Medium-Range Weather Forecast (ECMWF) model estimates (daily, 3-daily, 7-daily and 10-daily accumulated forecast) are used in this study. Retrievals are evaluated for their mean and standard deviation and their accuracies are evaluated via bias, root mean square error, error standard deviation and correlation coefficient statistics. Intensity vs frequency analysis and some contingency table statistics like percent correct, probability of detection, false alarm ratio and critical success index are determined using daily time-series. Both ECMWF forecasts and TRMM observations, on average, overestimate the precipitation compared to gauge estimates; wet biases are 10.26 mm/month and 8.65 mm/month, respectively for ECMWF and TRMM. RMSE values of ECMWF forecasts and TRMM estimates are 39.69 mm/month and 41.55 mm/month, respectively. Monthly correlations between Gauges-ECMWF, Gauges-TRMM and ECMWF-TRMM are 0.76, 0.73 and 0.81, respectively. The model and the satellite error statistics are further compared against the gauges error statistics based on inverse distance weighting (IWD) analysis. Both the model and satellite data have less IWD errors (14

  17. Precipitation Analysis at Fine Time Scales using TRMM and Other Satellites: Realtime and Research Products and Applications

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    Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric; Curtis, Scott; Pierce, Harold; Gu, Guojon

    2004-01-01

    Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the TRMM Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) by the end of 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25 deg latitude-longitude resolution over the latitude range from 50 deg N-50 deg S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, including: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.

  18. Early Examples from the Integrated Multi-Satellite Retrievals for GPM (IMERG)

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    Huffman, George; Bolvin, David; Braithwaite, Daniel; Hsu, Kuolin; Joyce, Robert; Kidd, Christopher; Sorooshian, Soroosh; Xie, Pingping

    2014-05-01

    The U.S. GPM Science Team's Day-1 algorithm for computing combined precipitation estimates as part of GPM is the Integrated Multi-satellitE Retrievals for GPM (IMERG). The goal is to compute the best time series of (nearly) global precipitation from "all" precipitation-relevant satellites and global surface precipitation gauge analyses. IMERG is being developed as a unified U.S. algorithm drawing on strengths in the three contributing groups, whose previous work includes: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA); 2) the CPC Morphing algorithm with Kalman Filtering (K-CMORPH); and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS). We review the IMERG design and development, plans for testing, and current status. Some of the lessons learned in running and reprocessing the previous data sets include the importance of quality-controlling input data sets, strategies for coping with transitions in the various input data sets, and practical approaches to retrospective analysis of multiple output products (namely the real- and post-real-time data streams). IMERG output will be illustrated using early test data, including the variety of supporting fields, such as the merged-microwave and infrared estimates, and the precipitation type. We end by considering recent changes in input data specifications, the transition from TRMM-based calibration to GPM-based, and further "Day 2" development.

  19. Evaluation of the Performance of Three Satellite Precipitation Products over Africa

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    Aleix Serrat-Capdevila

    2016-10-01

    Full Text Available We present an evaluation of daily estimates from three near real-time quasi-global Satellite Precipitation Products—Tropical Rainfall Measuring Mission (TRMM Multi-satellite Precipitation Analysis (TMPA, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, and Climate Prediction Center (CPC Morphing Technique (CMORPH—over the African continent, using the Global Precipitation Climatology Project one Degree Day (GPCP-1dd as a reference dataset for years 2001 to 2013. Different types of errors are characterized for each season as a function of spatial classifications (latitudinal bands, climatic zones and topography and in relationship with the main rain-producing mechanisms in the continent: the Intertropical Convergence Zone (ITCZ and the East African Monsoon. A bias correction of the satellite estimates is applied using a probability density function (pdf matching approach, with a bias analysis as a function of rain intensity, season and latitude. The effects of bias correction on different error terms are analyzed, showing an almost elimination of the mean and variance terms in most of the cases. While raw estimates of TMPA show higher efficiency, all products have similar efficiencies after bias correction. PERSIANN consistently shows the smallest median errors when it correctly detects precipitation events. The areas with smallest relative errors and other performance measures follow the position of the ITCZ oscillating seasonally over the equator, illustrating the close relationship between satellite estimates and rainfall regime.

  20. Inter-Comparison of High-Resolution Satellite Precipitation Products over Central Asia

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    Hao Guo

    2015-06-01

    Full Text Available This paper examines the spatial error structures of eight precipitation estimates derived from four different satellite retrieval algorithms including TRMM Multi-satellite Precipitation Analysis (TMPA, Climate Prediction Center morphing technique (CMORPH, Global Satellite Mapping of Precipitation (GSMaP and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN. All the original satellite and bias-corrected products of each algorithm (3B42RTV7 and 3B42V7, CMORPH_RAW and CMORPH_CRT, GSMaP_MVK and GSMaP_Gauge, PERSIANN_RAW and PERSIANN_CDR are evaluated against ground-based Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE over Central Asia for the period of 2004 to 2006. The analyses show that all products except PERSIANN exhibit overestimation over Aral Sea and its surrounding areas. The bias-correction improves the quality of the original satellite TMPA products and GSMaP significantly but slightly in CMORPH and PERSIANN over Central Asia. 3B42RTV7 overestimates precipitation significantly with large Relative Bias (RB (128.17% while GSMaP_Gauge shows consistent high correlation coefficient (CC (>0.8 but RB fluctuates between −57.95% and 112.63%. The PERSIANN_CDR outperforms other products in winter with the highest CC (0.67. Both the satellite-only and gauge adjusted products have particularly poor performance in detecting rainfall events in terms of lower POD (less than 65%, CSI (less than 45% and relatively high FAR (more than 35%.

  1. Evaluation of Version-7 TRMM Multi-Satellite Precipitation Analysis Product during the Beijing Extreme Heavy Rainfall Event of 21 July 2012

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    Yong Huang

    2013-12-01

    Full Text Available The latest Version-7 (V7 Tropical Rainfall Measuring Mission (TRMM Multi-satellite Precipitation Analysis (TMPA products were released by the National Aeronautics and Space Administration (NASA in December of 2012. Their performance on different climatology, locations, and precipitation types is of great interest to the satellite-based precipitation community. This paper presents a study of TMPA precipitation products (3B42RT and 3B42V7 for an extreme precipitation event in Beijing and its adjacent regions (from 00:00 UTC 21 July 2012 to 00:00 UTC 22 July 2012. Measurements from a dense rain gauge network were used as the ground truth to evaluate the latest TMPA products. Results are summarized as follows. Compared to rain gauge measurements, both 3B42RT and 3B42V7 generally captured the rainfall spatial and temporal pattern, having a moderate spatial correlation coefficient (CC, 0.6 and high CC values (0.88 over the broader Hebei, Beijing and Tianjin (HBT regions, but the rainfall peak is 6 h ahead of gauge observations. Overall, 3B42RT showed higher estimation than 3B42V7 over both HBT and Beijing. At the storm center, both 3B42RT and 3B42V7 presented a relatively large deviation from the temporal variation of rainfall and underestimated the storm by 29.02% and 36.07%, respectively. The current study suggests that the latest TMPA products still have limitations in terms of resolution and accuracy, especially for this type of extreme event within a latitude area on the edge of coverage of TRMM precipitation radar and microwave imager. Therefore, TMPA users should be cautious when 3B42RT and 3B42V7 are used to model, monitor, and forecast both flooding hazards in the Beijing urban area and landslides in the mountainous west and north of Beijing.

  2. Error Analysis of Satellite Precipitation-Driven Modeling of Flood Events in Complex Alpine Terrain

    Directory of Open Access Journals (Sweden)

    Yiwen Mei

    2016-03-01

    Full Text Available The error in satellite precipitation-driven complex terrain flood simulations is characterized in this study for eight different global satellite products and 128 flood events over the Eastern Italian Alps. The flood events are grouped according to two flood types: rain floods and flash floods. The satellite precipitation products and runoff simulations are evaluated based on systematic and random error metrics applied on the matched event pairs and basin-scale event properties (i.e., rainfall and runoff cumulative depth and time series shape. Overall, error characteristics exhibit dependency on the flood type. Generally, timing of the event precipitation mass center and dispersion of the time series derived from satellite precipitation exhibits good agreement with the reference; the cumulative depth is mostly underestimated. The study shows a dampening effect in both systematic and random error components of the satellite-driven hydrograph relative to the satellite-retrieved hyetograph. The systematic error in shape of the time series shows a significant dampening effect. The random error dampening effect is less pronounced for the flash flood events and the rain flood events with a high runoff coefficient. This event-based analysis of the satellite precipitation error propagation in flood modeling sheds light on the application of satellite precipitation in mountain flood hydrology.

  3. Statistical assessment and hydrological utility of the latest multi-satellite precipitation analysis IMERG in Ganjiang River basin

    Science.gov (United States)

    Li, Na; Tang, Guoqiang; Zhao, Ping; Hong, Yang; Gou, Yabin; Yang, Kai

    2017-01-01

    This study aims to statistically and hydrologically assess the hydrological utility of the latest Integrated Multi-satellitE Retrievals from Global Precipitation Measurement (IMERG) multi-satellite constellation over the mid-latitude Ganjiang River basin in China. The investigations are conducted at hourly and 0.1° resolutions throughout the rainy season from March 12 to September 30, 2014. Two high-quality quantitative precipitation estimation (QPE) datasets, i.e., a gauge-corrected radar mosaic QPE product (RQPE) and a highly dense network of 1200 rain gauges, are used as the reference. For the implementation of the study, first, we compare IMERG product and RQPE with rain gauge-interpolated data, respectively. The results indicate that both remote sensing products can estimate precipitation fairly well over the basin, while RQPE significantly outperforms IMERG product in almost all the studied cases. The correlation coefficients of RQPE (CC = 0.98 and CC = 0.67) are much higher than those of IMERG product (CC = 0.80 and CC = 0.33) at basin and grid scales, respectively. Then, the hydrological assessment is conducted with the Coupled Routing and Excess Storage (CREST) model under multiple parameterization scenarios, in which the model is calibrated using the rain gauge-interpolated data, RQPE, and IMERG products respectively. During the calibration period (from March 12 to May 31), the simulated streamflow based on rain gauge-interpolated data shows the highest Nash-Sutcliffe coefficient efficiency (NSCE) value (0.92), closely followed by the RQPE (NSCE = 0.84), while IMERG product performs barely acceptable (NSCE = 0.56). During the validation period (from June 1 to September 30), the three rainfall datasets are used to force the CREST model based on all the three calibrated parameter sets (i.e., nine combinations in total). RQPE outperforms rain gauge-interpolated data and IMERG product in all validation scenarios, possibly due to its advantageous capability

  4. Performance evaluation of latest integrated multi-satellite retrievals for Global Precipitation Measurement (IMERG) over the northern highlands of Pakistan

    Science.gov (United States)

    Anjum, Muhammad Naveed; Ding, Yongjian; Shangguan, Donghui; Ahmad, Ijaz; Ijaz, Muhammad Wajid; Farid, Hafiz Umar; Yagoub, Yousif Elnour; Zaman, Muhammad; Adnan, Muhammad

    2018-06-01

    Recently, the Global Precipitation Measurement (GPM) mission has released the Integrated Multi-satellite Retrievals for GPM (IMERG) at a fine spatial (0.1° × 0.1°) and temporal (half hourly) resolutions. A comprehensive evaluation of this newly launched precipitation product is very important for satellite-based precipitation data users as well as for algorithm developers. The objective of this study was to provide a preliminary and timely performance evaluation of the IMERG product over the northern high lands of Pakistan. For comparison reference, the real-time and post real-time Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) products were also evaluated parallel to the IMERG. All of the selected precipitation products were evaluated at annual, monthly, seasonal and daily time scales using reference gauges data from April 2014 to December 2016. The results showed that: (1) the precipitation estimates from IMERG, 3B42V7 and 3B42RT products correlated well with the reference gauges observations at monthly time scale (CC = 0.93, 0.91, 0.88, respectively), whereas moderately at the daily time scale (CC = 0.67, 0.61, and 0.58, respectively); (2) Compared to the 3B42V7 and 3B42RT, the precipitation estimates from IMERG were more reliable in all seasons particularly in the winter season with lowest relative bias (2.61%) and highest CC (0.87); (3) IMERG showed a clear superiority over 3B42V7 and 3B42RT products in order to capture spatial distribution of precipitation over the northern Pakistan; (4) Relative to the 3B42V7 and 3B42RT, daily precipitation estimates from IMEREG showed lowest relative bias (9.20% vs. 21.40% and 26.10%, respectively) and RMSE (2.05 mm/day vs. 2.49 mm/day and 2.88 mm/day, respectively); and (5) Light precipitation events (0-1 mm/day) were usually overestimated by all said satellite-based precipitation products. In contrast moderate (1-20 mm/day) to heavy (>20 mm/day) precipitation events were

  5. Precipitation Analysis at Fine Time Scales using TRMM and Other Satellites: Real-time and Research Products and Applications

    Science.gov (United States)

    Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric; Curtis, Scott; Pierce, Harold; Gu, Guo-Jon

    2004-01-01

    Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the TRMM Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) by the end of 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25" latitude-longitude resolution over the latitude range from 5O0N-50"S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, includmg: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.

  6. Evaluation of the Potential of NASA Multi-satellite Precipitation Analysis in Global Landslide Hazard Assessment

    Science.gov (United States)

    Hong, Yang; Adler, Robert F.; Huffman, George J.

    2007-01-01

    Landslides are one of the most widespread natural hazards on Earth, responsible for thousands of deaths and billions of dollars in property damage every year. In the U.S. alone landslides occur in every state, causing an estimated $2 billion in damage and 25- 50 deaths each year. Annual average loss of life from landslide hazards in Japan is 170. The situation is much worse in developing countries and remote mountainous regions due to lack of financial resources and inadequate disaster management ability. Recently, a landslide buried an entire village on the Philippines Island of Leyte on Feb 17,2006, with at least 1800 reported deaths and only 3 houses left standing of the original 300. Intense storms with high-intensity , long-duration rainfall have great potential to trigger rapidly moving landslides, resulting in casualties and property damage across the world. In recent years, through the availability of remotely sensed datasets, it has become possible to conduct global-scale landslide hazard assessment. This paper evaluates the potential of the real-time NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA) system to advance our understanding of and predictive ability for rainfall-triggered landslides. Early results show that the landslide occurrences are closely associated with the spatial patterns and temporal distribution of rainfall characteristics. Particularly, the number of landslide occurrences and the relative importance of rainfall in triggering landslides rely on the influence of rainfall attributes [e.g. rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms). TMPA precipitation data are available in both real-time and post-real-time versions, which are useful to assess the location and timing of rainfall-triggered landslide hazards by monitoring landslide-prone areas while receiving heavy rainfall. For the purpose of identifying rainfall-triggered landslides, an empirical global rainfall intensity

  7. Topography and Data Mining Based Methods for Improving Satellite Precipitation in Mountainous Areas of China

    Directory of Open Access Journals (Sweden)

    Ting Xia

    2015-07-01

    Full Text Available Topography is a significant factor influencing the spatial distribution of precipitation. This study developed a new methodology to evaluate and calibrate the Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA products by merging geographic and topographic information. In the proposed method, firstly, the consistency rule was introduced to evaluate the fitness of satellite rainfall with measurements on the grids with and without ground gauges. Secondly, in order to improve the consistency rate of satellite rainfall, genetic programming was introduced to mine the relationship between the gauge rainfall and location, elevation and TMPA rainfall. The proof experiment and analysis for the mean annual satellite precipitation from 2001–2012, 3B43 (V7 of TMPA rainfall product, was carried out in eight mountainous areas of China. The result shows that the proposed method is significant and efficient both for the assessment and improvement of satellite precipitation. It is found that the satellite rainfall consistency rates in the gauged and ungauged grids are different in the study area. In addition, the mined correlation of location-elevation-TMPA rainfall can noticeably improve the satellite precipitation, both in the context of the new criterion of the consistency rate and the existing criteria such as Bias and RMSD. The proposed method is also efficient for correcting the monthly and mean monthly rainfall of 3B43 and 3B42RT.

  8. Preparing Precipitation Data Access, Value-added Services and Scientific Exploration Tools for the Integrated Multi-satellitE Retrievals for GPM (IMERG)

    Science.gov (United States)

    Ostrenga, D.; Liu, Z.; Kempler, S. J.; Vollmer, B.; Teng, W. L.

    2013-12-01

    The Precipitation Data and Information Services Center (PDISC) (http://disc.gsfc.nasa.gov/precipitation or google: NASA PDISC), located at the NASA Goddard Space Flight Center (GSFC) Earth Sciences (GES) Data and Information Services Center (DISC), is home of the Tropical Rainfall Measuring Mission (TRMM) data archive. For over 15 years, the GES DISC has served not only TRMM, but also other space-based, airborne-based, field campaign and ground-based precipitation data products to the precipitation community and other disciplinary communities as well. The TRMM Multi-Satellite Precipitation Analysis (TMPA) products are the most popular products in the TRMM product family in terms of data download and access through Mirador, the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) and other services. The next generation of TMPA, the Integrated Multi-satellitE Retrievals for GPM (IMERG) to be released in 2014 after the launch of GPM, will be significantly improved in terms of spatial and temporal resolutions. To better serve the user community, we are preparing data services and samples are listed below. To enable scientific exploration of Earth science data products without going through complicated and often time consuming processes, such as data downloading, data processing, etc., the GES DISC has developed Giovanni in consultation with members of the user community, requesting quick search, subset, analysis and display capabilities for their specific data of interest. For example, the TRMM Online Visualization and Analysis System (TOVAS, http://disc2.nascom.nasa.gov/Giovanni/tovas/) has proven extremely popular, especially as additional datasets have been added upon request. Giovanni will continue to evolve to accommodate GPM data and the multi-sensor data inter-comparisons that will be sure to follow. Additional PDISC tool and service capabilities being adapted for GPM data include: An on-line PDISC Portal (includes user guide, etc

  9. An Innovative Metric to Evaluate Satellite Precipitation's Spatial Distribution

    Science.gov (United States)

    Liu, H.; Chu, W.; Gao, X.; Sorooshian, S.

    2011-12-01

    Thanks to its capability to cover the mountains, where ground measurement instruments cannot reach, satellites provide a good means of estimating precipitation over mountainous regions. In regions with complex terrains, accurate information on high-resolution spatial distribution of precipitation is critical for many important issues, such as flood/landslide warning, reservoir operation, water system planning, etc. Therefore, in order to be useful in many practical applications, satellite precipitation products should possess high quality in characterizing spatial distribution. However, most existing validation metrics, which are based on point/grid comparison using simple statistics, cannot effectively measure satellite's skill of capturing the spatial patterns of precipitation fields. This deficiency results from the fact that point/grid-wised comparison does not take into account of the spatial coherence of precipitation fields. Furth more, another weakness of many metrics is that they can barely provide information on why satellite products perform well or poor. Motivated by our recent findings of the consistent spatial patterns of the precipitation field over the western U.S., we developed a new metric utilizing EOF analysis and Shannon entropy. The metric can be derived through two steps: 1) capture the dominant spatial patterns of precipitation fields from both satellite products and reference data through EOF analysis, and 2) compute the similarities between the corresponding dominant patterns using mutual information measurement defined with Shannon entropy. Instead of individual point/grid, the new metric treat the entire precipitation field simultaneously, naturally taking advantage of spatial dependence. Since the dominant spatial patterns are shaped by physical processes, the new metric can shed light on why satellite product can or cannot capture the spatial patterns. For demonstration, a experiment was carried out to evaluate a satellite

  10. Performance Assessment of Multi-Source Weighted-Ensemble Precipitation (MSWEP Product over India

    Directory of Open Access Journals (Sweden)

    Akhilesh S. Nair

    2017-01-01

    Full Text Available Error characterization is vital for the advancement of precipitation algorithms, the evaluation of numerical model outputs, and their integration in various hydro-meteorological applications. The Tropical Rainfall Measuring Mission (TRMM Multi-satellite Precipitation Analysis (TMPA has been a benchmark for successive Global Precipitation Measurement (GPM based products. This has given way to the evolution of many multi-satellite precipitation products. This study evaluates the performance of the newly released multi-satellite Multi-Source Weighted-Ensemble Precipitation (MSWEP product, whose temporal variability was determined based on several data products including TMPA 3B42 RT. The evaluation was conducted over India with respect to the IMD-gauge-based rainfall for pre-monsoon, monsoon, and post monsoon seasons at daily scale for a 35-year (1979–2013 period. The rainfall climatology is examined over India and over four geographical extents within India known to be subject to uniform rainfall. The performance evaluation of rainfall time series was carried out. In addition to this, the performance of the product over different rainfall classes was evaluated along with the contribution of each class to the total rainfall. Further, seasonal evaluation of the MSWEP products was based on the categorical and volumetric indices from the contingency table. Upon evaluation it was observed that the MSWEP products show large errors in detecting the higher quantiles of rainfall (>75th and > 95th quantiles. The MSWEP precipitation product available at a 0.25° × 0.25° spatial resolution and daily temporal resolution matched well with the daily IMD rainfall over India. Overall results suggest that a suitable region and season-dependent bias correction is essential before its integration in hydrological applications. While the MSWEP was observed to perform well for daily rainfall, it suffered from poor detection capabilities for higher quantiles, making

  11. JPSS Preparations at the Satellite Proving Ground for Marine, Precipitation, and Satellite Analysis

    Science.gov (United States)

    Folmer, M. J.; Berndt, E.; Clark, J.; Orrison, A.; Kibler, J.; Sienkiewicz, J. M.; Nelson, J. A., Jr.; Goldberg, M.

    2016-12-01

    The National Oceanic and Atmospheric Administration (NOAA) Satellite Proving Ground (PG) for Marine, Precipitation, and Satellite Analysis (MPS) has been demonstrating and evaluating Suomi National Polar-orbiting Partnership (S-NPP) products along with other polar-orbiting satellite platforms in preparation for the Joint Polar Satellite System - 1 (JPSS-1) launch in March 2017. The first S-NPP imagery was made available to the MPS PG during the evolution of Hurricane Sandy in October 2012 and has since been popular in operations. Since this event the MPS PG Satellite Liaison has been working with forecasters on ways to integrate single-channel and multispectral imagery from the Visible Infrared Imaging Radiometer Suite (VIIRS), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Advanced Very High Resolution Radiometer (AVHRR)into operations to complement numerical weather prediction and geostationary satellite savvy National Weather Service (NWS) National Centers. Additional unique products have been introduced to operations to address specific forecast challenges, including the Cooperative Institute for Research in the Atmosphere (CIRA) Layered Precipitable Water, the National Environmental Satellite, Data, and Information Service (NESDIS) Snowfall Rate product, NOAA Unique Combined Atmospheric Processing System (NUCAPS) Soundings, ozone products from the Atmospheric Infrared Sounder (AIRS), Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS), and Infrared Atmospheric Sounding Interferometer (IASI). In addition, new satellite domains have been created to provide forecasters at the NWS Ocean Prediction Center and Weather Prediction Center with better quality imagery at high latitudes. This has led to research projects that are addressing forecast challenges such as tropical to extratropical transition and explosive cyclogenesis. This presentation will provide examples of how the MPS PG has been introducing and integrating

  12. Precipitation characteristics in tropical Africa using satellite and in situ observations

    Science.gov (United States)

    Dezfuli, A. K.; Ichoku, I.; Huffman, G. J.; Mohr, K. I.

    2017-12-01

    Tropical Africa receives nearly all its precipitation as a result of convection. The characteristics of rain-producing systems in this region have not been well-understood, despite their crucial role in regional and global circulation. This is mainly due to the lack of in situ observations. Here, we have used precipitation records from the Trans-African Hydro-Meteorological Observatory (TAHMO) ground-based gauge network to improve our knowledge about the rainfall systems in the region, and to validate the recently-released IMERG precipitation product based on satellite observations from the Global Precipitation Measurement (GPM) constellation. The high temporal resolution of the gauge data has allowed us to identify three classes of rain events based on their duration and intensity. The contribution of each class to the total rainfall and the favorable surface atmospheric conditions for each class have been examined. As IMERG aims to continue the legacy of its predecessor, TRMM Multi-Satellite Precipitation Analysis (TMPA), and provide higher resolution data, continent-wide comparisons are made between these two products. Due to its improved temporal resolution, IMERG shows some advantages over TMPA in capturing the diurnal cycle and propagation of the meso-scale convective systems. However, the performance of the two satellite-based products varies by season, region and the evaluation statistics. The results of this study serve as a basis for our ongoing work on the impacts of biomass burning on precipitation processes in Africa.

  13. Evaluation of satellite-retrieved extreme precipitation using gauge observations

    Science.gov (United States)

    Lockhoff, M.; Zolina, O.; Simmer, C.; Schulz, J.

    2012-04-01

    Precipitation extremes have already been intensively studied employing rain gauge datasets. Their main advantage is that they represent a direct measurement with a relatively high temporal coverage. Their main limitation however is their poor spatial coverage and thus a low representativeness in many parts of the world. In contrast, satellites can provide global coverage and there are meanwhile data sets available that are on one hand long enough to be used for extreme value analysis and that have on the other hand the necessary spatial and temporal resolution to capture extremes. However, satellite observations provide only an indirect mean to determine precipitation and there are many potential observational and methodological weaknesses in particular over land surfaces that may constitute doubts concerning their usability for the analysis of precipitation extremes. By comparing basic climatological metrics of precipitation (totals, intensities, number of wet days) as well as respective characteristics of PDFs, absolute and relative extremes of satellite and observational data this paper aims at assessing to which extent satellite products are suitable for analysing extreme precipitation events. In a first step the assessment focuses on Europe taking into consideration various satellite products available, e.g. data sets provided by the Global Precipitation Climatology Project (GPCP). First results indicate that satellite-based estimates do not only represent the monthly averaged precipitation very similar to rain gauge estimates but they also capture the day-to-day occurrence fairly well. Larger differences can be found though when looking at the corresponding intensities.

  14. Characterization of precipitation features over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.

    2013-12-01

    We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, surface observations, and models to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets of TMPA 3B42, CMORPH, and PERSIANN. The satellite based QPEs are compared over the concurrent period with the NCEP Stage IV product, which is a near real time product providing precipitation data at the hourly temporal scale gridded at a nominal 4-km spatial resolution. In addition, remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model), which provides gridded precipitation estimates that are used as a baseline for multi-sensor QPE products comparison. The comparisons are performed at the annual, seasonal, monthly, and daily scales with focus on selected river basins (Southeastern US, Pacific Northwest, Great Plains). While, unconditional annual rain rates present a satisfying agreement between all products, results suggest that satellite QPE datasets exhibit important biases in particular at higher rain rates (≥4 mm/day). Conversely, on seasonal scales differences between remotely sensed data and ground surface observations can be greater than 50% and up to 90% for low daily accumulation (≤1 mm/day) such as in the Western US (summer) and Central US (winter). The conditional analysis performed using different daily rainfall accumulation thresholds (from low rainfall intensity to intense precipitation) shows that while intense events measured at the ground are infrequent (around 2% for daily accumulation above 2 inches/day), remotely sensed products displayed differences from 20-50% and up to 90-100%. A discussion on the impact of differing spatial and temporal resolutions with respect to the datasets ability to capture extreme

  15. Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile

    Science.gov (United States)

    Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye; Lillo-Saavedra, Mario; Lagos, Octavio

    2017-04-01

    Precipitation is a key parameter for the study of climate change and variability and the detection and monitoring of natural disaster such as drought. Precipitation datasets that accurately capture the amount and spatial variability of rainfall is critical for drought monitoring and a wide range of other climate applications. This is challenging in many parts of the world, which often have a limited number of weather stations and/or historical data records. Satellite-derived precipitation products offer a viable alternative with several remotely sensed precipitation datasets now available with long historical data records (+30years), which include the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) datasets. This study presents a comparative analysis of three historical satellite-based precipitation datasets that include Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B43 version 7 (1998-2015), PERSIANN-CDR (1983-2015) and CHIRPS 2.0 (1981-2015) over Chile to assess their performance across the country and for the case of the two long-term products the applicability for agricultural drought were evaluated when used in the calculation of commonly used drought indicator as the Standardized Precipitation Index (SPI). In this analysis, 278 weather stations of in situ rainfall measurements across Chile were initially compared to the satellite data. The study area (Chile) was divided into five latitudinal zones: North, North-Central, Central, South-Central and South to determine if there were a regional difference among these satellite products, and nine statistics were used to evaluate their performance to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to analyze

  16. Understanding the Driver of Energetic Electron Precipitation Using Coordinated Multi-Satellite Measurements

    Science.gov (United States)

    Capannolo, L.; Li, W.; Ma, Q.

    2017-12-01

    Electron precipitation into the upper atmosphere is one of the important loss mechanisms in the Earth's inner magnetosphere. Various magnetospheric plasma waves (i.e., chorus, plasmaspheric hiss, electromagnetic ion cyclotron waves, etc.) play an important role in scattering energetic electrons into the loss cone, thus enhance ionization in the upper atmosphere and affect ring current and radiation belt dynamics. The present study evaluates conjunction events where low-earth-orbiting satellites (twin AeroCube-6) and near-equatorial satellites (twin Van Allen Probes) are located roughly along the same magnetic field line. By analyzing electron flux variation at various energies (> 35 keV) measured by AeroCube-6 and wave and electron measurements by Van Allen Probes, together with quasilinear diffusion theory and modeling, we determine the physical process of driving the observed energetic electron precipitation for the identified electron precipitation events. Moreover, the twin AeroCube-6 also helps us understand the spatiotemporal effect and constrain the coherent size of each electron precipitation event.

  17. Beyond reliability, multi-state failure analysis of satellite subsystems: A statistical approach

    International Nuclear Information System (INIS)

    Castet, Jean-Francois; Saleh, Joseph H.

    2010-01-01

    Reliability is widely recognized as a critical design attribute for space systems. In recent articles, we conducted nonparametric analyses and Weibull fits of satellite and satellite subsystems reliability for 1584 Earth-orbiting satellites launched between January 1990 and October 2008. In this paper, we extend our investigation of failures of satellites and satellite subsystems beyond the binary concept of reliability to the analysis of their anomalies and multi-state failures. In reliability analysis, the system or subsystem under study is considered to be either in an operational or failed state; multi-state failure analysis introduces 'degraded states' or partial failures, and thus provides more insights through finer resolution into the degradation behavior of an item and its progression towards complete failure. The database used for the statistical analysis in the present work identifies five states for each satellite subsystem: three degraded states, one fully operational state, and one failed state (complete failure). Because our dataset is right-censored, we calculate the nonparametric probability of transitioning between states for each satellite subsystem with the Kaplan-Meier estimator, and we derive confidence intervals for each probability of transitioning between states. We then conduct parametric Weibull fits of these probabilities using the Maximum Likelihood Estimation (MLE) approach. After validating the results, we compare the reliability versus multi-state failure analyses of three satellite subsystems: the thruster/fuel; the telemetry, tracking, and control (TTC); and the gyro/sensor/reaction wheel subsystems. The results are particularly revealing of the insights that can be gleaned from multi-state failure analysis and the deficiencies, or blind spots, of the traditional reliability analysis. In addition to the specific results provided here, which should prove particularly useful to the space industry, this work highlights the importance

  18. Evaluation of Integrated Multi-satellitE Retrievals for GPM with All Weather Gauge Observations over CONUS

    Science.gov (United States)

    Chen, S.; Qi, Y.; Hu, B.; Hu, J.; Hong, Y.

    2015-12-01

    The Global Precipitation Measurement (GPM) mission is composed of an international network of satellites that provide the next-generation global observations of rain and snow. Integrated Multi-satellitE Retrievals for GPM (IMERG) is the state-of-art precipitation products with high spatio-temporal resolution of 0.1°/30min. IMERG unifies precipitation measurements from a constellation of research and operational satellites with the core sensors dual-frequency precipitation radar (DPR) and microwave imager (GMI) on board a "Core" satellite. Additionally, IMERG blends the advantages of currently most popular satellite-based quantitative precipitation estimates (QPE) algorithms, i.e. TRMM Multi-satellite Precipitation Analysis (TMPA), Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS). The real-time and post real-time IMERG products are now available online at https://stormpps.gsfc.nasa.gov/storm. In this study, the final run post real-time IMERG is evaluated with all-weather manual gauge observations over CONUS from June 2014 through May 2015. Relative Bias (RB), Root-Mean-Squared Error (RMSE), Correlation Coefficient (CC), Probability Of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) are used to quantify the performance of IMERG. The performance of IMERG in estimating snowfall precipitation is highlighted in the study. This timely evaluation with all-weather gauge observations is expected to offer insights into performance of IMERG and thus provide useful feedback to the algorithm developers as well as the GPM data users.

  19. Satellite precipitation estimation over the Tibetan Plateau

    Science.gov (United States)

    Porcu, F.; Gjoka, U.

    2012-04-01

    Precipitation characteristics over the Tibetan Plateau are very little known, given the scarcity of reliable and widely distributed ground observation, thus the satellite approach is a valuable choice for large scale precipitation analysis and hydrological cycle studies. However,the satellite perspective undergoes various shortcomings at the different wavelengths used in atmospheric remote sensing. In the microwave spectrum often the high soil emissivity masks or hides the atmospheric signal upwelling from light-moderate precipitation layers, while low and relatively thin precipitating clouds are not well detected in the visible-infrared, because of their low contrast with cold and bright (if snow covered) background. In this work an IR-based, statistical rainfall estimation technique is trained and applied over the Tibetan Plateau hydrological basin to retrive precipitation intensity at different spatial and temporal scales. The technique is based on a simple artificial neural network scheme trained with two supervised training sets assembled for monsoon season and for the rest of the year. For the monsoon season (estimated from June to September), the ground radar precipitation data for few case studies are used to build the training set: four days in summer 2009 are considered. For the rest of the year, CloudSat-CPR derived snowfall rate has been used as reference precipitation data, following the Kulie and Bennartz (2009) algorithm. METEOSAT-7 infrared channels radiance (at 6.7 and 11 micometers) and derived local variability features (such as local standard deviation and local average) are used as input and the actual rainrate is obtained as output for each satellite slot, every 30 minutes on the satellite grid. The satellite rainrate maps for three years (2008-2010) are computed and compared with available global precipitation products (such as C-MORPH and TMPA products) and with other techniques applied to the Plateau area: similarities and differences are

  20. Developing Information Services and Tools to Access and Evaluate Data Quality in Global Satellite-based Precipitation Products

    Science.gov (United States)

    Liu, Z.; Shie, C. L.; Meyer, D. J.

    2017-12-01

    Global satellite-based precipitation products have been widely used in research and applications around the world. Compared to ground-based observations, satellite-based measurements provide precipitation data on a global scale, especially in remote continents and over oceans. Over the years, satellite-based precipitation products have evolved from single sensor and single algorithm to multi-sensors and multi-algorithms. As a result, many satellite-based precipitation products have been enhanced such as spatial and temporal coverages. With inclusion of ground-based measurements, biases of satellite-based precipitation products have been significantly reduced. However, data quality issues still exist and can be caused by many factors such as observations, satellite platform anomaly, algorithms, production, calibration, validation, data services, etc. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is home to NASA global precipitation product archives including the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM), as well as other global and regional precipitation products. Precipitation is one of the top downloaded and accessed parameters in the GES DISC data archive. Meanwhile, users want to easily locate and obtain data quality information at regional and global scales to better understand how precipitation products perform and how reliable they are. As data service providers, it is necessary to provide an easy access to data quality information, however, such information normally is not available, and when it is available, it is not in one place and difficult to locate. In this presentation, we will present challenges and activities at the GES DISC to address precipitation data quality issues.

  1. High-resolution Monthly Satellite Precipitation Product over the Conterminous United States

    Science.gov (United States)

    Hashemi, H.; Fayne, J.; Knight, R. J.; Lakshmi, V.

    2017-12-01

    We present a data set that enhanced the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) monthly product 3B43 in its accuracy and spatial resolution. For this, we developed a correction function to improve the accuracy of TRMM 3B43, spatial resolution of 25 km, by estimating and removing the bias in the satellite data using a ground-based precipitation data set. We observed a strong relationship between the bias and land surface elevation; TRMM 3B43 tends to underestimate the ground-based product at elevations above 1500 m above mean sea level (m.amsl) over the conterminous United States. A relationship was developed between satellite bias and elevation. We then resampled TRMM 3B43 to the Digital Elevation Model (DEM) data set at a spatial resolution of 30 arc second ( 1 km on the ground). The produced high-resolution satellite-based data set was corrected using the developed correction function based on the bias-elevation relationship. Assuming that each rain gauge represents an area of 1 km2, we verified our product against 9,200 rain gauges across the conterminous United States. The new product was compared with the gauges, which have 50, 60, 70, 80, 90, and 100% temporal coverage within the TRMM period of 1998 to 2015. Comparisons between the high-resolution corrected satellite-based data and gauges showed an excellent agreement. The new product captured more detail in the changes in precipitation over the mountainous region than the original TRMM 3B43.

  2. Rainfall frequency analysis for ungauged sites using satellite precipitation products

    Science.gov (United States)

    Gado, Tamer A.; Hsu, Kuolin; Sorooshian, Soroosh

    2017-11-01

    The occurrence of extreme rainfall events and their impacts on hydrologic systems and society are critical considerations in the design and management of a large number of water resources projects. As precipitation records are often limited or unavailable at many sites, it is essential to develop better methods for regional estimation of extreme rainfall at these partially-gauged or ungauged sites. In this study, an innovative method for regional rainfall frequency analysis for ungauged sites is presented. The new method (hereafter, this is called the RRFA-S) is based on corrected annual maximum series obtained from a satellite precipitation product (e.g., PERSIANN-CDR). The probability matching method (PMM) is used here for bias correction to match the CDF of satellite-based precipitation data with the gauged data. The RRFA-S method was assessed through a comparative study with the traditional index flood method using the available annual maximum series of daily rainfall in two different regions in USA (11 sites in Colorado and 18 sites in California). The leave-one-out cross-validation technique was used to represent the ungauged site condition. Results of this numerical application have found that the quantile estimates obtained from the new approach are more accurate and more robust than those given by the traditional index flood method.

  3. Statistical and Hydrological Evaluation of TRMM-Based Multi-Satellite Precipitation Analysis over the Wangchu Basin of Bhutan: Are the Latest Satellite Precipitation Products 3B42V7 Ready for Use in Ungauged Basins?

    Science.gov (United States)

    Xue, Xianwu; Hong, Yang; Limaye, Ashutosh S.; Gourley, Jonathan; Huffman, George J.; Khan, Sadiq Ibrahim; Dorji, Chhimi; Chen, Sheng

    2013-01-01

    The objective of this study is to quantitatively evaluate the successive Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) products and further to explore the improvements and error propagation of the latest 3B42V7 algorithm relative to its predecessor 3B42V6 using the Coupled Routing and Excess Storage (CREST) hydrologic model in the mountainous Wangchu Basin of Bhutan. First, the comparison to a decade-long (2001-2010) daily rain gauge dataset reveals that: 1) 3B42V7 generally improves upon 3B42V6s underestimation both for the whole basin (bias from -41.15 to -8.38) and for a 0.250.25 grid cell with high-density gauges (bias from -40.25 to 0.04), though with modest enhancement of correlation coefficients (CC) (from 0.36 to 0.40 for basin-wide and from 0.37 to 0.41 for grid); and 2) 3B42V7 also improves its occurrence frequency across the rain intensity spectrum. Using the CREST model that has been calibrated with rain gauge inputs, the 3B42V6-based simulation shows limited hydrologic prediction NSCE skill (0.23 in daily scale and 0.25 in monthly scale) while 3B42V7 performs fairly well (0.66 in daily scale and 0.77 in monthly scale), a comparable skill score with the gauge rainfall simulations. After recalibrating the model with the respective TMPA data, significant improvements are observed for 3B42V6 across all categories, but not as much enhancement for the already well-performing 3B42V7 except for a reduction in bias (from -26.98 to -4.81). In summary, the latest 3B42V7 algorithm reveals a significant upgrade from 3B42V6 both in precipitation accuracy (i.e., correcting the underestimation) thus improving its potential hydrological utility. Forcing the model with 3B42V7 rainfall yields comparable skill scores with in-situ gauges even without recalibration of the hydrological model by the satellite precipitation, a compensating approach often used but not favored by the hydrology community, particularly in ungauged basins.

  4. Hydrologic Evaluation of Integrated Multi-satellite Retrivals for GPM over Nanliu River Basin in Southern China

    Science.gov (United States)

    Zhenqing, L.; Sheng, C.; Chaoying, H.

    2017-12-01

    The core satellite of Global Precipitation Measurement (GPM) mission was launched on 27 February2014 with two core sensors dual-frequency precipitation radar (DPR) and microwave imager (GMI). The algorithm of Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) blends the advantages of currently most popular satellite-based quantitative precipitation estimates (QPE) algorithms, i.e. TRMM Multi-satellite Precipitation Analysis (TMPA), Climate Prediction Center morphing technique (CMORPH) ADDIN EN.CITE ADDIN EN.CITE.DATA , Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS).Therefore, IMERG is deemed to be the state-of-art precipitation product with high spatio-temporal resolution of 0.1°/30min. The real-time and post real-time IMERG products are now available online at https://stormpps.gsfc.nasa.gov/storm. Early studies about assessment of IMERG with gauge observations or analysis products show that the current version GPM Day-1 product IMERG demonstrates promising performance over China [1], Europe [2], and United States [3]. However, few studies are found to study the IMERG' potentials of hydrologic utility.In this study, the real-time and final run post real-time IMERG products are hydrologically evaluated with gauge analysis product as reference over Nanliu River basin (Fig.1) in Southern China since March 2014 to February 2017 with Xinanjiang model. Statistics metrics Relative Bias (RB), Root-Mean-Squared Error (RMSE), Correlation Coefficient (CC), Probability Of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), and Nash-Sutcliffe (NSCE) index will be used to compare the stream flow simulated with IMERG to the observed stream flow. This timely hydrologic evaluation is expected to offer insights into IMERG' potentials in hydrologic utility and thus provide useful feedback to the IMERG algorithm developers and

  5. Are satellite products good proxies for gauge precipitation over Singapore?

    Science.gov (United States)

    Hur, Jina; Raghavan, Srivatsan V.; Nguyen, Ngoc Son; Liong, Shie-Yui

    2018-05-01

    The uncertainties in two high-resolution satellite precipitation products (TRMM 3B42 v7.0 and GSMaP v5.222) were investigated by comparing them against rain gauge observations over Singapore on sub-daily scales. The satellite-borne precipitation products are assessed in terms of seasonal, monthly and daily variations, the diurnal cycle, and extreme precipitation over a 10-year period (2000-2010). Results indicate that the uncertainties in extreme precipitation is higher in GSMaP than in TRMM, possibly due to the issues such as satellite merging algorithm, the finer spatio-temporal scale of high intensity precipitation, and the swath time of satellite. Such discrepancies between satellite-borne and gauge-based precipitations at sub-daily scale can possibly lead to distorting analysis of precipitation characteristics and/or application model results. Overall, both satellite products are unable to capture the observed extremes and provide a good agreement with observations only at coarse time scales. Also, the satellite products agree well on the late afternoon maximum and heavier rainfall of gauge-based data in winter season when the Intertropical Convergence Zone (ITCZ) is located over Singapore. However, they do not reproduce the gauge-observed diurnal cycle in summer. The disagreement in summer could be attributed to the dominant satellite overpass time (about 14:00 SGT) later than the diurnal peak time (about 09:00 SGT) of gauge precipitation. From the analyses of extreme precipitation indices, it is inferred that both satellite datasets tend to overestimate the light rain and frequency but underestimate high intensity precipitation and the length of dry spells. This study on quantification of their uncertainty is useful in many aspects especially that these satellite products stand scrutiny over places where there are no good ground data to be compared against. This has serious implications on climate studies as in model evaluations and in particular, climate

  6. Applications of TRMM-based Multi-Satellite Precipitation Estimation for Global Runoff Simulation: Prototyping a Global Flood Monitoring System

    Science.gov (United States)

    Hong, Yang; Adler, Robert F.; Huffman, George J.; Pierce, Harold

    2008-01-01

    Advances in flood monitoring/forecasting have been constrained by the difficulty in estimating rainfall continuously over space (catchment-, national-, continental-, or even global-scale areas) and flood-relevant time scale. With the recent availability of satellite rainfall estimates at fine time and space resolution, this paper describes a prototype research framework for global flood monitoring by combining real-time satellite observations with a database of global terrestrial characteristics through a hydrologically relevant modeling scheme. Four major components included in the framework are (1) real-time precipitation input from NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA); (2) a central geospatial database to preprocess the land surface characteristics: water divides, slopes, soils, land use, flow directions, flow accumulation, drainage network etc.; (3) a modified distributed hydrological model to convert rainfall to runoff and route the flow through the stream network in order to predict the timing and severity of the flood wave, and (4) an open-access web interface to quickly disseminate flood alerts for potential decision-making. Retrospective simulations for 1998-2006 demonstrate that the Global Flood Monitor (GFM) system performs consistently at both station and catchment levels. The GFM website (experimental version) has been running at near real-time in an effort to offer a cost-effective solution to the ultimate challenge of building natural disaster early warning systems for the data-sparse regions of the world. The interactive GFM website shows close-up maps of the flood risks overlaid on topography/population or integrated with the Google-Earth visualization tool. One additional capability, which extends forecast lead-time by assimilating QPF into the GFM, also will be implemented in the future.

  7. A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

    Science.gov (United States)

    Tao, W. K.

    2017-12-01

    In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

  8. Systematical estimation of GPM-based global satellite mapping of precipitation products over China

    Science.gov (United States)

    Zhao, Haigen; Yang, Bogang; Yang, Shengtian; Huang, Yingchun; Dong, Guotao; Bai, Juan; Wang, Zhiwei

    2018-03-01

    As the Global Precipitation Measurement (GPM) Core Observatory satellite continues its mission, new version 6 products for Global Satellite Mapping of Precipitation (GSMaP) have been released. However, few studies have systematically evaluated the GSMaP products over mainland China. This study quantitatively evaluated three GPM-based GSMaP version 6 precipitation products for China and eight subregions referring to the Chinese daily Precipitation Analysis Product (CPAP). The GSMaP products included near-real-time (GSMaP_NRT), microwave-infrared reanalyzed (GSMaP_MVK), and gauge-adjusted (GSMaP_Gau) data. Additionally, the gauge-adjusted Integrated Multi-Satellite Retrievals for Global Precipitation Measurement Mission (IMERG_Gau) was also assessed and compared with GSMaP_Gau. The analyses of the selected daily products were carried out at spatiotemporal resolutions of 1/4° for the period of March 2014 to December 2015 in consideration of the resolution of CPAP and the consistency of the coverage periods of the satellite products. The results indicated that GSMaP_MVK and GSMaP_NRT performed comparably and underdetected light rainfall events (Pearson linear correlation coefficient (CC), fractional standard error (FSE), and root-mean-square error (RMSE) metrics during the summer. Compared with GSMaP_NRT and GSMaP_MVK, GSMaP_Gau possessed significantly improved metrics over mainland China and the eight subregions and performed better in terms of CC, RMSE, and FSE but underestimated precipitation to a greater degree than IMERG_Gau. As a quantitative assessment of the GPM-era GSMaP products, these validation results will supply helpful references for both end users and algorithm developers. However, the study findings need to be confirmed over a longer future study period when the longer-period IMERG retrospectively-processed data are available.

  9. Next-Generation Satellite Precipitation Products for Understanding Global and Regional Water Variability

    Science.gov (United States)

    Hou, Arthur Y.

    2011-01-01

    A major challenge in understanding the space-time variability of continental water fluxes is the lack of accurate precipitation estimates over complex terrains. While satellite precipitation observations can be used to complement ground-based data to obtain improved estimates, space-based and ground-based estimates come with their own sets of uncertainties, which must be understood and characterized. Quantitative estimation of uncertainties in these products also provides a necessary foundation for merging satellite and ground-based precipitation measurements within a rigorous statistical framework. Global Precipitation Measurement (GPM) is an international satellite mission that will provide next-generation global precipitation data products for research and applications. It consists of a constellation of microwave sensors provided by NASA, JAXA, CNES, ISRO, EUMETSAT, DOD, NOAA, NPP, and JPSS. At the heart of the mission is the GPM Core Observatory provided by NASA and JAXA to be launched in 2013. The GPM Core, which will carry the first space-borne dual-frequency radar and a state-of-the-art multi-frequency radiometer, is designed to set new reference standards for precipitation measurements from space, which can then be used to unify and refine precipitation retrievals from all constellation sensors. The next-generation constellation-based satellite precipitation estimates will be characterized by intercalibrated radiometric measurements and physical-based retrievals using a common observation-derived hydrometeor database. For pre-launch algorithm development and post-launch product evaluation, NASA supports an extensive ground validation (GV) program in cooperation with domestic and international partners to improve (1) physics of remote-sensing algorithms through a series of focused field campaigns, (2) characterization of uncertainties in satellite and ground-based precipitation products over selected GV testbeds, and (3) modeling of atmospheric processes and

  10. Evaluating the Global Precipitation Measurement mission with NOAA/NSSL Multi-Radar Multisensor: current status and future directions.

    Science.gov (United States)

    Kirstetter, P. E.; Petersen, W. A.; Gourley, J. J.; Kummerow, C.; Huffman, G. J.; Turk, J.; Tanelli, S.; Maggioni, V.; Anagnostou, E. N.; Hong, Y.; Schwaller, M.

    2017-12-01

    Accurate characterization of uncertainties in space-borne precipitation estimates is critical for many applications including water budget studies or prediction of natural hazards at the global scale. The GPM precipitation Level II (active and passive) and Level III (IMERG) estimates are compared to the high quality and high resolution NEXRAD-based precipitation estimates derived from the NOAA/NSSL's Multi-Radar, Multi-Sensor (MRMS) platform. A surface reference is derived from the MRMS suite of products to be accurate with known uncertainty bounds and measured at a resolution below the pixel sizes of any GPM estimate, providing great flexibility in matching to grid scales or footprints. It provides an independent and consistent reference research framework for directly evaluating GPM precipitation products across a large number of meteorological regimes as a function of resolution, accuracy and sample size. The consistency of the ground and space-based sensors in term of precipitation detection, typology and quantification are systematically evaluated. Satellite precipitation retrievals are further investigated in terms of precipitation distributions, systematic biases and random errors, influence of precipitation sub-pixel variability and comparison between satellite products. Prognostic analysis directly provides feedback to algorithm developers on how to improve the satellite estimates. Specific factors for passive (e.g. surface conditions for GMI) and active (e.g. non uniform beam filling for DPR) sensors are investigated. This cross products characterization acts as a bridge to intercalibrate microwave measurements from the GPM constellation satellites and propagate to the combined and global precipitation estimates. Precipitation features previously used to analyze Level II satellite estimates under various precipitation processes are now intoduced for Level III to test several assumptions in the IMERG algorithm. Specifically, the contribution of Level II is

  11. Day 1 for the Integrated Multi-Satellite Retrievals for GPM (IMERG) Data Sets

    Science.gov (United States)

    Huffman, G. J.; Bolvin, D. T.; Braithwaite, D.; Hsu, K. L.; Joyce, R.; Kidd, C.; Sorooshian, S.; Xie, P.

    2014-12-01

    The Integrated Multi-satellitE Retrievals for GPM (IMERG) is designed to compute the best time series of (nearly) global precipitation from "all" precipitation-relevant satellites and global surface precipitation gauge analyses. IMERG was developed to use GPM Core Observatory data as a reference for the international constellation of satellites of opportunity that constitute the GPM virtual constellation. Computationally, IMERG is a unified U.S. algorithm drawing on strengths in the three contributing groups, whose previous work includes: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA); 2) the CPC Morphing algorithm with Kalman Filtering (K-CMORPH); and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS). We review the IMERG design, development, testing, and current status. IMERG provides 0.1°x0.1° half-hourly data, and will be run at multiple times, providing successively more accurate estimates: 4 hours, 8 hours, and 2 months after observation time. In Day 1 the spatial extent is 60°N-S, for the period March 2014 to the present. In subsequent reprocessing the data will extend to fully global, covering the period 1998 to the present. Both the set of input data set retrievals and the IMERG system are substantially different than those used in previous U.S. products. The input passive microwave data are all being produced with GPROF2014, which is substantially upgraded compared to previous versions. For the first time, this includes microwave sounders. Accordingly, there is a strong need to carefully check the initial test data sets for performance. IMERG output will be illustrated using pre-operational test data, including the variety of supporting fields, such as the merged-microwave and infrared estimates, and the precipitation type. Finally, we will summarize the expected release of various output products, and the subsequent reprocessing sequence.

  12. The Version 2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979-Present)

    Science.gov (United States)

    Adler, Robert F.; Huffman, George J.; Chang, Alfred; Ferraro, Ralph; Xie, Ping-Ping; Janowiak, John; Rudolf, Bruno; Schneider, Udo; Curtis, Scott; Bolvin, David

    2003-01-01

    The Global Precipitation Climatology Project (GPCP) Version 2 Monthly Precipitation Analysis is described. This globally complete, monthly analysis of surface precipitation at 2.5 degrees x 2.5 degrees latitude-longitude resolution is available from January 1979 to the present. It is a merged analysis that incorporates precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit-satellite infrared data, and rain gauge observations. The merging approach utilizes the higher accuracy of the low-orbit microwave observations to calibrate, or adjust, the more frequent geosynchronous infrared observations. The data set is extended back into the premicrowave era (before 1987) by using infrared-only observations calibrated to the microwave-based analysis of the later years. The combined satellite-based product is adjusted by the raingauge analysis. This monthly analysis is the foundation for the GPCP suite of products including those at finer temporal resolution, satellite estimate, and error estimates for each field. The 23-year GPCP climatology is characterized, along with time and space variations of precipitation.

  13. Evaluation of TRMM Multi-satellite Precipitation Analysis (TMPA performance in the Central Andes region and its dependency on spatial and temporal resolution

    Directory of Open Access Journals (Sweden)

    M. L. M. Scheel

    2011-08-01

    Full Text Available Climate time series are of major importance for base line studies for climate change impact and adaptation projects. However, for instance, in mountain regions and in developing countries there exist significant gaps in ground based climate records in space and time. Specifically, in the Peruvian Andes spatially and temporally coherent precipitation information is a prerequisite for ongoing climate change adaptation projects in the fields of water resources, disasters and food security. The present work aims at evaluating the ability of Tropical Rainfall Measurement Mission (TRMM Multi-satellite Precipitation Analysis (TMPA to estimate precipitation rates at daily 0.25° × 0.25° scale in the Central Andes and the dependency of the estimate performance on changing spatial and temporal resolution. Comparison of the TMPA product with gauge measurements in the regions of Cuzco, Peru and La Paz, Bolivia were carried out and analysed statistically. Large biases are identified in both investigation areas in the estimation of daily precipitation amounts. The occurrence of strong precipitation events was well assessed, but their intensities were underestimated. TMPA estimates for La Paz show high false alarm ratio.

    The dependency of the TMPA estimate quality with changing resolution was analysed by comparisons of 1-, 7-, 15- and 30-day sums for Cuzco, Peru. The correlation of TMPA estimates with ground data increases strongly and almost linearly with temporal aggregation. The spatial aggregation to 0.5°, 0.75° and 1° grid box averaged precipitation and its comparison to gauge data of the same areas revealed no significant change in correlation coefficients and estimate performance.

    In order to profit from the TMPA combination product on a daily basis, a procedure to blend it with daily precipitation gauge measurements is proposed.

    Different sources of errors and uncertainties introduced by the sensors, sensor

  14. Flood modelling with global precipitation measurement (GPM) satellite rainfall data: a case study of Dehradun, Uttarakhand, India

    Science.gov (United States)

    Sai Krishna, V. V.; Dikshit, Anil Kumar; Pandey, Kamal

    2016-05-01

    Urban expansion, water bodies and climate change are inextricably linked with each other. The macro and micro level climate changes are leading to extreme precipitation events which have severe consequences on flooding in urban areas. Flood simulations shall be helpful in demarcation of flooded areas and effective flood planning and preparedness. The temporal availability of satellite rainfall data at varying spatial scale of 0.10 to 0.50 is helpful in near real time flood simulations. The present research aims at analysing stream flow and runoff to monitor flood condition using satellite rainfall data in a hydrologic model. The satellite rainfall data used in the research was NASA's Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG), which is available at 30 minutes temporal resolution. Landsat data was used for mapping the water bodies in the study area. Land use land cover (LULC) data was prepared using Landsat 8 data with maximum likelihood technique that was provided as an input to the HEC-HMS hydrological model. The research was applied to one of the urbanized cities of India, viz. Dehradun, which is the capital of Uttarakhand State. The research helped in identifying the flood vulnerability at the basin level on the basis of the runoff and various socio economic parameters using multi criteria analysis.

  15. Merging Satellite Precipitation Products for Improved Streamflow Simulations

    Science.gov (United States)

    Maggioni, V.; Massari, C.; Barbetta, S.; Camici, S.; Brocca, L.

    2017-12-01

    Accurate quantitative precipitation estimation is of great importance for water resources management, agricultural planning and forecasting and monitoring of natural hazards such as flash floods and landslides. In situ observations are limited around the Earth, especially in remote areas (e.g., complex terrain, dense vegetation), but currently available satellite precipitation products are able to provide global precipitation estimates with an accuracy that depends upon many factors (e.g., type of storms, temporal sampling, season, etc.). The recent SM2RAIN approach proposes to estimate rainfall by using satellite soil moisture observations. As opposed to traditional satellite precipitation methods, which sense cloud properties to retrieve instantaneous estimates, this new bottom-up approach makes use of two consecutive soil moisture measurements for obtaining an estimate of the fallen precipitation within the interval between two satellite overpasses. As a result, the nature of the measurement is different and complementary to the one of classical precipitation products and could provide a different valid perspective to substitute or improve current rainfall estimates. Therefore, we propose to merge SM2RAIN and the widely used TMPA 3B42RT product across Italy for a 6-year period (2010-2015) at daily/0.25deg temporal/spatial scale. Two conceptually different merging techniques are compared to each other and evaluated in terms of different statistical metrics, including hit bias, threat score, false alarm rates, and missed rainfall volumes. The first is based on the maximization of the temporal correlation with a reference dataset, while the second is based on a Bayesian approach, which provides a probabilistic satellite precipitation estimate derived from the joint probability distribution of observations and satellite estimates. The merged precipitation products show a better performance with respect to the parental satellite-based products in terms of categorical

  16. Improving the Regional Applicability of Satellite Precipitation Products by Ensemble Algorithm

    Directory of Open Access Journals (Sweden)

    Waseem Muhammad

    2018-04-01

    Full Text Available Satellite-based precipitation products (e.g., Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG and its predecessor, Tropical Rainfall Measuring Mission (TRMM are a critical source of precipitation estimation, particularly for a region with less, or no, hydrometric networking. However, the inconsistency in the performance of these products has been observed in different climatic and topographic diverse regions, timescales, and precipitation intensities and there is still room for improvement. Hence, using a projected ensemble algorithm, the regional precipitation estimate (RP is introduced here. The RP concept is mainly based on the regional performance weights derived from the Mean Square Error (MSE and the precipitation estimate from the TRMM product, that is, TRMM 3B42 (TR, real-time (late (IT and the research (post-real-time (IR products of IMERG. The overall results of the selected contingency table (e.g., Probability of detection (POD and statistical indices (e.g., Correlation Coefficient (CC signposted that the proposed RP product has shown an overall better potential to capture the gauge observations compared with the TR, IR, and IT in five different climatic regions of Pakistan from January 2015 to December 2016, at a diurnal time scale. The current study could be the first research providing preliminary feedback from Pakistan for global precipitation measurement researchers by highlighting the need for refinement in the IMERG.

  17. Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.

    2014-10-01

    We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets (bias-adjusted TMPA 3B42, near-real time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (± 6%). However, differences at the RFC are more important in particular for near-real time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near real time counterpart 3B42RT. However, large biases remained for 3B42 over the Western US for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in day-1) over the Northwest. Furthermore, the conditional analysis and the contingency analysis conducted illustrated the challenge of retrieving extreme precipitation from remote sensing estimates.

  18. Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN from a Geostationary Satellite.

    Directory of Open Access Journals (Sweden)

    Yu Liu

    Full Text Available The prediction of the short-term quantitative precipitation nowcasting (QPN from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC; the Horn-Schunck optical-flow scheme (PHS; and the Pyramid Lucas-Kanade Optical Flow method (PPLK, which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6. The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN.

  19. Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN) from a Geostationary Satellite.

    Science.gov (United States)

    Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang; Ji, Wei

    2015-01-01

    The prediction of the short-term quantitative precipitation nowcasting (QPN) from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F) which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC); the Horn-Schunck optical-flow scheme (PHS); and the Pyramid Lucas-Kanade Optical Flow method (PPLK), which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6). The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN.

  20. Improving User Access to the Integrated Multi-Satellite Retrievals for GPM (IMERG) Products

    Science.gov (United States)

    Huffman, George; Bolvin, David; Nelkin, Eric; Kidd, Christopher

    2016-04-01

    The U.S. Global Precipitation Measurement mission (GPM) team has developed the Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm to take advantage of the international constellation of precipitation-relevant satellites and the Global Precipitation Climatology Centre surface precipitation gauge analysis. The goal is to provide a long record of homogeneous, high-resolution quasi-global estimates of precipitation. While expert scientific researchers are major users of the IMERG products, it is clear that many other user communities and disciplines also desire access to the data for wide-ranging applications. Lessons learned during the Tropical Rainfall Measuring Mission, the predecessor to GPM, led to some basic design choices that provided the framework for supporting multiple user bases. For example, two near-real-time "runs" are computed, the Early and Late (currently 5 and 15 hours after observation time, respectively), then the Final Run about 3 months later. The datasets contain multiple fields that provide insight into the computation of the complete precipitation data field, as well as diagnostic (currently) estimates of the precipitation's phase. In parallel with this, the archive sites are working to provide the IMERG data in a variety of formats, and with subsetting and simple interactive analysis to make the data more easily available to non-expert users. The various options for accessing the data are summarized under the pmm.nasa.gov data access page. The talk will end by considering the feasibility of major user requests, including polar coverage, a simplified Data Quality Index, and reduced data latency for the Early Run. In brief, the first two are challenging, but under the team's control. The last requires significant action by some of the satellite data providers.

  1. Ground water level, Water storage, Soil moisture, Precipitation Variability Using Multi Satellite Data during 2003-2016 Associated with California Drought

    Science.gov (United States)

    Li, J. W.; Singh, R. P.

    2017-12-01

    The agricultural market of California is a multi-billion-dollar industry, however in the recent years, the state is facing severe drought. It is important to have a deeper understanding of how the agriculture is affected by the amount of rainfall as well as the ground conditions in California. We have considered 5 regions (each 2 degree by 2 degree) covering whole of California. Multi satellite (MODIS Terra, GRACE, GLDAS) data through NASA Giovanni portal were used to study long period variability 2003 - 2016 of ground water level and storage, soil moisture, root zone moisture level, precipitation and normalized vegetation index (NDVI) in these 5 regions. Our detailed analysis of these parameters show a strong correlation between the NDVI and some of these parameters. NDVI represents greenness showing strong drought conditions during the period 2011-2016 due to poor rainfall and recharge of ground water in the mid and southern parts of California. Effect of ground water level and underground storage will be also discussed on the frequency of earthquakes in five regions of California. The mid and southern parts of California show increasing frequency of small earthquakes during drought periods.

  2. Evaluating the MSG satellite Multi-Sensor Precipitation Estimate for extreme rainfall monitoring over northern Tunisia

    Directory of Open Access Journals (Sweden)

    Saoussen Dhib

    2017-06-01

    Full Text Available Knowledge and evaluation of extreme precipitation is important for water resources and flood risk management, soil and land degradation, and other environmental issues. Due to the high potential threat to local infrastructure, such as buildings, roads and power supplies, heavy precipitation can have an important social and economic impact on society. At present, satellite derived precipitation estimates are becoming more readily available. This paper aims to investigate the potential use of the Meteosat Second Generation (MSG Multi-Sensor Precipitation Estimate (MPE for extreme rainfall assessment in Tunisia. The MSGMPE data combine microwave rain rate estimations with SEVIRI thermal infrared channel data, using an EUMETSAT production chain in near real time mode. The MPE data can therefore be used in a now-casting mode, and are potentially useful for extreme weather early warning and monitoring. Daily precipitation observed across an in situ gauge network in the north of Tunisia were used during the period 2007–2009 for validation of the MPE extreme event data. As a first test of the MSGMPE product's performance, very light to moderate rainfall classes, occurring between January and October 2007, were evaluated. Extreme rainfall events were then selected, using a threshold criterion for large rainfall depth (>50 mm/day occurring at least at one ground station. Spatial interpolation methods were applied to generate rainfall maps for the drier summer season (from May to October and the wet winter season (from November to April. Interpolated gauge rainfall maps were then compared to MSGMPE data available from the EUMETSAT UMARF archive or from the GEONETCast direct dissemination system. The summation of the MPE data at 5 and/or 15 min time intervals over a 24 h period, provided a basis for comparison. The MSGMPE product was not very effective in the detection of very light and light rain events. Better results were obtained for the slightly

  3. Global daily precipitation fields from bias-corrected rain gauge and satellite observations. Pt. 1. Design and development

    Energy Technology Data Exchange (ETDEWEB)

    Kottek, M.; Rubel, F. [Univ. of Veterinary Medicine, Vienna (Austria). Biometeorology Group

    2007-10-15

    Global daily precipitation analyses are mainly based on satellite estimates, often calibrated with monthly ground analyses or merged with model predictions. We argue here that an essential improvement of their accuracy is only possible by incorporation of daily ground measurements. In this work we apply geostatistical methods to compile a global precipitation product based on daily rain gauge measurements. The raw ground measurements, disseminated via Global Telecommunication System (GTS), are corrected for their systematic measurement errors and interpolated onto a global 1 degree grid. For interpolation ordinary block kriging is applied, with precalculated spatial auto-correlation functions (ACFs). This technique allows to incorporate additional climate information. First, monthly ACFs are calculated from the daily data; second, they are regionalised according to the five main climatic zones of the Koeppen-Geiger climate classification. The interpolation error, a by-product of kriging, is used to flag grid points as missing if the error is above a predefined threshold. But for many applications missing values constitute a problem. Due to a combination of the ground analyses with the daily multi-satellite product of the Global Precipitation Climatology Project (GPCP-1DD) not only these missing values are replaced but also the spatial structure of the satellite estimates is considered. As merging method bivariate ordinary co-kriging is applied. The ACFs necessary for the gauge and the satellite fields as well as the corresponding spatial cross-correlation functions (CCFs) are again precalculated for each of the five main climatic zones and for each individual month. As a result two new global daily data sets for the period 1996 up to today will be available on the Internet (www.gmes-geoland.info): A precipitation product over land, analysed from ground measurements; and a global precipitation product merged from this and the GPCP-1DD multi-satellite product. (orig.)

  4. On Some Aspects of Precipitation over Tropical Indian Ocean Using Satellite Data

    Digital Repository Service at National Institute of Oceanography (India)

    RameshKumar, M.R.; Sreejith, O.P.

    The annual and inter-annual variability of precipitation over the tropical Indian Ocean is studied for the period 1979–1997, using satellite data from a variety of sensors. The Climate Prediction Center Merged Analysis Precipitation (CMAP...

  5. MSWEP : 3-hourly 0.25° global gridded precipitation (1979-2015) by merging gauge, satellite, and reanalysis data

    NARCIS (Netherlands)

    Beck, Hylke E.; Van Dijk, Albert I.J.M.; Levizzani, Vincenzo; Schellekens, Jaap; Miralles, Diego G.; Martens, Brecht; De Roo, Ad

    2017-01-01

    Current global precipitation (P) datasets do not take full advantage of the complementary nature of satellite and reanalysis data. Here, we present Multi-Source Weighted-Ensemble Precipitation (MSWEP) version 1.1, a global P dataset for the period 1979-2015 with a 3-hourly temporal and 0.25° spatial

  6. A global satellite assisted precipitation climatology

    Science.gov (United States)

    Funk, Christopher C.; Verdin, Andrew P.; Michaelsen, Joel C.; Pedreros, Diego; Husak, Gregory J.; Peterson, P.

    2015-01-01

    Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high resolution (0.05°) global precipitation climatologies that perform reasonably well in data sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate

  7. Assessment and Comparison of TMPA Satellite Precipitation Products in Varying Climatic and Topographic Regimes in Morocco

    Directory of Open Access Journals (Sweden)

    Adam Milewski

    2015-05-01

    Full Text Available TRMM Multi-satellite Precipitation Analysis (TMPA satellite precipitation products have been utilized to quantify, forecast, or understand precipitation patterns, climate change, hydrologic models, and drought in numerous scientific investigations. The TMPA products recently went through a series of algorithm developments to enhance the accuracy and reliability of high-quality precipitation measurements, particularly in low rainfall environments and complex terrain. In this study, we evaluated four TMPA products (3B42: V6, V7temp, V7, RTV7 against 125 rain gauges in Northern Morocco to assess the accuracy of TMPA products in various regimes, examine the performance metrics of new algorithm developments, and assess the impact of the processing error in 2012. Results show that the research products outperform the real-time products in all environments within Morocco, and the newest algorithm development (3B42 V7 outperforms the previous version (V6, particularly in low rainfall and high-elevation environments. TMPA products continue to overestimate precipitation in arid environments and underestimate it in high-elevation areas. Lastly, the temporary processing error resulted in little bias except in arid environments. These results corroborate findings from previous studies, provide scientific data for the Middle East, highlight the difficulty of using TMPA products in varying conditions, and present preliminary research for future algorithm development for the GPM mission.

  8. Improving Satellite Quantitative Precipitation Estimation Using GOES-Retrieved Cloud Optical Depth

    Energy Technology Data Exchange (ETDEWEB)

    Stenz, Ronald; Dong, Xiquan; Xi, Baike; Feng, Zhe; Kuligowski, Robert J.

    2016-02-01

    To address significant gaps in ground-based radar coverage and rain gauge networks in the U.S., geostationary satellite quantitative precipitation estimates (QPEs) such as the Self-Calibrating Multivariate Precipitation Retrievals (SCaMPR) can be used to fill in both the spatial and temporal gaps of ground-based measurements. Additionally, with the launch of GOES-R, the temporal resolution of satellite QPEs may be comparable to that of Weather Service Radar-1988 Doppler (WSR-88D) volume scans as GOES images will be available every five minutes. However, while satellite QPEs have strengths in spatial coverage and temporal resolution, they face limitations particularly during convective events. Deep Convective Systems (DCSs) have large cloud shields with similar brightness temperatures (BTs) over nearly the entire system, but widely varying precipitation rates beneath these clouds. Geostationary satellite QPEs relying on the indirect relationship between BTs and precipitation rates often suffer from large errors because anvil regions (little/no precipitation) cannot be distinguished from rain-cores (heavy precipitation) using only BTs. However, a combination of BTs and optical depth (τ) has been found to reduce overestimates of precipitation in anvil regions (Stenz et al. 2014). A new rain mask algorithm incorporating both τ and BTs has been developed, and its application to the existing SCaMPR algorithm was evaluated. The performance of the modified SCaMPR was evaluated using traditional skill scores and a more detailed analysis of performance in individual DCS components by utilizing the Feng et al. (2012) classification algorithm. SCaMPR estimates with the new rain mask applied benefited from significantly reduced overestimates of precipitation in anvil regions and overall improvements in skill scores.

  9. Validation of Satellite Precipitation (trmm 3B43) in Ecuadorian Coastal Plains, Andean Highlands and Amazonian Rainforest

    Science.gov (United States)

    Ballari, D.; Castro, E.; Campozano, L.

    2016-06-01

    Precipitation monitoring is of utmost importance for water resource management. However, in regions of complex terrain such as Ecuador, the high spatio-temporal precipitation variability and the scarcity of rain gauges, make difficult to obtain accurate estimations of precipitation. Remotely sensed estimated precipitation, such as the Multi-satellite Precipitation Analysis TRMM, can cope with this problem after a validation process, which must be representative in space and time. In this work we validate monthly estimates from TRMM 3B43 satellite precipitation (0.25° x 0.25° resolution), by using ground data from 14 rain gauges in Ecuador. The stations are located in the 3 most differentiated regions of the country: the Pacific coastal plains, the Andean highlands, and the Amazon rainforest. Time series, between 1998 - 2010, of imagery and rain gauges were compared using statistical error metrics such as bias, root mean square error, and Pearson correlation; and with detection indexes such as probability of detection, equitable threat score, false alarm rate and frequency bias index. The results showed that precipitation seasonality is well represented and TRMM 3B43 acceptably estimates the monthly precipitation in the three regions of the country. According to both, statistical error metrics and detection indexes, the coastal and Amazon regions are better estimated quantitatively than the Andean highlands. Additionally, it was found that there are better estimations for light precipitation rates. The present validation of TRMM 3B43 provides important results to support further studies on calibration and bias correction of precipitation in ungagged watershed basins.

  10. Does GPM-based multi-satellite precipitation enhance rainfall estimates over Pakistan and Bolivia arid regions?

    Science.gov (United States)

    Hussain, Y.; Satgé, F.; Bonnet, M. P.; Pillco, R.; Molina, J.; Timouk, F.; Roig, H.; Martinez-Carvajal, H., Sr.; Gulraiz, A.

    2016-12-01

    Arid regions are sensitive to rainfall variations which are expressed in the form of flooding and droughts. Unfortunately, those regions are poorly monitored and high quality rainfall estimates are still needed. The Global Precipitation Measurement (GPM) mission released two new satellite rainfall products named Integrated Multisatellite Retrievals GPM (IMERG) and Global Satellite Mapping of Precipitation version 6 (GSMaP-v6) bringing the possibility of accurate rainfall monitoring over these countries. This study assessed both products at monthly scale over Pakistan considering dry and wet season over the 4 main climatic zones from 2014 to 2016. With similar climatic conditions, the Altiplano region of Bolivia is considered to quantify the influence of big lakes (Titicaca and Poopó) in rainfall estimates. For comparison, the widely used TRMM-Multisatellite Precipitation Analysis 3B43 (TMPA-3B43) version 7 is also involved in the analysis to observe the potential enhancement in rainfall estimate brought by GPM products. Rainfall estimates derived from 110 rain-gauges are used as reference to compare IMERG, GSMaP-v6 and TMPA-3B43 at the 0.1° and 0.25° spatial resolution. Over both regions, IMERG and GSMaP-v6 capture the spatial pattern of precipitation as well as TMPA-3B43. All products tend to over estimates rainfall over very arid regions. This feature is even more marked during dry season. However, during this season, both reference and estimated rainfall remain very low and do not impact seasonal water budget computation. On a general way, IMERG slightly outperforms TMPA-3B43 and GSMaP-v6 which provides the less accurate rainfall estimate. The TMPA-3B43 rainfall underestimation previously found over Lake Titicaca is still observed in IMERG estimates. However, GSMaP-v6 considerably decreases the underestimation providing the most accurate rainfall estimate over the lake. MOD11C3 Land Surface Temperature (LST) and ASTER Global Emissivity Dataset reveal strong

  11. A coordinated two-satellite study of energetic electron precipitation events

    International Nuclear Information System (INIS)

    Imhof, W.L.; Nakano, G.H.; Gaines, E.E.; Reagan, J.B.

    1975-01-01

    A new technique for studying the spatial/temporal variations of energetic electron precipitation events is investigated. Data are presented in which precipitating electrons were measured simultaneously on two coordinated polar-orbiting satellites and the bremsstrahlung produced by the electrons precipitating into the atmosphere was observed from one of the satellites. Two electron spectrometers measuring the intensities and energy spectra of electrons of >130 keV were located on the oriented satellite 1971-089A (altitude, approx. =800 km), whereas a single similar spectrometer measuring electrons of >160 keV was located on the spinning low-altitude (approx.750 km) satellite 1972-076B. The X rays of >50 keV were measured with a 50-cm 3 germanium spectrometer placed on the 1972-076B satellite. With the coordinated data a study is made of events in which large fluctuations were observed in the precipitating energetic electron intensities. In the examples presented the satellite X ray data alone demonstrate that the spatially integrated electron influx was constant in time, and when the X ray data are combined with the direct electron measurements from the two satellites, the resulting data suggest that the major features in the flux profiles were primarily spatial in nature. The combination of X ray and electron measurements from two satellites is shown to provide an important method for studying and attempting to resolve spatial and temporal effects

  12. ASSESSMENT OF SATELLITE PRECIPITATION PRODUCTS IN THE PHILIPPINE ARCHIPELAGO

    Directory of Open Access Journals (Sweden)

    M. D. Ramos

    2016-06-01

    Full Text Available Precipitation is the most important weather parameter in the Philippines. Made up of more than 7100 islands, the Philippine archipelago is an agricultural country that depends on rain-fed crops. Located in the western rim of the North West Pacific Ocean, this tropical island country is very vulnerable to tropical cyclones that lead to severe flooding events. Recently, satellite-based precipitation estimates have improved significantly and can serve as alternatives to ground-based observations. These data can be used to fill data gaps not only for climatic studies, but can also be utilized for disaster risk reduction and management activities. This study characterized the statistical errors of daily precipitation from four satellite-based rainfall products from (1 the Tropical Rainfall Measuring Mission (TRMM, (2 the CPC Morphing technique (CMORPH of NOAA and (3 the Global Satellite Mapping of Precipitation (GSMAP and (4 Precipitation Estimation from Remotely Sensed information using Artificial Neural Networks (PERSIANN. Precipitation data were compared to 52 synoptic weather stations located all over the Philippines. Results show GSMAP to have over all lower bias and CMORPH with lowest Mean Absolute Error (MAE and Root Mean Square Error (RMSE. In addition, a dichotomous rainfall test reveals GSMAP and CMORPH have low Proportion Correct (PC for convective and stratiform rainclouds, respectively. TRMM consistently showed high PC for almost all raincloud types. Moreover, all four satellite precipitation showed high Correct Negatives (CN values for the north-western part of the country during the North-East monsoon and spring monsoonal transition periods.

  13. Assessment of Satellite Precipitation Products in the Philippine Archipelago

    Science.gov (United States)

    Ramos, M. D.; Tendencia, E.; Espana, K.; Sabido, J.; Bagtasa, G.

    2016-06-01

    Precipitation is the most important weather parameter in the Philippines. Made up of more than 7100 islands, the Philippine archipelago is an agricultural country that depends on rain-fed crops. Located in the western rim of the North West Pacific Ocean, this tropical island country is very vulnerable to tropical cyclones that lead to severe flooding events. Recently, satellite-based precipitation estimates have improved significantly and can serve as alternatives to ground-based observations. These data can be used to fill data gaps not only for climatic studies, but can also be utilized for disaster risk reduction and management activities. This study characterized the statistical errors of daily precipitation from four satellite-based rainfall products from (1) the Tropical Rainfall Measuring Mission (TRMM), (2) the CPC Morphing technique (CMORPH) of NOAA and (3) the Global Satellite Mapping of Precipitation (GSMAP) and (4) Precipitation Estimation from Remotely Sensed information using Artificial Neural Networks (PERSIANN). Precipitation data were compared to 52 synoptic weather stations located all over the Philippines. Results show GSMAP to have over all lower bias and CMORPH with lowest Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). In addition, a dichotomous rainfall test reveals GSMAP and CMORPH have low Proportion Correct (PC) for convective and stratiform rainclouds, respectively. TRMM consistently showed high PC for almost all raincloud types. Moreover, all four satellite precipitation showed high Correct Negatives (CN) values for the north-western part of the country during the North-East monsoon and spring monsoonal transition periods.

  14. Operational Estimation of Accumulated Precipitation using Satellite Observation, by Eumetsat Satellite Application facility in Support to Hydrology (H-SAF Consortium).

    Science.gov (United States)

    di Diodato, A.; de Leonibus, L.; Zauli, F.; Biron, D.; Melfi, D.

    2009-04-01

    compared by climatic thresholds got, basically, by the project "Climate Atlas of Europe" led by Meteo France inside the project ECSN (European Climate Support Network) of EUMETNET. To reduce the bias errors introduced by satellite estimates the rain gauge data are used to make an intercalibration with the satellite estimates, using information achieved by GTS network. Precipitation increments are estimated at each observation location from the observation and the interpolated background field. A field of the increments is carried out by standard Kriging method. The final precipitation analysis is achieved by the sum of the increments and the precipitation estimation at each grid points. It is also considered that major error sources in retrieval 15 minutes instantaneous precipitation from cloud top temperature comes from high (cold) non precipitating clouds and the use of same regression coefficients both for warm clouds (stratus) and cold clouds (convective). As that error is intrinsic in the blending technique applied, we are going to improve performances making use of cloud type specified retrievals. To apply such scheme on the products, we apply a discrimination from convective and stratified clouds, then we retrieve precipitation in parallel for the two clouds classes; the two outputs are merged again into one products, solving the double retrieval pixels keeping the convection retrieval. Basic tools for that is the computation of two different lookup tables to associate precipitation at a brightness temperature for the two kinds of cloudiness. The clouds discrimination will be done by the NWC-SAF product named "cloud type" for the stratified clouds and with an application, running operationally at Italian Met Service, named NEFODINA for automatic detection of convective phenomena. Results of studies to improve the accumulated precipitation as well are presented. The studies exploit the potential to use other source of information like quantitative precipitation

  15. Bias correction of satellite precipitation products for flood forecasting application at the Upper Mahanadi River Basin in Eastern India

    Science.gov (United States)

    Beria, H.; Nanda, T., Sr.; Chatterjee, C.

    2015-12-01

    High resolution satellite precipitation products such as Tropical Rainfall Measuring Mission (TRMM), Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts (ECMWF), etc., offer a promising alternative to flood forecasting in data scarce regions. At the current state-of-art, these products cannot be used in the raw form for flood forecasting, even at smaller lead times. In the current study, these precipitation products are bias corrected using statistical techniques, such as additive and multiplicative bias corrections, and wavelet multi-resolution analysis (MRA) with India Meteorological Department (IMD) gridded precipitation product,obtained from gauge-based rainfall estimates. Neural network based rainfall-runoff modeling using these bias corrected products provide encouraging results for flood forecasting upto 48 hours lead time. We will present various statistical and graphical interpretations of catchment response to high rainfall events using both the raw and bias corrected precipitation products at different lead times.

  16. Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

    Science.gov (United States)

    Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

    2017-03-01

    Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

  17. A Bayesian kriging approach for blending satellite and ground precipitation observations

    Science.gov (United States)

    Verdin, Andrew P.; Rajagopalan, Balaji; Kleiber, William; Funk, Christopher C.

    2015-01-01

    Drought and flood management practices require accurate estimates of precipitation. Gauge observations, however, are often sparse in regions with complicated terrain, clustered in valleys, and of poor quality. Consequently, the spatial extent of wet events is poorly represented. Satellite-derived precipitation data are an attractive alternative, though they tend to underestimate the magnitude of wet events due to their dependency on retrieval algorithms and the indirect relationship between satellite infrared observations and precipitation intensities. Here we offer a Bayesian kriging approach for blending precipitation gauge data and the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates for Central America, Colombia, and Venezuela. First, the gauge observations are modeled as a linear function of satellite-derived estimates and any number of other variables—for this research we include elevation. Prior distributions are defined for all model parameters and the posterior distributions are obtained simultaneously via Markov chain Monte Carlo sampling. The posterior distributions of these parameters are required for spatial estimation, and thus are obtained prior to implementing the spatial kriging model. This functional framework is applied to model parameters obtained by sampling from the posterior distributions, and the residuals of the linear model are subject to a spatial kriging model. Consequently, the posterior distributions and uncertainties of the blended precipitation estimates are obtained. We demonstrate this method by applying it to pentadal and monthly total precipitation fields during 2009. The model's performance and its inherent ability to capture wet events are investigated. We show that this blending method significantly improves upon the satellite-derived estimates and is also competitive in its ability to represent wet events. This procedure also provides a means to estimate a full conditional distribution

  18. Teamwork Reasoning and Multi-Satellite Missions

    Science.gov (United States)

    Marsella, Stacy C.; Plaunt, Christian (Technical Monitor)

    2002-01-01

    NASA is rapidly moving towards the use of spatially distributed multiple satellites operating in near Earth orbit and Deep Space. Effective operation of such multi-satellite constellations raises many key research issues. In particular, the satellites will be required to cooperate with each other as a team that must achieve common objectives with a high degree of autonomy from ground based operations. The multi-agent research community has made considerable progress in investigating the challenges of realizing such teamwork. In this report, we discuss some of the teamwork issues that will be faced by multi-satellite operations. The basis of the discussion is a particular proposed mission, the Magnetospheric MultiScale mission to explore Earth's magnetosphere. We describe this mission and then consider how multi-agent technologies might be applied in the design and operation of these missions. We consider the potential benefits of these technologies as well as the research challenges that will be raised in applying them to NASA multi-satellite missions. We conclude with some recommendations for future work.

  19. The Day-1 GPM Combined Precipitation Algorithm: IMERG

    Science.gov (United States)

    Huffman, G. J.; Bolvin, D. T.; Braithwaite, D.; Hsu, K.; Joyce, R.; Kidd, C.; Sorooshian, S.; Xie, P.

    2012-12-01

    The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) algorithm will provide the at-launch combined-sensor precipitation dataset being produced by the U.S. GPM Science Team. IMERG is being developed as a unified U.S. algorithm that takes advantage of strengths in three current U.S. algorithms: - the TRMM Multi-satellite Precipitation Analysis (TMPA), which addresses inter-satellite calibration of precipitation estimates and monthly scale combination of satellite and gauge analyses; - the CPC Morphing algorithm with Kalman Filtering (KF-CMORPH), which provides quality-weighted time interpolation of precipitation patterns following storm motion; and - the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS), which provides a neural-network-based scheme for generating microwave-calibrated precipitation estimates from geosynchronous infrared brightness temperatures, and filters out some non-raining cold clouds. The goal is to provide a long-term, fine-scale record of global precipitation from the entire constellation of precipitation-relevant satellite sensors, with input from surface precipitation gauges. The record will begin January 1998 at the start of the Tropical Rainfall Measuring Mission (TRMM) and extend as GPM records additional data. Although homogeneity is considered desirable, the use of diverse and evolving data sources works against the strict long-term homogeneity that characterizes a Climate Data Record (CDR). This talk will briefly review the design requirements for IMERG, including multiple runs at different latencies (most likely around 4 hours, 12 hours, and 2 months after observation time), various intermediate data fields as part of the IMERG data file, and the plans to bring up IMERG with calibration by TRMM initially, transitioning to GPM when its individual-sensor precipitation algorithms are fully functional

  20. Electromagnetic Modeling of the Propagation Characteristics of Satellite Communications Through Composite Precipitation Layers, Part1: Mathematical Formulation

    Directory of Open Access Journals (Sweden)

    H.M. Al-Rizzo

    2000-12-01

    Full Text Available A systematic and general formulation of a Propagation Simulation Program (PSP is developed for the coherent field of microwave and millimeter wave carrier signals traversing intermediate layered precipitation media, taking into account the random behavior of particle size, orientation, shape and concentration distributions.  Based on a rigorous solution of the volumetric multiple-scattering integral equations, the formalism offers the capability of treating the potential transmission impairments on satellite-earth links and radar remote sensing generated by composite atmospheric layers of precipitation in conjunction with the finite polarization isolation of dual-polarized transmitting and receiving antennas. A multi-layered formulation is employed which encompasses an ensemble of discrete particles comprising an arbitrary mixture of ice crystals, melting snow and raindrops that may exist simultaneously along satellite-earth communication paths.

  1. Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002-2012)

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.

    2015-04-01

    We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over the contiguous United States (CONUS) for the period 2002-2012. This comparison effort includes satellite multi-sensor data sets (bias-adjusted TMPA 3B42, near-real-time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation data sets are compared with surface observations from the Global Historical Climatology Network-Daily (GHCN-D) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (±6%). However, differences at the RFC are more important in particular for near-real-time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near-real-time counterpart 3B42RT. However, large biases remained for 3B42 over the western USA for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in. day-1) over the Pacific Northwest. Furthermore, the conditional analysis and a contingency analysis conducted illustrated the challenge in retrieving extreme precipitation from remote sensing estimates.

  2. Global Precipitation Measurement. Report 7; Bridging from TRMM to GPM to 3-Hourly Precipitation Estimates

    Science.gov (United States)

    Shepherd, J. Marshall; Smith, Eric A.; Adams, W. James (Editor)

    2002-01-01

    Historically, multi-decadal measurements of precipitation from surface-based rain gauges have been available over continents. However oceans remained largely unobserved prior to the beginning of the satellite era. Only after the launch of the first Defense Meteorological Satellite Program (DMSP) satellite in 1987 carrying a well-calibrated and multi-frequency passive microwave radiometer called Special Sensor Microwave/Imager (SSM/I) have systematic and accurate precipitation measurements over oceans become available on a regular basis; see Smith et al. (1994, 1998). Recognizing that satellite-based data are a foremost tool for measuring precipitation, NASA initiated a new research program to measure precipitation from space under its Mission to Planet Earth program in the 1990s. As a result, the Tropical Rainfall Measuring Mission (TRMM), a collaborative mission between NASA and NASDA, was launched in 1997 to measure tropical and subtropical rain. See Simpson et al. (1996) and Kummerow et al. (2000). Motivated by the success of TRMM, and recognizing the need for more comprehensive global precipitation measurements, NASA and NASDA have now planned a new mission, i.e., the Global Precipitation Measurement (GPM) mission. The primary goal of GPM is to extend TRMM's rainfall time series while making substantial improvements in precipitation observations, specifically in terms of measurement accuracy, sampling frequency, Earth coverage, and spatial resolution. This report addresses four fundamental questions related to the transition from current to future global precipitation observations as denoted by the TRMM and GPM eras, respectively.

  3. Spatio-Temporal Analysis of the Accuracy of Tropical Multisatellite Precipitation Analysis 3B42 Precipitation Data in Mid-High Latitudes of China

    Science.gov (United States)

    Cai, Yancong; Jin, Changjie; Wang, Anzhi; Guan, Dexin; Wu, Jiabing; Yuan, Fenghui; Xu, Leilei

    2015-01-01

    Satellite-based precipitation data have contributed greatly to quantitatively forecasting precipitation, and provides a potential alternative source for precipitation data allowing researchers to better understand patterns of precipitation over ungauged basins. However, the absence of calibration satellite data creates considerable uncertainties for The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 product over high latitude areas beyond the TRMM satellites latitude band (38°NS). This study attempts to statistically assess TMPA V7 data over the region beyond 40°NS using data obtained from numerous weather stations in 1998–2012. Comparative analysis at three timescales (daily, monthly and annual scale) indicates that adoption of a monthly adjustment significantly improved correlation at a larger timescale increasing from 0.63 to 0.95; TMPA data always exhibits a slight overestimation that is most serious at a daily scale (the absolute bias is 103.54%). Moreover, the performance of TMPA data varies across all seasons. Generally, TMPA data performs best in summer, but worst in winter, which is likely to be associated with the effects of snow/ice-covered surfaces and shortcomings of precipitation retrieval algorithms. Temporal and spatial analysis of accuracy indices suggest that the performance of TMPA data has gradually improved and has benefited from upgrades; the data are more reliable in humid areas than in arid regions. Special attention should be paid to its application in arid areas and in winter with poor scores of accuracy indices. Also, it is clear that the calibration can significantly improve precipitation estimates, the overestimation by TMPA in TRMM-covered area is about a third as much as that in no-TRMM area for monthly and annual precipitation. The systematic evaluation of TMPA over mid-high latitudes provides a broader understanding of satellite-based precipitation estimates, and these data are

  4. Spatio-temporal analysis of the accuracy of tropical multisatellite precipitation analysis 3B42 precipitation data in mid-high latitudes of China.

    Directory of Open Access Journals (Sweden)

    Yancong Cai

    Full Text Available Satellite-based precipitation data have contributed greatly to quantitatively forecasting precipitation, and provides a potential alternative source for precipitation data allowing researchers to better understand patterns of precipitation over ungauged basins. However, the absence of calibration satellite data creates considerable uncertainties for The Tropical Rainfall Measuring Mission (TRMM Multisatellite Precipitation Analysis (TMPA 3B42 product over high latitude areas beyond the TRMM satellites latitude band (38°NS. This study attempts to statistically assess TMPA V7 data over the region beyond 40°NS using data obtained from numerous weather stations in 1998-2012. Comparative analysis at three timescales (daily, monthly and annual scale indicates that adoption of a monthly adjustment significantly improved correlation at a larger timescale increasing from 0.63 to 0.95; TMPA data always exhibits a slight overestimation that is most serious at a daily scale (the absolute bias is 103.54%. Moreover, the performance of TMPA data varies across all seasons. Generally, TMPA data performs best in summer, but worst in winter, which is likely to be associated with the effects of snow/ice-covered surfaces and shortcomings of precipitation retrieval algorithms. Temporal and spatial analysis of accuracy indices suggest that the performance of TMPA data has gradually improved and has benefited from upgrades; the data are more reliable in humid areas than in arid regions. Special attention should be paid to its application in arid areas and in winter with poor scores of accuracy indices. Also, it is clear that the calibration can significantly improve precipitation estimates, the overestimation by TMPA in TRMM-covered area is about a third as much as that in no-TRMM area for monthly and annual precipitation. The systematic evaluation of TMPA over mid-high latitudes provides a broader understanding of satellite-based precipitation estimates, and these

  5. Japanese Global Precipitation Measurement (GPM) mission status and application of satellite-based global rainfall map

    Science.gov (United States)

    Kachi, Misako; Shimizu, Shuji; Kubota, Takuji; Yoshida, Naofumi; Oki, Riko; Kojima, Masahiro; Iguchi, Toshio; Nakamura, Kenji

    2010-05-01

    . Collaboration with GCOM-W is not only limited to its participation to GPM constellation but also coordination in areas of algorithm development and validation in Japan. Generation of high-temporal and high-accurate global rainfall map is one of targets of the GPM mission. As a proto-type for GPM era, JAXA has developed and operates the Global Precipitation Map algorithm in near-real-time since October 2008, and hourly and 0.1-degree resolution binary data and images available at http://sharaku.eorc.jaxa.jp/GSMaP/ four hours after observation. The algorithms are based on outcomes from the Global Satellite Mapping for Precipitation (GSMaP) project, which was sponsored by the Japan Science and Technology Agency (JST) under the Core Research for Evolutional Science and Technology (CREST) framework between 2002 and 2007 (Okamoto et al., 2005; Aonashi et al., 2009; Ushio et al., 2009). Target of GSMaP project is to produce global rainfall maps that are highly accurate and in high temporal and spatial resolution through the development of rain rate retrieval algorithms based on reliable precipitation physical models by using several microwave radiometer data, and comprehensive use of precipitation radar and geostationary infrared imager data. Near-real-time GSMaP data is distributed via internet and utilized by end users. Purpose of data utilization by each user covers broad areas and in world wide; Science researches (model validation, data assimilation, typhoon study, etc.), weather forecast/service, flood warning and rain analysis over river basin, oceanographic condition forecast, agriculture, and education. Toward the GPM era, operational application should be further emphasized as well as science application. JAXA continues collaboration with hydrological communities to utilize satellite-based precipitation data as inputs to future flood prediction and warning system, as well as with meteorological agencies to proceed further data utilization in numerical weather prediction

  6. Seasonal to Interannual Variability of Satellite-Based Precipitation Estimates in the Pacific Ocean Associated with ENSO from 1998 to 2014

    Directory of Open Access Journals (Sweden)

    Xueyan Hou

    2016-10-01

    Full Text Available Based on a widely used satellite precipitation product (TRMM Multi-satellite Precipitation Analysis 3B43, we analyzed the spatiotemporal variability of precipitation over the Pacific Ocean for 1998–2014 at seasonal and interannual timescales, separately, using the conventional empirical orthogonal function (EOF and investigated the seasonal patterns associated with El Niño–Southern Oscillation (ENSO cycles using season-reliant empirical orthogonal function (SEOF analysis. Lagged correlation analysis was also applied to derive the lead/lag correlations of the first two SEOF modes for precipitation with Pacific Decadal Oscillation (PDO and two types of El Niño, i.e., central Pacific (CP El Niño and eastern Pacific (EP El Niño. We found that: (1 The first two seasonal EOF modes for precipitation represent the annual cycle of precipitation variations for the Pacific Ocean and the first interannual EOF mode shows the spatiotemporal variability associated with ENSO; (2 The first SEOF mode for precipitation is simultaneously associated with the development of El Niño and most likely coincides with CP El Niño. The second SEOF mode lagged behind ENSO by one year and is associated with post-El Niño years. PDO modulates precipitation variability significantly only when ENSO occurs by strengthening and prolonging the impacts of ENSO; (3 Seasonally evolving patterns of the first two SEOF modes represent the consecutive precipitation patterns associated with the entire development of EP El Niño and the following recovery year. The most significant variation occurs over the tropical Pacific, especially in the Intertropical Convergence Zone (ITCZ and South Pacific Convergence Zone (SPCZ; (4 Dry conditions in the western basin of the warm pool and wet conditions along the ITCZ and SPCZ bands during the mature phase of El Niño are associated with warm sea surface temperatures in the central tropical Pacific, and a subtropical anticyclone dominating

  7. The trend of the multi-scale temporal variability of precipitation in Colorado River Basin

    Science.gov (United States)

    Jiang, P.; Yu, Z.

    2011-12-01

    Hydrological problems like estimation of flood and drought frequencies under future climate change are not well addressed as a result of the disability of current climate models to provide reliable prediction (especially for precipitation) shorter than 1 month. In order to assess the possible impacts that multi-scale temporal distribution of precipitation may have on the hydrological processes in Colorado River Basin (CRB), a comparative analysis of multi-scale temporal variability of precipitation as well as the trend of extreme precipitation is conducted in four regions controlled by different climate systems. Multi-scale precipitation variability including within-storm patterns and intra-annual, inter-annual and decadal variabilities will be analyzed to explore the possible trends of storm durations, inter-storm periods, average storm precipitation intensities and extremes under both long-term natural climate variability and human-induced warming. Further more, we will examine the ability of current climate models to simulate the multi-scale temporal variability and extremes of precipitation. On the basis of these analyses, a statistical downscaling method will be developed to disaggregate the future precipitation scenarios which will provide a more reliable and finer temporal scale precipitation time series for hydrological modeling. Analysis results and downscaling results will be presented.

  8. Validating GPM-based Multi-satellite IMERG Products Over South Korea

    Science.gov (United States)

    Wang, J.; Petersen, W. A.; Wolff, D. B.; Ryu, G. H.

    2017-12-01

    Accurate precipitation estimates derived from space-borne satellite measurements are critical for a wide variety of applications such as water budget studies, and prevention or mitigation of natural hazards caused by extreme precipitation events. This study validates the near-real-time Early Run, Late Run and the research-quality Final Run Integrated Multi-Satellite Retrievals for GPM (IMERG) using Korean Quantitative Precipitation Estimation (QPE). The Korean QPE data are at a 1-hour temporal resolution and 1-km by 1-km spatial resolution, and were developed by Korea Meteorological Administration (KMA) from a Real-time ADjusted Radar-AWS (Automatic Weather Station) Rainrate (RAD-RAR) system utilizing eleven radars over the Republic of Korea. The validation is conducted by comparing Version-04A IMERG (Early, Late and Final Runs) with Korean QPE over the area (124.5E-130.5E, 32.5N-39N) at various spatial and temporal scales during March 2014 through November 2016. The comparisons demonstrate the reasonably good ability of Version-04A IMERG products in estimating precipitation over South Korea's complex topography that consists mainly of hills and mountains, as well as large coastal plains. Based on this data, the Early Run, Late Run and Final Run IMERG precipitation estimates higher than 0.1mm h-1 are about 20.1%, 7.5% and 6.1% higher than Korean QPE at 0.1o and 1-hour resolutions. Detailed comparison results are available at https://wallops-prf.gsfc.nasa.gov/KoreanQPE.V04/index.html

  9. A multi-source precipitation approach to fill gaps over a radar precipitation field

    Science.gov (United States)

    Tesfagiorgis, K. B.; Mahani, S. E.; Khanbilvardi, R.

    2012-12-01

    Satellite Precipitation Estimates (SPEs) may be the only available source of information for operational hydrologic and flash flood prediction due to spatial limitations of radar and gauge products. The present work develops an approach to seamlessly blend satellite, radar, climatological and gauge precipitation products to fill gaps over ground-based radar precipitation fields. To mix different precipitation products, the bias of any of the products relative to each other should be removed. For bias correction, the study used an ensemble-based method which aims to estimate spatially varying multiplicative biases in SPEs using a radar rainfall product. Bias factors were calculated for a randomly selected sample of rainy pixels in the study area. Spatial fields of estimated bias were generated taking into account spatial variation and random errors in the sampled values. A weighted Successive Correction Method (SCM) is proposed to make the merging between error corrected satellite and radar rainfall estimates. In addition to SCM, we use a Bayesian spatial method for merging the gap free radar with rain gauges, climatological rainfall sources and SPEs. We demonstrate the method using SPE Hydro-Estimator (HE), radar- based Stage-II, a climatological product PRISM and rain gauge dataset for several rain events from 2006 to 2008 over three different geographical locations of the United States. Results show that: the SCM method in combination with the Bayesian spatial model produced a precipitation product in good agreement with independent measurements. The study implies that using the available radar pixels surrounding the gap area, rain gauge, PRISM and satellite products, a radar like product is achievable over radar gap areas that benefits the scientific community.

  10. Characterising volcanic cycles at Soufriere Hills Volcano, Montserrat: Time series analysis of multi-parameter satellite data

    Science.gov (United States)

    Flower, Verity J. B.; Carn, Simon A.

    2015-10-01

    The identification of cyclic volcanic activity can elucidate underlying eruption dynamics and aid volcanic hazard mitigation. Whilst satellite datasets are often analysed individually, here we exploit the multi-platform NASA A-Train satellite constellation to cross-correlate cyclical signals identified using complementary measurement techniques at Soufriere Hills Volcano (SHV), Montserrat. In this paper we present a Multi-taper (MTM) Fast Fourier Transform (FFT) analysis of coincident SO2 and thermal infrared (TIR) satellite measurements at SHV facilitating the identification of cyclical volcanic behaviour. These measurements were collected by the Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) (respectively) in the A-Train. We identify a correlating cycle in both the OMI and MODIS data (54-58 days), with this multi-week feature attributable to episodes of dome growth. The 50 day cycles were also identified in ground-based SO2 data at SHV, confirming the validity of our analysis and further corroborating the presence of this cycle at the volcano. In addition a 12 day cycle was identified in the OMI data, previously attributed to variable lava effusion rates on shorter timescales. OMI data also display a one week (7-8 days) cycle attributable to cyclical variations in viewing angle resulting from the orbital characteristics of the Aura satellite. Longer period cycles possibly relating to magma intrusion were identified in the OMI record (102-, 121-, and 159 days); in addition to a 238-day cycle identified in the MODIS data corresponding to periodic destabilisation of the lava dome. Through the analysis of reconstructions generated from cycles identified in the OMI and MODIS data, periods of unrest were identified, including the major dome collapse of 20th May 2006 and significant explosive event of 3rd January 2009. Our analysis confirms the potential for identification of cyclical volcanic activity through combined

  11. Geographically weighted regression based methods for merging satellite and gauge precipitation

    Science.gov (United States)

    Chao, Lijun; Zhang, Ke; Li, Zhijia; Zhu, Yuelong; Wang, Jingfeng; Yu, Zhongbo

    2018-03-01

    Real-time precipitation data with high spatiotemporal resolutions are crucial for accurate hydrological forecasting. To improve the spatial resolution and quality of satellite precipitation, a three-step satellite and gauge precipitation merging method was formulated in this study: (1) bilinear interpolation is first applied to downscale coarser satellite precipitation to a finer resolution (PS); (2) the (mixed) geographically weighted regression methods coupled with a weighting function are then used to estimate biases of PS as functions of gauge observations (PO) and PS; and (3) biases of PS are finally corrected to produce a merged precipitation product. Based on the above framework, eight algorithms, a combination of two geographically weighted regression methods and four weighting functions, are developed to merge CMORPH (CPC MORPHing technique) precipitation with station observations on a daily scale in the Ziwuhe Basin of China. The geographical variables (elevation, slope, aspect, surface roughness, and distance to the coastline) and a meteorological variable (wind speed) were used for merging precipitation to avoid the artificial spatial autocorrelation resulting from traditional interpolation methods. The results show that the combination of the MGWR and BI-square function (MGWR-BI) has the best performance (R = 0.863 and RMSE = 7.273 mm/day) among the eight algorithms. The MGWR-BI algorithm was then applied to produce hourly merged precipitation product. Compared to the original CMORPH product (R = 0.208 and RMSE = 1.208 mm/hr), the quality of the merged data is significantly higher (R = 0.724 and RMSE = 0.706 mm/hr). The developed merging method not only improves the spatial resolution and quality of the satellite product but also is easy to implement, which is valuable for hydrological modeling and other applications.

  12. PoPSat: The Polar Precipitation Satellite Mission

    Science.gov (United States)

    Binder, Matthias J.; Agten, Dries; Arago-Higueras, Nadia; Borderies, Mary; Diaz-Schümmer, Carlos; Jamali, Maryam; Jimenez-Lluva, David; Kiefer, Joshua; Larsson, Anna; Lopez-Gilabert, Lola; Mione, Michele; Mould, Toby JD; Pavesi, Sara; Roth, Georg; Tomicic, Maja

    2017-04-01

    The terrestrial water cycle is one of many unique regulatory systems on planet Earth. It is directly responsible for sustaining biological life on land and human populations by ensuring sustained crop yields. However, this delicate balanced system continues to be influenced significantly by a changing climate, which has had drastic impacts particularly on the polar regions. Precipitation is a key process in the weather and climate system, due to its storage, transport and release of latent heat in the atmosphere. It has been extensively investigated in low latitudes, in which detailed models have been established for weather prediction. However, a gap has been left in higher latitudes above 65°, which show the strongest response to climate changes and where increasing precipitations have been foreseen in the future. In order to establish a global perspective of atmospheric processes, space observation of high-latitude areas is crucial to produce globally consistent data. The increasing demand for those data has driven a critical need to devise a mission which fills the gaps in current climate models. The authors propose the Polar Precipitation Satellite (PoPSat), an innovative satellite mission to provide enhanced observation of light and medium precipitation, focusing on snowfall and light rain in high latitudes. PoPSat is the first mission aimed to provide high resolution 3D structural information about snow and light precipitation systems and cloud structure in the covered areas. The satellite is equipped with a dual band (Ka and W band) phased-array radar. These antennas provide a horizontal resolution of 2 km and 4 km respectively which will exceed all other observations made to date at high-latitudes, while providing the additional capability to monitor snowfall. The data gathered will be compatible and complementary with measurements made during previous missions. PoPSat has been designed to fly on a sun-synchronous, dawn-dusk orbit at 460 km. This orbit

  13. Online Assessment of Satellite-Derived Global Precipitation Products

    Science.gov (United States)

    Liu, Zhong; Ostrenga, D.; Teng, W.; Kempler, S.

    2012-01-01

    Precipitation is difficult to measure and predict. Each year droughts and floods cause severe property damages and human casualties around the world. Accurate measurement and forecast are important for mitigation and preparedness efforts. Significant progress has been made over the past decade in satellite precipitation product development. In particular, products' spatial and temporal resolutions as well as timely availability have been improved by blended techniques. Their resulting products are widely used in various research and applications. However biases and uncertainties are common among precipitation products and an obstacle exists in quickly gaining knowledge of product quality, biases and behavior at a local or regional scale, namely user defined areas or points of interest. Current online inter-comparison and validation services have not addressed this issue adequately. To address this issue, we have developed a prototype to inter-compare satellite derived daily products in the TRMM Online Visualization and Analysis System (TOVAS). Despite its limited functionality and datasets, users can use this tool to generate customized plots within the United States for 2005. In addition, users can download customized data for further analysis, e.g. comparing their gauge data. To meet increasing demands, we plan to increase the temporal coverage and expanded the spatial coverage from the United States to the globe. More products have been added as well. In this poster, we present two new tools: Inter-comparison of 3B42RT and 3B42 Inter-comparison of V6 and V7 TRMM L-3 monthly products The future plans include integrating IPWG (International Precipitation Working Group) Validation Algorithms/statistics, allowing users to generate customized plots and data. In addition, we will expand the current daily products to monthly and their climatology products. Whenever the TRMM science team changes their product version number, users would like to know the differences by

  14. Satellite-Enhanced Regional Downscaling for Applied Studies: Extreme Precipitation Events in Southeastern South America

    Science.gov (United States)

    Nunes, A.; Gomes, G.; Ivanov, V. Y.

    2016-12-01

    Frequently found in southeastern South America during the warm season from October through May, strong and localized precipitation maxima are usually associated with the presence of mesoscale convective complexes (MCCs) travelling across the region. Flashfloods and landslides can be caused by these extremes in precipitation, with damages to the local communities. Heavily populated, southeastern South America hosts many agricultural activities and hydroelectric production. It encompasses one of the most important river basins in South America, the La Plata River Basin. Therefore, insufficient precipitation is equally prejudicial to the region socio-economic activities. MCCs are originated in the warm season of many regions of the world, however South American MCCs are related to the most severe thunderstorms, and have significantly contributed to the precipitation regime. We used the hourly outputs of Satellite-enhanced Regional Downscaling for Applied Studies (SRDAS), developed at the Federal University of Rio de Janeiro in Brazil, in the analysis of the dynamics and physical characteristics of MCCs in South America. SRDAS is the 25-km resolution downscaling of a global reanalysis available from January 1998 through December 2010. The Regional Spectral Model is the SRDAS atmospheric component and assimilates satellite-based precipitation estimates from the NOAA/Climate Prediction Center MORPHing technique global precipitation analyses. In this study, the SRDAS atmospheric and land-surface variables, global reanalysis products, infrared satellite imagery, and the physical retrievals from the Atmospheric Infrared Sounder (AIRS), on board of the NASA's Aqua satellite, were used in the evaluation of the MCCs developed in southeastern South America from 2008 and 2010. Low-level circulations and vertical profiles were analyzed together to establish the relevance of the moisture transport in connection with the upper-troposphere dynamics to the development of those MCCs.

  15. Ionospheric response to daytime auroral electron precipitation: Results and analysis of a coordinated experiment between the AUREOL-3 satellite and the EISCAT radar

    International Nuclear Information System (INIS)

    Stamnes, K.; Roble, R.G.

    1986-01-01

    On June 2, 1982 the Soviet-French polar orbiting satellite AUREOL-3 passed over the EISCAT facility in northern Scandinavia. The EISCAT UHF radar measured electron and ion temperatures, electron density and ion composition, while the satellite measured the incident auroral particle spectra (protons and electrons) presumably giving rise to the densities and temperatures inferred from the radar data. The link between the satellite data obtained well above the atmosphere (at about 1300 km), and the radar measurements is an auroral model that simulates the ionospheric response to auroral particle precipitation and solar EUV radiation and makes predictions of ionospheric properties that 1) can be measured by the radar and 2) are the consequence of the satellite-observed particle precipitation. The analysis shows that there is good agreement between model-predicted and radar-inferred electron and ion temperatures and ion composition. However, inference of the ion composition from the radar data is a non-trivial and time-consuming undertaking which requires very good data (i.e. long integration times). Our initial attempts at analyzing the radar data with a fixed ion composition (as commonly practiced) which greatly simplifies the analysis yielded poor agreement between model predictions and radar measurements. Thus, our analysis demonstrates that the proper ion composition is crucial in order to obtain reliable temperature and density results from the measured autocorrelation functions

  16. Multi-Satellite Synergy for Aerosol Analysis in the Asian Monsoon Region

    Science.gov (United States)

    Ichoku, Charles; Petrenko, Maksym

    2012-01-01

    Atmospheric aerosols represent one of the greatest uncertainties in environmental and climate research, particularly in tropical monsoon regions such as the Southeast Asian regions, where significant contributions from a variety of aerosol sources and types is complicated by unstable atmospheric dynamics. Although aerosols are now routinely retrieved from multiple satellite Sensors, in trying to answer important science questions about aerosol distribution, properties, and impacts, researchers often rely on retrievals from only one or two sensors, thereby running the risk of incurring biases due to sensor/algorithm peculiarities. We are conducting detailed studies of aerosol retrieval uncertainties from various satellite sensors (including Terra-/ Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, SeaWiFS, and Calipso-CALIOP), based on the collocation of these data products over AERONET and other important ground stations, within the online Multi-sensor Aerosol Products Sampling System (MAPSS) framework that was developed recently. Such analyses are aimed at developing a synthesis of results that can be utilized in building reliable unified aerosol information and climate data records from multiple satellite measurements. In this presentation, we will show preliminary results of. an integrated comparative uncertainly analysis of aerosol products from multiple satellite sensors, particularly focused on the Asian Monsoon region, along with some comparisons from the African Monsoon region.

  17. Geostationary Satellite Observation of Precipitable Water Vapor Using an Empirical Orthogonal Function (EOF based Reconstruction Technique over Eastern China

    Directory of Open Access Journals (Sweden)

    Man Sing Wong

    2015-05-01

    Full Text Available Water vapor, as one of the most important greenhouse gases, is crucial for both climate and atmospheric studies. Considering the high spatial and temporal variations of water vapor, a timely and accurate retrieval of precipitable water vapor (PWV is urgently needed, but has long been constrained by data availability. Our study derived the vertically integrated precipitable water vapor over eastern China using Multi-functional Transport Satellite (MTSAT data, which is in geostationary orbit with high temporal resolution. The missing pixels caused by cloud contamination were reconstructed using an Empirical Orthogonal Function (EOF decomposition method over both spatial and temporal dimensions. GPS meteorology data were used to validate the retrieval and the reconstructed results. The diurnal variation of PWV over eastern China was analyzed using harmonic analysis, which indicates that the reconstructed PWV data can depict the diurnal cycle of PWV caused by evapotranspiration and local thermal circulation.

  18. Global Precipitation Measurement (GPM) Mission: Overview and Status

    Science.gov (United States)

    Hou, Arthur Y.

    2012-01-01

    The Global Precipitation Measurement (GPM) Mission is an international satellite mission specifically designed to unify and advance precipitation measurements from a constellation of research and operational microwave sensors. NASA and JAXA will deploy a Core Observatory in 2014 to serve as a reference satellite to unify precipitation measurements from the constellation of sensors. The GPM Core Observatory will carry a Ku/Ka-band Dual-frequency Precipitation Radar (DPR) and a conical-scanning multi-channel (10-183 GHz) GPM Microwave Radiometer (GMI). The DPR will be the first dual-frequency radar in space to provide not only measurements of 3-D precipitation structures but also quantitative information on microphysical properties of precipitating particles. The DPR and GMI measurements will together provide a database that relates vertical hydrometeor profiles to multi-frequency microwave radiances over a variety of environmental conditions across the globe. This combined database will be used as a common transfer standard for improving the accuracy and consistency of precipitation retrievals from all constellation radiometers. For global coverage, GPM relies on existing satellite programs and new mission opportunities from a consortium of partners through bilateral agreements with either NASA or JAXA. Each constellation member may have its unique scientific or operational objectives but contributes microwave observations to GPM for the generation and dissemination of unified global precipitation data products. In addition to the DPR and GMI on the Core Observatory, the baseline GPM constellation consists of the following sensors: (1) Special Sensor Microwave Imager/Sounder (SSMIS) instruments on the U.S. Defense Meteorological Satellite Program (DMSP) satellites, (2) the Advanced Microwave Scanning Radiometer-2 (AMSR-2) on the GCOM-W1 satellite of JAXA, (3) the Multi-Frequency Microwave Scanning Radiometer (MADRAS) and the multi-channel microwave humidity sounder

  19. Precipitation Estimation Using Combined Radar/Radiometer Measurements Within the GPM Framework

    Science.gov (United States)

    Hou, Arthur

    2012-01-01

    The Global Precipitation Measurement (GPM) Mission is an international satellite mission specifically designed to unify and advance precipitation measurements from a constellation of research and operational microwave sensors. The GPM mission centers upon the deployment of a Core Observatory in a 65o non-Sun-synchronous orbit to serve as a physics observatory and a transfer standard for intersatellite calibration of constellation radiometers. The GPM Core Observatory will carry a Ku/Ka-band Dual-frequency Precipitation Radar (DPR) and a conical-scanning multi-channel (10-183 GHz) GPM Microwave Radiometer (GMI). The DPR will be the first dual-frequency radar in space to provide not only measurements of 3-D precipitation structures but also quantitative information on microphysical properties of precipitating particles needed for improving precipitation retrievals from microwave sensors. The DPR and GMI measurements will together provide a database that relates vertical hydrometeor profiles to multi-frequency microwave radiances over a variety of environmental conditions across the globe. This combined database will be used as a common transfer standard for improving the accuracy and consistency of precipitation retrievals from all constellation radiometers. For global coverage, GPM relies on existing satellite programs and new mission opportunities from a consortium of partners through bilateral agreements with either NASA or JAXA. Each constellation member may have its unique scientific or operational objectives but contributes microwave observations to GPM for the generation and dissemination of unified global precipitation data products. In addition to the DPR and GMI on the Core Observatory, the baseline GPM constellation consists of the following sensors: (1) Special Sensor Microwave Imager/Sounder (SSMIS) instruments on the U.S. Defense Meteorological Satellite Program (DMSP) satellites, (2) the Advanced Microwave Scanning Radiometer-2 (AMSR-2) on the GCOM-W1

  20. Tropical Rainfall Analysis Using TRMM in Combination With Other Satellite Gauge Data: Comparison with Global Precipitation Climatology Project (GPCP) Results

    Science.gov (United States)

    Adler, Robert F.; Huffman, George J.; Bolvin, David; Nelkin, Eric; Curtis, Scott

    1999-01-01

    This paper describes recent results of using Tropical Rainfall Measuring Mission (TRMM) information as the key calibration tool in a merged analysis on a 1 deg x 1 deg latitude/longitude monthly scale based on multiple satellite sources and raingauge analysis. The procedure used to produce the GPCP data set is a stepwise approach which first combines the satellite low-orbit microwave and geosynchronous IR observations into a "multi-satellite" product and than merges that result with the raingauge analysis. Preliminary results produced with the still-stabilizing TRMM algorithms indicate that TRMM shows tighter spatial gradients in tropical rain maxima with higher peaks in the center of the maxima. The TRMM analyses will be used to evaluate the evolution of the 1998 ENSO variations, again in comparison with the GPCP analyses.

  1. Seasonal analysis of precipitation, drought and Vegetation index in Indonesian paddy field based on remote sensing data

    International Nuclear Information System (INIS)

    Darmawan, S; Takeuchi, W; Shofiyati, R; Sari, D K; Wikantika, K

    2014-01-01

    Paddy field is important agriculture crop in Indonesia. Rice is a food staple for 237,6 million Indonesian people. Paddy field growth is strongly influenced by water, but the amount of precipitation is unpredictable. Annual and interannual climate variability in Indonesia is unusual. In recent years remote sensing data has been used for measurement and monitoring of precipitation, drought and Vegetation index such as Global Satellite Mapping of Precipitation (GSMaP), Multi-purpose Transmission SATellite (MTSAT) and Moderate Resolution Imaging Spectroradiometer (MODIS). The objective of this research is to investigate seasonal variability of precipitation, drought and Vegetation index in Indonesian paddy field based on remote sensing data. The methodology consists of collecting of enhanced vegetation index (EVI) from MODIS data, mosaicking of image, collecting of region of interest of paddy field, collecting of precipitation and drought index based on Keetch Bryam Drought Index (KBDI) from GSMaP and MTSAT, and seasonal analysis. The result of this research has showed seasonal variability of precipitation, KBDI and EVI on Indonesia paddy field from 2007 until 2012. Precipitation begins from January until May and October until December, and KBDI begins to increase from June and peak in September only in South Sumatera precipitation almost in all month. Seasonal analysis has showed precipitation and KBDI affect on EVI that can indicate variety phenology of Indonesian paddy field. Peak of EVI occurs before peak of KBDI occurs and increasing of KBDI followed by decreasing of EVI. In 2010 all province got higher precipitation and smaller KBDI so EVI has three peaks such as in West Java that can indicated increasing of rice production

  2. CDRD and PNPR satellite passive microwave precipitation retrieval algorithms: EuroTRMM/EURAINSAT origins and H-SAF operations

    Science.gov (United States)

    Mugnai, A.; Smith, E. A.; Tripoli, G. J.; Bizzarri, B.; Casella, D.; Dietrich, S.; Di Paola, F.; Panegrossi, G.; Sanò, P.

    2013-04-01

    Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) is a EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) program, designed to deliver satellite products of hydrological interest (precipitation, soil moisture and snow parameters) over the European and Mediterranean region to research and operations users worldwide. Six satellite precipitation algorithms and concomitant precipitation products are the responsibility of various agencies in Italy. Two of these algorithms have been designed for maximum accuracy by restricting their inputs to measurements from conical and cross-track scanning passive microwave (PMW) radiometers mounted on various low Earth orbiting satellites. They have been developed at the Italian National Research Council/Institute of Atmospheric Sciences and Climate in Rome (CNR/ISAC-Rome), and are providing operational retrievals of surface rain rate and its phase properties. Each of these algorithms is physically based, however, the first of these, referred to as the Cloud Dynamics and Radiation Database (CDRD) algorithm, uses a Bayesian-based solution solver, while the second, referred to as the PMW Neural-net Precipitation Retrieval (PNPR) algorithm, uses a neural network-based solution solver. Herein we first provide an overview of the two initial EU research and applications programs that motivated their initial development, EuroTRMM and EURAINSAT (European Satellite Rainfall Analysis and Monitoring at the Geostationary Scale), and the current H-SAF program that provides the framework for their operational use and continued development. We stress the relevance of the CDRD and PNPR algorithms and their precipitation products in helping secure the goals of H-SAF's scientific and operations agenda, the former helpful as a secondary calibration reference to other algorithms in H-SAF's complete mix of algorithms. Descriptions of the algorithms' designs are provided

  3. CDRD and PNPR satellite passive microwave precipitation retrieval algorithms: EuroTRMM/EURAINSAT origins and H-SAF operations

    Directory of Open Access Journals (Sweden)

    A. Mugnai

    2013-04-01

    Full Text Available Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF is a EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites program, designed to deliver satellite products of hydrological interest (precipitation, soil moisture and snow parameters over the European and Mediterranean region to research and operations users worldwide. Six satellite precipitation algorithms and concomitant precipitation products are the responsibility of various agencies in Italy. Two of these algorithms have been designed for maximum accuracy by restricting their inputs to measurements from conical and cross-track scanning passive microwave (PMW radiometers mounted on various low Earth orbiting satellites. They have been developed at the Italian National Research Council/Institute of Atmospheric Sciences and Climate in Rome (CNR/ISAC-Rome, and are providing operational retrievals of surface rain rate and its phase properties. Each of these algorithms is physically based, however, the first of these, referred to as the Cloud Dynamics and Radiation Database (CDRD algorithm, uses a Bayesian-based solution solver, while the second, referred to as the PMW Neural-net Precipitation Retrieval (PNPR algorithm, uses a neural network-based solution solver. Herein we first provide an overview of the two initial EU research and applications programs that motivated their initial development, EuroTRMM and EURAINSAT (European Satellite Rainfall Analysis and Monitoring at the Geostationary Scale, and the current H-SAF program that provides the framework for their operational use and continued development. We stress the relevance of the CDRD and PNPR algorithms and their precipitation products in helping secure the goals of H-SAF's scientific and operations agenda, the former helpful as a secondary calibration reference to other algorithms in H-SAF's complete mix of algorithms. Descriptions of the algorithms' designs are

  4. On the performance of satellite precipitation products in riverine flood modeling: A review

    Science.gov (United States)

    Maggioni, Viviana; Massari, Christian

    2018-03-01

    This work is meant to summarize lessons learned on using satellite precipitation products for riverine flood modeling and to propose future directions in this field of research. Firstly, the most common satellite precipitation products (SPPs) during the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM) eras are reviewed. Secondly, we discuss the main errors and uncertainty sources in these datasets that have the potential to affect streamflow and runoff model simulations. Thirdly, past studies that focused on using SPPs for predicting streamflow and runoff are analyzed. As the impact of floods depends not only on the characteristics of the flood itself, but also on the characteristics of the region (population density, land use, geophysical and climatic factors), a regional analysis is required to assess the performance of hydrologic models in monitoring and predicting floods. The performance of SPP-forced hydrological models was shown to largely depend on several factors, including precipitation type, seasonality, hydrological model formulation, topography. Across several basins around the world, the bias in SPPs was recognized as a major issue and bias correction methods of different complexity were shown to significantly reduce streamflow errors. Model re-calibration was also raised as a viable option to improve SPP-forced streamflow simulations, but caution is necessary when recalibrating models with SPP, which may result in unrealistic parameter values. From a general standpoint, there is significant potential for using satellite observations in flood forecasting, but the performance of SPP in hydrological modeling is still inadequate for operational purposes.

  5. The Global Precipitation Climatology Project (GPCP) Combined Precipitation Dataset

    Science.gov (United States)

    Huffman, George J.; Adler, Robert F.; Arkin, Philip; Chang, Alfred; Ferraro, Ralph; Gruber, Arnold; Janowiak, John; McNab, Alan; Rudolf, Bruno; Schneider, Udo

    1997-01-01

    The Global Precipitation Climatology Project (GPCP) has released the GPCP Version 1 Combined Precipitation Data Set, a global, monthly precipitation dataset covering the period July 1987 through December 1995. The primary product in the dataset is a merged analysis incorporating precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit -satellite infrared data, and rain gauge observations. The dataset also contains the individual input fields, a combination of the microwave and infrared satellite estimates, and error estimates for each field. The data are provided on 2.5 deg x 2.5 deg latitude-longitude global grids. Preliminary analyses show general agreement with prior studies of global precipitation and extends prior studies of El Nino-Southern Oscillation precipitation patterns. At the regional scale there are systematic differences with standard climatologies.

  6. First evaluation of the utility of GPM precipitation in global flood monitoring

    Science.gov (United States)

    Wu, H.; Yan, Y.; Gao, Z.

    2017-12-01

    The Global Flood Monitoring System (GFMS) has been developed and used to provide real-time flood detection and streamflow estimates over the last few years with significant success shown by validation against global flood event data sets and observed streamflow variations (Wu et al., 2014). It has become a tool for various national and international organizations to appraise flood conditions in various areas, including where rainfall and hydrology information is limited. The GFMS has been using the TRMM Multi-satellite Precipitation Analysis (TMPA) as its main rainfall input. Now, with the advent of the Global Precipitation Measurement (GPM) mission there is an opportunity to significantly improve global flood monitoring and forecasting. GPM's Integrated Multi-satellitE Retrievals for GPM (IMERG) multi-satellite product is designed to take advantage of various technical advances in the field and combine that with an efficient processing system producing "early" (4 hrs) and "late" (12 hrs) products for operational use. Specifically, this study is focused on (1) understanding the difference between the new IMERG products and other existing satellite precipitation products, e.g., TMPA, CMORPH, and ground observations; (2) addressing the challenge in the usage of the IMERG for flood monitoring through hydrologic models, given that only a short period of precipitation data record has been accumulated since the lunch of GPM in 2014; and (3) comparing the statistics of flood simulation based on the DRIVE model with IMERG, TMPA, CMORPH etc. as precipitation inputs respectively. Derivation of a global threshold map is a necessary step to define flood events out of modelling results, which requires a relatively longer historic information. A set of sensitivity tests are conducted by adjusting IMERG's light, moderate, heavy rain to existing precipitation products with long-term records separately, to optimize the strategy of PDF matching. Other aspects are also examined

  7. Improving precipitation estimates over the western United States using GOES-R precipitation data

    Science.gov (United States)

    Karbalaee, N.; Kirstetter, P. E.; Gourley, J. J.

    2017-12-01

    Satellite remote sensing data with fine spatial and temporal resolution are widely used for precipitation estimation for different applications such as hydrological modeling, storm prediction, and flash flood monitoring. The Geostationary Operational Environmental Satellites-R series (GOES-R) is the next generation of environmental satellites that provides hydrologic, atmospheric, and climatic information every 30 seconds over the western hemisphere. The high-resolution and low-latency of GOES-R observations is essential for the monitoring and prediction of floods, specifically in the Western United States where the vantage point of space can complement the degraded weather radar coverage of the NEXRAD network. The GOES-R rainfall rate algorithm will yield deterministic quantitative precipitation estimates (QPE). Accounting for inherent uncertainties will further advance the GOES-R QPEs since with quantifiable error bars, the rainfall estimates can be more readily fused with ground radar products. On the ground, the high-resolution NEXRAD-based precipitation estimation from the Multi-Radar/Multi-Sensor (MRMS) system, which is now operational in the National Weather Service (NWS), is challenged due to a lack of suitable coverage of operational weather radars over complex terrain. Distribution of QPE uncertainties associated with the GOES-R deterministic retrievals are derived and analyzed using MRMS over regions with good radar coverage. They will be merged with MRMS-based probabilistic QPEs developed to advance multisensor QPE integration. This research aims at improving precipitation estimation over the CONUS by combining the observations from GOES-R and MRMS to provide consistent, accurate and fine resolution precipitation rates with uncertainties over the CONUS.

  8. Capabilities and uncertainties of aircraft measurements for the validation of satellite precipitation products – a virtual case study

    Directory of Open Access Journals (Sweden)

    Andrea Lammert

    2015-08-01

    Full Text Available Remote sensing sensors on board of research aircraft provide detailed measurements of clouds and precipitation which can be used as reference data to validate satellite products. Such satellite derived precipitation data using passive microwave radiometers with a resolution of typically 50×50km2$50\\times50\\,\\text{km}^2$ stands against high spatial and temporal resolved airborne measurements, but only along a chosen line. This paper focuses on analysis on the uncertainty arising from the different spatial resolution and coverage. Therefore we use a perfect model approach, with a high resolved forecast model yielding perfect virtual aircraft and satellite observations. The mean precipitation and standard deviation per satellite box were estimated with a Gaussian approach. The comparison of the mean values shows a high correlation of 0.92, but a very wide spread. As criterion to define good agreement between satellite mean and reference, we choose a deviation of one standard deviation of the virtual aircraft as threshold. Considering flight tracks in the range of 50 km (one overflight, the perfect agreement of satellite and aircraft observations is only detected in 65 % of the cases. To increase this low reliability the precipitation distributions of the virtual aircraft were fitted by a gamma density function. Using the same quality criterion, the usage of gamma density fit yields an improvement of the Aircraft reliability up to 80 %.

  9. Evaluation of NWP-based Satellite Precipitation Error Correction with Near-Real-Time Model Products and Flood-inducing Storms

    Science.gov (United States)

    Zhang, X.; Anagnostou, E. N.; Schwartz, C. S.

    2017-12-01

    Satellite precipitation products tend to have significant biases over complex terrain. Our research investigates a statistical approach for satellite precipitation adjustment based solely on numerical weather simulations. This approach has been evaluated in two mid-latitude (Zhang et al. 2013*1, Zhang et al. 2016*2) and three topical mountainous regions by using the WRF model to adjust two high-resolution satellite products i) National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center morphing technique (CMORPH) and ii) Global Satellite Mapping of Precipitation (GSMaP). Results show the adjustment effectively reduces the satellite underestimation of high rain rates, which provides a solid proof-of-concept for continuing research of NWP-based satellite correction. In this study we investigate the feasibility of using NCAR Real-time Ensemble Forecasts*3 for adjusting near-real-time satellite precipitation datasets over complex terrain areas in the Continental United States (CONUS) such as Olympic Peninsula, California coastal mountain ranges, Rocky Mountains and South Appalachians. The research will focus on flood-inducing storms occurred from May 2015 to December 2016 and four satellite precipitation products (CMORPH, GSMaP, PERSIANN-CCS and IMERG). The error correction performance evaluation will be based on comparisons against the gauge-adjusted Stage IV precipitation data. *1 Zhang, Xinxuan, et al. "Using NWP simulations in satellite rainfall estimation of heavy precipitation events over mountainous areas." Journal of Hydrometeorology 14.6 (2013): 1844-1858. *2 Zhang, Xinxuan, et al. "Hydrologic Evaluation of NWP-Adjusted CMORPH Estimates of Hurricane-Induced Precipitation in the Southern Appalachians." Journal of Hydrometeorology 17.4 (2016): 1087-1099. *3 Schwartz, Craig S., et al. "NCAR's experimental real-time convection-allowing ensemble prediction system." Weather and Forecasting 30.6 (2015): 1645-1654.

  10. Variability of Evaporation and Precipitation over the Ocean from Satellite Data

    Science.gov (United States)

    Malinin, V. N.; Gordeeva, S. M.

    2017-12-01

    HOAPS-3 and PMWC satellite archives for 1988-2008 are used to estimate moisture-exchange components between the ocean and atmosphere (evaporation, precipitation, and the difference between them or effective evaporation). Moisture-exchange components for the entire World Ocean and for the North Atlantic Ocean within 30°-60° N are calculated. A strong overestimation of the global values of effective evaporation by HOAPS data (mainly caused by a decrease in precipitation) is shown. In the interannual variability of effective evaporation, there is clearly an overestimated positive trend, which contradicts the real increase in the Global Sea Level. Large systematic errors in moisture-exchange components are revealed for the North Atlantic water area. According to HOAPS data, there is a significant underestimation of evaporation and effective evaporation. According to PMWC data, the amount of precipitation is significantly overestimated and evaporation is underestimated. As a consequence, effective evaporation becomes negative, which is impossible. Low accuracy in the estimation of moisture-exchange components and the need to improve old estimates and develop new evaporation and precipitation databases based on satellite data are noted.

  11. Hydrological modeling of the Peruvian–Ecuadorian Amazon Basin using GPM-IMERG satellite-based precipitation dataset

    Directory of Open Access Journals (Sweden)

    R. Zubieta

    2017-07-01

    Full Text Available In the last two decades, rainfall estimates provided by the Tropical Rainfall Measurement Mission (TRMM have proven applicable in hydrological studies. The Global Precipitation Measurement (GPM mission, which provides the new generation of rainfall estimates, is now considered a global successor to TRMM. The usefulness of GPM data in hydrological applications, however, has not yet been evaluated over the Andean and Amazonian regions. This study uses GPM data provided by the Integrated Multi-satellite Retrievals (IMERG (product/final run as input to a distributed hydrological model for the Amazon Basin of Peru and Ecuador for a 16-month period (from March 2014 to June 2015 when all datasets are available. TRMM products (TMPA V7 and TMPA RT datasets and a gridded precipitation dataset processed from observed rainfall are used for comparison. The results indicate that precipitation data derived from GPM-IMERG correspond more closely to TMPA V7 than TMPA RT datasets, but both GPM-IMERG and TMPA V7 precipitation data tend to overestimate, compared to observed rainfall (by 11.1 and 15.7 %, respectively. In general, GPM-IMERG, TMPA V7 and TMPA RT correlate with observed rainfall, with a similar number of rain events correctly detected ( ∼  20 %. Statistical analysis of modeled streamflows indicates that GPM-IMERG is as useful as TMPA V7 or TMPA RT datasets in southern regions (Ucayali Basin. GPM-IMERG, TMPA V7 and TMPA RT do not properly simulate streamflows in northern regions (Marañón and Napo basins, probably because of the lack of adequate rainfall estimates in northern Peru and the Ecuadorian Amazon.

  12. Multi-Band Multi-Tone Tunable Millimeter-Wave Frequency Synthesizer For Satellite Beacon Transmitter

    Science.gov (United States)

    Simons, Rainee N.; Wintucky, Edwin G.

    2016-01-01

    This paper presents the design and test results of a multi-band multi-tone tunable millimeter-wave frequency synthesizer, based on a solid-state frequency comb generator. The intended application of the synthesizer is in a satellite beacon transmitter for radio wave propagation studies at K-band (18 to 26.5 GHz), Q-band (37 to 42 GHz), and E-band (71 to 76 GHz). In addition, the architecture for a compact beacon transmitter, which includes the multi-tone synthesizer, polarizer, horn antenna, and power/control electronics, has been investigated for a notional space-to-ground radio wave propagation experiment payload on a small satellite. The above studies would enable the design of robust high throughput multi-Gbps data rate future space-to-ground satellite communication links.

  13. Improved nowcasting of precipitation based on convective analysis fields

    Directory of Open Access Journals (Sweden)

    T. Haiden

    2007-04-01

    Full Text Available The high-resolution analysis and nowcasting system INCA (Integrated Nowcasting through Comprehensive Analysis developed at the Austrian national weather service provides three-dimensional fields of temperature, humidity, and wind on an hourly basis, and two-dimensional fields of precipitation rate in 15 min intervals. The system operates on a horizontal resolution of 1 km and a vertical resolution of 100–200 m. It combines surface station data, remote sensing data (radar, satellite, forecast fields of the numerical weather prediction model ALADIN, and high-resolution topographic data. An important application of the INCA system is nowcasting of convective precipitation. Based on fine-scale temperature, humidity, and wind analyses a number of convective analysis fields are routinely generated. These fields include convective boundary layer (CBL flow convergence and specific humidity, lifted condensation level (LCL, convective available potential energy (CAPE, convective inhibition (CIN, and various convective stability indices. Based on the verification of areal precipitation nowcasts it is shown that the pure translational forecast of convective cells can be improved by using a decision algorithm which is based on a subset of the above fields, combined with satellite products.

  14. Local wavelet correlation: applicationto timing analysis of multi-satellite CLUSTER data

    Directory of Open Access Journals (Sweden)

    J. Soucek

    2004-12-01

    Full Text Available Multi-spacecraft space observations, such as those of CLUSTER, can be used to infer information about local plasma structures by exploiting the timing differences between subsequent encounters of these structures by individual satellites. We introduce a novel wavelet-based technique, the Local Wavelet Correlation (LWC, which allows one to match the corresponding signatures of large-scale structures in the data from multiple spacecraft and determine the relative time shifts between the crossings. The LWC is especially suitable for analysis of strongly non-stationary time series, where it enables one to estimate the time lags in a more robust and systematic way than ordinary cross-correlation techniques. The technique, together with its properties and some examples of its application to timing analysis of bow shock and magnetopause crossing observed by CLUSTER, are presented. We also compare the performance and reliability of the technique with classical discontinuity analysis methods. Key words. Radio science (signal processing – Space plasma physics (discontinuities; instruments and techniques

  15. Projected changes in precipitation intensity and frequency over complex topography: a multi-model perspective

    Science.gov (United States)

    Fischer, Andreas; Keller, Denise; Liniger, Mark; Rajczak, Jan; Schär, Christoph; Appenzeller, Christof

    2014-05-01

    Fundamental changes in the hydrological cycle are expected in a future warmer climate. This is of particular relevance for the Alpine region, as a source and reservoir of several major rivers in Europe and being prone to extreme events such as floodings. For this region, climate change assessments based on the ENSEMBLES regional climate models (RCMs) project a significant decrease in summer mean precipitation under the A1B emission scenario by the mid-to-end of this century, while winter mean precipitation is expected to slightly rise. From an impact perspective, projected changes in seasonal means, however, are often insufficient to adequately address the multifaceted challenges of climate change adaptation. In this study, we revisit the full matrix of the ENSEMBLES RCM projections regarding changes in frequency and intensity, precipitation-type (convective versus stratiform) and temporal structure (wet/dry spells and transition probabilities) over Switzerland and surroundings. As proxies for raintype changes, we rely on the model parameterized convective and large-scale precipitation components. Part of the analysis involves a Bayesian multi-model combination algorithm to infer changes from the multi-model ensemble. The analysis suggests a summer drying that evolves altitude-specific: over low-land regions it is associated with wet-day frequency decreases of convective and large-scale precipitation, while over elevated regions it is primarily associated with a decline in large-scale precipitation only. As a consequence, almost all the models project an increase in the convective fraction at elevated Alpine altitudes. The decrease in the number of wet days during summer is accompanied by decreases (increases) in multi-day wet (dry) spells. This shift in multi-day episodes also lowers the likelihood of short dry spell occurrence in all of the models. For spring and autumn the combined multi-model projections indicate higher mean precipitation intensity north of the

  16. Kriging and local polynomial methods for blending satellite-derived and gauge precipitation estimates to support hydrologic early warning systems

    Science.gov (United States)

    Verdin, Andrew; Funk, Christopher C.; Rajagopalan, Balaji; Kleiber, William

    2016-01-01

    Robust estimates of precipitation in space and time are important for efficient natural resource management and for mitigating natural hazards. This is particularly true in regions with developing infrastructure and regions that are frequently exposed to extreme events. Gauge observations of rainfall are sparse but capture the precipitation process with high fidelity. Due to its high resolution and complete spatial coverage, satellite-derived rainfall data are an attractive alternative in data-sparse regions and are often used to support hydrometeorological early warning systems. Satellite-derived precipitation data, however, tend to underrepresent extreme precipitation events. Thus, it is often desirable to blend spatially extensive satellite-derived rainfall estimates with high-fidelity rain gauge observations to obtain more accurate precipitation estimates. In this research, we use two different methods, namely, ordinary kriging and κ-nearest neighbor local polynomials, to blend rain gauge observations with the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates in data-sparse Central America and Colombia. The utility of these methods in producing blended precipitation estimates at pentadal (five-day) and monthly time scales is demonstrated. We find that these blending methods significantly improve the satellite-derived estimates and are competitive in their ability to capture extreme precipitation.

  17. Evaluating Satellite Products for Precipitation Estimation in Mountain Regions: A Case Study for Nepal

    Directory of Open Access Journals (Sweden)

    Tarendra Lakhankar

    2013-08-01

    Full Text Available Precipitation in mountain regions is often highly variable and poorly observed, limiting abilities to manage water resource challenges. Here, we evaluate remote sensing and ground station-based gridded precipitation products over Nepal against weather station precipitation observations on a monthly timescale. We find that the Tropical Rainfall Measuring Mission (TRMM 3B-43 precipitation product exhibits little mean bias and reasonable skill in giving precipitation over Nepal. Compared to station observations, the TRMM precipitation product showed an overall Nash-Sutcliffe efficiency of 0.49, which is similar to the skill of the gridded station-based product Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE. The other satellite precipitation products considered (Global Satellite Mapping of Precipitation (GSMaP, the Climate Prediction Center Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS were less skillful, as judged by Nash-Sutcliffe efficiency, and, on average, substantially underestimated precipitation compared to station observations, despite their, in some cases, higher nominal spatial resolution compared to TRMM. None of the products fully captured the dependence of mean precipitation on elevation seen in the station observations. Overall, the TRMM product is promising for use in water resources applications.

  18. Optimizing Orbit-Instrument Configuration for Global Precipitation Mission (GPM) Satellite Fleet

    Science.gov (United States)

    Smith, Eric A.; Adams, James; Baptista, Pedro; Haddad, Ziad; Iguchi, Toshio; Im, Eastwood; Kummerow, Christian; Einaudi, Franco (Technical Monitor)

    2001-01-01

    Following the scientific success of the Tropical Rainfall Measuring Mission (TRMM) spearheaded by a group of NASA and NASDA scientists, their external scientific collaborators, and additional investigators within the European Union's TRMM Research Program (EUROTRMM), there has been substantial progress towards the development of a new internationally organized, global scale, and satellite-based precipitation measuring mission. The highlights of this newly developing mission are a greatly expanded scope of measuring capability and a more diversified set of science objectives. The mission is called the Global Precipitation Mission (GPM). Notionally, GPM will be a constellation-type mission involving a fleet of nine satellites. In this fleet, one member is referred to as the "core" spacecraft flown in an approximately 70 degree inclined non-sun-synchronous orbit, somewhat similar to TRMM in that it carries both a multi-channel polarized passive microwave radiometer (PMW) and a radar system, but in this case it will be a dual frequency Ku-Ka band radar system enabling explicit measurements of microphysical DSD properties. The remainder of fleet members are eight orbit-synchronized, sun-synchronous "constellation" spacecraft each carrying some type of multi-channel PMW radiometer, enabling no worse than 3-hour diurnal sampling over the entire globe. In this configuration the "core" spacecraft serves as a high quality reference platform for training and calibrating the PMW rain retrieval algorithms used with the "constellation" radiometers. Within NASA, GPM has advanced to the pre-formulation phase which has enabled the initiation of a set of science and technology studies which will help lead to the final mission design some time in the 2003 period. This presentation first provides an overview of the notional GPM program and mission design, including its organizational and programmatic concepts, scientific agenda, expected instrument package, and basic flight

  19. An adaptive spatial model for precipitation data from multiple satellites over large regions

    KAUST Repository

    Chakraborty, Avishek

    2015-03-01

    Satellite measurements have of late become an important source of information for climate features such as precipitation due to their near-global coverage. In this article, we look at a precipitation dataset during a 3-hour window over tropical South America that has information from two satellites. We develop a flexible hierarchical model to combine instantaneous rainrate measurements from those satellites while accounting for their potential heterogeneity. Conceptually, we envision an underlying precipitation surface that influences the observed rain as well as absence of it. The surface is specified using a mean function centered at a set of knot locations, to capture the local patterns in the rainrate, combined with a residual Gaussian process to account for global correlation across sites. To improve over the commonly used pre-fixed knot choices, an efficient reversible jump scheme is used to allow the number of such knots as well as the order and support of associated polynomial terms to be chosen adaptively. To facilitate computation over a large region, a reduced rank approximation for the parent Gaussian process is employed.

  20. Satellite rainfall monitoring over Africa for food security, using multi-channel MSG data

    Science.gov (United States)

    Chadwick, R.; Grimes, D.; Saunders, R.; Blackmore, T.; Francis, P.

    2009-04-01

    Near real-time rainfall estimates are crucial in sub-Saharan Africa for a variety of humanitarian and agricultural purposes. However, for economic and infrastructural reasons, regularly reporting rain-gauges are sparse and precipitation radar networks extremely rare. Satellite rainfall estimates, particularly from geostationary satellites such as Meteosat Second Generation (MSG), present one method of filling this information gap, as they produce data at high temporal and spatial resolution. An algorithm has been developed to produce rainfall estimates for Africa from multi-channel MSG data. The algorithm is calibrated using precipitation radar data collected in Niamey, Niger as part of the African Monsoon Multidisciplinary Analyses (AMMA) project in 2006, and is based on an algorithm used operationally over Europe by the UK Met Office. Contingency tables are used to establish a statistical relationship between multi-channel MSG data and probability of rainfall at several different rain-rate magnitudes as sensed by the radar. Rain-rate estimates can then be produced at a variety of spatial and temporal scales, with MSG scan length (15 minutes) and pixel size (3-4km) as the lower limit. Results will be presented of a validation of this algorithm over the Sahel region of Africa. Rainfall estimates from this algorithm, processed for 2004, will be validated against gridded rain-gauge data at a 0.5 degree and 10 day timescale suitable for drought monitoring purposes. A comparison will also be made against rainfall estimates from the TAMSAT algorithm, which uses single channel IR data from MSG, and has been shown to perform well in the Sahel region.

  1. Spectrum and power allocation in cognitive multi-beam satellite communications with flexible satellite payloads

    Science.gov (United States)

    Liu, Zhihui; Wang, Haitao; Dong, Tao; Yin, Jie; Zhang, Tingting; Guo, Hui; Li, Dequan

    2018-02-01

    In this paper, the cognitive multi-beam satellite system, i.e., two satellite networks coexist through underlay spectrum sharing, is studied, and the power and spectrum allocation method is employed for interference control and throughput maximization. Specifically, the multi-beam satellite with flexible payload reuses the authorized spectrum of the primary satellite, adjusting its transmission band as well as power for each beam to limit its interference on the primary satellite below the prescribed threshold and maximize its own achievable rate. This power and spectrum allocation problem is formulated as a mixed nonconvex programming. For effective solving, we first introduce the concept of signal to leakage plus noise ratio (SLNR) to decouple multiple transmit power variables in the both objective and constraint, and then propose a heuristic algorithm to assign spectrum sub-bands. After that, a stepwise plus slice-wise algorithm is proposed to implement the discrete power allocation. Finally, simulation results show that adopting cognitive technology can improve spectrum efficiency of the satellite communication.

  2. Hydrologic Evaluation of TRMM Multisatellite Precipitation Analysis for Nanliu River Basin in Humid Southwestern China.

    Science.gov (United States)

    Zhao, Yinjun; Xie, Qiongying; Lu, Yuan; Hu, Baoqing

    2017-06-01

    The accuracy of Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis (TMPA) daily accumulated precipitation products (3B42RTV7 and 3B42V7) was evaluated for a small basin (the Nanliu river basin). A direct comparison was performed against gauge observations from a period of 9 years (2000-2009) at temporal and spatial scales. The results show that the temporal-spatial precipitation characteristics of the Nanliu river basin are highly consistent with 3B42V7 relative to 3B42RTV7, with higher correlation coefficient (CC) approximately 0.9 at all temporal scales except for the daily scale and a lower relative bias percentage. 3B42V7 slightly overestimates precipitation at all temporal scales except the yearly scale; it slightly underestimates the precipitation at the daily spatial scale. The results also reveal that the precision of TMPA products increases with longer time-aggregated data, and the detection capability of daily TMPA precipitation products are enhanced by augmentation with daily precipitation rates. In addition, daily TMPA products were input into the Xin'anjiang hydrologic model; the results show that 3B42V7-based simulated outputs were well in line with actual stream flow observations, with a high CC (0.90) and Nash-Sutcliffe efficiency coefficient (NSE, 0.79), and the results adequately captured the pattern of the observed flow curve.

  3. Validation of satellite based precipitation over diverse topography of Pakistan

    Science.gov (United States)

    Iqbal, Muhammad Farooq; Athar, H.

    2018-03-01

    This study evaluates the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) product data with 0.25° × 0.25° spatial and post-real-time 3 h temporal resolution using point-based Surface Precipitation Gauge (SPG) data from 40 stations, for the period 1998-2013, and using gridded Asian Precipitation ˗ Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) data abbreviated as APH data with 0.25° × 0.25° spatial and daily temporal resolution for the period 1998-2007, over vulnerable and data sparse regions of Pakistan (24-37° N and 62-75° E). To evaluate the performance of TMPA relative to SPG and APH, four commonly used statistical indicator metrics including Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Correlation Coefficient (CC) are employed on daily, monthly, seasonal as well as on annual timescales. The TMPA slightly overestimated both SPG and APH at daily, monthly, and annual timescales, however close results were obtained between TMPA and SPG as compared to those between TMPA and APH, on the same timescale. The TMPA overestimated both SPG and APH during the Pre-Monsoon and Monsoon seasons, whereas it underestimated during the Post-Monsoon and Winter seasons, with different magnitudes. Agreement between TMPA and SPG was good in plain and medium elevation regions, whereas TMPA overestimated APH in 31 stations. The magnitudes of MAE and RMSE were high at daily timescale as compared to monthly and annual timescales. Relatively large MAE was observed in stations located over high elevation regions, whereas minor MAE was recorded in plain area stations at daily, monthly, and annual timescales. A strong positive linear relationship between TMPA and SPG was established at monthly (0.98), seasonal (0.93 to 0.98) and annual (0.97) timescales. Precipitation increased with the increase of elevation, and not only elevation but latitude also affected the

  4. Validation of an semi-automated multi component method using protein precipitation LC-MS-MS for the analysis of whole blood samples

    DEFF Research Database (Denmark)

    Slots, Tina

    BACKGROUND: Solid phase extraction (SPE) are one of many multi-component methods, but can be very time-consuming and labour-intensive. Protein precipitation is, on the other hand, a much simpler and faster sample pre-treatment than SPE, and protein precipitation also has the ability to cover a wi......-mortem whole blood sample preparation for toxicological analysis; from the primary sample tube to a 96-deepwell plate ready for injection on the liquid chromatography mass spectrometry (LC-MS/MS)....

  5. A review of the PERSIANN family global satellite precipitation data products

    Science.gov (United States)

    Nguyen, P.; Ombadi, M.; Ashouri, H.; Thorstensen, A.; Hsu, K. L.; Braithwaite, D.; Sorooshian, S.; William, L.

    2017-12-01

    Precipitation is an integral part of the hydrologic cycle and plays an important role in the water and energy balance of the Earth. Careful and consistent observation of precipitation is important for several reasons. Over the last two decades, the PERSIANN system of precipitation products have been developed at the Center for Hydrometeorology and Remote Sensing (CHRS) at the University of California, Irvine in collaboration with NASA, NOAA and the UNESCO G-WADI program. The PERSIANN family includes three main satellite-based precipitation estimation products namely PERSIANN, PERSIANN-CCS, and PERSIANN-CDR. They are accessible through several web-based interfaces maintained by CHRS to serve the needs of researchers, professionals and general public. These interfaces are CHRS iRain, Data Portal and RainSphere, which can be accessed at http://irain.eng.uci.edu, http://chrsdata.eng.uci.edu, and http://rainsphere.eng.uci.edu respectively and can be used for visualization, analysis or download of the data. The main objective of this presentation is to provide a concise and clear summary of the similarities and differences between the three products in terms of attributes and algorithm structure. Moreover, the presentation aims to provide an evaluation of the performance of the products over the Contiguous United States (CONUS) using Climate Prediction Center (CPC) precipitation dataset as a baseline of comparison. Also, an assessment of the behavior of PERSIANN family products over the globe (60°S - 60°N) is performed.

  6. Evaluation of TRMM satellite-based precipitation indexes for flood forecasting over Riyadh City, Saudi Arabia

    Science.gov (United States)

    Tekeli, Ahmet Emre; Fouli, Hesham

    2016-10-01

    Floods are among the most common disasters harming humanity. In particular, flash floods cause hazards to life, property and any type of structures. Arid and semi-arid regions are equally prone to flash floods like regions with abundant rainfall. Despite rareness of intensive and frequent rainfall events over Kingdom of Saudi Arabia (KSA); an arid/semi-arid region, occasional flash floods occur and result in large amounts of damaging surface runoff. The flooding of 16 November, 2013 in Riyadh; the capital city of KSA, resulted in killing some people and led to much property damage. The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) Real Time (RT) data (3B42RT) are used herein for flash flood forecasting. 3B42RT detected high-intensity rainfall events matching with the distribution of observed floods over KSA. A flood early warning system based on exceedance of threshold limits on 3B42RT data is proposed for Riyadh. Three different indexes: Constant Threshold (CT), Cumulative Distribution Functions (CDF) and Riyadh Flood Precipitation Index (RFPI) are developed using 14-year 3B42RT data from 2000 to 2013. RFPI and CDF with 90% captured the three major flooding events that occurred in February 2005, May 2010 and November 2013 in Riyadh. CT with 3 mm/h intensity indicated the 2013 flooding, but missed those of 2005 and 2010. The methodology implemented herein is a first-step simple and accurate way for flash flood forecasting over Riyadh. The simplicity of the methodology enables its applicability for the TRMM follow-on missions like Global Precipitation Measurement (GPM) mission.

  7. A statistical method to get surface level air-temperature from satellite observations of precipitable water

    Digital Repository Service at National Institute of Oceanography (India)

    Pankajakshan, T.; Shikauchi, A; Sugimori, Y.; Kubota, M.

    -T a and precipitable water. The rms errors of the SSMI-T a , in this case are found to be reduced to 1.0°C. 1. Introduction Satellite derived surface-level meteorological parameters are considered to be a better alternative to sparse ship... Vol. 49, pp. 551 to 558. 1993 A Statistical Method to Get Surface Level Air-Temperature from Satellite Observations of Precipitable Water PANKAJAKSHAN THADATHIL*, AKIRA SHIKAUCHI, YASUHIRO SUGIMORI and MASAHISA KUBOTA School of Marine Science...

  8. A Space-Based Perspective of the 2017 Hurricane Season from the Global Precipitation Measurement (GPM) Mission

    Science.gov (United States)

    Skofronick Jackson, G.; Petersen, W. A.; Huffman, G. J.; Kirschbaum, D.; Wolff, D. B.; Tan, J.; Zavodsky, B.

    2017-12-01

    The Global Precipitation Measurement (GPM) mission collected unique, near real time 3-D satellite-based views of hurricanes in 2017 together with estimated precipitation accumulation using merged satellite data for scientific studies and societal applications. Central to GPM is the NASA-JAXA GPM Core Observatory (CO). The GPM-CO carries an advanced dual-frequency precipitation radar (DPR) and a well-calibrated, multi-frequency passive microwave radiometer that together serve as an on orbit reference for precipitation measurements made by the international GPM satellite constellation. GPM-CO overpasses of major Hurricanes such as Harvey, Irma, Maria, and Ophelia revealed intense convective structures in DPR radar reflectivity together with deep ice-phase microphysics in both the eyewalls and outer rain bands. Of considerable scientific interest, and yet to be determined, will be DPR-diagnosed characteristics of the rain drop size distribution as a function of convective structure, intensity and microphysics. The GPM-CO active/passive suite also provided important decision support information. For example, the National Hurricane Center used GPM-CO observations as a tool to inform track and intensity estimates in their forecast briefings. Near-real-time rainfall accumulation from the Integrated Multi-satellitE Retrievals for GPM (IMERG) was also provided via the NASA SPoRT team to Puerto Rico following Hurricane Maria when ground-based radar systems on the island failed. Comparisons between IMERG, NOAA Multi-Radar Multi-Sensor data, and rain gauge rainfall accumulations near Houston, Texas during Hurricane Harvey revealed spatial biases between ground and IMERG satellite estimates, and a general underestimation of IMERG rain accumulations associated with infrared observations, collectively illustrating the difficulty of measuring rainfall in hurricanes.GPM data continue to advance scientific research on tropical cyclone intensification and structure, and contribute to

  9. Assessment of the Latest GPM-Era High-Resolution Satellite Precipitation Products by Comparison with Observation Gauge Data over the Chinese Mainland

    Directory of Open Access Journals (Sweden)

    Shaowei Ning

    2016-10-01

    Full Text Available The Global Precipitation Mission (GPM Core Observatory that was launched on 27 February 2014 ushered in a new era for estimating precipitation from satellites. Based on their high spatial–temporal resolution and near global coverage, satellite-based precipitation products have been applied in many research fields. The goal of this study was to quantitatively compare two of the latest GPM-era satellite precipitation products (GPM IMERG and GSMap-Gauge Ver. 6 with a network of 840 precipitation gauges over the Chinese mainland. Direct comparisons of satellite-based precipitation products with rain gauge observations over a 20 month period from April 2014 to November 2015 at 0.1° and daily/monthly resolutions showed the following results: Both of the products were capable of capturing the overall spatial pattern of the 20 month mean daily precipitation, which was characterized by a decreasing trend from the southeast to the northwest. GPM IMERG overestimated precipitation by approximately 0.09 mm/day while GSMap-Gauge Ver. 6 underestimated precipitation by −0.04 mm/day. The two satellite-based precipitation products performed better over wet southern regions than over dry northern regions. They also showed better performance in summer than in winter. In terms of mean error, root mean square error, correlation coefficient, and probability of detection, GSMap-Gauge was better able to estimate precipitation and had more stable quality results than GPM IMERG on both daily and monthly scales. GPM IMERG was more sensitive to conditions of no rain or light rainfall and demonstrated good capability of capturing the behavior of extreme precipitation events. Overall, the results revealed some limitations of these two latest satellite-based precipitation products when used over the Chinese mainland, helping to characterize some of the error features in these datasets for potential users.

  10. Statistical evaluation of the performance of gridded monthly precipitation products from reanalysis data, satellite estimates, and merged analyses over China

    Science.gov (United States)

    Deng, Xueliang; Nie, Suping; Deng, Weitao; Cao, Weihua

    2018-04-01

    In this study, we compared the following four different gridded monthly precipitation products: the National Centers for Environmental Prediction version 2 (NCEP-2) reanalysis data, the satellite-based Climate Prediction Center Morphing technique (CMORPH) data, the merged satellite-gauge Global Precipitation Climatology Project (GPCP) data, and the merged satellite-gauge-model data from the Beijing Climate Center Merged Estimation of Precipitation (BMEP). We evaluated the performances of these products using monthly precipitation observations spanning the period of January 2003 to December 2013 from a dense, national, rain gauge network in China. Our assessment involved several statistical techniques, including spatial pattern, temporal variation, bias, root-mean-square error (RMSE), and correlation coefficient (CC) analysis. The results show that NCEP-2, GPCP, and BMEP generally overestimate monthly precipitation at the national scale and CMORPH underestimates it. However, all of the datasets successfully characterized the northwest to southeast increase in the monthly precipitation over China. Because they include precipitation gauge information from the Global Telecommunication System (GTS) network, GPCP and BMEP have much smaller biases, lower RMSEs, and higher CCs than NCEP-2 and CMORPH. When the seasonal and regional variations are considered, NCEP-2 has a larger error over southern China during the summer. CMORPH poorly reproduces the magnitude of the precipitation over southeastern China and the temporal correlation over western and northwestern China during all seasons. BMEP has a lower RMSE and higher CC than GPCP over eastern and southern China, where the station network is dense. In contrast, BMEP has a lower CC than GPCP over western and northwestern China, where the gauge network is relatively sparse.

  11. Electron precipitation burst in the nighttime slot region measured simultaneously from two satellites

    International Nuclear Information System (INIS)

    Imhof, W.L.; Voss, H.D.; Mobilla, J.; Gaines, E.E.; Evans, D.S.

    1987-01-01

    Based on data acquired in 1982 with the Stimulated Emission of Energetic Particles payload on the low-altitude (170--280 km) S81-1 spacecraft and the Space Environment Monitor instrumentation on the NOAA 6 satellite (800--830 km), a study has been made of short-duration nighttime electron precipitation bursts at L = 2.0--35. From 54 passes of each satellite across the slot region simultaneously in time, 21 bursts were observed on the NOAA 6 spacecraft, and 76 on the S81-1 satellite. Five events, probably associated with lightning, were observed simultaneously from the two spacecraft within 1.2 s, providing a measure of the spatial extent of the bursts. This limited sample indicates that the intensity of precipitation events falls off with width in longitude and L shell but individual events extend as much as 5 0 in invariant latitude and 43 0 in longitude. The number of events above a given flux observed in each satellite was found to be approximately inversely proportional to the flux. The time average energy input to the atmosphere over the longitude range 180 0 E to 360 0 E at a local time of 2230 directly from short-duration bursts spanning a wide range of intensity enhancements was estimated to be about 6 x 10/sup -6/ ergs/cm 2 s in the northern hemisphere and about 1.5 x 10/sup -5/ ergs/cm 2 s in the southern hemisphere. In the south, this energy precipitation rate is lower than that from electrons in the drift loss cone by about 2 orders of magnitude. However, on the basis of these data alone we cannot discount weak bursts from being a major contributor to populating the drift loss cone with electrons which ultimately precipitate into the atmosphere. copyrightAmerican Geophysical Union 1987

  12. Assessment of GPM-IMERG and Other Precipitation Products against Gauge Data under Different Topographic and Climatic Conditions in Iran: Preliminary Results

    Directory of Open Access Journals (Sweden)

    Ehsan Sharifi

    2016-02-01

    Full Text Available The new generation of weather observatory satellites, namely Global Precipitation Measurement (GPM constellation satellites, is the lead observatory of the 10 highly advanced earth orbiting weather research satellites. Indeed, GPM is the first satellite that has been designed to measure light rain and snowfall, in addition to heavy tropical rainfall. This work compares the final run of the Integrated Multi-satellitE Retrievals for GPM (IMERG product, the post real time of TRMM and Multi-satellite Precipitation Analysis (TMPA-3B42 and the Era-Interim product from the European Centre for Medium Range Weather Forecasts (ECMWF against the Iran Meteorological Organization (IMO daily precipitation measured by the synoptic rain-gauges over four regions with different topography and climate conditions in Iran. Assessment is implemented for a one-year period from March 2014 to February 2015. Overall, in daily scale the results reveal that all three products lead to underestimation but IMERG performs better than other products and underestimates precipitation slightly in all four regions. Based on monthly and seasonal scale, in Guilan all products, in Bushehr and Kermanshah ERA-Interim and in Tehran IMERG and ERA-Interim tend to underestimate. The correlation coefficient between IMERG and the rain-gauge data in daily scale is far superior to that of Era-Interim and TMPA-3B42. On the basis of daily timescale of bias in comparison with the ground data, the IMERG product far outperforms ERA-Interim and 3B42 products. According to the categorical verification technique in this study, IMERG yields better results for detection of precipitation events on the basis of Probability of Detection (POD, Critical Success Index (CSI and False Alarm Ratio (FAR in those areas with stratiform and orographic precipitation, such as Tehran and Kermanshah, compared with other satellite/model data sets. In particular, for heavy precipitation (>15 mm/day, IMERG is superior to

  13. Multi-GNSS orbit determination using satellite laser ranging

    Science.gov (United States)

    Bury, Grzegorz; Sośnica, Krzysztof; Zajdel, Radosław

    2018-04-01

    Galileo, BeiDou, QZSS, and NavIC are emerging global navigation satellite systems (GNSSs) and regional navigation satellite systems all of which are equipped with laser retroreflector arrays for range measurements. This paper summarizes the GNSS-intensive tracking campaigns conducted by the International Laser Ranging Service and provides results from multi-GNSS orbit determination using solely SLR observations. We consider the whole constellation of GLONASS, all active Galileo, four BeiDou satellites: 1 MEO, 3 IGSO, and one QZSS. We analyze the influence of the number of SLR observations on the quality of the 3-day multi-GNSS orbit solution. About 60 SLR observations are needed for obtaining MEO orbits of sufficient quality with the root mean square (RMS) of 3 cm for the radial component when compared to microwave-based orbits. From the analysis of a minimum number of tracking stations, when considering the 3-day arcs, 5 SLR stations do not provide a sufficient geometry of observations. The solution obtained using ten stations is characterized with RMS of 4, 9, and 18 cm in the radial, along-track, and cross-track direction, respectively, for MEO satellites. We also investigate the impact of the length of orbital arc on the quality of SLR-derived orbits. Hence, 5- and 7-day arcs constitute the best solution, whereas 3-day arcs are of inferior quality due to an insufficient number of SLR observations and 9-day arcs deteriorate the along-track component. The median RMS from the comparison between 7-day orbital arcs determined using SLR data with microwave-based orbits assumes values in the range of 3-4, 11-16, and 15-27 cm in radial, along-track, and cross-track, respectively, for MEO satellites. BeiDou IGSO and QZSS are characterized by RMS values higher by a factor of 8 and 24, respectively, than MEO orbits.

  14. Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational 1-Norm Regularization in the Derivative Domain

    Science.gov (United States)

    Foufoula-Georgiou, E.; Ebtehaj, A. M.; Zhang, S. Q.; Hou, A. Y.

    2013-01-01

    The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall),and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients(called 1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a database of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case

  15. Multi precursors analysis associated with the powerful Ecuador (MW = 7.8) earthquake of 16 April 2016 using Swarm satellites data in conjunction with other multi-platform satellite and ground data

    Science.gov (United States)

    Akhoondzadeh, Mehdi; De Santis, Angelo; Marchetti, Dedalo; Piscini, Alessandro; Cianchini, Gianfranco

    2018-01-01

    After DEMETER satellite mission (2004-2010), the launch of the Swarm satellites (Alpha (A), Bravo (B) and Charlie (C)) has created a new opportunity in the study of earthquake ionospheric precursors. Nowadays, there is no doubt that multi precursors analysis is a necessary phase to better understand the LAIC (Lithosphere Atmosphere Ionosphere Coupling) mechanism before large earthquakes. In this study, using absolute scalar magnetometer, vector field magnetometer and electric field instrument on board Swarm satellites, GPS (Global Positioning System) measurements, MODIS-Aqua satellite and ECMWF (European Centre for Medium-Range Weather Forecasts) data, the variations of the electron density and temperature, magnetic field, TEC (Total Electron Content), LST (Land Surface Temperature), AOD (Aerosol Optical Depth) and SKT (SKin Temperature) have been surveyed to find the potential seismic anomalies around the strong Ecuador (Mw = 7.8) earthquake of 16 April 2016. The four solar and geomagnetic indices: F10.7, Dst, Kp and ap were investigated to distinguish whether the preliminary detected anomalies might be associated with the solar-geomagnetic activities instead of the seismo-ionospheric anomalies. The Swarm satellites (A, B and C) data analysis indicate the anomalies in time series of electron density variations on 7, 11 and 12 days before the event; the unusual variations in time series of electron temperature on 8 days preceding the earthquake; the analysis of the magnetic field scalar and vectors data show the considerable anomalies 52, 48, 23, 16, 11, 9 and 7 days before the main shock. A striking anomaly is detected in TEC variations on 1 day before earthquake at 9:00 UTC. The analysis of MODIS-Aqua night-time images shows that LST increase unusually on 11 days prior to main shock. In addition, the AOD variations obtained from MODIS measurements reach the maximum value on 10 days before the earthquake. The SKT around epicentral region presents anomalous higher

  16. Software defined radio (SDR) architecture for concurrent multi-satellite communications

    Science.gov (United States)

    Maheshwarappa, Mamatha R.

    SDRs have emerged as a viable approach for space communications over the last decade by delivering low-cost hardware and flexible software solutions. The flexibility introduced by the SDR concept not only allows the realisation of concurrent multiple standards on one platform, but also promises to ease the implementation of one communication standard on differing SDR platforms by signal porting. This technology would facilitate implementing reconfigurable nodes for parallel satellite reception in Mobile/Deployable Ground Segments and Distributed Satellite Systems (DSS) for amateur radio/university satellite operations. This work outlines the recent advances in embedded technologies that can enable new communication architectures for concurrent multi-satellite or satellite-to-ground missions where multi-link challenges are associated. This research proposes a novel concept to run advanced parallelised SDR back-end technologies in a Commercial-Off-The-Shelf (COTS) embedded system that can support multi-signal processing for multi-satellite scenarios simultaneously. The initial SDR implementation could support only one receiver chain due to system saturation. However, the design was optimised to facilitate multiple signals within the limited resources available on an embedded system at any given time. This was achieved by providing a VHDL solution to the existing Python and C/C++ programming languages along with parallelisation so as to accelerate performance whilst maintaining the flexibility. The improvement in the performance was validated at every stage through profiling. Various cases of concurrent multiple signals with different standards such as frequency (with Doppler effect) and symbol rates were simulated in order to validate the novel architecture proposed in this research. Also, the architecture allows the system to be reconfigurable by providing the opportunity to change the communication standards in soft real-time. The chosen COTS solution provides a

  17. Satellite Imagery Analysis for Automated Global Food Security Forecasting

    Science.gov (United States)

    Moody, D.; Brumby, S. P.; Chartrand, R.; Keisler, R.; Mathis, M.; Beneke, C. M.; Nicholaeff, D.; Skillman, S.; Warren, M. S.; Poehnelt, J.

    2017-12-01

    The recent computing performance revolution has driven improvements in sensor, communication, and storage technology. Multi-decadal remote sensing datasets at the petabyte scale are now available in commercial clouds, with new satellite constellations generating petabytes/year of daily high-resolution global coverage imagery. Cloud computing and storage, combined with recent advances in machine learning, are enabling understanding of the world at a scale and at a level of detail never before feasible. We present results from an ongoing effort to develop satellite imagery analysis tools that aggregate temporal, spatial, and spectral information and that can scale with the high-rate and dimensionality of imagery being collected. We focus on the problem of monitoring food crop productivity across the Middle East and North Africa, and show how an analysis-ready, multi-sensor data platform enables quick prototyping of satellite imagery analysis algorithms, from land use/land cover classification and natural resource mapping, to yearly and monthly vegetative health change trends at the structural field level.

  18. The Relationships Between Insoluble Precipitation Residues, Clouds, and Precipitation Over California's Southern Sierra Nevada During Winter Storms

    Science.gov (United States)

    Creamean, Jessie M.; White, Allen B.; Minnis, Patrick; Palikonda, Rabindra; Spangenberg, Douglas A.; Prather, Kimberly A.

    2016-01-01

    Ice formation in orographic mixed-phase clouds can enhance precipitation and depends on the type of aerosols that serve as ice nucleating particles (INP). The resulting precipitation from these clouds is a viable source of water, especially for regions such as the California Sierra Nevada. Thus, a better understanding of the sources of INP that impact orographic clouds is important for assessing water availability in California. This study presents a multi-site, multi-year analysis of single particle insoluble residues in precipitation samples that likely influenced cloud ice and precipitation formation above Yosemite National Park. Dust and biological particles represented the dominant fraction of the residues (64% on average). Cloud glaciation, determined using GOES satellite observations, not only depended on high cloud tops (greater than 6.2 km) and low temperatures (less than -26 C), but also on the composition of the dust and biological residues. The greatest prevalence of ice-phase clouds occurred in conjunction with biologically-rich residues and mineral dust rich in calcium, followed by iron and aluminosilicates. Dust and biological particles are known to be efficient INP, thus these residues are what likely influenced ice formation in clouds above the sites and subsequent precipitation quantities reaching the surface during events with similar meteorology. The goal of this study is to use precipitation chemistry information to gain a better understanding of the potential sources of INP in the south-central Sierra Nevada, where cloud-aerosol-precipitation interactions are under-studied and where mixed-phase orographic clouds represent a key element in the generation of precipitation and thus the water supply in California.

  19. Evaluation of high-resolution satellite precipitation products with surface rain gauge observations from Laohahe Basin in northern China

    Directory of Open Access Journals (Sweden)

    Shan-hu Jiang

    2010-12-01

    Full Text Available Three high-resolution satellite precipitation products, the Tropical Rainfall Measuring Mission (TRMM standard precipitation products 3B42V6 and 3B42RT and the Climate Precipitation Center's (CPC morphing technique precipitation product (CMORPH, were evaluated against surface rain gauge observations from the Laohahe Basin in northern China. Widely used statistical validation indices and categorical statistics were adopted. The evaluations were performed at multiple time scales, ranging from daily to yearly, for the years from 2003 to 2008. The results show that all three satellite precipitation products perform very well in detecting the occurrence of precipitation events, but there are some different biases in the amount of precipitation. 3B42V6, which has a bias of 21%, fits best with the surface rain gauge observations at both daily and monthly scales, while the biases of 3B42RT and CMORPH, with values of 81% and 67%, respectively, are much higher than a normal receivable threshold. The quality of the satellite precipitation products also shows monthly and yearly variation: 3B42RT has a large positive bias in the cold season from September to April, while CMORPH has a large positive bias in the warm season from May to August, and they all attained their best values in 2006 (with 10%, 50%, and −5% biases for 3B42V6, 3B42RT, and CMORPH, respectively. Our evaluation shows that, for the Laohahe Basin, 3B42V6 has the best correspondence with the surface observations, and CMORPH performs much better than 3B42RT. The large errors of 3B42RT and CMORPH remind us of the need for new improvements to satellite precipitation retrieval algorithms or feasible bias adjusting methods.

  20. Characterizing the spatio-temporal and energy-dependent response of riometer absorption to particle precipitation

    Science.gov (United States)

    Kellerman, Adam; Makarevich, Roman; Spanswick, Emma; Donovan, Eric; Shprits, Yuri

    2016-07-01

    Energetic electrons in the 10's of keV range precipitate to the upper D- and lower E-region ionosphere, and are responsible for enhanced ionization. The same particles are important in the inner magnetosphere, as they provide a source of energy for waves, and thus relate to relativistic electron enhancements in Earth's radiation belts.In situ observations of plasma populations and waves are usually limited to a single point, which complicates temporal and spatial analysis. Also, the lifespan of satellite missions is often limited to several years which does not allow one to infer long-term climatology of particle precipitation, important for affecting ionospheric conditions at high latitudes. Multi-point remote sensing of the ionospheric plasma conditions can provide a global view of both ionospheric and magnetospheric conditions, and the coupling between magnetospheric and ionospheric phenomena can be examined on time-scales that allow comprehensive statistical analysis. In this study we utilize multi-point riometer measurements in conjunction with in situ satellite data, and physics-based modeling to investigate the spatio-temporal and energy-dependent response of riometer absorption. Quantifying this relationship may be a key to future advancements in our understanding of the complex D-region ionosphere, and may lead to enhanced specification of auroral precipitation both during individual events and over climatological time-scales.

  1. Bias correction of daily satellite precipitation data using genetic algorithm

    Science.gov (United States)

    Pratama, A. W.; Buono, A.; Hidayat, R.; Harsa, H.

    2018-05-01

    Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) was producted by blending Satellite-only Climate Hazards Group InfraRed Precipitation (CHIRP) with Stasion observations data. The blending process was aimed to reduce bias of CHIRP. However, Biases of CHIRPS on statistical moment and quantil values were high during wet season over Java Island. This paper presented a bias correction scheme to adjust statistical moment of CHIRP using observation precipitation data. The scheme combined Genetic Algorithm and Nonlinear Power Transformation, the results was evaluated based on different season and different elevation level. The experiment results revealed that the scheme robustly reduced bias on variance around 100% reduction and leaded to reduction of first, and second quantile biases. However, bias on third quantile only reduced during dry months. Based on different level of elevation, the performance of bias correction process is only significantly different on skewness indicators.

  2. Multi-agent robotic systems and applications for satellite missions

    Science.gov (United States)

    Nunes, Miguel A.

    A revolution in the space sector is happening. It is expected that in the next decade there will be more satellites launched than in the previous sixty years of space exploration. Major challenges are associated with this growth of space assets such as the autonomy and management of large groups of satellites, in particular with small satellites. There are two main objectives for this work. First, a flexible and distributed software architecture is presented to expand the possibilities of spacecraft autonomy and in particular autonomous motion in attitude and position. The approach taken is based on the concept of distributed software agents, also referred to as multi-agent robotic system. Agents are defined as software programs that are social, reactive and proactive to autonomously maximize the chances of achieving the set goals. Part of the work is to demonstrate that a multi-agent robotic system is a feasible approach for different problems of autonomy such as satellite attitude determination and control and autonomous rendezvous and docking. The second main objective is to develop a method to optimize multi-satellite configurations in space, also known as satellite constellations. This automated method generates new optimal mega-constellations designs for Earth observations and fast revisit times on large ground areas. The optimal satellite constellation can be used by researchers as the baseline for new missions. The first contribution of this work is the development of a new multi-agent robotic system for distributing the attitude determination and control subsystem for HiakaSat. The multi-agent robotic system is implemented and tested on the satellite hardware-in-the-loop testbed that simulates a representative space environment. The results show that the newly proposed system for this particular case achieves an equivalent control performance when compared to the monolithic implementation. In terms on computational efficiency it is found that the multi

  3. Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational ℓ1-Norm Regularization in the Derivative Domain

    Science.gov (United States)

    Foufoula-Georgiou, E.; Ebtehaj, A. M.; Zhang, S. Q.; Hou, A. Y.

    2014-05-01

    The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall), and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients (called ℓ1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a data base of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case

  4. Supporting Hydrometeorological Research and Applications with Global Precipitation Measurement (GPM) Products and Services

    Science.gov (United States)

    Liu, Zhong; Ostrenga, D.; Vollmer, B.; Deshong, B.; MacRitchie, K.; Greene, M.; Kempler, S.

    2016-01-01

    Precipitation is an important dataset in hydrometeorological research and applications such as flood modeling, drought monitoring, etc. On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http:pmm.nasa.govGPM). The GPM mission consists of an international network of satellites in which a GPM Core Observatory satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data. The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). GPM products currently available include the following:1. Level-1 GPM Microwave Imager (GMI) and partner radiometer products2. Goddard Profiling Algorithm (GPROF) GMI and partner products (Level-2 and Level-3)3. GPM dual-frequency precipitation radar and their combined products (Level-2 and Level-3)4. Integrated Multi-satellitE Retrievals for GPM (IMERG) products (early, late, and final run)GPM data can be accessed through a number of data services (e.g., Simple Subset Wizard, OPeNDAP, WMS, WCS, ftp, etc.). A newly released Unified User Interface or UUI is a single interface to provide users seamless access to data, information and services. For example, a search for precipitation products will not only return TRMM and GPM products, but also other global precipitation products such as MERRA (Modern Era Retrospective-Analysis for Research and Applications), GLDAS (Global Land Data Assimilation Systems), etc.New features and capabilities have been recently added in GIOVANNI to allow exploring and inter-comparing GPM IMERG (Integrated Multi-satelliE Retrievals for GPM) half-hourly and monthly precipitation

  5. Comparison of the characteristic energy of precipitating electrons derived from ground-based and DMSP satellite data

    Directory of Open Access Journals (Sweden)

    M. Ashrafi

    2005-01-01

    Full Text Available Energy maps are important for ionosphere-magnetosphere coupling studies, because quantitative determination of field-aligned currents requires knowledge of the conductances and their spatial gradients. By combining imaging riometer absorption and all-sky auroral optical data it is possible to produce high temporal and spatial resolution maps of the Maxwellian characteristic energy of precipitating electrons within a 240240 common field of view. These data have been calibrated by inverting EISCAT electron density profiles into equivalent energy spectra. In this paper energy maps produced by ground-based instruments (optical and riometer are compared with DMSP satellite data during geomagnetic conjunctions. For the period 1995-2002, twelve satellite passes over the ground-based instruments' field of view for the cloud-free conditions have been considered. Four of the satellite conjunctions occurred during moderate geomagnetic, steady-state conditions and without any ion precipitation. In these cases with Maxwellian satellite spectra, there is 71% agreement between the characteristic energies derived from the satellite and the ground-based energy map method.

  6. Comparison of the characteristic energy of precipitating electrons derived from ground-based and DMSP satellite data

    Directory of Open Access Journals (Sweden)

    M. Ashrafi

    2005-01-01

    Full Text Available Energy maps are important for ionosphere-magnetosphere coupling studies, because quantitative determination of field-aligned currents requires knowledge of the conductances and their spatial gradients. By combining imaging riometer absorption and all-sky auroral optical data it is possible to produce high temporal and spatial resolution maps of the Maxwellian characteristic energy of precipitating electrons within a 240240 common field of view. These data have been calibrated by inverting EISCAT electron density profiles into equivalent energy spectra. In this paper energy maps produced by ground-based instruments (optical and riometer are compared with DMSP satellite data during geomagnetic conjunctions. For the period 1995-2002, twelve satellite passes over the ground-based instruments' field of view for the cloud-free conditions have been considered. Four of the satellite conjunctions occurred during moderate geomagnetic, steady-state conditions and without any ion precipitation. In these cases with Maxwellian satellite spectra, there is 71% agreement between the characteristic energies derived from the satellite and the ground-based energy map method.

  7. Monitoring of Calcite Precipitation in Hardwater Lakes with Multi-Spectral Remote Sensing Archives

    Directory of Open Access Journals (Sweden)

    Iris Heine

    2017-01-01

    Full Text Available Calcite precipitation is a common phenomenon in calcium-rich hardwater lakes during spring and summer, but the number and spatial distribution of lakes with calcite precipitation is unknown. This paper presents a remote sensing based method to observe calcite precipitation over large areas, which are an important prerequisite for a systematic monitoring and evaluation of restoration measurements. We use globally archived satellite remote sensing data for a retrospective systematic assessment of past multi-temporal calcite precipitation events. The database of this study consists of 205 data sets that comprise freely available Landsat and Sentinel 2 data acquired between 1998 and 2015 covering the Northeast German Plain. Calcite precipitation is automatically identified using the green spectra and the metric BGR area, the triangular area between the blue, green and red reflectance value. The validation is based on field measurements of CaCO3 concentrations at three selected lakes, Feldberger Haussee, Breiter Luzin and Schmaler Luzin. The classification accuracy (0.88 is highest for calcite concentrations ≥0.7 mg/L. False negative results are caused by the choice of a conservative classification threshold. False positive results can be explained by already increased calcite concentrations. We successfully transferred the developed method to 21 other hardwater lakes in Northeast Germany. The average duration of lakes with regular calcite precipitation is 37 days. The frequency of calcite precipitation reaches from single time detections up to detections nearly every year. False negative classification results and gaps in Landsat time series reduce the accuracy of frequency and duration monitoring, but in future the image density will increase by acquisitions of Sentinel-2a (and 2b. Our study tested successfully the transfer of the classification approach to Sentinel-2 images. Our study shows that 15 of the 24 lakes have at least one phase of

  8. The Goddard multi-scale modeling system with unified physics

    Directory of Open Access Journals (Sweden)

    W.-K. Tao

    2009-08-01

    Full Text Available Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1 a cloud-resolving model (CRM, (2 a regional-scale model, the NASA unified Weather Research and Forecasting Model (WRF, and (3 a coupled CRM-GCM (general circulation model, known as the Goddard Multi-scale Modeling Framework or MMF. The same cloud-microphysical processes, long- and short-wave radiative transfer and land-surface processes are applied in all of the models to study explicit cloud-radiation and cloud-surface interactive processes in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator for comparison and validation with NASA high-resolution satellite data.

    This paper reviews the development and presents some applications of the multi-scale modeling system, including results from using the multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols. In addition, use of the multi-satellite simulator to identify the strengths and weaknesses of the model-simulated precipitation processes will be discussed as well as future model developments and applications.

  9. NWP-Based Adjustment of IMERG Precipitation for Flood-Inducing Complex Terrain Storms: Evaluation over CONUS

    Directory of Open Access Journals (Sweden)

    Xinxuan Zhang

    2018-04-01

    Full Text Available This paper evaluates the use of precipitation forecasts from a numerical weather prediction (NWP model for near-real-time satellite precipitation adjustment based on 81 flood-inducing heavy precipitation events in seven mountainous regions over the conterminous United States. The study is facilitated by the National Center for Atmospheric Research (NCAR real-time ensemble forecasts (called model, the Integrated Multi-satellitE Retrievals for GPM (IMERG near-real-time precipitation product (called raw IMERG and the Stage IV multi-radar/multi-sensor precipitation product (called Stage IV used as a reference. We evaluated four precipitation datasets (the model forecasts, raw IMERG, gauge-adjusted IMERG and model-adjusted IMERG through comparisons against Stage IV at six-hourly and event length scales. The raw IMERG product consistently underestimated heavy precipitation in all study regions, while the domain average rainfall magnitudes exhibited by the model were fairly accurate. The model exhibited error in the locations of intense precipitation over inland regions, however, while the IMERG product generally showed correct spatial precipitation patterns. Overall, the model-adjusted IMERG product performed best over inland regions by taking advantage of the more accurate rainfall magnitude from NWP and the spatial distribution from IMERG. In coastal regions, although model-based adjustment effectively improved the performance of the raw IMERG product, the model forecast performed even better. The IMERG product could benefit from gauge-based adjustment, as well, but the improvement from model-based adjustment was consistently more significant.

  10. Online Tools for Uncovering Data Quality (DQ) Issues in Satellite-Based Global Precipitation Products

    Science.gov (United States)

    Liu, Zhong; Heo, Gil

    2015-01-01

    Data quality (DQ) has many attributes or facets (i.e., errors, biases, systematic differences, uncertainties, benchmark, false trends, false alarm ratio, etc.)Sources can be complicated (measurements, environmental conditions, surface types, algorithms, etc.) and difficult to be identified especially for multi-sensor and multi-satellite products with bias correction (TMPA, IMERG, etc.) How to obtain DQ info fast and easily, especially quantified info in ROI Existing parameters (random error), literature, DIY, etc.How to apply the knowledge in research and applications.Here, we focus on online systems for integration of products and parameters, visualization and analysis as well as investigation and extraction of DQ information.

  11. Development of Deep Learning Based Data Fusion Approach for Accurate Rainfall Estimation Using Ground Radar and Satellite Precipitation Products

    Science.gov (United States)

    Chen, H.; Chandra, C. V.; Tan, H.; Cifelli, R.; Xie, P.

    2016-12-01

    Rainfall estimation based on onboard satellite measurements has been an important topic in satellite meteorology for decades. A number of precipitation products at multiple time and space scales have been developed based upon satellite observations. For example, NOAA Climate Prediction Center has developed a morphing technique (i.e., CMORPH) to produce global precipitation products by combining existing space based rainfall estimates. The CMORPH products are essentially derived based on geostationary satellite IR brightness temperature information and retrievals from passive microwave measurements (Joyce et al. 2004). Although the space-based precipitation products provide an excellent tool for regional and global hydrologic and climate studies as well as improved situational awareness for operational forecasts, its accuracy is limited due to the sampling limitations, particularly for extreme events such as very light and/or heavy rain. On the other hand, ground-based radar is more mature science for quantitative precipitation estimation (QPE), especially after the implementation of dual-polarization technique and further enhanced by urban scale radar networks. Therefore, ground radars are often critical for providing local scale rainfall estimation and a "heads-up" for operational forecasters to issue watches and warnings as well as validation of various space measurements and products. The CASA DFW QPE system, which is based on dual-polarization X-band CASA radars and a local S-band WSR-88DP radar, has demonstrated its excellent performance during several years of operation in a variety of precipitation regimes. The real-time CASA DFW QPE products are used extensively for localized hydrometeorological applications such as urban flash flood forecasting. In this paper, a neural network based data fusion mechanism is introduced to improve the satellite-based CMORPH precipitation product by taking into account the ground radar measurements. A deep learning system is

  12. Stochastic generation of multi-site daily precipitation focusing on extreme events

    Directory of Open Access Journals (Sweden)

    G. Evin

    2018-01-01

    Full Text Available Many multi-site stochastic models have been proposed for the generation of daily precipitation, but they generally focus on the reproduction of low to high precipitation amounts at the stations concerned. This paper proposes significant extensions to the multi-site daily precipitation model introduced by Wilks, with the aim of reproducing the statistical features of extremely rare events (in terms of frequency and magnitude at different temporal and spatial scales. In particular, the first extended version integrates heavy-tailed distributions, spatial tail dependence, and temporal dependence in order to obtain a robust and appropriate representation of the most extreme precipitation fields. A second version enhances the first version using a disaggregation method. The performance of these models is compared at different temporal and spatial scales on a large region covering approximately half of Switzerland. While daily extremes are adequately reproduced at the stations by all models, including the benchmark Wilks version, extreme precipitation amounts at larger temporal scales (e.g., 3-day amounts are clearly underestimated when temporal dependence is ignored.

  13. Comparison between satellite precipitation product and observation rain gauges in the Red-Thai Binh River Basin

    Science.gov (United States)

    Lakshmi, V.; Le, M. H.; Sutton, J. R. P.; Bui, D. D.; Bolten, J. D.

    2017-12-01

    The Red-ThaiBinh River is the second largest river in Vietnam in terms of economic impact and is home to around 29 million people. The river has been facing challenges for water resources allocation, which require reliable and routine hydrological assessments. However, hydrological analysis is difficult due to insufficient spatial coverage by rain gauges. Satellite-based precipitation estimates are a promising alternative with high-resolution in both time and space. This study aims at investigating the uncertainties in satellite-based precipitation product TRMM 3B42 v7.0 by comparing them against in-situ measurements over the Red-ThaiBinh River basin. The TRMM 3B42 v7.0 are assessed in terms of seasonal, monthly and daily variations over a 17-year period (1998 - 2014). Preliminary results indicate that at a daily scale, except for low Mean Bias Error (MBE), satellite based rainfall product has weak relationship with ground observation data, indicating by average performance of 0.326 and -0.485 for correlation coefficient and Nash Sutcliffe Efficiency (NSE), respectively. At monthly scale, we observe that the TRMM 3B42 v7.0 has higher correlation with the correlation increased significantly to 0.863 and NSE of 0.522. By analyzing wet season (May - October) and dry season (November - April) separately we find that the correlation between the TRMM 3B42 v7.0 with ground observations were higher for wet season than the dry season.

  14. Orbit Determination of the SELENE Satellites Using Multi-Satellite Data Types and Evaluation of SELENE Gravity Field Models

    Science.gov (United States)

    Goossens, S.; Matsumoto, K.; Noda, H.; Araki, H.; Rowlands, D. D.; Lemoine, F. G.

    2011-01-01

    The SELENE mission, consisting of three separate satellites that use different terrestrial-based tracking systems, presents a unique opportunity to evaluate the contribution of these tracking systems to orbit determination precision. The tracking data consist of four-way Doppler between the main orbiter and one of the two sub-satellites while the former is over the far side, and of same-beam differential VLBI tracking between the two sub-satellites. Laser altimeter data are also used for orbit determination. The contribution to orbit precision of these different data types is investigated through orbit overlap analysis. It is shown that using four-way and VLBI data improves orbit consistency for all satellites involved by reducing peak values in orbit overlap differences that exist when only standard two-way Doppler and range data are used. Including laser altimeter data improves the orbit precision of the SELENE main satellite further, resulting in very smooth total orbit errors at an average level of 18m. The multi-satellite data have also resulted in improved lunar gravity field models, which are assessed through orbit overlap analysis using Lunar Prospector tracking data. Improvements over a pre-SELENE model are shown to be mostly in the along-track and cross-track directions. Orbit overlap differences are at a level between 13 and 21 m with the SELENE models, depending on whether l-day data overlaps or I-day predictions are used.

  15. Data Visualization and Analysis Tools for the Global Precipitation Measurement (GPM) Validation Network

    Science.gov (United States)

    Morris, Kenneth R.; Schwaller, Mathew

    2010-01-01

    The Validation Network (VN) prototype for the Global Precipitation Measurement (GPM) Mission compares data from the Tropical Rainfall Measuring Mission (TRMM) satellite Precipitation Radar (PR) to similar measurements from U.S. and international operational weather radars. This prototype is a major component of the GPM Ground Validation System (GVS). The VN provides a means for the precipitation measurement community to identify and resolve significant discrepancies between the ground radar (GR) observations and similar satellite observations. The VN prototype is based on research results and computer code described by Anagnostou et al. (2001), Bolen and Chandrasekar (2000), and Liao et al. (2001), and has previously been described by Morris, et al. (2007). Morris and Schwaller (2009) describe the PR-GR volume-matching algorithm used to create the VN match-up data set used for the comparisons. This paper describes software tools that have been developed for visualization and statistical analysis of the original and volume matched PR and GR data.

  16. Multi-satellite observations of magnetic fields in space plasmas

    International Nuclear Information System (INIS)

    Potemra, T.A.; Zanetti, L.J.; Bythrow, P.F.; Erlandson, R.E.

    1987-01-01

    The most common method of detecting electric currents in space has been by virtue of the magnetic perturbations they produce. A satellite can pass through a field-aligned ''Birkeland'' current and measure the in-situ magnetic perturbations. Satellite-borne magnetic field experiments may also be used to observe characteristics of resonant oscillations of the Earth's magnetic field at ULF frequencies. Examples of such measurements with magnetic field experiments on the Viking, AMPTE/CCE, and DMSP-F7 satellites will be presented. The Viking satellite, launched in February, 1986, is Sweden's first satellite and is in a polar orbit with 3.1 R/sub e/ apogee. AMPTE/CCE was launched in August, 1984, with satellites from West Germany and the United Kingdom, for the purpose of creating artificial comets in space. It is in an equatorial orbit with a 8.8 R/sub e/ apogee. The Defense Meteorological Satellite Program (DMSP)-F7 satellite was launched in October, 1983 into an 800 km circular sun-synchronous orbit in the 0830-2030 magnetic local time plane. Viking and AMPTE/CCE observed harmonic ULF pulsations when they were near the same flux tube, but separated by about 10 R/sub e/. These unique observations are used to investigate the characteristics and sources of multiple field line resonances of Alfven waves. On another occasion, Viking and DMSP-F7 observed similar magnetic perturbations at widely separated locations. The authors interpret these perturbations as due to a complicated system of large-scale stable Birkeland currents in the morning sector. This multi-satellite data set is in the early stages of exploration, but already confirms the usefulness of coordinated multi-position observations of magnetic fields in space

  17. Second-degree Stokes coefficients from multi-satellite SLR

    Czech Academy of Sciences Publication Activity Database

    Blossfeld, M.; Mueller, H.; Gerstl, M.; Štefka, Vojtěch; Bouman, J.; Goettl, F.; Horwath, M.

    2015-01-01

    Roč. 89, č. 9 (2015), s. 857-871 ISSN 0949-7714 Institutional support: RVO:67985815 Keywords : multi-satellite SLR * stokes coefficients * equatorial excitation functions Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 2.486, year: 2015

  18. Application Research of Horn Array Multi-Beam Antenna in Reference Source System for Satellite Interference Location

    Science.gov (United States)

    Zhou, Ping; Lin, Hui; Zhang, Qi

    2018-01-01

    The reference source system is a key factor to ensure the successful location of the satellite interference source. Currently, the traditional system used a mechanical rotating antenna which leaded to the disadvantages of slow rotation and high failure-rate, which seriously restricted the system’s positioning-timeliness and became its obvious weaknesses. In this paper, a multi-beam antenna scheme based on the horn array was proposed as a reference source for the satellite interference location, which was used as an alternative to the traditional reference source antenna. The new scheme has designed a small circularly polarized horn antenna as an element and proposed a multi-beamforming algorithm based on planar array. Moreover, the simulation analysis of horn antenna pattern, multi-beam forming algorithm and simulated satellite link cross-ambiguity calculation have been carried out respectively. Finally, cross-ambiguity calculation of the traditional reference source system has also been tested. The comparison between the results of computer simulation and the actual test results shows that the scheme is scientific and feasible, obviously superior to the traditional reference source system.

  19. Onboard autonomous mission re-planning for multi-satellite system

    Science.gov (United States)

    Zheng, Zixuan; Guo, Jian; Gill, Eberhard

    2018-04-01

    This paper presents an onboard autonomous mission re-planning system for Multi-Satellites System (MSS) to perform onboard re-planing in disruptive situations. The proposed re-planning system can deal with different potential emergency situations. This paper uses Multi-Objective Hybrid Dynamic Mutation Genetic Algorithm (MO-HDM GA) combined with re-planning techniques as the core algorithm. The Cyclically Re-planning Method (CRM) and the Near Real-time Re-planning Method (NRRM) are developed to meet different mission requirements. Simulations results show that both methods can provide feasible re-planning sequences under unforeseen situations. The comparisons illustrate that using the CRM is average 20% faster than the NRRM on computation time. However, by using the NRRM more raw data can be observed and transmitted than using the CRM within the same period. The usability of this onboard re-planning system is not limited to multi-satellite system. Other mission planning and re-planning problems related to autonomous multiple vehicles with similar demands are also applicable.

  20. The Global Precipitation Measurement (GPM) Mission: Overview and U.S. Status

    Science.gov (United States)

    Hou, Arthur Y.; Azarbarzin, Ardeshir A.; Kakar, Ramesh K.; Neeck, Steven

    2011-01-01

    The Global Precipitation Measurement (GPM) Mission is an international satellite mission specifically designed to unify and advance precipitation measurements from a constellation of research and operational microwave sensors. The cornerstone of the GPM mission is the deployment of a Core Observatory in a 65 deg non-Sun-synchronous orbit to serve as a physics observatory and a transfer standard for inter-calibration of constellation radiometers. The GPM Core Observatory will carry a Ku/Ka-band Dual-frequency Precipitation Radar (DPR) and a conical-scanning multi-channel (10-183 GHz) GPM Microwave Radiometer (GMI). The first space-borne dual-frequency radar will provide not only measurements of 3-D precipitation structures but also quantitative information on microphysical properties of precipitating particles needed for improving precipitation retrievals from passive microwave sensors. The combined use of DPR and GMI measurements will place greater constraints on radiometer retrievals to improve the accuracy and consistency of precipitation estimates from all constellation radiometers. The GPM constellation is envisioned to comprise five or more conical-scanning microwave radiometers and four or more cross-track microwave sounders on operational satellites. NASA and the Japan Aerospace Exploration Agency (JAXA) plan to launch the GPM Core in July 2013. NASA will provide a second radiometer to be flown on a partner-provided GPM Low-Inclination Observatory (L10) to improve near real-time monitoring of hurricanes and mid-latitude storms. NASA and the Brazilian Space Program (AEB/IPNE) are currently engaged in a one-year study on potential L10 partnership. JAXA will contribute to GPM data from the Global Change Observation Mission-Water (GCOM-W) satellite. Additional partnerships are under development to include microwave radiometers on the French-Indian Megha-Tropiques satellite and U.S. Defense Meteorological Satellite Program (DMSP) satellites, as well as cross

  1. Total Discharge Estimation in the Korean Peninsula Using Multi-Satellite Products

    Directory of Open Access Journals (Sweden)

    Jae Young Seo

    2017-07-01

    Full Text Available Estimation of total discharge is necessary to understand the hydrological cycle and to manage water resources efficiently. However, the task is problematic in an area where ground observations are limited. The North Korea region is one example. Here, the total discharge was estimated based on the water balance using multiple satellite products. They are the terrestrial water storage changes (TWSC derived from the Gravity Recovery and Climate Experiment (GRACE, precipitation from the Tropical Rainfall Measuring Mission (TRMM, and evapotranspiration from the Moderate Resolution Imaging Spectroradiometer (MODIS. The satellite-based discharge was compared with land surface model products of the Global Land Data Assimilation System (GLDAS, and a positive relationship between the results was obtained (r = 0.70–0.86; bias = −9.08–16.99 mm/month; RMSE = 36.90–62.56 mm/month; NSE = 0.01–0.62. Among the four land surface models of GLDAS (CLM, Mosaic, Noah, and VIC, CLM corresponded best with the satellite-based discharge, satellite-based discharge has a tendency to slightly overestimate compared to model-based discharge (CLM, Mosaic, Noah, and VIC in the dry season. Also, the total discharge data based on the Precipitation-Runoff Modeling System (PRMS and the in situ discharge for major five river basins in South Korea show comparable seasonality and high correlation with the satellite-based discharge. In spite of the relatively low spatial resolution of GRACE, and loss of information incurred during the process of integrating three different satellite products, the proposed methodology can be a practical tool to estimate the total discharge with reasonable accuracy, especially in a region with scarce hydrologic data.

  2. Comparison of GPM IMERG, TMPA 3B42 and PERSIANN-CDR satellite precipitation products over Malaysia

    Science.gov (United States)

    Tan, Mou Leong; Santo, Harrif

    2018-04-01

    The launch of the Global Precipitation Measurement (GPM) mission has prompted the assessment of the newly released satellite precipitation products (SPPs) in different parts of the world. This study performed an initial comparison of three GPM IMERG products (IMERG_E, IMERG_L and IMERG_F) with its predecessor, the TMPA 3B42 and 3B42RT products, and a long-term PERSIANN-CDR product over Malaysia. The performance of six SPPs was evaluated using 501 precipitation gauges from 12 March 2014 to 29 February 2016. The annual, seasonal, monthly and daily precipitation measurements were validated using three widely used statistical metrics (CC, RMSE and RB). The precipitation detection capability (POD, FAR and CSI), probability density function (PDF) and the 2014-2015 flood event analysis were also considered in this assessment. The results show that all the SPPs perform well in annual and monthly precipitation measurements. The spatial variability of the total annual precipitation in 2015 is well captured by all six SPPs, with high precipitation amount in southern East Malaysia, and low precipitation amount in the middle part of Peninsular Malaysia. In contrast, all the SPPs show moderate correlation at daily precipitation estimations, with better performance during the northeast monsoon season. The performance of all the SPPs is better in eastern Peninsular Malaysia, but poorer in northern Peninsular Malaysia. All the SPPs have good precipitation detection ability, except the PERSIANN-CDR. All the SPPs underestimate the light (0-1 mm/day) and violent (> 50 mm/day) precipitation classes, but overestimate moderate and heavy (1-50 mm/day) precipitation classes. The IMERG is shown to have a better capability in detecting light precipitation (0-1 mm/day) compared to the other SPPs. The PERSIANN-CDR has the worst performance in capturing all the precipitation classes, with significant underestimation of light precipitation (0-1 mm/day) class and overestimation of moderate and

  3. A Satellite Data Analysis and CubeSat Instrument Simulator Tool for Simultaneous Multi-spacecraft Measurements of Solar Energetic Particles

    Science.gov (United States)

    Vannitsen, Jordan; Rizzitelli, Federico; Wang, Kaiti; Segret, Boris; Juang, Jyh-Ching; Miau, Jiun-Jih

    2017-12-01

    This paper presents a Multi-satellite Data Analysis and Simulator Tool (MDAST), developed with the original goal to support the science requirements of a Martian 3-Unit CubeSat mission profile named Bleeping Interplanetary Radiation Determination Yo-yo (BIRDY). MDAST was firstly designed and tested by taking into account the positions, attitudes, instruments field of view and energetic particles flux measurements from four spacecrafts (ACE, MSL, STEREO A, and STEREO B). Secondly, the simulated positions, attitudes and instrument field of view from the BIRDY CubeSat have been adapted for input. And finally, this tool can be used for data analysis of the measurements from the four spacecrafts mentioned above so as to simulate the instrument trajectory and observation capabilities of the BIRDY CubeSat. The onset, peak and end time of a solar particle event is specifically defined and identified with this tool. It is not only useful for the BIRDY mission but also for analyzing data from the four satellites aforementioned and can be utilized for other space weather missions with further customization.

  4. Satellite-based Flood Modeling Using TRMM-based Rainfall Products

    Directory of Open Access Journals (Sweden)

    Greg Easson

    2007-12-01

    Full Text Available Increasingly available and a virtually uninterrupted supply of satellite-estimatedrainfall data is gradually becoming a cost-effective source of input for flood predictionunder a variety of circumstances. However, most real-time and quasi-global satelliterainfall products are currently available at spatial scales ranging from 0.25o to 0.50o andhence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scaleflood events. This study assesses the question: what are the hydrologic implications ofuncertainty of satellite rainfall data at the coarse scale? We investigated this question onthe 970 km2 Upper Cumberland river basin of Kentucky. The satellite rainfall productassessed was NASA’s Tropical Rainfall Measuring Mission (TRMM Multi-satellitePrecipitation Analysis (TMPA product called 3B41RT that is available in pseudo real timewith a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data canimprove application in flood prediction to some extent with the trade-off of more falsealarms in peak flow. However, a more rational and regime-based adjustment procedureneeds to be identified before the use of satellite data can be institutionalized among floodmodelers.

  5. The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments

    Science.gov (United States)

    Chuan, Zun Liang; Ismail, Noriszura; Shinyie, Wendy Ling; Lit Ken, Tan; Fam, Soo-Fen; Senawi, Azlyna; Yusoff, Wan Nur Syahidah Wan

    2018-04-01

    Due to the limited of historical precipitation records, agglomerative hierarchical clustering algorithms widely used to extrapolate information from gauged to ungauged precipitation catchments in yielding a more reliable projection of extreme hydro-meteorological events such as extreme precipitation events. However, identifying the optimum number of homogeneous precipitation catchments accurately based on the dendrogram resulted using agglomerative hierarchical algorithms are very subjective. The main objective of this study is to propose an efficient regionalized algorithm to identify the homogeneous precipitation catchments for non-stationary precipitation time series. The homogeneous precipitation catchments are identified using average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling, while uncentered correlation coefficient as the similarity measure. The regionalized homogeneous precipitation is consolidated using K-sample Anderson Darling non-parametric test. The analysis result shows the proposed regionalized algorithm performed more better compared to the proposed agglomerative hierarchical clustering algorithm in previous studies.

  6. Precipitation Characteristics in Tropical Africa Using Satellite and In-Situ Observations

    Science.gov (United States)

    Dezfuli, Amin; Ichoku, Charles; Huffman, George; Mohr, Karen

    2017-01-01

    Tropical Africa receives nearly all its precipitation as a result of convection. The characteristics of rain-producing systems in this region, despite their crucial role in regional and global circulation, have not been well-understood. This is mainly due to the lack of in situ observations. Here, we have used precipitation records from the Trans-African Hydro-Meteorological Observatory (TAHMO) to improve our knowledge about the rainfall systems in the region, and to validate the recently-released IMERG precipitation product. The high temporal resolution of the gauge data has allowed us to identify three classes of rain events based on their duration and intensity. The contribution of each class to the total rainfall and the favorable surface atmospheric conditions for each class have been examined. As IMERG aims to continue the legacy of its predecessor, TMPA, and provide higher resolution data, continent-wide comparisons are made between these two products. IMERG, due to its improved temporal resolution, shows some advantages over TMPA in capturing the diurnal cycle and propagation of the meso-scale convective systems. However, the performance of the two satellite-based products varies by season, region and the evaluation statistics. The results of this study serve as a basis for our ongoing work on the impacts of biomass burning on precipitation processes in Africa.

  7. Evidence of Urban Precipitation Anomalies from Satellite and Ground-Based Measurements

    Science.gov (United States)

    Shepherd, J. Marshall; Manyin, M.; Negri, Andrew

    2004-01-01

    Urbanization is one of the extreme cases of land use change. Most of world's population has moved to urban areas. Although currently only 1.2% of the land is considered urban, the spatial coverage and density of cities are expected to rapidly increase in the near future. It is estimated that by the year 2025, 60% of the world's population will live in cities. Human activity in urban environments also alters weather and climate processes. However, our understanding of urbanization on the total Earth-weather-climate system is incomplete. Recent literature continues to provide evidence that anomalies in precipitation exist over and downwind of major cities. Current and future research efforts are actively seeking to verify these literature findings and understand potential cause-effect relationships. The novelty of this study is that it utilizes rainfall data from multiple satellite data sources (e.g. TRMM precipitation radar, TRMM-geosynchronous-rain gauge merged product, and SSM/I) and ground-based measurements to identify spatial anomalies and temporal trends in precipitation for cities around the world. Early results will be presented and placed within the context of weather prediction, climate assessment, and societal applications.

  8. An Experimental System for a Global Flood Prediction: From Satellite Precipitation Data to a Flood Inundation Map

    Science.gov (United States)

    Adler, Robert

    2007-01-01

    Floods impact more people globally than any other type of natural disaster. It has been established by experience that the most effective means to reduce the property damage and life loss caused by floods is the development of flood early warning systems. However, advances for such a system have been constrained by the difficulty in estimating rainfall continuously over space (catchment-. national-, continental-. or even global-scale areas) and time (hourly to daily). Particularly, insufficient in situ data, long delay in data transmission and absence of real-time data sharing agreements in many trans-boundary basins hamper the development of a real-time system at the regional to global scale. In many countries around the world, particularly in the tropics where rainfall and flooding co-exist in abundance, satellite-based precipitation estimation may be the best source of rainfall data for those data scarce (ungauged) areas and trans-boundary basins. Satellite remote sensing data acquired and processed in real time can now provide the space-time information on rainfall fluxes needed to monitor severe flood events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models, which can be parameterized by a tailored geospatial database. An example that is a key to this progress is NASA's contribution to the Tropical Rainfall Measuring Mission (TRMM), launched in November 1997. Hence, in an effort to evolve toward a more hydrologically-relevant flood alert system, this talk articulates a module-structured framework for quasi-global flood potential naming, that is 'up to date' with the state of the art on satellite rainfall estimation and the improved geospatial datasets. The system is modular in design with the flexibility that permits changes in the model structure and in the choice of components. Four major components included in the system are: 1) multi-satellite precipitation estimation; 2) characterization of

  9. Assessing water availability over peninsular Malaysia using public domain satellite data products

    International Nuclear Information System (INIS)

    Ali, M I; Hashim, M; Zin, H S M

    2014-01-01

    Water availability monitoring is an essential task for water resource sustainability and security. In this paper, the assessment of satellite remote sensing technique for determining water availability is reported. The water-balance analysis is used to compute the spatio-temporal water availability with main inputs; the precipitation and actual evapotranspiration rate (AET), both fully derived from public-domain satellite products of Tropical Rainfall Measurement Mission (TRMM) and MODIS, respectively. Both these satellite products were first subjected to calibration to suit corresponding selected local precipitation and AET samples. Multi-temporal data sets acquired 2000-2010 were used in this study. The results of study, indicated strong agreement of monthly water availability with the basin flow rate (r 2 = 0.5, p < 0.001). Similar agreements were also noted between the estimated annual average water availability with the in-situ measurement. It is therefore concluded that the method devised in this study provide a new alternative for water availability mapping over large area, hence offers the only timely and cost-effective method apart from providing comprehensive spatio-temporal patterns, crucial in water resource planning to ensure water security

  10. Evaluation of Satellite-Based Precipitation Products from IMERG V04A and V03D, CMORPH and TMPA with Gauged Rainfall in Three Climatologic Zones in China

    Directory of Open Access Journals (Sweden)

    Guanghua Wei

    2017-12-01

    Full Text Available A critical evaluation of the newly released precipitation data set is very important for both the end users and data developers. Meanwhile, the evaluation may provide a benchmark for the product’s continued development and future improvement. To these ends, the four precipitation estimates including IMERG (the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement V04A, IMERG V03D, CMORPH (the Climate Prediction Center Morphing technique-CRT and TRMM (the Tropical Rainfall Measuring Mission 3B42 are systematically evaluated against the gauge precipitation estimates at multiple spatiotemporal scales from 1 June 2014 to 30 November 2015 over three different topographic and climatic watersheds in China. Meanwhile, the statistical methods are utilized to quantize the performance of the four satellite-based precipitation estimates. The results show that: (1 over the Tibetan Plateau cold region, among all products, IMERG V04A underestimates precipitation with the largest RB (−46.98% during the study period and the similar results are seen at the seasonal scale. However, IMERG V03D demonstrates the best performance according to RB (7.46%, RMSE (0.44 mm/day and RRMSE (28.37%. Except for in summer, TRMM 3B42 perform better than CMORPH according to RMSEs, RRMSEs and Rs; (2 within the semi-humid Huaihe River Basin, IMERG V04A has a slight advantage over the other three satellite-based precipitation products with the lowest RMSE (0.32 mm/day during the evaluation period and followed by IMERG V03D, TRMM 3B42 and CMORPH orderly; (3 over the arid/semi-arid Weihe River Basin, in comparison with the other three products, TRMM 3B42 demonstrates the best performance with the lowest RMSE (0.1 mm/day, RRMSE (8.44% and highest R (0.92 during the study period. Meanwhile, IMERG V03D perform better than IMERG V04A according all the statistical indicators; (4 in winter, IMERG V04A and IMERG V03D tend to underestimate the total precipitation

  11. Downscaling atmospheric patterns to multi-site precipitation amounts in southern Scandinavia

    DEFF Research Database (Denmark)

    Gelati, Emiliano; Christensen, O.B.; Rasmussen, P.F.

    2010-01-01

    A non-homogeneous hidden Markov model (NHMM) is applied for downscaling atmospheric synoptic patterns to winter multi-site daily precipitation amounts. The implemented NHMM assumes precipitation to be conditional on a hidden weather state that follows a Markov chain, whose transition probabilities...... depend on current atmospheric information. The gridded atmospheric fields are summarized through the singular value decomposition (SVD) technique. SVD is applied to geopotential height and relative humidity at several pressure levels, to identify their principal spatial patterns co...... products of bivariate distributions. Conditional on the weather state, precipitation amounts are modelled separately at each gauge as independent gamma-distributed random variables. This modelling approach is applied to 51 precipitation gauges in Denmark and southern Sweden for the period 1981...

  12. Precipitation estimates and comparison of satellite rainfall data to in situ rain gauge observations to further develop the watershed-modeling capabilities for the Lower Mekong River Basin

    Science.gov (United States)

    Dandridge, C.; Lakshmi, V.; Sutton, J. R. P.; Bolten, J. D.

    2017-12-01

    This study focuses on the lower region of the Mekong River Basin (MRB), an area including Burma, Cambodia, Vietnam, Laos, and Thailand. This region is home to expansive agriculture that relies heavily on annual precipitation over the basin for its prosperity. Annual precipitation amounts are regulated by the global monsoon system and therefore vary throughout the year. This research will lead to improved prediction of floods and management of floodwaters for the MRB. We compare different satellite estimates of precipitation to each other and to in-situ precipitation estimates for the Mekong River Basin. These comparisons will help us determine which satellite precipitation estimates are better at predicting precipitation in the MRB and will help further our understanding of watershed-modeling capabilities for the basin. In this study we use: 1) NOAA's PERSIANN daily 0.25° precipitation estimate Climate Data Record (CDR), 2) NASA's Tropical Rainfall Measuring Mission (TRMM) daily 0.25° estimate, and 3) NASA's Global Precipitation Measurement (GPM) daily 0.1 estimate and 4) 488 in-situ stations located in the lower MRB provide daily precipitation estimates. The PERSIANN CDR precipitation estimate was able to provide the longest data record because it is available from 1983 to present. The TRMM precipitation estimate is available from 2000 to present and the GPM precipitation estimates are available from 2015 to present. It is for this reason that we provide several comparisons between our precipitation estimates. Comparisons were done between each satellite product and the in-situ precipitation estimates based on geographical location and date using the entire available data record for each satellite product for daily, monthly, and yearly precipitation estimates. We found that monthly PERSIANN precipitation estimates were able to explain up to 90% of the variability in station precipitation depending on station location.

  13. A near real-time satellite-based global drought climate data record

    International Nuclear Information System (INIS)

    AghaKouchak, Amir; Nakhjiri, Navid

    2012-01-01

    Reliable drought monitoring requires long-term and continuous precipitation data. High resolution satellite measurements provide valuable precipitation information on a quasi-global scale. However, their short lengths of records limit their applications in drought monitoring. In addition to this limitation, long-term low resolution satellite-based gauge-adjusted data sets such as the Global Precipitation Climatology Project (GPCP) one are not available in near real-time form for timely drought monitoring. This study bridges the gap between low resolution long-term satellite gauge-adjusted data and the emerging high resolution satellite precipitation data sets to create a long-term climate data record of droughts. To accomplish this, a Bayesian correction algorithm is used to combine GPCP data with real-time satellite precipitation data sets for drought monitoring and analysis. The results showed that the combined data sets after the Bayesian correction were a significant improvement compared to the uncorrected data. Furthermore, several recent major droughts such as the 2011 Texas, 2010 Amazon and 2010 Horn of Africa droughts were detected in the combined real-time and long-term satellite observations. This highlights the potential application of satellite precipitation data for regional to global drought monitoring. The final product is a real-time data-driven satellite-based standardized precipitation index that can be used for drought monitoring especially over remote and/or ungauged regions. (letter)

  14. Accounting for spatiotemporal errors of gauges: A critical step to evaluate gridded precipitation products

    Science.gov (United States)

    Tang, Guoqiang; Behrangi, Ali; Long, Di; Li, Changming; Hong, Yang

    2018-04-01

    Rain gauge observations are commonly used to evaluate the quality of satellite precipitation products. However, the inherent difference between point-scale gauge measurements and areal satellite precipitation, i.e. a point of space in time accumulation v.s. a snapshot of time in space aggregation, has an important effect on the accuracy and precision of qualitative and quantitative evaluation results. This study aims to quantify the uncertainty caused by various combinations of spatiotemporal scales (0.1°-0.8° and 1-24 h) of gauge network designs in the densely gauged and relatively flat Ganjiang River basin, South China, in order to evaluate the state-of-the-art satellite precipitation, the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG). For comparison with the dense gauge network serving as "ground truth", 500 sparse gauge networks are generated through random combinations of gauge numbers at each set of spatiotemporal scales. Results show that all sparse gauge networks persistently underestimate the performance of IMERG according to most metrics. However, the probability of detection is overestimated because hit and miss events are more likely fewer than the reference numbers derived from dense gauge networks. A nonlinear error function of spatiotemporal scales and the number of gauges in each grid pixel is developed to estimate the errors of using gauges to evaluate satellite precipitation. Coefficients of determination of the fitting are above 0.9 for most metrics. The error function can also be used to estimate the required minimum number of gauges in each grid pixel to meet a predefined error level. This study suggests that the actual quality of satellite precipitation products could be better than conventionally evaluated or expected, and hopefully enables non-subject-matter-expert researchers to have better understanding of the explicit uncertainties when using point-scale gauge observations to evaluate areal products.

  15. Multi model and data analysis of terrestrial carbon cycle in Asia: From 2001 to 2006

    Science.gov (United States)

    Ichii, K.; Takahashi, K.; Suzuki, T.; Ueyama, M.; Sasai, T.; Hirata, R.; Saigusa, N.

    2009-12-01

    Accurate monitoring and modeling of the current status and their causes of interannual variations in terrestrial carbon cycle are important. Recently, many studies analyze using multiple methods (e.g. satellite data and ecosystem models) to clarify the underlain mechanisms and recent trend since each single methodology contains its own biases. The multi-model and data ensemble approach is a powerful method to clarify the current status and their underlain mechanisms. So far, many studies using multiple sources of data and models are conducted in North America, Europe, Africa, Amazon, and Japan, however, studies in monsoon Asia are lacking. In this study, we analyzed interannual variations in terrestrial carbon cycles in monsoon Asia, and evaluated current capability of remote sensing and ecosystem model to capture them based on multiple model and data sources; flux observations, remote sensing (e.g. MODIS, AVHRR, and VGT), and ecosystem models (e.g. SVM, BEAMS, CASA, Biome-BGC, LPJ, and TRIFFID). The satellite observation and ecosystem models show clear characteristics in interannual variabilities in satellite-based NDVI and model-based GPP. These are characterized by (1) spring NDVI and modeled GPP anomalies related to temperature anomaly in mid and high latitudinal areas (positive anomalies in 2002 and 2005 and negative one in 2006), (2) NDVI and GPP anomalies in southeastern and central Asia related to precipitation (e.g. India from 2003-2006), and (3) summer NDVI and GPP anomalies in 2003 related to strong anomalies in solar radiations. NDVI anomalies related to radiation ones (2003 summer) were not accurately captured by terrestrial ecosystem models. For example, LPJ model rather shows GPP positive anomalies in Far East Asia regions probably caused by positive precipitation anomalies. Further analysis requires improvement of models to reproduce more consistent spatial patterns in NDVI anomaly, and longer term analysis (e.g. after 1982).

  16. Advanced Analysis of the Influence of Clouds, Precipiation and Surface Emissivity on DMSP/NPOESS Satellite Microwave Channels

    National Research Council Canada - National Science Library

    Isaacs, R

    2002-01-01

    ...: development of databases of brightness temperatures from various satellite sensors; development databases of conventional analysis to verify the presence and amount of clouds and precipitation and for verification of retrieval results...

  17. Performance Analysis of Satellite Missions for Multi-Temporal SAR Interferometry.

    Science.gov (United States)

    Bovenga, Fabio; Belmonte, Antonella; Refice, Alberto; Pasquariello, Guido; Nutricato, Raffaele; Nitti, Davide O; Chiaradia, Maria T

    2018-04-27

    Multi-temporal InSAR (MTI) applications pose challenges related to the availability of coherent scattering from the ground surface, the complexity of the ground deformations, atmospheric artifacts, and visibility problems related to ground elevation. Nowadays, several satellite missions are available providing interferometric SAR data at different wavelengths, spatial resolutions, and revisit time. A new and interesting opportunity is provided by Sentinel-1, which has a spatial resolution comparable to that of previous ESA C-band sensors, and revisit times improved by up to 6 days. According to these different SAR space-borne missions, the present work discusses current and future opportunities of MTI applications in terms of ground instability monitoring. Issues related to coherent target detection, mean velocity precision, and product geo-location are addressed through a simple theoretical model assuming backscattering mechanisms related to point scatterers. The paper also presents an example of a multi-sensor ground instability investigation over Lesina Marina, a village in Southern Italy lying over a gypsum diapir, where a hydration process, involving the underlying anhydride, causes a smooth uplift and the formation of scattered sinkholes. More than 20 years of MTI SAR data have been processed, coming from both legacy ERS and ENVISAT missions, and latest-generation RADARSAT-2, COSMO-SkyMed, and Sentinel-1A sensors. Results confirm the presence of a rather steady uplift process, with limited to null variations throughout the whole monitored time-period.

  18. Performance Analysis of Satellite Missions for Multi-Temporal SAR Interferometry

    Directory of Open Access Journals (Sweden)

    Fabio Bovenga

    2018-04-01

    Full Text Available Multi-temporal InSAR (MTI applications pose challenges related to the availability of coherent scattering from the ground surface, the complexity of the ground deformations, atmospheric artifacts, and visibility problems related to ground elevation. Nowadays, several satellite missions are available providing interferometric SAR data at different wavelengths, spatial resolutions, and revisit time. A new and interesting opportunity is provided by Sentinel-1, which has a spatial resolution comparable to that of previous ESA C-band sensors, and revisit times improved by up to 6 days. According to these different SAR space-borne missions, the present work discusses current and future opportunities of MTI applications in terms of ground instability monitoring. Issues related to coherent target detection, mean velocity precision, and product geo-location are addressed through a simple theoretical model assuming backscattering mechanisms related to point scatterers. The paper also presents an example of a multi-sensor ground instability investigation over Lesina Marina, a village in Southern Italy lying over a gypsum diapir, where a hydration process, involving the underlying anhydride, causes a smooth uplift and the formation of scattered sinkholes. More than 20 years of MTI SAR data have been processed, coming from both legacy ERS and ENVISAT missions, and latest-generation RADARSAT-2, COSMO-SkyMed, and Sentinel-1A sensors. Results confirm the presence of a rather steady uplift process, with limited to null variations throughout the whole monitored time-period.

  19. Mapping global precipitation with satellite borne microwave radiometer and infrared radiometer using Kalman filter

    International Nuclear Information System (INIS)

    Noda, S.; Sasashige, K.; Katagami, D.; Ushio, T.; Kubota, T.; Okamoto, K.; Iida, Y.; Kida, S.; Shige, S.; Shimomura, S.; Aonashi, K.; Inoue, T.; Morimoto, T.; Kawasaki, Z.

    2007-01-01

    Estimates of precipitation at a high time and space resolution are required for many important applications. In this paper, a new global precipitation map with high spatial (0.1 degree) and temporal (1 hour) resolution using Kalman filter technique is presented and evaluated. Infrared radiometer data, which are available globally nearly everywhere and nearly all the time from geostationary orbit, are used with the several microwave radiometers aboard the LEO satellites. IR data is used as a means to move the precipitation estimates from microwave observation during periods when microwave data are not available at a given location. Moving vector is produced by computing correlations on successive images of IR data. When precipitation is moved, the Kalman filter is applied for improving the moving technique in this research. The new approach showed a better score than the technique without Kalman filter. The correlation coefficient was 0.1 better than without the Kalman filter about 6 hours after the last microwave overpasses, and the RMS error was improved about 0.1 mm/h with the Kalman filter technique. This approach is unique in that 1) the precipitation estimates from the microwave radiometer is mainly used, 2) the IR temperature in every hour is also used for the precipitation estimates based on the Kalman filter theory

  20. Effective Assimilation of Global Precipitation

    Science.gov (United States)

    Lien, G.; Kalnay, E.; Miyoshi, T.; Huffman, G. J.

    2012-12-01

    global model and with high-resolution TRMM Multi-satellite Precipitation Analysis (TMPA) data is ongoing work. The climatological probability distribution of these precipitation data is calculated in preparation for the use of the proposed transformation algorithm. The impact of using an efficient precipitation assimilation in real global analyses and forecasts will be investigated.

  1. Tile-Level Annotation of Satellite Images Using Multi-Level Max-Margin Discriminative Random Field

    Directory of Open Access Journals (Sweden)

    Hong Sun

    2013-05-01

    Full Text Available This paper proposes a multi-level max-margin discriminative analysis (M3DA framework, which takes both coarse and fine semantics into consideration, for the annotation of high-resolution satellite images. In order to generate more discriminative topic-level features, the M3DA uses the maximum entropy discrimination latent Dirichlet Allocation (MedLDA model. Moreover, for improving the spatial coherence of visual words neglected by M3DA, conditional random field (CRF is employed to optimize the soft label field composed of multiple label posteriors. The framework of M3DA enables one to combine word-level features (generated by support vector machines and topic-level features (generated by MedLDA via the bag-of-words representation. The experimental results on high-resolution satellite images have demonstrated that, using the proposed method can not only obtain suitable semantic interpretation, but also improve the annotation performance by taking into account the multi-level semantics and the contextual information.

  2. Evaluating Cloud and Precipitation Processes in Numerical Models using Current and Potential Future Satellite Missions

    Science.gov (United States)

    van den Heever, S. C.; Tao, W. K.; Skofronick Jackson, G.; Tanelli, S.; L'Ecuyer, T. S.; Petersen, W. A.; Kummerow, C. D.

    2015-12-01

    Cloud, aerosol and precipitation processes play a fundamental role in the water and energy cycle. It is critical to accurately represent these microphysical processes in numerical models if we are to better predict cloud and precipitation properties on weather through climate timescales. Much has been learned about cloud properties and precipitation characteristics from NASA satellite missions such as TRMM, CloudSat, and more recently GPM. Furthermore, data from these missions have been successfully utilized in evaluating the microphysical schemes in cloud-resolving models (CRMs) and global models. However, there are still many uncertainties associated with these microphysics schemes. These uncertainties can be attributed, at least in part, to the fact that microphysical processes cannot be directly observed or measured, but instead have to be inferred from those cloud properties that can be measured. Evaluation of microphysical parameterizations are becoming increasingly important as enhanced computational capabilities are facilitating the use of more sophisticated schemes in CRMs, and as future global models are being run on what has traditionally been regarded as cloud-resolving scales using CRM microphysical schemes. In this talk we will demonstrate how TRMM, CloudSat and GPM data have been used to evaluate different aspects of current CRM microphysical schemes, providing examples of where these approaches have been successful. We will also highlight CRM microphysical processes that have not been well evaluated and suggest approaches for addressing such issues. Finally, we will introduce a potential NASA satellite mission, the Cloud and Precipitation Processes Mission (CAPPM), which would facilitate the development and evaluation of different microphysical-dynamical feedbacks in numerical models.

  3. Long-Term Large-Scale Bias-Adjusted Precipitation Estimates at High Spatial and Temporal Resolution Derived from the National Mosaic and Multi-Sensor QPE (NMQ/Q2) Precipitation Reanalysis over CONUS

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.; Stevens, S. E.; Seo, D. J.; Kim, B.

    2014-12-01

    The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (Nexrad) network over Continental United States (CONUS) is nearly completed for the period covering from 2000 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Rain gauge networks such as the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), the Climate Reference Network (CRN), and the Global Historical Climatology Network - Daily (GHCN-D) are used to adjust for those biases and to merge with the radar only product to provide a multi-sensor estimate. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. After assessing the bias and applying reduction or elimination techniques, we are investigating the kriging method and its variants such as simple kriging (SK), ordinary kriging (OK), and conditional bias-penalized Kriging (CBPK) among others. In addition we hope to generate estimates of uncertainty for the gridded estimate. In this work the methodology is presented as well as a comparison between the radar-only product and the final multi-sensor QPE product. The comparison is performed at various time scales from the sub-hourly, to annual. In addition, comparisons over the same period with a suite of lower resolution QPEs derived from ground based radar

  4. Evaluation of TRMM 3B42V7 product on extreme precipitation measurements over peninsular Malaysia

    Science.gov (United States)

    Paska, Jacquoelyne; Lau, Alvin M. S.; Tan, Mou Leong; Tan, Kok Chooi

    2017-10-01

    Climate variability has become a matter worth our attention as this issue has unveiled to the extreme water-related disasters such as flood and drought. Increments in heavy precipitation have happened over the past century and future climate scenarios show that it may alter the recurrence, timing, force, and length of these occasions. Satellite precipitation products (SPPs) could be used as representation of precipitation over a large region. This could be useful for the monitoring of the precipitation pattern as well as extreme events. Nevertheless, application of these products in monitoring extreme precipitation is still limited because insufficiency of quality assessment. This study aims to evaluate the performance of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42V7 product in capturing the behavior of extreme precipitation events over Peninsular Malaysia from 2000 to 2015. Four extreme precipitation indices, in two general categories of absolute threshold (R10mm, R20mm and R50mm) and maximum (Rx1d) indices that recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) were used. General evaluation has shown that the TRMM 3B42V7 product performed good on the measurements of monthly and annual precipitation. In the respect of extreme precipitation measurements, weak to moderate positive correlations were found between the TRMM 3B42 product and rain gauges over Peninsular Malaysia. The TRMM 3B42V7 product overestimated the R10mm and R20mm indices, while an underestimation was found for the R50mm and Rx1d indices.

  5. Substorm related changes in precipitation in the dayside auroral zone – a multi instrument case study

    Directory of Open Access Journals (Sweden)

    A. J. Kavanagh

    Full Text Available A period (08:10–14:40 MLT, 11 February 1997 of enhanced electron density in the D- and E-regions is investigated using EISCAT, IRIS and other complementary instruments. The precipitation is determined to be due to substorm processes occurring close to magnetic midnight. Energetic electrons drift eastward after substorm injection and precipitate in the morning sector. The precipitation is triggered by small pulses in the solar wind pressure, which drive wave particle interactions. The characteristic energy of precipitation is inferred from drift timing on different L-shells and apparently verified by EISCAT measurements. The IMF influence on the precipitation in the auroral zone is also briefly discussed. A large change in the precipitation spectrum is attributed to increased numbers of ions and much reduced electron fluxes. These are detected by a close passing DMSP satellite. The possibility that these ions are from the low latitude boundary layer (LLBL is discussed with reference to structured narrow band Pc1 waves observed by a search coil magnetometer, co-located with IRIS. The intensity of the waves grows with increased distance equatorward of the cusp position (determined by both satellite and HF radar, contrary to expectations if the precipitation is linked to the LLBL. It is suggested that the ion precipitation is, instead, due to the recovery phase of a small geomagnetic storm, following on from very active conditions. The movement of absorption in the later stages of the event is compared with observations of the ionospheric convection velocities. A good agreement is found to exist in this time interval suggesting that E × B drift has become the dominant drift mechanism over the gradient-curvature drift separation of the moving absorption patches observed at the beginning of the morning precipitation event.

    Key words. Ionosphere (auroral ionosphere; particle precipitation Magnetospheric physics (storms and substorms

  6. Substorm related changes in precipitation in the dayside auroral zone – a multi instrument case study

    Directory of Open Access Journals (Sweden)

    A. J. Kavanagh

    2002-09-01

    Full Text Available A period (08:10–14:40 MLT, 11 February 1997 of enhanced electron density in the D- and E-regions is investigated using EISCAT, IRIS and other complementary instruments. The precipitation is determined to be due to substorm processes occurring close to magnetic midnight. Energetic electrons drift eastward after substorm injection and precipitate in the morning sector. The precipitation is triggered by small pulses in the solar wind pressure, which drive wave particle interactions. The characteristic energy of precipitation is inferred from drift timing on different L-shells and apparently verified by EISCAT measurements. The IMF influence on the precipitation in the auroral zone is also briefly discussed. A large change in the precipitation spectrum is attributed to increased numbers of ions and much reduced electron fluxes. These are detected by a close passing DMSP satellite. The possibility that these ions are from the low latitude boundary layer (LLBL is discussed with reference to structured narrow band Pc1 waves observed by a search coil magnetometer, co-located with IRIS. The intensity of the waves grows with increased distance equatorward of the cusp position (determined by both satellite and HF radar, contrary to expectations if the precipitation is linked to the LLBL. It is suggested that the ion precipitation is, instead, due to the recovery phase of a small geomagnetic storm, following on from very active conditions. The movement of absorption in the later stages of the event is compared with observations of the ionospheric convection velocities. A good agreement is found to exist in this time interval suggesting that E × B drift has become the dominant drift mechanism over the gradient-curvature drift separation of the moving absorption patches observed at the beginning of the morning precipitation event.Key words. Ionosphere (auroral ionosphere; particle precipitation Magnetospheric physics (storms and substorms

  7. Hyper Hospital on the satellite multi-media network.

    Science.gov (United States)

    Yamaguchi, T

    1997-01-01

    We have been developing the Hyper Hospital, a network based VR mediated medical care system. The Hyper Hospital is composed of two seamlessly integrated environments, that is, the virtual and the real worlds. Of them, its virtual environment expands the conventional medical care system using the virtual reality technology as a principal human interface and a collaboration tool, in the present study, an attempt to extend the Hyper Hospital system to various modalities of communication network is reported. A satellite communication based multi-media network using Internet protocols with the WWW interface is used. Data transmission rate and other performances were measured under various conditions and the satellite network was shown to be suitable to the Hyper Hospital network.

  8. Introducing the VISAGE project - Visualization for Integrated Satellite, Airborne, and Ground-based data Exploration

    Science.gov (United States)

    Gatlin, P. N.; Conover, H.; Berendes, T.; Maskey, M.; Naeger, A. R.; Wingo, S. M.

    2017-12-01

    A key component of NASA's Earth observation system is its field experiments, for intensive observation of particular weather phenomena, or for ground validation of satellite observations. These experiments collect data from a wide variety of airborne and ground-based instruments, on different spatial and temporal scales, often in unique formats. The field data are often used with high volume satellite observations that have very different spatial and temporal coverage. The challenges inherent in working with such diverse datasets make it difficult for scientists to rapidly collect and analyze the data for physical process studies and validation of satellite algorithms. The newly-funded VISAGE project will address these issues by combining and extending nascent efforts to provide on-line data fusion, exploration, analysis and delivery capabilities. A key building block is the Field Campaign Explorer (FCX), which allows users to examine data collected during field campaigns and simplifies data acquisition for event-based research. VISAGE will extend FCX's capabilities beyond interactive visualization and exploration of coincident datasets, to provide interrogation of data values and basic analyses such as ratios and differences between data fields. The project will also incorporate new, higher level fused and aggregated analysis products from the System for Integrating Multi-platform data to Build the Atmospheric column (SIMBA), which combines satellite and ground-based observations into a common gridded atmospheric column data product; and the Validation Network (VN), which compiles a nationwide database of coincident ground- and satellite-based radar measurements of precipitation for larger scale scientific analysis. The VISAGE proof-of-concept will target "golden cases" from Global Precipitation Measurement Ground Validation campaigns. This presentation will introduce the VISAGE project, initial accomplishments and near term plans.

  9. Evaluation of Satellite Precipitation Products and Their Potential Influence on Hydrological Modeling over the Ganzi River Basin of the Tibetan Plateau

    Directory of Open Access Journals (Sweden)

    Alaa Alden Alazzy

    2017-01-01

    Full Text Available In the last few years, satellite-based precipitation datasets are believed to be a potential source for forcing inputs in driving hydrological models, which are important especially in complex terrain areas or ungauged basins where ground gauges are generally sparse or nonexistent. This study aims to comprehensively evaluate the satellite precipitation products, CMORPH-CRT, PERSIANN-CDR, 3B42RT, and 3B42 against gauge-based datasets and to infer their relative potential impacts on hydrological processes simulation using the HEC-HMS model in the Ganzi River Basin (GRB of the Tibetan Plateau. Results from a quantitative statistical comparison reveal that, at annual and seasonal scales, both CMORPH-CRT and 3B42 perform better than PERSIANN-CDR and 3B42RT. The CMORPH-CRT and 3B42 tend to underestimate values at the medium and high precipitation intensities ranges, whereas the opposite tendency is found for PERSIANN-CDR and 3B42RT. Overall, 3B42 exhibits the best performance for streamflow simulations over GRB and even outperforms simulation driven by gauge data during the validation period. PERSIANN-CDR shows the worst overall performance. After recalibrating with input-specific precipitation data, the performance of all satellite precipitation forced simulations is substantially improved, except for PERSIANN-CDR. Furthermore, 3B42 is more suitable to drive hydrological models and can be a potential alternative source of sparse data in Tibetan Plateau basins.

  10. Multi-Satellite Observation Scheduling for Large Area Disaster Emergency Response

    Science.gov (United States)

    Niu, X. N.; Tang, H.; Wu, L. X.

    2018-04-01

    an optimal imaging plan, plays a key role in coordinating multiple satellites to monitor the disaster area. In the paper, to generate imaging plan dynamically according to the disaster relief, we propose a dynamic satellite task scheduling method for large area disaster response. First, an initial robust scheduling scheme is generated by a robust satellite scheduling model in which both the profit and the robustness of the schedule are simultaneously maximized. Then, we use a multi-objective optimization model to obtain a series of decomposing schemes. Based on the initial imaging plan, we propose a mixed optimizing algorithm named HA_NSGA-II to allocate the decomposing results thus to obtain an adjusted imaging schedule. A real disaster scenario, i.e., 2008 Wenchuan earthquake, is revisited in terms of rapid response using satellite resources and used to evaluate the performance of the proposed method with state-of-the-art approaches. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.

  11. Global Precipitation Measurement Poster

    Science.gov (United States)

    Azarbarzin, Art

    2010-01-01

    This poster presents an overview of the Global Precipitation Measurement (GPM) constellation of satellites which are designed to measure the Earth's precipitation. It includes the schedule of launches for the various satellites in the constellation, and the coverage of the constellation, It also reviews the mission capabilities, and the mission science objectives.

  12. Analysis of Decadal Vegetation Dynamics Using Multi-Scale Satellite Images

    Science.gov (United States)

    Chiang, Y.; Chen, K.

    2013-12-01

    This study aims at quantifying vegetation fractional cover (VFC) by incorporating multi-resolution satellite images, including Formosat-2(RSI), SPOT(HRV/HRG), Landsat (MSS/TM) and Terra/Aqua(MODIS), to investigate long-term and seasonal vegetation dynamics in Taiwan. We used 40-year NDVI records for derivation of VFC, with field campaigns routinely conducted to calibrate the critical NDVI threshold. Given different sensor capabilities in terms of their spatial and spectral properties, translation and infusion of NDVIs was used to assure NDVI coherence and to determine the fraction of vegetation cover at different spatio-temporal scales. Based on the proposed method, a bimodal sequence of intra-annual VFC which corresponds to the dual-cropping agriculture pattern was observed. Compared to seasonal VFC variation (78~90%), decadal VFC reveals moderate oscillations (81~86%), which were strongly linked with landuse changes and several major disturbances. This time-series mapping of VFC can be used to examine vegetation dynamics and its response associated with short-term and long-term anthropogenic/natural events.

  13. Multi-band microwave photonic satellite repeater scheme employing intensity Mach-Zehnder modulators

    Institute of Scientific and Technical Information of China (English)

    Yin Jie; Dong Tao; Zhang Bin; Hao Yan; Cao Guixing; Cheng Zijing; Xu Kun; Zhou Yue; Dai Jian

    2017-01-01

    To solve the satellite repeater's flexible and wideband frequency conversion problem,we propose a novel microwave photonic repeater system,which can convert the upload signal's carrier to six different frequencies.The scheme employs one 20 GHz bandwidth dual-drive Mach-Zehnder modulator (MZM) and two 10 GHz bandwidth MZMs.The basic principle of this scheme is filtering out two optical sidebands after the optical carrier suppression (OCS) modulation and combining two sidebands modulated by the input radio frequency (RF) signal.This structure can realize simultaneous multi-band frequency conversion with only one frequency-fixed microwave source and prevent generating harmful interference sidebands by using two corresponding optical filters after optical modulation.In the simulation,one C-band signal of 6 GHz carrier can be successfully converted to 12 GHz (Ku-band),28 GHz,34 GHz,40 GHz,46 GHz (Ka-band) and 52 GHz (V-band),which can be an attractive method to realize multi-band microwave photonic satellite repeater.Alternatively,the scheme can be configured to generate multi-band local oscillators (LOs) for widely satellite onboard clock distribution when the input RF signal is replaced by the internal clock source.

  14. Global, Persistent, Real-time Multi-sensor Automated Satellite Image Analysis and Crop Forecasting in Commercial Cloud

    Science.gov (United States)

    Brumby, S. P.; Warren, M. S.; Keisler, R.; Chartrand, R.; Skillman, S.; Franco, E.; Kontgis, C.; Moody, D.; Kelton, T.; Mathis, M.

    2016-12-01

    Cloud computing, combined with recent advances in machine learning for computer vision, is enabling understanding of the world at a scale and at a level of space and time granularity never before feasible. Multi-decadal Earth remote sensing datasets at the petabyte scale (8×10^15 bits) are now available in commercial cloud, and new satellite constellations will generate daily global coverage at a few meters per pixel. Public and commercial satellite observations now provide a wide range of sensor modalities, from traditional visible/infrared to dual-polarity synthetic aperture radar (SAR). This provides the opportunity to build a continuously updated map of the world supporting the academic community and decision-makers in government, finanace and industry. We report on work demonstrating country-scale agricultural forecasting, and global-scale land cover/land, use mapping using a range of public and commercial satellite imagery. We describe processing over a petabyte of compressed raw data from 2.8 quadrillion pixels (2.8 petapixels) acquired by the US Landsat and MODIS programs over the past 40 years. Using commodity cloud computing resources, we convert the imagery to a calibrated, georeferenced, multiresolution tiled format suited for machine-learning analysis. We believe ours is the first application to process, in less than a day, on generally available resources, over a petabyte of scientific image data. We report on work combining this imagery with time-series SAR collected by ESA Sentinel 1. We report on work using this reprocessed dataset for experiments demonstrating country-scale food production monitoring, an indicator for famine early warning. We apply remote sensing science and machine learning algorithms to detect and classify agricultural crops and then estimate crop yields and detect threats to food security (e.g., flooding, drought). The software platform and analysis methodology also support monitoring water resources, forests and other general

  15. Global Precipitation Measurement (GPM) Mission: Precipitation Processing System (PPS) GPM Mission Gridded Text Products Provide Surface Precipitation Retrievals

    Science.gov (United States)

    Stocker, Erich Franz; Kelley, O.; Kummerow, C.; Huffman, G.; Olson, W.; Kwiatkowski, J.

    2015-01-01

    In February 2015, the Global Precipitation Measurement (GPM) mission core satellite will complete its first year in space. The core satellite carries a conically scanning microwave imager called the GPM Microwave Imager (GMI), which also has 166 GHz and 183 GHz frequency channels. The GPM core satellite also carries a dual frequency radar (DPR) which operates at Ku frequency, similar to the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar, and a new Ka frequency. The precipitation processing system (PPS) is producing swath-based instantaneous precipitation retrievals from GMI, both radars including a dual-frequency product, and a combined GMIDPR precipitation retrieval. These level 2 products are written in the HDF5 format and have many additional parameters beyond surface precipitation that are organized into appropriate groups. While these retrieval algorithms were developed prior to launch and are not optimal, these algorithms are producing very creditable retrievals. It is appropriate for a wide group of users to have access to the GPM retrievals. However, for researchers requiring only surface precipitation, these L2 swath products can appear to be very intimidating and they certainly do contain many more variables than the average researcher needs. Some researchers desire only surface retrievals stored in a simple easily accessible format. In response, PPS has begun to produce gridded text based products that contain just the most widely used variables for each instrument (surface rainfall rate, fraction liquid, fraction convective) in a single line for each grid box that contains one or more observations.This paper will describe the gridded data products that are being produced and provide an overview of their content. Currently two types of gridded products are being produced: (1) surface precipitation retrievals from the core satellite instruments GMI, DPR, and combined GMIDPR (2) surface precipitation retrievals for the partner constellation

  16. Fifteen Years (1993–2007 of Surface Freshwater Storage Variability in the Ganges-Brahmaputra River Basin Using Multi-Satellite Observations

    Directory of Open Access Journals (Sweden)

    Edward Salameh

    2017-03-01

    Full Text Available Surface water storage is a key component of the terrestrial hydrological and biogeochemical cycles that also plays a major role in water resources management. In this study, surface water storage (SWS variations are estimated at monthly time-scale over 15 years (1993–2007 using a hypsographic approach based on the combination of topographic information from Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER and Hydrological Modeling and Analysis Platform (HyMAP-based Global Digital Elevation Models (GDEM and the Global Inundation Extent Multi-Satellite (GIEMS product in the Ganges-Brahmaputra basin. The monthly variations of the surface water storage are in good accordance with precipitation from Global Precipitation Climatology Project (GPCP, river discharges at the outlet of the Ganges and the Brahmaputra, and terrestrial water storage (TWS from the Gravity Recovery And Climate Experiment (GRACE, with correlations higher than 0.85. Surface water storage presents a strong seasonal signal (~496 km3 estimated by GIEMS/ASTER and ~378 km3 by GIEMS/HyMAPs, representing ~51% and ~41% respectively of the total water storage signal and it exhibits a large inter-annual variability with strong negative anomalies during the drought-like conditions of 1994 or strong positive anomalies such as in 1998. This new dataset of SWS is a new, highly valuable source of information for hydrological and climate modeling studies of the Ganges-Brahmaputra river basin.

  17. Precise positioning with current multi-constellation Global Navigation Satellite Systems: GPS, GLONASS, Galileo and BeiDou.

    Science.gov (United States)

    Li, Xingxing; Zhang, Xiaohong; Ren, Xiaodong; Fritsche, Mathias; Wickert, Jens; Schuh, Harald

    2015-02-09

    The world of satellite navigation is undergoing dramatic changes with the rapid development of multi-constellation Global Navigation Satellite Systems (GNSSs). At the moment more than 70 satellites are already in view, and about 120 satellites will be available once all four systems (BeiDou + Galileo + GLONASS + GPS) are fully deployed in the next few years. This will bring great opportunities and challenges for both scientific and engineering applications. In this paper we develop a four-system positioning model to make full use of all available observations from different GNSSs. The significant improvement of satellite visibility, spatial geometry, dilution of precision, convergence, accuracy, continuity and reliability that a combining utilization of multi-GNSS brings to precise positioning are carefully analyzed and evaluated, especially in constrained environments.

  18. Determination of the Impact of Urbanization on Agricultural Lands using Multi-temporal Satellite Sensor Images

    Science.gov (United States)

    Kaya, S.; Alganci, U.; Sertel, E.; Ustundag, B.

    2015-12-01

    Throughout the history, agricultural activities have been performed close to urban areas. Main reason behind this phenomenon is the need of fast marketing of the agricultural production to urban residents and financial provision. Thus, using the areas nearby cities for agricultural activities brings out advantage of easy transportation of productions and fast marketing. For decades, heavy migration to cities has directly and negatively affected natural grasslands, forests and agricultural lands. This pressure has caused agricultural lands to be changed into urban areas. Dense urbanization causes increase in impervious surfaces, heat islands and many other problems in addition to destruction of agricultural lands. Considering the negative impacts of urbanization on agricultural lands and natural resources, a periodic monitoring of these changes becomes indisputably important. At this point, satellite images are known to be good data sources for land cover / use change monitoring with their fast data acquisition, large area coverages and temporal resolution properties. Classification of the satellite images provides thematic the land cover / use maps of the earth surface and changes can be determined with GIS based analysis multi-temporal maps. In this study, effects of heavy urbanization over agricultural lands in Istanbul, metropolitan city of Turkey, were investigated with use of multi-temporal Landsat TM satellite images acquired between 1984 and 2011. Images were geometrically registered to each other and classified using supervised maximum likelihood classification algorithm. Resulting thematic maps were exported to GIS environment and destructed agricultural lands by urbanization were determined using spatial analysis.

  19. Verification of the Global Precipitation Measurement (GPM) Satellite by the Olympic Mountains Experiment (OLYMPEX)

    Science.gov (United States)

    McMurdie, L. A.; Houze, R.

    2017-12-01

    Measurements of global precipitation are critical for monitoring Earth's water resources and hydrological processes, including flooding and snowpack accumulation. As such, the Global Precipitation Measurement (GPM) Mission `Core' satellite detects precipitation ranging from light snow to heavy downpours in a wide range locations including remote mountainous regions. The Olympic Mountains Experiment (OLYMPEX) during the 2015-2016 fall-winter season in the mountainous Olympic Peninsula of Washington State provide physical and hydrological validation for GPM precipitation algorithms and insight into the modification of midlatitude storms by passage over mountains. The instrumentation included ground-based dual-polarization Doppler radars on the windward and leeward sides of the Olympic Mountains, surface stations that measured precipitation rates, particle size distributions and fall velocities at various altitudes, research aircraft equipped with cloud microphysics probes, radars, lidar, and passive radiometers, supplemental rawinsondes and dropsondes, and autonomous recording cameras that monitored snowpack accumulation. Results based on dropsize distributions (DSDs) and cross-sections of radar reflectivity over the ocean and windward slopes have revealed important considerations for GPM algorithm development. During periods of great precipitation accumulation and enhancement by the mountains on windward slopes, both warm rain and ice-phase processes are present, implying that it is important for GPM retrievals be sensitive to both types of precipitation mechanisms and to represent accurately the concentration of precipitation at the lowest possible altitudes. OLYMPEX data revealed that a given rain rate could be associated with a variety of DSDs, which presents a challenge for GPM precipitation retrievals in extratropical cyclones passing over mountains. Some of the DSD regimes measured during OLYMPEX stratiform periods have the same characteristics found in prior

  20. Evaluating 20th Century precipitation characteristics between multi-scale atmospheric models with different land-atmosphere coupling

    Science.gov (United States)

    Phillips, M.; Denning, A. S.; Randall, D. A.; Branson, M.

    2016-12-01

    Multi-scale models of the atmosphere provide an opportunity to investigate processes that are unresolved by traditional Global Climate Models while at the same time remaining viable in terms of computational resources for climate-length time scales. The MMF represents a shift away from large horizontal grid spacing in traditional GCMs that leads to overabundant light precipitation and lack of heavy events, toward a model where precipitation intensity is allowed to vary over a much wider range of values. Resolving atmospheric motions on the scale of 4 km makes it possible to recover features of precipitation, such as intense downpours, that were previously only obtained by computationally expensive regional simulations. These heavy precipitation events may have little impact on large-scale moisture and energy budgets, but are outstanding in terms of interaction with the land surface and potential impact on human life. Three versions of the Community Earth System Model were used in this study; the standard CESM, the multi-scale `Super-Parameterized' CESM where large-scale parameterizations have been replaced with a 2D cloud-permitting model, and a multi-instance land version of the SP-CESM where each column of the 2D CRM is allowed to interact with an individual land unit. These simulations were carried out using prescribed Sea Surface Temperatures for the period from 1979-2006 with daily precipitation saved for all 28 years. Comparisons of the statistical properties of precipitation between model architectures and against observations from rain gauges were made, with specific focus on detection and evaluation of extreme precipitation events.

  1. Assessment of Precipitation Data Generated by GPM and TRMM Satellites

    Directory of Open Access Journals (Sweden)

    Luísa Carolina Silva Lelis

    Full Text Available Abstract This study aimed to verify the performance of the information produced by the GPM (Global Precipitation Measurement mission and TRMM (Tropical Rainfall Measurement Mission on the eastern region of São Paulo state, based on a comparison of rainfall data from DAEE (Department of Waters and Electric Energy of São Paulo State. The comparison was done by comparing spatially aggregated information from both sources. In order to analyze the results, we measured: (1 Relative Difference, (2 BIAS and (3 Root Mean Square Error (RMSE. It was found that the relative differences were in the range of -20% to 20% for both missions. Analyzing the BIAS for both satellites it was observed that 68% of the measurements were overestimated. The highest agreement was obtained for the mesoregion of Campinas and the lowest for Araraquara. In the TRMM, the lowest RMSE values were found in the Araraquara mesoregion and the highest in Piracicaba. In the GPM the closest measured values were observed in the Piracicaba mesoregion, while the most distant values were identified in Araraquara. All the analyzes of this work demonstrated similarity between the errors generated by both satellites. New comparison studies are needed to better understand the products.

  2. Statistical characterisation of COSMO Sky-Med X-SAR retrieved precipitation fields by scale-invariance analysis

    Science.gov (United States)

    Deidda, Roberto; Mascaro, Giuseppe; Hellies, Matteo; Baldini, Luca; Roberto, Nicoletta

    2013-04-01

    COSMO Sky-Med (CSK) is an important programme of the Italian Space Agency aiming at supporting environmental monitoring and management of exogenous, endogenous and anthropogenic risks through X-band Synthetic Aperture Radar (X-SAR) on board of 4 satellites forming a constellation. Most of typical SAR applications are focused on land or ocean observation. However, X-band SAR can be detect precipitation that results in a specific signature caused by the combination of attenuation of surface returns induced by precipitation and enhancement of backscattering determined by the hydrometeors in the SAR resolution volume. Within CSK programme, we conducted an intercomparison between the statistical properties of precipitation fields derived by CSK SARs and those derived by the CNR Polar 55C (C-band) ground based weather radar located in Rome (Italy). This contribution presents main results of this research which was aimed at the robust characterisation of rainfall statistical properties across different scales by means of scale-invariance analysis and multifractal theory. The analysis was performed on a dataset of more two years of precipitation observations collected by the CNR Polar 55C radar and rainfall fields derived from available images collected by the CSK satellites during intense rainfall events. Scale-invariance laws and multifractal properties were detected on the most intense rainfall events derived from the CNR Polar 55C radar for spatial scales from 4 km to 64 km. The analysis on X-SAR retrieved rainfall fields, although based on few images, leaded to similar results and confirmed the existence of scale-invariance and multifractal properties for scales larger than 4 km. These outcomes encourage investigating SAR methodologies for future development of meteo-hydrological forecasting models based on multifractal theory.

  3. On the Characterization of Rainfall Associated with U.S. Landfalling North Atlantic Tropical Cyclones Based on Satellite Data and Numerical Weather Prediction Outputs

    Science.gov (United States)

    Luitel, B. N.; Villarini, G.; Vecchi, G. A.

    2014-12-01

    When we talk about tropical cyclones (TCs), the first things that come to mind are strong winds and storm surge affecting the coastal areas. However, according to the Federal Emergency Management Agency (FEMA) 59% of the deaths caused by TCs since 1970 is due to fresh water flooding. Heavy rainfall associated with TCs accounts for 13% of heavy rainfall events nationwide for the June-October months, with this percentage being much higher if the focus is on the eastern and southern United States. This study focuses on the evaluation of precipitation associated with the North Atlantic TCs that affected the continental United States over the period 2007 - 2012. We evaluate the rainfall associated with these TCs using four satellite based rainfall products: Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA; both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); Climate Prediction Center (CPC) MORPHing technique (CMORPH). As a reference data we use gridded rainfall provided by CPC (Daily US Unified Gauge-Based Analysis of Precipitation). Rainfall fields from each of these satellite products are compared to the reference data, providing valuable information about the realism of these products in reproducing the rainfall associated with TCs affecting the continental United States. In addition to the satellite products, we evaluate the forecasted rainfall produced by five state-of-the-art numerical weather prediction (NWP) models: European Centre for Medium-Range Weather Forecasts (ECMWF), UK Met Office (UKMO), National Centers for Environmental Prediction (NCEP), China Meteorological Administration (CMA), and Canadian Meteorological Center (CMC). The skill of these models in reproducing TC rainfall is quantified for different lead times, and discussed in light of the performance of the satellite products.

  4. Effect of intermetallic precipitation on the properties of multi passed duplex stainless steel weldment

    Energy Technology Data Exchange (ETDEWEB)

    Bae, Seong Han [Technology research institute, Ulsan (Korea, Republic of); Lee, Hae Woo [Dong-A University, Busan (Korea, Republic of)

    2014-01-15

    This study investigated the effect of the aging time of weldment of 24Cr-3.5Mo duplex stainless steel on the microstructure and corrosion behavior. After performing FCAW, we carried out heat treatments at varying times at 850 ℃ and performed observation of microstructure, potentio dynamic test, SEM-EDS analysis, and X-ray diffraction analysis. As the aging time increased, the fraction of δ-ferrite decreased sharply, but the fraction of γ slightly increased. The σ phase was generated at a non-metallic inclusion along the grain boundaries of δ-ferrite and γ, while the χ phase was generated in the structure of δ-ferrite. As the intermetallic compounds increased, the critical pitting potential fell sharply, and PREN of the surrounding structure decreased by 5 due to precipitation of the σ phase in 3.5% NaCl at 60 ℃. Pitting occurred intensively under a multi-pass line which relatively had more intermetallic compounds, and the precipitation of the σ phase caused the formation of Cr carbide.

  5. Effect of intermetallic precipitation on the properties of multi passed duplex stainless steel weldment

    International Nuclear Information System (INIS)

    Bae, Seong Han; Lee, Hae Woo

    2014-01-01

    This study investigated the effect of the aging time of weldment of 24Cr-3.5Mo duplex stainless steel on the microstructure and corrosion behavior. After performing FCAW, we carried out heat treatments at varying times at 850 ℃ and performed observation of microstructure, potentio dynamic test, SEM-EDS analysis, and X-ray diffraction analysis. As the aging time increased, the fraction of δ-ferrite decreased sharply, but the fraction of γ slightly increased. The σ phase was generated at a non-metallic inclusion along the grain boundaries of δ-ferrite and γ, while the χ phase was generated in the structure of δ-ferrite. As the intermetallic compounds increased, the critical pitting potential fell sharply, and PREN of the surrounding structure decreased by 5 due to precipitation of the σ phase in 3.5% NaCl at 60 ℃. Pitting occurred intensively under a multi-pass line which relatively had more intermetallic compounds, and the precipitation of the σ phase caused the formation of Cr carbide.

  6. 3D reconstruction from multi-view VHR-satellite images in MicMac

    Science.gov (United States)

    Rupnik, Ewelina; Pierrot-Deseilligny, Marc; Delorme, Arthur

    2018-05-01

    This work addresses the generation of high quality digital surface models by fusing multiple depths maps calculated with the dense image matching method. The algorithm is adapted to very high resolution multi-view satellite images, and the main contributions of this work are in the multi-view fusion. The algorithm is insensitive to outliers, takes into account the matching quality indicators, handles non-correlated zones (e.g. occlusions), and is solved with a multi-directional dynamic programming approach. No geometric constraints (e.g. surface planarity) or auxiliary data in form of ground control points are required for its operation. Prior to the fusion procedures, the RPC geolocation parameters of all images are improved in a bundle block adjustment routine. The performance of the algorithm is evaluated on two VHR (Very High Resolution)-satellite image datasets (Pléiades, WorldView-3) revealing its good performance in reconstructing non-textured areas, repetitive patterns, and surface discontinuities.

  7. Multi-pentad prediction of precipitation variability over Southeast Asia during boreal summer using BCC_CSM1.2

    Science.gov (United States)

    Li, Chengcheng; Ren, Hong-Li; Zhou, Fang; Li, Shuanglin; Fu, Joshua-Xiouhua; Li, Guoping

    2018-06-01

    Precipitation is highly variable in space and discontinuous in time, which makes it challenging for models to predict on subseasonal scales (10-30 days). We analyze multi-pentad predictions from the Beijing Climate Center Climate System Model version 1.2 (BCC_CSM1.2), which are based on hindcasts from 1997 to 2014. The analysis focus on the skill of the model to predict precipitation variability over Southeast Asia from May to September, as well as its connections with intraseasonal oscillation (ISO). The effective precipitation prediction length is about two pentads (10 days), during which the skill measured by anomaly correlation is greater than 0.1. In order to further evaluate the performance of the precipitation prediction, the diagnosis results of the skills of two related circulation fields show that the prediction skills for the circulation fields exceed that of precipitation. Moreover, the prediction skills tend to be higher when the amplitude of ISO is large, especially for a boreal summer intraseasonal oscillation. The skills associated with phases 2 and 5 are higher, but that of phase 3 is relatively lower. Even so, different initial phases reflect the same spatial characteristics, which shows higher skill of precipitation prediction in the northwest Pacific Ocean. Finally, filter analysis is used on the prediction skills of total and subseasonal anomalies. The results of the two anomaly sets are comparable during the first two lead pentads, but thereafter the skill of the total anomalies is significantly higher than that of the subseasonal anomalies. This paper should help advance research in subseasonal precipitation prediction.

  8. Appraising city-scale pollution monitoring capabilities of multi-satellite datasets using portable pollutant monitors

    Science.gov (United States)

    Aliyu, Yahaya A.; Botai, Joel O.

    2018-04-01

    The retrieval characteristics for a city-scale satellite experiment was explored over a Nigerian city. The study evaluated carbon monoxide and aerosol contents in the city atmosphere. We utilized the MSA Altair 5× gas detector and CW-HAT200 particulate counter to investigate the city-scale monitoring capabilities of satellite pollution observing instruments; atmospheric infrared sounder (AIRS), measurement of pollution in the troposphere (MOPITT), moderate resolution imaging spectroradiometer (MODIS), multi-angle imaging spectroradiometer (MISR) and ozone monitoring instrument (OMI). To achieve this, we employed the Kriging interpolation technique to collocate the satellite pollutant estimations over 19 ground sample sites for the period of 2015-2016. The portable pollutant devices were validated using the WHO air filter sampling model. To determine the city-scale performance of the satellite datasets, performance indicators: correlation coefficient, model efficiency, reliability index and root mean square error, were adopted as measures. The comparative analysis revealed that MOPITT carbon monoxide (CO) and MODIS aerosol optical depth (AOD) estimates are the appropriate satellite measurements for ground equivalents in Zaria, Nigeria. Our findings were within the acceptable limits of similar studies that utilized reference stations. In conclusion, this study offers direction to Nigeria's air quality policy organizers about available alternative air pollution measurements for mitigating air quality effects within its limited resource environment.

  9. MultiSpec—a tool for multispectral hyperspectral image data analysis

    Science.gov (United States)

    Biehl, Larry; Landgrebe, David

    2002-12-01

    MultiSpec is a multispectral image data analysis software application. It is intended to provide a fast, easy-to-use means for analysis of multispectral image data, such as that from the Landsat, SPOT, MODIS or IKONOS series of Earth observational satellites, hyperspectral data such as that from the Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) and EO-1 Hyperion satellite system or the data that will be produced by the next generation of Earth observational sensors. The primary purpose for the system was to make new, otherwise complex analysis tools available to the general Earth science community. It has also found use in displaying and analyzing many other types of non-space related digital imagery, such as medical image data and in K-12 and university level educational activities. MultiSpec has been implemented for both the Apple Macintosh ® and Microsoft Windows ® operating systems (OS). The effort was first begun on the Macintosh OS in 1988. The GLOBE ( http://www.globe.gov) program supported the development of a subset of MultiSpec for the Windows OS in 1995. Since then most (but not all) of the features in the Macintosh OS version have been ported to the Windows OS version. Although copyrighted, MultiSpec with its documentation is distributed without charge. The Macintosh and Windows versions and documentation on its use are available from the World Wide Web at URL: http://dynamo.ecn.purdue.edu/˜biehl/MultiSpec/ MultiSpec is copyrighted (1991-2001) by Purdue Research Foundation, West Lafayette, Indiana 47907.

  10. Handbook of satellite applications

    CERN Document Server

    Madry, Scott; Camacho-Lara, Sergio

    2013-01-01

    Top space experts from around the world have collaborated to produce this comprehensive, authoritative, and clearly illustrated reference guide to the fast growing, multi-billion dollar field of satellite applications and space communications. This handbook, done under the auspices of the International Space University based in France, addresses not only system technologies but also examines market dynamics, technical standards and regulatory constraints. The handbook is a completely multi-disciplinary reference book that covers, in an in-depth fashion, the fields of satellite telecommunications, Earth observation, remote sensing, satellite navigation, geographical information systems, and geosynchronous meteorological systems. It covers current practices and designs as well as advanced concepts and future systems. It provides a comparative analysis of the common technologies and design elements for satellite application bus structures, thermal controls, power systems, stabilization techniques, telemetry, com...

  11. Multi sensor satellite imagers for commercial remote sensing

    Science.gov (United States)

    Cronje, T.; Burger, H.; Du Plessis, J.; Du Toit, J. F.; Marais, L.; Strumpfer, F.

    2005-10-01

    This paper will discuss and compare recent refractive and catodioptric imager designs developed and manufactured at SunSpace for Multi Sensor Satellite Imagers with Panchromatic, Multi-spectral, Area and Hyperspectral sensors on a single Focal Plane Array (FPA). These satellite optical systems were designed with applications to monitor food supplies, crop yield and disaster monitoring in mind. The aim of these imagers is to achieve medium to high resolution (2.5m to 15m) spatial sampling, wide swaths (up to 45km) and noise equivalent reflectance (NER) values of less than 0.5%. State-of-the-art FPA designs are discussed and address the choice of detectors to achieve these performances. Special attention is given to thermal robustness and compactness, the use of folding prisms to place multiple detectors in a large FPA and a specially developed process to customize the spectral selection with the need to minimize mass, power and cost. A refractive imager with up to 6 spectral bands (6.25m GSD) and a catodioptric imager with panchromatic (2.7m GSD), multi-spectral (6 bands, 4.6m GSD), hyperspectral (400nm to 2.35μm, 200 bands, 15m GSD) sensors on the same FPA will be discussed. Both of these imagers are also equipped with real time video view finding capabilities. The electronic units could be subdivided into the Front-End Electronics and Control Electronics with analogue and digital signal processing. A dedicated Analogue Front-End is used for Correlated Double Sampling (CDS), black level correction, variable gain and up to 12-bit digitizing and high speed LVDS data link to a mass memory unit.

  12. Microphysics in Multi-scale Modeling System with Unified Physics

    Science.gov (United States)

    Tao, Wei-Kuo

    2012-01-01

    Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.

  13. Validation of precipitation over Japan during 1985-2004 simulated by three regional climate models and two multi-model ensemble means

    Energy Technology Data Exchange (ETDEWEB)

    Ishizaki, Yasuhiro [Meteorological Research Institute, Tsukuba (Japan); National Institute for Environmental Studies, Tsukuba (Japan); Nakaegawa, Toshiyuki; Takayabu, Izuru [Meteorological Research Institute, Tsukuba (Japan)

    2012-07-15

    We dynamically downscaled Japanese reanalysis data (JRA-25) for 60 regions of Japan using three regional climate models (RCMs): the Non-Hydrostatic Regional Climate Model (NHRCM), modified RAMS version 4.3 (NRAMS), and modified Weather Research and Forecasting model (TWRF). We validated their simulations of the precipitation climatology and interannual variations of summer and winter precipitation. We also validated precipitation for two multi-model ensemble means: the arithmetic ensemble mean (AEM) and an ensemble mean weighted according to model reliability. In the 60 regions NRAMS simulated both the winter and summer climatological precipitation better than JRA-25, and NHRCM simulated the wintertime precipitation better than JRA-25. TWRF, however, overestimated precipitation in the 60 regions in both the winter and summer, and NHRCM overestimated precipitation in the summer. The three RCMs simulated interannual variations, particularly summer precipitation, better than JRA-25. AEM simulated both climatological precipitation and interannual variations during the two seasons more realistically than JRA-25 and the three RCMs overall, but the best RCM was often superior to the AEM result. In contrast, the weighted ensemble mean skills were usually superior to those of the best RCM. Thus, both RCMs and multi-model ensemble means, especially multi-model ensemble means weighted according to model reliability, are powerful tools for simulating seasonal and interannual variability of precipitation in Japan under the current climate. (orig.)

  14. Assessing the Relative Performance of Microwave-Based Satellite Rain Rate Retrievals Using TRMM Ground Validation Data

    Science.gov (United States)

    Wolff, David B.; Fisher, Brad L.

    2011-01-01

    -B, however, agreed well with GV when the matching data was analyzed on monthly scales. These results signal developers of global rainfall products, such as the TRMM Multi-Satellite Precipitation Analysis (TMPA), and the Climate Data Center s Morphing (CMORPH) technique, that care must be taken when incorporating data from these input satellite estimates in order to provide the highest quality estimates in their products.

  15. DS-CDMA satellite diversity reception for personal satellite communication: Downlink performance analysis

    Science.gov (United States)

    DeGaudenzi, Riccardo; Giannetti, Filippo

    1995-01-01

    The downlink of a satellite-mobile personal communication system employing power-controlled Direct Sequence Code Division Multiple Access (DS-CDMA) and exploiting satellite-diversity is analyzed and its performance compared with a more traditional communication system utilizing single satellite reception. The analytical model developed has been thoroughly validated by means of extensive Monte Carlo computer simulations. It is shown how the capacity gain provided by diversity reception shrinks considerably in the presence of increasing traffic or in the case of light shadowing conditions. Moreover, the quantitative results tend to indicate that to combat system capacity reduction due to intra-system interference, no more than two satellites shall be active over the same region. To achieve higher system capacity, differently from terrestrial cellular systems, Multi-User Detection (MUD) techniques are likely to be required in the mobile user terminal, thus considerably increasing its complexity.

  16. Impact of Asian Aerosols on Precipitation Over California: An Observational and Model Based Approach

    Science.gov (United States)

    Naeger, Aaron R.; Molthan, Andrew L.; Zavodsky, Bradley T.; Creamean, Jessie M.

    2015-01-01

    Dust and pollution emissions from Asia are often transported across the Pacific Ocean to over the western United States. Therefore, it is essential to fully understand the impact of these aerosols on clouds and precipitation forming over the eastern Pacific and western United States, especially during atmospheric river events that account for up to half of California's annual precipitation and can lead to widespread flooding. In order for numerical modeling simulations to accurately represent the present and future regional climate of the western United States, we must account for the aerosol-cloud-precipitation interactions associated with Asian dust and pollution aerosols. Therefore, we have constructed a detailed study utilizing multi-sensor satellite observations, NOAA-led field campaign measurements, and targeted numerical modeling studies where Asian aerosols interacted with cloud and precipitation processes over the western United States. In particular, we utilize aerosol optical depth retrievals from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS), NOAA Geostationary Operational Environmental Satellite (GOES-11), and Japan Meteorological Agency (JMA) Multi-functional Transport Satellite (MTSAT) to effectively detect and monitor the trans-Pacific transport of Asian dust and pollution. The aerosol optical depth (AOD) retrievals are used in assimilating the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) in order to provide the model with an accurate representation of the aerosol spatial distribution across the Pacific. We conduct WRF-Chem model simulations of several cold-season atmospheric river events that interacted with Asian aerosols and brought significant precipitation over California during February-March 2011 when the NOAA CalWater field campaign was ongoing. The CalWater field campaign consisted of aircraft and surface measurements of aerosol and precipitation processes that help extensively validate our WRF

  17. Improving PERSIANN-CCS rain estimation using probabilistic approach and multi-sensors information

    Science.gov (United States)

    Karbalaee, N.; Hsu, K. L.; Sorooshian, S.; Kirstetter, P.; Hong, Y.

    2016-12-01

    This presentation discusses the recent implemented approaches to improve the rainfall estimation from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Cloud Classification System (PERSIANN-CCS). PERSIANN-CCS is an infrared (IR) based algorithm being integrated in the IMERG (Integrated Multi-Satellite Retrievals for the Global Precipitation Mission GPM) to create a precipitation product in 0.1x0.1degree resolution over the chosen domain 50N to 50S every 30 minutes. Although PERSIANN-CCS has a high spatial and temporal resolution, it overestimates or underestimates due to some limitations.PERSIANN-CCS can estimate rainfall based on the extracted information from IR channels at three different temperature threshold levels (220, 235, and 253k). This algorithm relies only on infrared data to estimate rainfall indirectly from this channel which cause missing the rainfall from warm clouds and false estimation for no precipitating cold clouds. In this research the effectiveness of using other channels of GOES satellites such as visible and water vapors has been investigated. By using multi-sensors the precipitation can be estimated based on the extracted information from multiple channels. Also, instead of using the exponential function for estimating rainfall from cloud top temperature, the probabilistic method has been used. Using probability distributions of precipitation rates instead of deterministic values has improved the rainfall estimation for different type of clouds.

  18. Inter-comparison of Rainfall Estimation from Radar and Satellite During 2016 June 23 Yancheng Tornado Event over Eastern China

    Science.gov (United States)

    Huang, C.; Chen, S.; Liang, Z.; Hu, B.

    2017-12-01

    ABSTRACT: On the afternoon of June 23, 2016, Yancheng city in eastern China was hit by a severe thunderstorm that produced a devastating tornado. This tornado was ranked as an EF4 on the Enhanced Fujita scale by China Meteorological Administration, and killed at least 99 people and injured 846 others (152 seriously). This study evaluates rainfall estimates from ground radar network and four satellite algorithms with a relatively dense rain gauge network over eastern China including Jiangsu province and its adjacent regions for the Yancheng June 23 Tornado extreme convective storm in different spatiotemporal scales (from 0.04° to 0.1° and hourly to event total accumulation). The radar network is composed of about 6 S-band Doppler weather radars. Satellite precipitation products include Integrated Multi-satellitE Retrievals for GPM (IMERG), Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS), and Global Satellite Mapping of Precipitation (GSMap). Relative Bias (RB), Root-Mean-Squared Error (RMSE), Correlation Coefficient (CC), Probability Of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) are used to quantify the performance of these precipitation products.

  19. Error Analysis and Evaluation of the Latest GSMap and IMERG Precipitation Products over Eastern China

    Directory of Open Access Journals (Sweden)

    Shaowei Ning

    2017-01-01

    Full Text Available The present study comprehensively analyzes error characteristics and performance of the two latest GPM-era satellite precipitation products over eastern China from April 2014 to March 2016. Analysis results indicate that the two products have totally different spatial distributions of total bias. Many of the underestimations for the GSMap-gauged could be traced to significant hit bias, with a secondary contribution from missed precipitation. For IMERG, total bias illustrates significant overestimation over most of the eastern part of China, except upper reaches of Yangtze and Yellow River basins. GSMap-gauged tends to overestimate light precipitation (<16 mm/day and underestimate precipitation with rain rate larger than 16 mm/day; however, IMERG underestimates precipitation at rain rate between 8 and 64 mm/day and overestimates precipitation at rain rate more than 64 mm/day. IMERG overestimates extreme precipitation indices (RR99P and R20TOT, with relative bias values of 17.9% and 11.5%, respectively. But GSMap-gauged shows significant underestimation of these indices. In addition, both products performed well in the Huaihe, Liaohe, and Yangtze River basins for extreme precipitation detection. At basin scale comparisons, the GSMap-gauged data has a relatively higher accuracy than IMERG, especially at the Haihe, Huaihe, Liaohe, and Yellow River basins.

  20. Multi-Point Measurements to Characterize Radiation Belt Electron Precipitation Loss

    Science.gov (United States)

    Blum, L. W.

    2017-12-01

    Multipoint measurements in the inner magnetosphere allow the spatial and temporal evolution of various particle populations and wave modes to be disentangled. To better characterize and quantify radiation belt precipitation loss, we utilize multi-point measurements both to study precipitating electrons directly as well as the potential drivers of this loss process. Magnetically conjugate CubeSat and balloon measurements are combined to estimate of the temporal and spatial characteristics of dusk-side precipitation features and quantify loss due to these events. To then understand the drivers of precipitation events, and what determines their spatial structure, we utilize measurements from the dual Van Allen Probes to estimate spatial and temporal scales of various wave modes in the inner magnetosphere, and compare these to precipitation characteristics. The structure, timing, and spatial extent of waves are compared to those of MeV electron precipitation during a few individual events to determine when and where EMIC waves cause radiation belt electron precipitation. Magnetically conjugate measurements provide observational support of the theoretical picture of duskside interaction of EMIC waves and MeV electrons leading to radiation belt loss. Finally, understanding the drivers controlling the spatial scales of wave activity in the inner magnetosphere is critical for uncovering the underlying physics behind the wave generation as well as for better predicting where and when waves will be present. Again using multipoint measurements from the Van Allen Probes, we estimate the spatial and temporal extents and evolution of plasma structures and their gradients in the inner magnetosphere, to better understand the drivers of magnetospheric wave characteristic scales. In particular, we focus on EMIC waves and the plasma parameters important for their growth, namely cold plasma density and cool and warm ion density, anisotropy, and composition.

  1. SHORT-TERM PRECIPITATION OCCURRENCE PREDICTION FOR STRONG CONVECTIVE WEATHER USING FY2-G SATELLITE DATA: A CASE STUDY OF SHENZHEN,SOUTH CHINA

    Directory of Open Access Journals (Sweden)

    K. Chen

    2016-06-01

    Full Text Available Short-term precipitation commonly occurs in south part of China, which brings intensive precipitation in local region for very short time. Massive water would cause the intensive flood inside of city when precipitation amount beyond the capacity of city drainage system. Thousands people’s life could be influenced by those short-term disasters and the higher city managements are required to facing these challenges. How to predict the occurrence of heavy precipitation accurately is one of the worthwhile scientific questions in meteorology. According to recent studies, the accuracy of short-term precipitation prediction based on numerical simulation model still remains low reliability, in some area where lack of local observations, the accuracy may be as low as 10%. The methodology for short term precipitation occurrence prediction still remains a challenge. In this paper, a machine learning method based on SVM was presented to predict short-term precipitation occurrence by using FY2-G satellite imagery and ground in situ observation data. The results were validated by traditional TS score which commonly used in evaluation of weather prediction. The results indicate that the proposed algorithm can present overall accuracy up to 90% for one-hour to six-hour forecast. The result implies the prediction accuracy could be improved by using machine learning method combining with satellite image. This prediction model can be further used to evaluated to predicted other characteristics of weather in Shenzhen in future.

  2. Satellite observations of energetic electron precipitation during the 1979 solar eclipse and comparisons with rocket measurements

    Science.gov (United States)

    Gaines, E. E.; Imhof, W. L.; Voss, H. D.; Reagan, J. B.

    1983-07-01

    During the solar eclipse of 26 February 1979, the P78-1 satellite passed near Red Lake, Ontario, at an altitude of about 600 km. On two consecutive orbits spanning the time of total eclipse, energetic electrons were measured with two silicon solid state detector spectrometers having excellent energy and angular resolution. Significant fluxes of precipitating electrons were observed near the path of totality. Comparisons of flux intensities and energy spectra with those measured from a Nike Orion and two Nike Tomahawk rockets launched near Red Lake before and during total eclipse give good agreement and indicate that the electron precipitation was relatively uniform for more than an hour and over a broad geographical area.

  3. Satellite observations of energetic electron precipitation during the 1979 solar eclipse and comparisons with rocket measurements

    International Nuclear Information System (INIS)

    Gaines, E.E.; Imhof, W.L.; Voss, H.D.; Reagan, J.B.

    1983-01-01

    During the solar eclipse of 26 February 1979, the P78-1 satellite passed near Red Lake, Ontario, at an altitude of approx. 600 km. On two consecutive orbits spanning the time of total eclipse, energetic electrons were measured with two silicon solid state detector spectrometers having excellent energy and angular resolution. Significant fluxes of precipitating electrons were observed near the path of totality. Comparisons of flux intensities and energy spectra with those measured from a Nike Orion and two Nike Tomahawk rockets launched near Red Lake before and during total eclipse give good agreement and indicate that the electron precipitation was relatively uniform for more than an hour and over a broad geographical area. (author)

  4. Adaptation of an aerosol retrieval algorithm using multi-wavelength and multi-pixel information of satellites (MWPM) to GOSAT/TANSO-CAI

    Science.gov (United States)

    Hashimoto, M.; Takenaka, H.; Higurashi, A.; Nakajima, T.

    2017-12-01

    Aerosol in the atmosphere is an important constituent for determining the earth's radiation budget, so the accurate aerosol retrievals from satellite is useful. We have developed a satellite remote sensing algorithm to retrieve the aerosol optical properties using multi-wavelength and multi-pixel information of satellite imagers (MWPM). The method simultaneously derives aerosol optical properties, such as aerosol optical thickness (AOT), single scattering albedo (SSA) and aerosol size information, by using spatial difference of wavelegths (multi-wavelength) and surface reflectances (multi-pixel). The method is useful for aerosol retrieval over spatially heterogeneous surface like an urban region. In this algorithm, the inversion method is a combination of an optimal method and smoothing constraint for the state vector. Furthermore, this method has been combined with the direct radiation transfer calculation (RTM) numerically solved by each iteration step of the non-linear inverse problem, without using look up table (LUT) with several constraints. However, it takes too much computation time. To accelerate the calculation time, we replaced the RTM with an accelerated RTM solver learned by neural network-based method, EXAM (Takenaka et al., 2011), using Rster code. And then, the calculation time was shorternd to about one thouthandth. We applyed MWPM combined with EXAM to GOSAT/TANSO-CAI (Cloud and Aerosol Imager). CAI is a supplement sensor of TANSO-FTS, dedicated to measure cloud and aerosol properties. CAI has four bands, 380, 674, 870 and 1600 nm, and observes in 500 meters resolution for band1, band2 and band3, and 1.5 km for band4. Retrieved parameters are aerosol optical properties, such as aerosol optical thickness (AOT) of fine and coarse mode particles at a wavelenth of 500nm, a volume soot fraction in fine mode particles, and ground surface albedo of each observed wavelength by combining a minimum reflectance method and Fukuda et al. (2013). We will show

  5. Climatology and Interannual Variability of Quasi-Global Intense Precipitation Using Satellite Observations

    Science.gov (United States)

    Ricko, Martina; Adler, Robert F.; Huffman, George J.

    2016-01-01

    Climatology and variations of recent mean and intense precipitation over a near-global (50 deg. S 50 deg. N) domain on a monthly and annual time scale are analyzed. Data used to derive daily precipitation to examine the effects of spatial and temporal coverage of intense precipitation are from the current Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 version 7 precipitation product, with high spatial and temporal resolution during 1998 - 2013. Intense precipitation is defined by several different parameters, such as a 95th percentile threshold of daily precipitation, a mean precipitation that exceeds that percentile, or a fixed threshold of daily precipitation value [e.g., 25 and 50 mm day(exp -1)]. All parameters are used to identify the main characteristics of spatial and temporal variation of intense precipitation. High correlations between examined parameters are observed, especially between climatological monthly mean precipitation and intense precipitation, over both tropical land and ocean. Among the various parameters examined, the one best characterizing intense rainfall is a fraction of daily precipitation Great than or equal to 25 mm day(exp. -1), defined as a ratio between the intense precipitation above the used threshold and mean precipitation. Regions that experience an increase in mean precipitation likely experience a similar increase in intense precipitation, especially during the El Nino Southern Oscillation (ENSO) events. Improved knowledge of this intense precipitation regime and its strong connection to mean precipitation given by the fraction parameter can be used for monitoring of intense rainfall and its intensity on a global to regional scale.

  6. A meteo-hydrological prediction system based on a multi-model approach for precipitation forecasting

    Directory of Open Access Journals (Sweden)

    S. Davolio

    2008-02-01

    Full Text Available The precipitation forecasted by a numerical weather prediction model, even at high resolution, suffers from errors which can be considerable at the scales of interest for hydrological purposes. In the present study, a fraction of the uncertainty related to meteorological prediction is taken into account by implementing a multi-model forecasting approach, aimed at providing multiple precipitation scenarios driving the same hydrological model. Therefore, the estimation of that uncertainty associated with the quantitative precipitation forecast (QPF, conveyed by the multi-model ensemble, can be exploited by the hydrological model, propagating the error into the hydrological forecast.

    The proposed meteo-hydrological forecasting system is implemented and tested in a real-time configuration for several episodes of intense precipitation affecting the Reno river basin, a medium-sized basin located in northern Italy (Apennines. These episodes are associated with flood events of different intensity and are representative of different meteorological configurations responsible for severe weather affecting northern Apennines.

    The simulation results show that the coupled system is promising in the prediction of discharge peaks (both in terms of amount and timing for warning purposes. The ensemble hydrological forecasts provide a range of possible flood scenarios that proved to be useful for the support of civil protection authorities in their decision.

  7. Joint Center for Satellite Data Assimilation Overview and Research Activities

    Science.gov (United States)

    Auligne, T.

    2017-12-01

    In 2001 NOAA/NESDIS, NOAA/NWS, NOAA/OAR, and NASA, subsequently joined by the US Navy and Air Force, came together to form the Joint Center for Satellite Data Assimilation (JCSDA) for the common purpose of accelerating the use of satellite data in environmental numerical prediction modeling by developing, using, and anticipating advances in numerical modeling, satellite-based remote sensing, and data assimilation methods. The primary focus was to bring these advances together to improve operational numerical model-based forecasting, under the premise that these partners have common technical and logistical challenges assimilating satellite observations into their modeling enterprises that could be better addressed through cooperative action and/or common solutions. Over the last 15 years, the JCSDA has made and continues to make major contributions to operational assimilation of satellite data. The JCSDA is a multi-agency U.S. government-owned-and-operated organization that was conceived as a venue for the several agencies NOAA, NASA, USAF and USN to collaborate on advancing the development and operational use of satellite observations into numerical model-based environmental analysis and forecasting. The primary mission of the JCSDA is to "accelerate and improve the quantitative use of research and operational satellite data in weather, ocean, climate and environmental analysis and prediction systems." This mission is fulfilled through directed research targeting the following key science objectives: Improved radiative transfer modeling; new instrument assimilation; assimilation of humidity, clouds, and precipitation observations; assimilation of land surface observations; assimilation of ocean surface observations; atmospheric composition; and chemistry and aerosols. The goal of this presentation is to briefly introduce the JCSDA's mission and vision, and to describe recent research activities across various JCSDA partners.

  8. Multi-satellite sensor study on precipitation-induced emission pulses of NOx from soils in semi-arid ecosystems

    Directory of Open Access Journals (Sweden)

    J. Zörner

    2016-07-01

    Full Text Available We present a top-down approach to infer and quantify rain-induced emission pulses of NOx ( ≡  NO + NO2, stemming from biotic emissions of NO from soils, from satellite-borne measurements of NO2. This is achieved by synchronizing time series at single grid pixels according to the first day of rain after a dry spell of prescribed duration. The full track of the temporal evolution several weeks before and after a rain pulse is retained with daily resolution. These are needed for a sophisticated background correction, which accounts for seasonal variations in the time series and allows for improved quantification of rain-induced soil emissions. The method is applied globally and provides constraints on pulsed soil emissions of NOx in regions where the NOx budget is seasonally dominated by soil emissions. We find strong peaks of enhanced NO2 vertical column densities (VCDs induced by the first intense precipitation after prolonged droughts in many semi-arid regions of the world, in particular in the Sahel. Detailed investigations show that the rain-induced NO2 pulse detected by the OMI (Ozone Monitoring Instrument, GOME-2 and SCIAMACHY satellite instruments could not be explained by other sources, such as biomass burning or lightning, or by retrieval artefacts (e.g. due to clouds. For the Sahel region, absolute enhancements of the NO2 VCDs on the first day of rain based on OMI measurements 2007–2010 are on average 4 × 1014  molec cm−2 and exceed 1 × 1015  molec cm−2 for individual grid cells. Assuming a NOx lifetime of 4 h, this corresponds to soil NOx emissions in the range of 6 up to 65 ng N m−2 s−1, which is in good agreement with literature values. Apart from the clear first-day peak, NO2 VCDs are moderately enhanced (2 × 1014  molec cm−2 compared to the background over the following 2 weeks, suggesting potential further emissions during that period of about 3.3 ng N m−2

  9. A Regional-Scale Assessment of Satellite Derived Precipitable Water Vapor Across The Amazon Basin

    Science.gov (United States)

    DeLiberty, Tracy; Callahan, John; Guillory, Anthony R.; Jedlovec, Gary

    2000-01-01

    Atmospheric water vapor is widely recognized as a key climate variable, linking an assortment of poorly understood and complex processes. It is a major element of the hydrological cycle and provides a mechanism for energy exchange among many of the Earth system components. Reducing uncertainty in our current knowledge of water vapor and its role in the climate system requires accurate measurement, improved modeling techniques, and long-term prediction. Satellites have the potential to satisfy these criteria, as well as provide high resolution measurements that are not available from conventional sources. The focus of this paper is to examine the temporal and mesoscale variations of satellite derived precipitable water vapor (PW) across the Amazon Basin. This region is pivotal in the functioning of the global climate system through its abundant release of latent heat associated with heavy precipitation events. In addition, anthropogenic deforestation and biomass burning activities in recent decades are altering the conditions of the atmosphere, especially in the planetary boundary layer. A physical split-window (PSW) algorithm estimates PW using images from the GOES satellites along with the NCEP/NCAR Reanalysis data that provides the first guess information. Retrievals are made at a three-hourly time step during daylight hours in the Amazon Basin and surrounding areas for the months of June and October in 1988 (dry year) and 1995 (wet year). Spatially continuous fields are generated 5 times daily at 12Z, 15Z, 18Z, 21Z, and 00Z. These fields are then averaged to create monthly and 3 hourly monthly grids. Overall, the PSW estimates PW reasonable well in the Amazon with MAE ranging from 3.0 - 9.0 mm and MAE/observed mean around 20% in comparison to radiosonde observations. The distribution of PW generally mimics that of precipitation. Maximum values (42 - 52 mm) are located in the Northwest whereas minimum values (18 - 27 mm) are found along Brazil's East coast. Aside

  10. Similarity and Error Intercomparison of the GPM and Its Predecessor-TRMM Multisatellite Precipitation Analysis Using the Best Available Hourly Gauge Network over the Tibetan Plateau

    Directory of Open Access Journals (Sweden)

    Yingzhao Ma

    2016-07-01

    Full Text Available The performance of Day-1 Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM mission (IMERG and its predecessor, the Tropical Rainfall Measuring Mission (TRMM Multisatellite Precipitation Analysis 3B42 Version 7 (3B42V7, was cross-evaluated using data from the best-available hourly gauge network over the Tibetan Plateau (TP. Analyses of three-hourly rainfall estimates in the warm season of 2014 reveal that IMERG shows appreciably better correlations and lower errors than 3B42V7, though with very similar spatial patterns for all assessment indicators. IMERG also appears to detect light rainfall better than 3B42V7. However, IMERG shows slightly lower POD than 3B42V7 for elevations above 4200 m. Both IMERG and 3B42V7 successfully capture the northward dynamic life cycle of the Indian monsoon reasonably well over the TP. In particular, the relatively light rain from early and end Indian monsoon moisture surge events often fails to be captured by the sparsely-distributed gauges. In spite of limited snowfall field observations, IMERG shows the potential of detecting solid precipitation, which cannot be retrieved from the 3B42V7 products.

  11. Precipitation Data Merging over Mountainous Areas Using Satellite Estimates and Sparse Gauge Observations (PDMMA-USESGO) for Hydrological Modeling — A Case Study over the Tibetan Plateau

    Science.gov (United States)

    Yang, Z.; Hsu, K. L.; Sorooshian, S.; Xu, X.

    2017-12-01

    Precipitation in mountain regions generally occurs with high-frequency-intensity, whereas it is not well-captured by sparsely distributed rain-gauges imposing a great challenge on water management. Satellite-based Precipitation Estimation (SPE) provides global high-resolution alternative data for hydro-climatic studies, but are subject to considerable biases. In this study, a model named PDMMA-USESGO for Precipitation Data Merging over Mountainous Areas Using Satellite Estimates and Sparse Gauge Observations is developed to support precipitation mapping and hydrological modeling in mountainous catchments. The PDMMA-USESGO framework includes two calculating steps—adjusting SPE biases and merging satellite-gauge estimates—using the quantile mapping approach, a two-dimensional Gaussian weighting scheme (considering elevation effect), and an inverse root mean square error weighting method. The model is applied and evaluated over the Tibetan Plateau (TP) with the PERSIANN-CCS precipitation retrievals (daily, 0.04°×0.04°) and sparse observations from 89 gauges, for the 11-yr period of 2003-2013. To assess the data merging effects on streamflow modeling, a hydrological evaluation is conducted over a watershed in southeast TP based on the Soil and Water Assessment Tool (SWAT). Evaluation results indicate effectiveness of the model in generating high-resolution-accuracy precipitation estimates over mountainous terrain, with the merged estimates (Mer-SG) presenting consistently improved correlation coefficients, root mean square errors and absolute mean biases from original satellite estimates (Ori-CCS). It is found the Mer-SG forced streamflow simulations exhibit great improvements from those simulations using Ori-CCS, with coefficient of determination (R2) and Nash-Sutcliffe efficiency reach to 0.8 and 0.65, respectively. The presented model and case study serve as valuable references for the hydro-climatic applications using remote sensing-gauge information in

  12. Assessment of Evolving TRMM-Based Real-Time Precipitation Estimation Methods and Their Impacts on Hydrologic Prediction in a High-Latitude Basin

    Science.gov (United States)

    Yong, Bin; Hong, Yang; Ren, Li-Liang; Gourley, Jonathan; Huffman, George J.; Chen, Xi; Wang, Wen; Khan, Sadiq I.

    2013-01-01

    The real-time availability of satellite-derived precipitation estimates provides hydrologists an opportunity to improve current hydrologic prediction capability for medium to large river basins. Due to the availability of new satellite data and upgrades to the precipitation algorithms, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis real-time estimates (TMPA-RT) have been undergoing several important revisions over the past ten years. In this study, the changes of the relative accuracy and hydrologic potential of TMPA-RT estimates over its three major evolving periods were evaluated and inter-compared at daily, monthly and seasonal scales in the high-latitude Laohahe basin in China. Assessment results show that the performance of TMPA-RT in terms of precipitation estimation and streamflow simulation was significantly improved after 3 February 2005. Overestimation during winter months was noteworthy and consistent, which is suggested to be a consequence from interference of snow cover to the passive microwave retrievals. Rainfall estimated by the new version 6 of TMPA-RT starting from 1 October 2008 to present has higher correlations with independent gauge observations and tends to perform better in detecting rain compared to the prior periods, although it suffers larger mean error and relative bias. After a simple bias correction, this latest dataset of TMPA-RT exhibited the best capability in capturing hydrologic response among the three tested periods. In summary, this study demonstrated that there is an increasing potential in the use of TMPA-RT in hydrologic streamflow simulations over its three algorithm upgrade periods, but still with significant challenges during the winter snowing events.

  13. A multi-state weather generator for daily precipitation for the Torne River basin, northern Sweden/western Finland

    Directory of Open Access Journals (Sweden)

    David Rayner

    2016-03-01

    Results showed that the 10-state empirical model represented accumulated 2- to 14-day precipitation most realistically. Further, the distribution of precipitation on wet days in the catchment is related to the placement of a wet day within a wet-spell, and the 10-state models represented this realistically, while the wet/dry models did not. Although all four models accurately reproduced the annual and monthly averages in the training data, all models underestimated inter-annual and inter-seasonal variance. Even so, the 10-state empirical model performed best. We conclude that the multi-state model is a promising candidate for hydrological applications, as it simulates multi-day precipitation well, but that further development is required to improve the simulation of interannual variation.

  14. Multi-instrument observations of midlatitude summer nighttime anomaly from satellite and ground

    Science.gov (United States)

    Yamamoto, Mamoru; Thampi, Smitha V.; Liu, Huixin; Lin, Charles

    "Midlatitude Summer Nighttime Anomaly (MSNA)" is a phenomenon that the nighttime elec-tron densities exceed the daytime values on almost all days in summer over latitudes of 33-34N of more. We recently found the MSNA over the northeast Asian region from multi-instrument observations. The observations include the tomography analysis based on the chain of digital beacon receivers at Shionomisaki (33.45N, 135.8E), Shigaraki (34.85N, 136.1E), and Fukui (36.06N,136E), the ionosonde network over Japan (especially data from Wakkanai (45.4N, 141.7E)), ground-based GPS TEC observations using the GEONET. Also from satellites, CHAMP in situ electron density measurements, and Formosat3/COSMIC (F3/C) occultation measurements are useful to confirm the presence of MSNA over this region. In the presen-tation we show detailed features of the MSNA based on these multi-instrument, and discuss importance of the neutral atmosphere as a driver of the phenomenon.

  15. A multi-source satellite data approach for modelling Lake Turkana water level: calibration and validation using satellite altimetry data

    Directory of Open Access Journals (Sweden)

    N. M. Velpuri

    2012-01-01

    Full Text Available Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of inter- and intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellite-driven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE of 0.80 during the validation period (2004–2009. Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1–2 m. The lake level fluctuated in the range up to 4 m between the years 1998–2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated

  16. Contrasting the co-variability of daytime cloud and precipitation over tropical land and ocean

    Science.gov (United States)

    Jin, Daeho; Oreopoulos, Lazaros; Lee, Dongmin; Cho, Nayeong; Tan, Jackson

    2018-03-01

    The co-variability of cloud and precipitation in the extended tropics (35° N-35° S) is investigated using contemporaneous data sets for a 13-year period. The goal is to quantify potential relationships between cloud type fractions and precipitation events of particular strength. Particular attention is paid to whether the relationships exhibit different characteristics over tropical land and ocean. A primary analysis metric is the correlation coefficient between fractions of individual cloud types and frequencies within precipitation histogram bins that have been matched in time and space. The cloud type fractions are derived from Moderate Resolution Imaging Spectroradiometer (MODIS) joint histograms of cloud top pressure and cloud optical thickness in 1° grid cells, and the precipitation frequencies come from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) data set aggregated to the same grid.It is found that the strongest coupling (positive correlation) between clouds and precipitation occurs over ocean for cumulonimbus clouds and the heaviest rainfall. While the same cloud type and rainfall bin are also best correlated over land compared to other combinations, the correlation magnitude is weaker than over ocean. The difference is attributed to the greater size of convective systems over ocean. It is also found that both over ocean and land the anti-correlation of strong precipitation with weak (i.e., thin and/or low) cloud types is of greater absolute strength than positive correlations between weak cloud types and weak precipitation. Cloud type co-occurrence relationships explain some of the cloud-precipitation anti-correlations. Weak correlations between weaker rainfall and clouds indicate poor predictability for precipitation when cloud types are known, and this is even more true over land than over ocean.

  17. Depth-area-duration characteristics of storm rainfall in Texas using Multi-Sensor Precipitation Estimates

    Science.gov (United States)

    McEnery, J. A.; Jitkajornwanich, K.

    2012-12-01

    This presentation will describe the methodology and overall system development by which a benchmark dataset of precipitation information has been used to characterize the depth-area-duration relations in heavy rain storms occurring over regions of Texas. Over the past two years project investigators along with the National Weather Service (NWS) West Gulf River Forecast Center (WGRFC) have developed and operated a gateway data system to ingest, store, and disseminate NWS multi-sensor precipitation estimates (MPE). As a pilot project of the Integrated Water Resources Science and Services (IWRSS) initiative, this testbed uses a Standard Query Language (SQL) server to maintain a full archive of current and historic MPE values within the WGRFC service area. These time series values are made available for public access as web services in the standard WaterML format. Having this volume of information maintained in a comprehensive database now allows the use of relational analysis capabilities within SQL to leverage these multi-sensor precipitation values and produce a valuable derivative product. The area of focus for this study is North Texas and will utilize values that originated from the West Gulf River Forecast Center (WGRFC); one of three River Forecast Centers currently represented in the holdings of this data system. Over the past two decades, NEXRAD radar has dramatically improved the ability to record rainfall. The resulting hourly MPE values, distributed over an approximate 4 km by 4 km grid, are considered by the NWS to be the "best estimate" of rainfall. The data server provides an accepted standard interface for internet access to the largest time-series dataset of NEXRAD based MPE values ever assembled. An automated script has been written to search and extract storms over the 18 year period of record from the contents of this massive historical precipitation database. Not only can it extract site-specific storms, but also duration-specific storms and

  18. Accuracy analysis of indirect georeferencing about TH-1 satellite in Weinan test area

    International Nuclear Information System (INIS)

    Yunlan, Yang; Haiyan, Hu

    2014-01-01

    Optical linear scanning sensors can be divided into single-lens sensors and multi-lens sensors according to the number of lenses. In order to build stereo imaging, for single-lens optical systems such as aerial mapping camera ADS40 and ADS80, there are more than two parallel linear arrays placed on the focal plane. And for a multi-lens optical system there is only one linear CCD arrays placed on the center of every focal plan for each lens which is often carried on spacecraft. The difference of design between these two kinds of optical systems leads to the systematic errors, calibration in orbit and approach of data adjustment are different completely. Recent years the domestic space optical sensor systems are focused on multi-lens linear CCD sensor in China, such as TH-1 and ZY-3 both belong to multi-lens optical systems. The parameters influencing the position accuracy of the satellite system which are unknown or unknown precisely even changed after sensor posted launch can be estimated by self-calibration in orbit. So after self-calibration in orbit the accuracy of mapping satellite will often be improved strongly. Comparing to direct georeferencing, the indirect georeferencing as a research approach is introduced to TH-1 satellite in this paper considering the systematic errors completely. Parameters about geometry position systematic error are introduced to the basic co-linearity equations for multi-lenses linear array CCD sensor, and based on the extended model the method of space multi-lens linear array CCD sensor self-calibration bundle adjustment is presented. The test field is in some area of Weinan, Shaanxi province, and the observation data of GCPs and orbit are collected. The extended rigors model is used in bundle adjustment and the accuracy analysis shown that TH-1 has a satisfied metric performance

  19. Decadal Seasonal Shifts of Precipitation and Temperature in TRMM and AIRS Data

    Science.gov (United States)

    Savtchenko, Andrey; Huffman, George; Meyer, David; Vollmer, Bruce

    2018-01-01

    We present results from an analysis of seasonal phase shifts in the global precipitation and surface temperatures. We use data from the TRMM (Tropical Rainfall Measuring Mission) Multi-satellite Precipitation Algorithm (TMPA), and the Atmospheric Infrared Sounder (AIRS) on Aqua satellite, all hosted at NASA Goddard Earth Science Data and Information Services Center (GES DISC). We explore the information content and data usability by first aggregating daily grids from the entire records of both missions to pentad (5-day) series which are then processed using Singular Value Decomposition approach. A strength of this approach is the normalized principal components that can then be easily converted from real to complex time series. Thus, we can separate the most informative, the seasonal, components and analyze unambiguously for potential seasonal phase drifts. TMPA and AIRS records represent correspondingly 20 and 15 years of data, which allows us to run simple “phase learning†from the first 5 years of records and use it as reference. The most recent 5 years are then phase-compared with the reference. We demonstrate that the seasonal phase of global precipitation and surface temperatures has been stable in the past two decades. However, a small global trend of delayed precipitation, and earlier arrival of surface temperatures seasons, are detectable at 95% confidence level. Larger phase shifts are detectable at regional level, in regions recognizable from the Eigen vectors to having strong seasonal patterns. For instance, in Central North America, including the North American Monsoon region, confident phase shifts of 1-2 days per decade are detected at 95% confidence level. While seemingly symbolic, these shifts are indicative of larger changes in the Earth Climate System. We thus also demonstrate a potential usability scenario of Earth Science Data Records curated at the NASA GES DISC in partnership with Earth Science Missions.

  20. How well do the GCMs/RCMs capture the multi-scale temporal variability of precipitation in the Southwestern United States?

    Science.gov (United States)

    Jiang, Peng; Gautam, Mahesh R.; Zhu, Jianting; Yu, Zhongbo

    2013-02-01

    SummaryMulti-scale temporal variability of precipitation has an established relationship with floods and droughts. In this paper, we present the diagnostics on the ability of 16 General Circulation Models (GCMs) from Bias Corrected and Downscaled (BCSD) World Climate Research Program's (WCRP's) Coupled Model Inter-comparison Project Phase 3 (CMIP3) projections and 10 Regional Climate Models (RCMs) that participated in the North American Regional Climate Change Assessment Program (NARCCAP) to represent multi-scale temporal variability determined from the observed station data. Four regions (Los Angeles, Las Vegas, Tucson, and Cimarron) in the Southwest United States are selected as they represent four different precipitation regions classified by clustering method. We investigate how storm properties and seasonal, inter-annual, and decadal precipitation variabilities differed between GCMs/RCMs and observed records in these regions. We find that current GCMs/RCMs tend to simulate longer storm duration and lower storm intensity compared to those from observed records. Most GCMs/RCMs fail to produce the high-intensity summer storms caused by local convective heat transport associated with the summer monsoon. Both inter-annual and decadal bands are present in the GCM/RCM-simulated precipitation time series; however, these do not line up to the patterns of large-scale ocean oscillations such as El Nino/La Nina Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Our results show that the studied GCMs/RCMs can capture long-term monthly mean as the examined data is bias-corrected and downscaled, but fail to simulate the multi-scale precipitation variability including flood generating extreme events, which suggests their inadequacy for studies on floods and droughts that are strongly associated with multi-scale temporal precipitation variability.

  1. CHANGE DETECTION OF CROPPING PATTERN IN PADDY FIELD USING MULTI SPECTRAL SATELLITE DATA FOR ESTIMATING IRRIGATION WATER NEEDS

    Directory of Open Access Journals (Sweden)

    Rizatus Shofiyati1

    2012-10-01

    Full Text Available This paper investigates the use of multi spectral satellite data for cropping pattern monitoring in paddy field. The southern coastal of Citarum watershed, West Java Province was selected as study sites. The analysis used in this study is identifying crop pattern based on growth stages of wetland paddy and other crops by investi-gating the characteristic of Normalized Differen-ce Vegetation Indices (NDVI and Wetness of Tasseled Cap Transformation (TCT derived from 14 scenes of Landsat TM date 1988 to 2001. In general, the phenological of growth stages of wetland paddy can be used to distinguish with other seasonal crops. The research results indicate that multi spectral satellite data has a great potential for identi-fication and monitoring cropping pattern in paddy field. Specific character of NDVI and Wetness can also produce a map of cropping pattern in paddy field that is useful to monitor agricultural land condition. The cropping pattern can also be used to estimate irrigation water needed of paddy field in the area. Expected implication of the information obtained from this analysis is useful for guiding more appropriate planning and better agricultural management.

  2. Evaluation of Satellite Precipitation Products with Rain Gauge Data at Different Scales: Implications for Hydrological Applications

    Directory of Open Access Journals (Sweden)

    Ruifang Guo

    2016-07-01

    Full Text Available Rain gauge and satellite-retrieved data have been widely used in basin-scale hydrological applications. While rain gauges provide accurate measurements that are generally unevenly distributed in space, satellites offer spatially regular observations and common error prone retrieval. Comparative evaluation of gauge-based and satellite-based data is necessary in hydrological studies, as precipitation is the most important input in basin-scale water balance. This study uses quality-controlled rain gauge data and prevailing satellite products (Tropical Rainfall Measuring Mission (TRMM 3B43, 3B42 and 3B42RT to examine the consistency and discrepancies between them at different scales. Rain gauges and TRMM products were available in the Poyang Lake Basin, China, from 1998 to 2007 (3B42RT: 2000–2007. Our results show that the performance of TRMM products generally increases with increasing spatial scale. At both the monthly and annual scales, the accuracy is highest for TRMM 3B43, with 3B42 second and 3B42RT third. TRMM products generally overestimate precipitation because of a high frequency and degree of overestimation in light and moderate rain cases. At the daily scale, the accuracy is relatively low between TRMM 3B42 and 3B42RT. Meanwhile, the performances of TRMM 3B42 and 3B42RT are highly variable in different seasons. At both the basin and pixel scales, TRMM 3B43 and 3B42 exhibit significant discrepancies from July to September, performing worst in September. For TRMM 3B42RT, all statistical indices fluctuate and are low throughout the year, performing worst in July at the pixel scale and January at the basin scale. Furthermore, the spatial distributions of the statistical indices of TRMM 3B43 and 3B42 performed well, while TRMM 3B42RT displayed a poor performance.

  3. A multi-source satellite data approach for modelling Lake Turkana water level: Calibration and validation using satellite altimetry data

    Science.gov (United States)

    Velpuri, N.M.; Senay, G.B.; Asante, K.O.

    2012-01-01

    Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of interand intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellitedriven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE) of 0.80 during the validation period (2004-2009). Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1-2m. The lake level fluctuated in the range up to 4m between the years 1998-2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated satellite-driven water balance

  4. Validation of the H-SAF precipitation product H03 over Greece using rain gauge data

    Science.gov (United States)

    Feidas, H.; Porcu, F.; Puca, S.; Rinollo, A.; Lagouvardos, C.; Kotroni, V.

    2018-01-01

    This paper presents an extensive validation of the combined infrared/microwave H-SAF (EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management) precipitation product H03, for a 1-year period, using gauge observations from a relatively dense network of 233 stations over Greece. First, the quality of the interpolated data used to validate the precipitation product is assessed and a quality index is constructed based on parameters such as the density of the station network and the orography. Then, a validation analysis is conducted based on comparisons of satellite (H03) with interpolated rain gauge data to produce continuous and multi-categorical statistics at monthly and annual timescales by taking into account the different geophysical characteristics of the terrain (land, coast, sea, elevation). Finally, the impact of the quality of interpolated data on the validation statistics is examined in terms of different configurations of the interpolation model and the rain gauge network characteristics used in the interpolation. The possibility of using a quality index of the interpolated data as a filter in the validation procedure is also investigated. The continuous validation statistics show yearly root mean squared error (RMSE) and mean absolute error (MAE) corresponding to the 225 and 105 % of the mean rain rate, respectively. Mean error (ME) indicates a slight overall tendency for underestimation of the rain gauge rates, which takes large values for the high rain rates. In general, the H03 algorithm cannot retrieve very well the light (10 mm/h) precipitation. The poor correlation between satellite and gauge data points to algorithm problems in co-locating precipitation patterns. Seasonal comparison shows that retrieval errors are lower for cold months than in the summer months of the year. The multi-categorical statistics indicate that the H03 algorithm is able to discriminate efficiently the rain from the no rain events

  5. The Precipitation Products Generation Chain for the EUMETSAT Hydrological Satellite Application Facility at C.N.M.C.A.

    Science.gov (United States)

    Zauli, Francesco; Biron, Daniele; Melfi, Davide

    2009-11-01

    The EUMETSA T Satellite Application Facility in support to Hydrology (H-SAF) focuses on the development of new geophysical products on precipitation, soil moisture and snow parameters and the utilisation of these parameters in hydrological models, NWP models and water management. The development phase of the H-SAF started in September 2005 under the leadership of Italian Meteorological Service.The Centro Nazionale di Meteorologia e Climatologia Aeronautica (C.N.M.C.A.), the Italian National Weather Centre, that physically hosts the generation chain of precipitation products, developed activities to reach the final target: development of algorithms, validation of results, implementation of operative procedure to supply the service and to monitor the service performances.The paper shows the recent architectural review of H- SAF precipitation group, stressing components of operation for high sustainability, full redundancy, absolute continuity of service.

  6. Long-Term Quantitative Precipitation Estimates (QPE) at High Spatial and Temporal Resolution over CONUS: Bias-Adjustment of the Radar-Only National Mosaic and Multi-sensor QPE (NMQ/Q2) Precipitation Reanalysis (2001-2012)

    Science.gov (United States)

    Prat, Olivier; Nelson, Brian; Stevens, Scott; Seo, Dong-Jun; Kim, Beomgeun

    2015-04-01

    The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (NEXRAD) network over Continental United States (CONUS) is completed for the period covering from 2001 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Several in-situ datasets are available to assess the biases of the radar-only product and to adjust for those biases to provide a multi-sensor QPE. The rain gauge networks that are used such as the Global Historical Climatology Network-Daily (GHCN-D), the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), and the Climate Reference Network (CRN), have different spatial density and temporal resolution. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. The objective of this work is threefold. First, we investigate how the different in-situ networks can impact the precipitation estimates as a function of the spatial density, sensor type, and temporal resolution. Second, we assess conditional and un-conditional biases of the radar-only QPE for various time scales (daily, hourly, 5-min) using in-situ precipitation observations. Finally, after assessing the bias and applying reduction or elimination techniques, we are using a unique in-situ dataset merging the different RG networks (CRN, ASOS, HADS, GHCN-D) to

  7. Precipitation from Space: Advancing Earth System Science

    Science.gov (United States)

    Kucera, Paul A.; Ebert, Elizabeth E.; Turk, F. Joseph; Levizzani, Vicenzo; Kirschbaum, Dalia; Tapiador, Francisco J.; Loew, Alexander; Borsche, M.

    2012-01-01

    Of the three primary sources of spatially contiguous precipitation observations (surface networks, ground-based radar, and satellite-based radar/radiometers), only the last is a viable source over ocean and much of the Earth's land. As recently as 15 years ago, users needing quantitative detail of precipitation on anything under a monthly time scale relied upon products derived from geostationary satellite thermal infrared (IR) indices. The Special Sensor Microwave Imager (SSMI) passive microwave (PMW) imagers originated in 1987 and continue today with the SSMI sounder (SSMIS) sensor. The fortunate longevity of the joint National Aeronautics and Space Administration (NASA) and Japan Aerospace Exploration Agency (JAXA) Tropical Rainfall Measuring Mission (TRMM) is providing the environmental science community a nearly unbroken data record (as of April 2012, over 14 years) of tropical and sub-tropical precipitation processes. TRMM was originally conceived in the mid-1980s as a climate mission with relatively modest goals, including monthly averaged precipitation. TRMM data were quickly exploited for model data assimilation and, beginning in 1999 with the availability of near real time data, for tropical cyclone warnings. To overcome the intermittently spaced revisit from these and other low Earth-orbiting satellites, many methods to merge PMW-based precipitation data and geostationary satellite observations have been developed, such as the TRMM Multisatellite Precipitation Product and the Climate Prediction Center (CPC) morphing method (CMORPH. The purpose of this article is not to provide a survey or assessment of these and other satellite-based precipitation datasets, which are well summarized in several recent articles. Rather, the intent is to demonstrate how the availability and continuity of satellite-based precipitation data records is transforming the ways that scientific and societal issues related to precipitation are addressed, in ways that would not be

  8. Radar adjusted data versus modelled precipitation: a case study over Cyprus

    Directory of Open Access Journals (Sweden)

    M. Casaioli

    2006-01-01

    Full Text Available In the framework of the European VOLTAIRE project (Fifth Framework Programme, simulations of relatively heavy precipitation events, which occurred over the island of Cyprus, by means of numerical atmospheric models were performed. One of the aims of the project was indeed the comparison of modelled rainfall fields with multi-sensor observations. Thus, for the 5 March 2003 event, the 24-h accumulated precipitation BOlogna Limited Area Model (BOLAM forecast was compared with the available observations reconstructed from ground-based radar data and estimated by rain gauge data. Since radar data may be affected by errors depending on the distance from the radar, these data could be range-adjusted by using other sensors. In this case, the Precipitation Radar aboard the Tropical Rainfall Measuring Mission (TRMM satellite was used to adjust the ground-based radar data with a two-parameter scheme. Thus, in this work, two observational fields were employed: the rain gauge gridded analysis and the observational analysis obtained by merging the range-adjusted radar and rain gauge fields. In order to verify the modelled precipitation, both non-parametric skill scores and the contiguous rain area (CRA analysis were applied. Skill score results show some differences when using the two observational fields. CRA results are instead quite in agreement, showing that in general a 0.27° eastward shift optimizes the forecast with respect to the two observational analyses. This result is also supported by a subjective inspection of the shifted forecast field, whose gross features agree with the analysis pattern more than the non-shifted forecast one. However, some open questions, especially regarding the effect of other range adjustment techniques, remain open and need to be addressed in future works.

  9. The Impacts of Satellite Remotely Sensed Winds and Total Precipitable Vapour in WRF Tropical Cyclone Track Forecasts

    Directory of Open Access Journals (Sweden)

    Diandong Ren

    2016-01-01

    Full Text Available This study assesses the impact assimilating the scatterometer near-surface wind observations and total precipitable water from the SSMI, into WRF on genesis and track forecasting of four tropical cyclones (TCs. These TCs are selected to be representative of different intensity categories and basins. Impact is via a series of data denial experiments that systematically exclude the remote sensed information. Compared with the control case, in which only the final analysis atmospheric variables are used to initialize and provide the lateral boundary conditions, the data assimilation runs performed consistently better, but with very different skill levels for the different TCs. Eliassen-Palm flux analyses are employed. It is confirmed that if a polar orbital satellite footprint passes over the TC’s critical genesis region, the forecast will profit most from assimilating the remotely sensed information. If the critical genesis region lies within an interorbital gap then, regardless of how strong the TC later becomes (e.g., Katrina 2005, the improvement from assimilating near-surface winds and total precipitable water in the model prediction is severely limited. This underpins the need for a synergy of data from different scatterometers/radiometers. Other approaches are suggested to improve the accuracy in the prediction of TC genesis and tracks.

  10. Estimating Tropical Cyclone Precipitation from Station Observations

    Institute of Scientific and Technical Information of China (English)

    REN Fumin; WANG Yongmei; WANG Xiaoling; LI Weijing

    2007-01-01

    In this paper, an objective technique for estimating the tropical cyclone (TC) precipitation from station observations is proposed. Based on a comparison between the Original Objective Method (OOM) and the Expert Subjective Method (ESM), the Objective Synoptic Analysis Technique (OSAT) for partitioning TC precipitation was developed by analyzing the western North Pacific (WNP) TC historical track and the daily precipitation datasets. Being an objective way of the ESM, OSAT overcomes the main problems in OOM,by changing two fixed parameters in OOM, the thresholds for the distance of the absolute TC precipitation (D0) and the TC size (D1), into variable parameters.Case verification for OSAT was also carried out by applying CMORPH (Climate Prediction Center MORPHing technique) daily precipitation measurements, which is NOAA's combined satellite precipitation measurement system. This indicates that OSAT is capable of distinguishing simultaneous TC precipitation rain-belts from those associated with different TCs or with middle-latitude weather systems.

  11. Research on Scheduling Algorithm for Multi-satellite and Point Target Task on Swinging Mode

    Science.gov (United States)

    Wang, M.; Dai, G.; Peng, L.; Song, Z.; Chen, G.

    2012-12-01

    Nowadays, using satellite in space to observe ground is an important and major method to obtain ground information. With the development of the scientific technology in the field of space, many fields such as military and economic and other areas have more and more requirement of space technology because of the benefits of the satellite's widespread, timeliness and unlimited of area and country. And at the same time, because of the wide use of all kinds of satellites, sensors, repeater satellites and ground receiving stations, ground control system are now facing great challenge. Therefore, how to make the best value of satellite resources so as to make full use of them becomes an important problem of ground control system. Satellite scheduling is to distribute the resource to all tasks without conflict to obtain the scheduling result so as to complete as many tasks as possible to meet user's requirement under considering the condition of the requirement of satellites, sensors and ground receiving stations. Considering the size of the task, we can divide tasks into point task and area task. This paper only considers point targets. In this paper, a description of satellite scheduling problem and a chief introduction of the theory of satellite scheduling are firstly made. We also analyze the restriction of resource and task in scheduling satellites. The input and output flow of scheduling process are also chiefly described in the paper. On the basis of these analyses, we put forward a scheduling model named as multi-variable optimization model for multi-satellite and point target task on swinging mode. In the multi-variable optimization model, the scheduling problem is transformed the parametric optimization problem. The parameter we wish to optimize is the swinging angle of every time-window. In the view of the efficiency and accuracy, some important problems relating the satellite scheduling such as the angle relation between satellites and ground targets, positive

  12. Multi-Stage Hybrid Rocket Conceptual Design for Micro-Satellites Launch using Genetic Algorithm

    Science.gov (United States)

    Kitagawa, Yosuke; Kitagawa, Koki; Nakamiya, Masaki; Kanazaki, Masahiro; Shimada, Toru

    The multi-objective genetic algorithm (MOGA) is applied to the multi-disciplinary conceptual design problem for a three-stage launch vehicle (LV) with a hybrid rocket engine (HRE). MOGA is an optimization tool used for multi-objective problems. The parallel coordinate plot (PCP), which is a data mining method, is employed in the post-process in MOGA for design knowledge discovery. A rocket that can deliver observing micro-satellites to the sun-synchronous orbit (SSO) is designed. It consists of an oxidizer tank containing liquid oxidizer, a combustion chamber containing solid fuel, a pressurizing tank and a nozzle. The objective functions considered in this study are to minimize the total mass of the rocket and to maximize the ratio of the payload mass to the total mass. To calculate the thrust and the engine size, the regression rate is estimated based on an empirical model for a paraffin (FT-0070) propellant. Several non-dominated solutions are obtained using MOGA, and design knowledge is discovered for the present hybrid rocket design problem using a PCP analysis. As a result, substantial knowledge on the design of an LV with an HRE is obtained for use in space transportation.

  13. Image Fusion-Based Land Cover Change Detection Using Multi-Temporal High-Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Biao Wang

    2017-08-01

    Full Text Available Change detection is usually treated as a problem of explicitly detecting land cover transitions in satellite images obtained at different times, and helps with emergency response and government management. This study presents an unsupervised change detection method based on the image fusion of multi-temporal images. The main objective of this study is to improve the accuracy of unsupervised change detection from high-resolution multi-temporal images. Our method effectively reduces change detection errors, since spatial displacement and spectral differences between multi-temporal images are evaluated. To this end, a total of four cross-fused images are generated with multi-temporal images, and the iteratively reweighted multivariate alteration detection (IR-MAD method—a measure for the spectral distortion of change information—is applied to the fused images. In this experiment, the land cover change maps were extracted using multi-temporal IKONOS-2, WorldView-3, and GF-1 satellite images. The effectiveness of the proposed method compared with other unsupervised change detection methods is demonstrated through experimentation. The proposed method achieved an overall accuracy of 80.51% and 97.87% for cases 1 and 2, respectively. Moreover, the proposed method performed better when differentiating the water area from the vegetation area compared to the existing change detection methods. Although the water area beneath moderate and sparse vegetation canopy was captured, vegetation cover and paved regions of the water body were the main sources of omission error, and commission errors occurred primarily in pixels of mixed land use and along the water body edge. Nevertheless, the proposed method, in conjunction with high-resolution satellite imagery, offers a robust and flexible approach to land cover change mapping that requires no ancillary data for rapid implementation.

  14. The assessment of Global Precipitation Measurement estimates over the Indian subcontinent

    Science.gov (United States)

    Murali Krishna, U. V.; Das, Subrata Kumar; Deshpande, Sachin M.; Doiphode, S. L.; Pandithurai, G.

    2017-08-01

    Accurate and real-time precipitation estimation is a challenging task for current and future spaceborne measurements, which is essential to understand the global hydrological cycle. Recently, the Global Precipitation Measurement (GPM) satellites were launched as a next-generation rainfall mission for observing the global precipitation characteristics. The purpose of the GPM is to enhance the spatiotemporal resolution of global precipitation. The main objective of the present study is to assess the rainfall products from the GPM, especially the Integrated Multi-satellitE Retrievals for the GPM (IMERG) data by comparing with the ground-based observations. The multitemporal scale evaluations of rainfall involving subdaily, diurnal, monthly, and seasonal scales were performed over the Indian subcontinent. The comparison shows that the IMERG performed better than the Tropical Rainfall Measuring Mission (TRMM)-3B42, although both rainfall products underestimated the observed rainfall compared to the ground-based measurements. The analyses also reveal that the TRMM-3B42 and IMERG data sets are able to represent the large-scale monsoon rainfall spatial features but are having region-specific biases. The IMERG shows significant improvement in low rainfall estimates compared to the TRMM-3B42 for selected regions. In the spatial distribution, the IMERG shows higher rain rates compared to the TRMM-3B42, due to its enhanced spatial and temporal resolutions. Apart from this, the characteristics of raindrop size distribution (DSD) obtained from the GPM mission dual-frequency precipitation radar is assessed over the complex mountain terrain site in the Western Ghats, India, using the DSD measured by a Joss-Waldvogel disdrometer.

  15. The concurrent multiplicative-additive approach for gauge-radar/satellite multisensor precipitation estimates

    Science.gov (United States)

    Garcia-Pintado, J.; Barberá, G. G.; Erena Arrabal, M.; Castillo, V. M.

    2010-12-01

    Objective analysis schemes (OAS), also called ``succesive correction methods'' or ``observation nudging'', have been proposed for multisensor precipitation estimation combining remote sensing data (meteorological radar or satellite) with data from ground-based raingauge networks. However, opposite to the more complex geostatistical approaches, the OAS techniques for this use are not optimized. On the other hand, geostatistical techniques ideally require, at the least, modelling the covariance from the rain gauge data at every time step evaluated, which commonly cannot be soundly done. Here, we propose a new procedure (concurrent multiplicative-additive objective analysis scheme [CMA-OAS]) for operational rainfall estimation using rain gauges and meteorological radar, which does not require explicit modelling of spatial covariances. On the basis of a concurrent multiplicative-additive (CMA) decomposition of the spatially nonuniform radar bias, within-storm variability of rainfall and fractional coverage of rainfall are taken into account. Thus both spatially nonuniform radar bias, given that rainfall is detected, and bias in radar detection of rainfall are handled. The interpolation procedure of CMA-OAS is built on the OAS, whose purpose is to estimate a filtered spatial field of the variable of interest through a successive correction of residuals resulting from a Gaussian kernel smoother applied on spatial samples. The CMA-OAS, first, poses an optimization problem at each gauge-radar support point to obtain both a local multiplicative-additive radar bias decomposition and a regionalization parameter. Second, local biases and regionalization parameters are integrated into an OAS to estimate the multisensor rainfall at the ground level. The approach considers radar estimates as background a priori information (first guess), so that nudging to observations (gauges) may be relaxed smoothly to the first guess, and the relaxation shape is obtained from the sequential

  16. Application of Observed Precipitation in NCEP Global and Regional Data Assimilation Systems, Including Reanalysis and Land Data Assimilation

    Science.gov (United States)

    Mitchell, K. E.

    2006-12-01

    The Environmental Modeling Center (EMC) of the National Centers for Environmental Prediction (NCEP) applies several different analyses of observed precipitation in both the data assimilation and validation components of NCEP's global and regional numerical weather and climate prediction/analysis systems (including in NCEP global and regional reanalysis). This invited talk will survey these data assimilation and validation applications and methodologies, as well as the temporal frequency, spatial domains, spatial resolution, data sources, data density and data quality control in the precipitation analyses that are applied. Some of the precipitation analyses applied by EMC are produced by NCEP's Climate Prediction Center (CPC), while others are produced by the River Forecast Centers (RFCs) of the National Weather Service (NWS), or by automated algorithms of the NWS WSR-88D Radar Product Generator (RPG). Depending on the specific type of application in data assimilation or model forecast validation, the temporal resolution of the precipitation analyses may be hourly, daily, or pentad (5-day) and the domain may be global, continental U.S. (CONUS), or Mexico. The data sources for precipitation include ground-based gauge observations, radar-based estimates, and satellite-based estimates. The precipitation analyses over the CONUS are analyses of either hourly, daily or monthly totals of precipitation, and they are of two distinct types: gauge-only or primarily radar-estimated. The gauge-only CONUS analysis of daily precipitation utilizes an orographic-adjustment technique (based on the well-known PRISM precipitation climatology of Oregon State University) developed by the NWS Office of Hydrologic Development (OHD). The primary NCEP global precipitation analysis is the pentad CPC Merged Analysis of Precipitation (CMAP), which blends both gauge observations and satellite estimates. The presentation will include a brief comparison between the CMAP analysis and other global

  17. Optimization of Joint Power and Bandwidth Allocation in Multi-Spot-Beam Satellite Communication Systems

    Directory of Open Access Journals (Sweden)

    Heng Wang

    2014-01-01

    Full Text Available Multi-spot-beam technique has been widely applied in modern satellite communication systems. However, the satellite power and bandwidth resources in a multi-spot-beam satellite communication system are scarce and expensive; it is urgent to utilize the resources efficiently. To this end, dynamically allocating the power and bandwidth is an available way. This paper initially formulates the problem of resource joint allocation as a convex optimization problem, taking into account a compromise between the maximum total system capacity and the fairness among the spot beams. A joint bandwidth and power allocation iterative algorithm based on duality theory is then proposed to obtain the optimal solution of this optimization problem. Compared with the existing separate bandwidth or power optimal allocation algorithms, it is shown that the joint allocation algorithm improves both the total system capacity and the fairness among spot beams. Moreover, it is easy to be implemented in practice, as the computational complexity of the proposed algorithm is linear with the number of spot beams.

  18. Satellite image analysis and a hybrid ESSS/ANN model to forecast solar irradiance in the tropics

    International Nuclear Information System (INIS)

    Dong, Zibo; Yang, Dazhi; Reindl, Thomas; Walsh, Wilfred M.

    2014-01-01

    Highlights: • Satellite image analysis is performed and cloud cover index is classified using self-organizing maps (SOM). • The ESSS model is used to forecast cloud cover index. • Solar irradiance is estimated using multi-layer perceptron (MLP). • The proposed model shows better accuracy than other investigated models. - Abstract: We forecast hourly solar irradiance time series using satellite image analysis and a hybrid exponential smoothing state space (ESSS) model together with artificial neural networks (ANN). Since cloud cover is the major factor affecting solar irradiance, cloud detection and classification are crucial to forecast solar irradiance. Geostationary satellite images provide cloud information, allowing a cloud cover index to be derived and analysed using self-organizing maps (SOM). Owing to the stochastic nature of cloud generation in tropical regions, the ESSS model is used to forecast cloud cover index. Among different models applied in ANN, we favour the multi-layer perceptron (MLP) to derive solar irradiance based on the cloud cover index. This hybrid model has been used to forecast hourly solar irradiance in Singapore and the technique is found to outperform traditional forecasting models

  19. Harmonic analysis of the precipitation in Greece

    Science.gov (United States)

    Nastos, P. T.; Zerefos, C. S.

    2009-04-01

    Greece is a country with a big variety of climates due to its geographical position, to the many mountain ranges and also to the multifarious and long coastline. The mountainous volumes are of such orientation that influences the distribution of the precipitation, having as a result, Western Greece to present great differentiations from Central and Eastern Greece. The application of harmonic analysis to the annual variability of precipitation is the goal of this study, so that the components, which compose the annual variability, be elicited. For this purpose, the mean monthly precipitation data from 30 meteorological stations of National Meteorological Service were used for the time period 1950-2000. The initial target is to reduce the number of variables and to detect structure in the relationships between variables. The most commonly used technique for this purpose is the application of Factor Analysis to a table having as columns the meteorological stations-variables and rows the monthly mean precipitation, so that 2 main factors were calculated, which explain the 98% of total variability of precipitation in Greece. Factor 1, representing the so-called uniform field and interpreting the most of the total variance, refers in fact to the Mediterranean depressions, affecting mainly the West of Greece and also the East Aegean and the Asia Minor coasts. In the process, the Fourier Analysis was applied to the factor scores extracted from the Factor Analysis, so that 2 harmonic components are resulted, which explain above the 98% of the total variability of each main factor, and are due to different synoptic and thermodynamic processes associated with Greece's precipitation construction. Finally, the calculation of the time of occurrence of the maximum precipitation, for each harmonic component of each one of the two main factors, gives the spatial distribution of appearance of the maximum precipitation in the Hellenic region.

  20. Successes with the Global Precipitation Measurement (GPM) Mission

    Science.gov (United States)

    Skofronick-Jackson, Gail; Huffman, George; Stocker, Erich; Petersen, Walter

    2016-01-01

    Water is essential to our planet Earth. Knowing when, where and how precipitation falls is crucial for understanding the linkages between the Earth's water and energy cycles and is extraordinarily important for sustaining life on our planet during climate change. The Global Precipitation Measurement (GPM) Core Observatory spacecraft launched February 27, 2014, is the anchor to the GPM international satellite mission to unify and advance precipitation measurements from a constellation of research and operational sensors to provide "next-generation" precipitation products. GPM is currently a partnership between NASA and the Japan Aerospace Exploration Agency (JAXA). Status and successes in terms of spacecraft, instruments, retrieval products, validation, and impacts for science and society will be presented. Precipitation, microwave, satellite

  1. Effects of assimilating precipitation zones derived from satellite and lightning data on numerical simulations of tropical-like Mediterranean storms

    Science.gov (United States)

    Fita, L.; Romero, R.; Luque, A.; Ramis, C.

    2009-08-01

    The scarcity of meteorological observations in maritime areas is a well-known problem that can be an important limitation in the study of different phenomena. Tropical-like storms or medicanes developed over the Mediterranean sea are intense storms with some similarities to the tropical ones. Although they do not reach the hurricane intensity, their potential for damage is very high, due to the densely populated Mediterranean coastal regions. In this study, the two notable cases of medicane development which occurred in the western Mediterranean basin in September 1996 and October 2003, are considered. The capability of mesoscale numerical models to simulate general aspects of such a phenomena has been previously shown. With the aim of improving the numerical results, an adjustment of the humidity vertical profiles in MM5 simulations is performed by means of satellite derived precipitation. Convective and stratiform precipitation types obtained from satellite images are used to individually adjust the profiles. Lightning hits are employed to identify convective grid points. The adjustment of the vertical humidity profiles is carried out in the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses used as initial conditions for the simulations. Analyses nudging to ECMWF analyses and to the satellite-based humidity-corrected version of these analyses has also been applied using Four Dimensional Data Assimilation (FDDA). An additional adjustment is applied as observation nudging of satellite/lightning information at different time and spatial resolutions. Statistical parameters are proposed and tested as an objective way to intercompare satellite-derived and simulated trajectories. Simulations of medicanes exhibit a strong sensitivity to vertical humidity profiles. Trajectories of the storms are improved or worsened by using FDDA. A case dependence is obtained on the characteristics of the humidity-corrected medicanes. FDDA sensitivity on temporal and

  2. Effects of assimilating precipitation zones derived from satellite and lightning data on numerical simulations of tropical-like Mediterranean storms

    Directory of Open Access Journals (Sweden)

    L. Fita

    2009-08-01

    Full Text Available The scarcity of meteorological observations in maritime areas is a well-known problem that can be an important limitation in the study of different phenomena. Tropical-like storms or medicanes developed over the Mediterranean sea are intense storms with some similarities to the tropical ones. Although they do not reach the hurricane intensity, their potential for damage is very high, due to the densely populated Mediterranean coastal regions. In this study, the two notable cases of medicane development which occurred in the western Mediterranean basin in September 1996 and October 2003, are considered. The capability of mesoscale numerical models to simulate general aspects of such a phenomena has been previously shown. With the aim of improving the numerical results, an adjustment of the humidity vertical profiles in MM5 simulations is performed by means of satellite derived precipitation. Convective and stratiform precipitation types obtained from satellite images are used to individually adjust the profiles. Lightning hits are employed to identify convective grid points. The adjustment of the vertical humidity profiles is carried out in the European Centre for Medium-Range Weather Forecasts (ECMWF analyses used as initial conditions for the simulations. Analyses nudging to ECMWF analyses and to the satellite-based humidity-corrected version of these analyses has also been applied using Four Dimensional Data Assimilation (FDDA. An additional adjustment is applied as observation nudging of satellite/lightning information at different time and spatial resolutions. Statistical parameters are proposed and tested as an objective way to intercompare satellite-derived and simulated trajectories. Simulations of medicanes exhibit a strong sensitivity to vertical humidity profiles. Trajectories of the storms are improved or worsened by using FDDA. A case dependence is obtained on the characteristics of the humidity-corrected medicanes. FDDA sensitivity

  3. Effects of assimilating precipitation zones derived from satellite and lightning data on numerical simulations of tropical-like Mediterranean storms

    Energy Technology Data Exchange (ETDEWEB)

    Fita, L.; Romero, R.; Luque, A.; Ramis, C. [Univ. de les Illes Balears, Palma de Mallorca (Spain). Grup de Meteorologia

    2009-07-01

    The scarcity of meteorological observations in maritime areas is a well-known problem that can be an important limitation in the study of different phenomena. Tropical-like storms or medicanes developed over the Mediterranean sea are intense storms with some similarities to the tropical ones. Although they do not reach the hurricane intensity, their potential for damage is very high, due to the densely populated Mediterranean coastal regions. In this study, the two notable cases of medicane development which occurred in the western Mediterranean basin in September 1996 and October 2003, are considered. The capability of mesoscale numerical models to simulate general aspects of such a phenomena has been previously shown. With the aim of improving the numerical results, an adjustment of the humidity vertical profiles in MM5 simulations is performed by means of satellite derived precipitation. Convective and stratiform precipitation types obtained from satellite images are used to individually adjust the profiles. Lightning hits are employed to identify convective grid points. The adjustment of the vertical humidity profiles is carried out in the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses used as initial conditions for the simulations. Analyses nudging to ECMWF analyses and to the satellite-based humidity-corrected version of these analyses has also been applied using Four Dimensional Data Assimilation (FDDA). An additional adjustment is applied as observation nudging of satellite/lightning information at different time and spatial resolutions. Statistical parameters are proposed and tested as an objective way to intercompare satellite-derived and simulated trajectories. Simulations of medicanes exhibit a strong sensitivity to vertical humidity profiles. Trajectories of the storms are improved or worsened by using FDDA. A case dependence is obtained on the characteristics of the humidity-corrected medicanes. FDDA sensitivity on temporal and

  4. Surface Runoff Estimation Using SMOS Observations, Rain-gauge Measurements and Satellite Precipitation Estimations. Comparison with Model Predictions

    Science.gov (United States)

    Garcia Leal, Julio A.; Lopez-Baeza, Ernesto; Khodayar, Samiro; Estrela, Teodoro; Fidalgo, Arancha; Gabaldo, Onofre; Kuligowski, Robert; Herrera, Eddy

    Surface runoff is defined as the amount of water that originates from precipitation, does not infiltrates due to soil saturation and therefore circulates over the surface. A good estimation of runoff is useful for the design of draining systems, structures for flood control and soil utilisation. For runoff estimation there exist different methods such as (i) rational method, (ii) isochrone method, (iii) triangular hydrograph, (iv) non-dimensional SCS hydrograph, (v) Temez hydrograph, (vi) kinematic wave model, represented by the dynamics and kinematics equations for a uniforme precipitation regime, and (vii) SCS-CN (Soil Conservation Service Curve Number) model. This work presents a way of estimating precipitation runoff through the SCS-CN model, using SMOS (Soil Moisture and Ocean Salinity) mission soil moisture observations and rain-gauge measurements, as well as satellite precipitation estimations. The area of application is the Jucar River Basin Authority area where one of the objectives is to develop the SCS-CN model in a spatial way. The results were compared to simulations performed with the 7-km COSMO-CLM (COnsortium for Small-scale MOdelling, COSMO model in CLimate Mode) model. The use of SMOS soil moisture as input to the COSMO-CLM model will certainly improve model simulations.

  5. Python-Based Scientific Analysis and Visualization of Precipitation Systems at NASA Marshall Space Flight Center

    Science.gov (United States)

    Lang, Timothy J.

    2015-01-01

    larger regional or national picture of precipitating weather systems. Composites, horizontal and vertical crosssections, and combinations thereof are easily displayed using as little as one line of code. MMM-Py can also write to the native MRMS binary format, and sub-sectioning of tiles (or multiple stitched tiles) is anticipated to be in place by the time of this meeting. Thus, MMM-Py also can be used to power the creation of custom mosaics for targeted regional studies. Overlays of other data (e.g., lightning observations) are easily accomplished. Demonstrations of MMM-Py, including the creation of animations, will be shown. Finally, Marshall has done significant work to interface Python-based analysis routines with the U.S. Department of Energy's Py-ART software package for radar data ingest, processing, and analysis. One example of this is the Python Turbulence Detection Algorithm (PyTDA), an MSFC-based implementation of the National Center for Atmospheric Research (NCAR) Turbulence Detection Algorithm (NTDA) for the purposes of convective-scale analysis, situational awareness, and forensic meteorology. PyTDA exploits Py-ART's radar data ingest routines and data model to rapidly produce aviation-relevant turbulence estimates from Doppler radar data. Work toward processing speed optimization and better integration within the Py-ART framework will be highlighted. Python-based analysis within the Py-ART framework is also being done for new research related to intercomparison of ground-based radar data with satellite estimates of ocean winds, as well as research on the electrification of pyrocumulus clouds.

  6. Multiple continuous coverage of the earth based on multi-satellite systems with linear structure

    Science.gov (United States)

    Saulskiy, V. K.

    2009-04-01

    A new and wider definition is given to multi-satellite systems with linear structure (SLS), and efficiency of their application to multiple continuous coverage of the Earth is substantiated. Owing to this widening, SLS have incorporated already well-recognized “polar systems” by L. Rider and W.S. Adams, “kinematically regular systems” by G.V. Mozhaev, and “delta-systems” by J.G. Walker, as well as “near-polar systems” by Yu.P. Ulybyshev, and some other satellite constellations unknown before. A universal method of SLS optimization is presented, valid for any values of coverage multiplicity and the number of satellites in a system. The method uses the criterion of minimum radius of a circle seen from a satellite on the surface of the globe. Among the best SLS found in this way there are both systems representing the well-known classes mentioned above and new orbit constellations of satellites.

  7. The 3D Radiation Dose Analysis For Satellite

    Science.gov (United States)

    Cai, Zhenbo; Lin, Guocheng; Chen, Guozhen; Liu, Xia

    2002-01-01

    the earth. These particles come from the Van Allen Belt, Solar Cosmic Ray and Galaxy Cosmic Ray. They have different energy and flux, varying with time and space, and correlating with solar activity tightly. These particles interact with electrical components and materials used on satellites, producing various space radiation effects, which will damage satellite to some extent, or even affect its safety. orbit. Space energy particles inject into components and materials used on satellites, and generate radiation dose by depositing partial or entire energy in them through ionization, which causes their characteristic degradation or even failure. As a consequence, the analysis and protection for radiation dose has been paid more attention during satellite design and manufacture. Designers of satellites need to analyze accurately the space radiation dose while satellites are on orbit, and use the results as the basis for radiation protection designs and ground experiments for satellites. can be calculated, using the model of the trapped proton and the trapped electron in the Van Allen Belt (AE8 and AP8). This is the 1D radiation dose analysis for satellites. Obviously, the mass shielding from the outside space to the computed point in all directions is regarded as a simple sphere shell. The actual structure of satellites, however, is very complex. When energy particles are injecting into a given equipment inside satellite from outside space, they will travel across satellite structure, other equipment, the shell of the given equipment, and so on, which depends greatly on actual layout of satellite. This complex radiation shielding has two characteristics. One is that the shielding masses for the computed point are different in different injecting directions. The other is that for different computed points, the shielding conditions vary in all space directions. Therefore, it is very difficult to tell the differences described above using the 1D radiation analysis, and

  8. A Land Product Characterization System for Comparative Analysis of Satellite Data and Products

    Directory of Open Access Journals (Sweden)

    Kevin Gallo

    2017-12-01

    Full Text Available A Land Product Characterization System (LPCS has been developed to provide land data and products to the community of individuals interested in validating space-based land products by comparing them with similar products available from other sensors or surface-based observations. The LPCS facilitates the application of global multi-satellite and in situ data for characterization and validation of higher-level, satellite-derived, land surface products (e.g., surface reflectance, normalized difference vegetation index, and land surface temperature. The LPCS includes data search, inventory, access, and analysis functions that will permit data to be easily identified, retrieved, co-registered, and compared statistically through a single interface. The system currently includes data and products available from Landsat 4 through 8, Moderate Resolution Imaging Spectroradiometer (MODIS Terra and Aqua, Suomi National Polar-Orbiting Partnership (S-NPP/Joint Polar Satellite System (JPSS Visible Infrared Imaging Radiometer Suite (VIIRS, and simulated data for the Geostationary Operational Environmental Satellite (GOES-16 Advanced Baseline Imager (ABI. In addition to the future inclusion of in situ data, higher-level land products from the European Space Agency (ESA Sentinel-2 and -3 series of satellites, and other high and medium resolution spatial sensors, will be included as available. When fully implemented, any of the sensor data or products included in the LPCS would be available for comparative analysis.

  9. SatelliteDL: a Toolkit for Analysis of Heterogeneous Satellite Datasets

    Science.gov (United States)

    Galloy, M. D.; Fillmore, D.

    2014-12-01

    SatelliteDL is an IDL toolkit for the analysis of satellite Earth observations from a diverse set of platforms and sensors. The core function of the toolkit is the spatial and temporal alignment of satellite swath and geostationary data. The design features an abstraction layer that allows for easy inclusion of new datasets in a modular way. Our overarching objective is to create utilities that automate the mundane aspects of satellite data analysis, are extensible and maintainable, and do not place limitations on the analysis itself. IDL has a powerful suite of statistical and visualization tools that can be used in conjunction with SatelliteDL. Toward this end we have constructed SatelliteDL to include (1) HTML and LaTeX API document generation,(2) a unit test framework,(3) automatic message and error logs,(4) HTML and LaTeX plot and table generation, and(5) several real world examples with bundled datasets available for download. For ease of use, datasets, variables and optional workflows may be specified in a flexible format configuration file. Configuration statements may specify, for example, a region and date range, and the creation of images, plots and statistical summary tables for a long list of variables. SatelliteDL enforces data provenance; all data should be traceable and reproducible. The output NetCDF file metadata holds a complete history of the original datasets and their transformations, and a method exists to reconstruct a configuration file from this information. Release 0.1.0 distributes with ingest methods for GOES, MODIS, VIIRS and CERES radiance data (L1) as well as select 2D atmosphere products (L2) such as aerosol and cloud (MODIS and VIIRS) and radiant flux (CERES). Future releases will provide ingest methods for ocean and land surface products, gridded and time averaged datasets (L3 Daily, Monthly and Yearly), and support for 3D products such as temperature and water vapor profiles. Emphasis will be on NPP Sensor, Environmental and

  10. Oak Forest Responses to Episodic-Seasonal-Drought, Chronic Multi-year Precipitation Change and Acute Drought Manipulations in a Region With Deep Soils and High Precipitation

    Science.gov (United States)

    Hanson, Paul J.; Wullschleger, Stan D.; Todd, Donald E.; Auge, Robert M.; Froberg, Mats; Johnson, Dale W.

    2010-05-01

    Implications of episodic-seasonal drought (extremely dry late summers), chronic multi-year precipitation manipulations (±33 percent over 12 years) and acute drought (-100 percent over 3 years) were evaluated for the response of vegetation and biogeochemical cycles for an upland-oak forest. The Quercus-Acer forest is located in eastern Tennessee on deep acidic soils with mean annual temperatures of 14.2 °C and abundant precipitation (1352 mm y-1). The multi-year observations and chronic manipulations were conducted from 1993 through 2005 using understory throughfall collection troughs and redistribution gutters and pipes. Acute manipulations of dominant canopy trees (Quercus prinus; Liriodendron tulipifera) were conducted from 2003 through 2005 using full understory tents. Regional and severe late-summer droughts were produced reduced stand water use and photosynthetic carbon gain as expected. Likewise, seedlings and saplings exhibited reduced survival and cumulative growth reductions. Conversely, multi-year chronic increases or decreases in precipitation and associated soil water deficits did not reduce large tree basal area growth for the tree species present. The resilience of canopy trees to chronic-change was the result of a disconnect between carbon allocation to tree growth (an early-season phenomenon) and late-season drought occurrence. Acute precipitation exclusion from the largest canopy trees also produced limited physiological responses and minimal cumulative growth reductions. Lateral root water sources were removed through trenching and could not explain the lack of response to extreme soil drying. Therefore, deep rooting the primary mechanism for large-tree resilience to severe drought. Extensive trench-based assessments of rooting depth suggested that ‘deep' water supplies were being obtained from limited numbers of deep fine roots. Observations of carbon stocks in organic horizons demonstrated accumulation with precipitation reductions and

  11. Statistical Projections for Multi-resolution, Multi-dimensional Visual Data Exploration and Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen, Hoa T. [Univ. of Utah, Salt Lake City, UT (United States); Stone, Daithi [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bethel, E. Wes [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2016-01-01

    An ongoing challenge in visual exploration and analysis of large, multi-dimensional datasets is how to present useful, concise information to a user for some specific visualization tasks. Typical approaches to this problem have proposed either reduced-resolution versions of data, or projections of data, or both. These approaches still have some limitations such as consuming high computation or suffering from errors. In this work, we explore the use of a statistical metric as the basis for both projections and reduced-resolution versions of data, with a particular focus on preserving one key trait in data, namely variation. We use two different case studies to explore this idea, one that uses a synthetic dataset, and another that uses a large ensemble collection produced by an atmospheric modeling code to study long-term changes in global precipitation. The primary findings of our work are that in terms of preserving the variation signal inherent in data, that using a statistical measure more faithfully preserves this key characteristic across both multi-dimensional projections and multi-resolution representations than a methodology based upon averaging.

  12. From TRMM to GPM: How well can heavy rainfall be detected from space?

    Science.gov (United States)

    Prakash, Satya; Mitra, Ashis K.; Pai, D. S.; AghaKouchak, Amir

    2016-02-01

    In this study, we investigate the capabilities of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and the recently released Integrated Multi-satellitE Retrievals for GPM (IMERG) in detecting and estimating heavy rainfall across India. First, the study analyzes TMPA data products over a 17-year period (1998-2014). While TMPA and reference gauge-based observations show similar mean monthly variations of conditional heavy rainfall events, the multi-satellite product systematically overestimates its inter-annual variations. Categorical as well as volumetric skill scores reveal that TMPA over-detects heavy rainfall events (above 75th percentile of reference data), but it shows reasonable performance in capturing the volume of heavy rain across the country. An initial assessment of the GPM-based multi-satellite IMERG precipitation estimates for the southwest monsoon season shows notable improvements over TMPA in capturing heavy rainfall over India. The recently released IMERG shows promising results to help improve modeling of hydrological extremes (e.g., floods and landslides) using satellite observations.

  13. Geostationary satellites collocation

    CERN Document Server

    Li, Hengnian

    2014-01-01

    Geostationary Satellites Collocation aims to find solutions for deploying a safe and reliable collocation control. Focusing on the orbital perturbation analysis, the mathematical foundations for orbit and control of the geostationary satellite are summarized. The mathematical and physical principle of orbital maneuver and collocation strategies for multi geostationary satellites sharing with the same dead band is also stressed. Moreover, the book presents some applications using the above algorithms and mathematical models to help readers master the corrective method for planning station keeping maneuvers. Engineers and scientists in the fields of aerospace technology and space science can benefit from this book. Hengnian Li is the Deputy Director of State Key Laboratory of Astronautic Dynamics, China.

  14. Predictability of Precipitation Over the Conterminous U.S. Based on the CMIP5 Multi-Model Ensemble

    Science.gov (United States)

    Jiang, Mingkai; Felzer, Benjamin S.; Sahagian, Dork

    2016-01-01

    Characterizing precipitation seasonality and variability in the face of future uncertainty is important for a well-informed climate change adaptation strategy. Using the Colwell index of predictability and monthly normalized precipitation data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensembles, this study identifies spatial hotspots of changes in precipitation predictability in the United States under various climate scenarios. Over the historic period (1950–2005), the recurrent pattern of precipitation is highly predictable in the East and along the coastal Northwest, and is less so in the arid Southwest. Comparing the future (2040–2095) to the historic period, larger changes in precipitation predictability are observed under Representative Concentration Pathways (RCP) 8.5 than those under RCP 4.5. Finally, there are region-specific hotspots of future changes in precipitation predictability, and these hotspots often coincide with regions of little projected change in total precipitation, with exceptions along the wetter East and parts of the drier central West. Therefore, decision-makers are advised to not rely on future total precipitation as an indicator of water resources. Changes in precipitation predictability and the subsequent changes on seasonality and variability are equally, if not more, important factors to be included in future regional environmental assessment. PMID:27425819

  15. Satellite Monitoring of Vegetation Response to Precipitation and Dust Storm Outbreaks in Gobi Desert Regions

    Directory of Open Access Journals (Sweden)

    Yuki Sofue

    2018-02-01

    Full Text Available Recently, droughts have become widespread in the Northern Hemisphere, including in Mongolia. The ground surface condition, particularly vegetation coverage, affects the occurrence of dust storms. The main sources of dust storms in the Asian region are the Taklimakan and Mongolian Gobi desert regions. In these regions, precipitation is one of the most important factors for growth of plants especially in arid and semi-arid land. The purpose of this study is to clarify the relationship between precipitation and vegetation cover dynamics over 29 years in the Gobi region. We compared the patterns between precipitation and Normalized Difference Vegetation Index (NDVI for a period of 29 years. The precipitation and vegetation datasets were examined to investigate the trends during 1985–2013. Cross correlation analysis between the precipitation and the NDVI anomalies was performed. Data analysis showed that the variations of NDVI anomalies in the east region correspond well with the precipitation anomalies during this period. However, in the southwest region of the Gobi region, the NDVI had decreased regardless of the precipitation amount, especially since 2010. This result showed that vegetation in this region was more degraded than in the other areas.

  16. The Effectiveness of Using Limited Gauge Measurements for Bias Adjustment of Satellite-Based Precipitation Estimation over Saudi Arabia

    Science.gov (United States)

    Alharbi, Raied; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan

    2018-01-01

    Precipitation is a key input variable for hydrological and climate studies. Rain gauges are capable of providing reliable precipitation measurements at point scale. However, the uncertainty of rain measurements increases when the rain gauge network is sparse. Satellite -based precipitation estimations appear to be an alternative source of precipitation measurements, but they are influenced by systematic bias. In this study, a method for removing the bias from the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) over a region where the rain gauge is sparse is investigated. The method consists of monthly empirical quantile mapping, climate classification, and inverse-weighted distance method. Daily PERSIANN-CCS is selected to test the capability of the method for removing the bias over Saudi Arabia during the period of 2010 to 2016. The first six years (2010 - 2015) are calibrated years and 2016 is used for validation. The results show that the yearly correlation coefficient was enhanced by 12%, the yearly mean bias was reduced by 93% during validated year. Root mean square error was reduced by 73% during validated year. The correlation coefficient, the mean bias, and the root mean square error show that the proposed method removes the bias on PERSIANN-CCS effectively that the method can be applied to other regions where the rain gauge network is sparse.

  17. Optimization of Power Allocation for Multiusers in Multi-Spot-Beam Satellite Communication Systems

    Directory of Open Access Journals (Sweden)

    Heng Wang

    2014-01-01

    Full Text Available In recent years, multi-spot-beam satellite communication systems have played a key role in global seamless communication. However, satellite power resources are scarce and expensive, due to the limitations of satellite platform. Therefore, this paper proposes optimizing the power allocation of each user in order to improve the power utilization efficiency. Initially the capacity allocated to each user is calculated according to the satellite link budget equations, which can be achieved in the practical satellite communication systems. The problem of power allocation is then formulated as a convex optimization, taking account of a trade-off between the maximization of the total system capacity and the fairness of power allocation amongst the users. Finally, an iterative algorithm based on the duality theory is proposed to obtain the optimal solution to the optimization. Compared with the traditional uniform resource allocation or proportional resource allocation algorithms, the proposed optimal power allocation algorithm improves the fairness of power allocation amongst the users. Moreover, the computational complexity of the proposed algorithm is linear with both the numbers of the spot beams and users. As a result, the proposed power allocation algorithm is easy to be implemented in practice.

  18. Winter precipitation particle size distribution measurement by Multi-Angle Snowflake Camera

    Science.gov (United States)

    Huang, Gwo-Jong; Kleinkort, Cameron; Bringi, V. N.; Notaroš, Branislav M.

    2017-12-01

    From the radar meteorology viewpoint, the most important properties for quantitative precipitation estimation of winter events are 3D shape, size, and mass of precipitation particles, as well as the particle size distribution (PSD). In order to measure these properties precisely, optical instruments may be the best choice. The Multi-Angle Snowflake Camera (MASC) is a relatively new instrument equipped with three high-resolution cameras to capture the winter precipitation particle images from three non-parallel angles, in addition to measuring the particle fall speed using two pairs of infrared motion sensors. However, the results from the MASC so far are usually presented as monthly or seasonally, and particle sizes are given as histograms, no previous studies have used the MASC for a single storm study, and no researchers use MASC to measure the PSD. We propose the methodology for obtaining the winter precipitation PSD measured by the MASC, and present and discuss the development, implementation, and application of the new technique for PSD computation based on MASC images. Overall, this is the first study of the MASC-based PSD. We present PSD MASC experiments and results for segments of two snow events to demonstrate the performance of our PSD algorithm. The results show that the self-consistency of the MASC measured single-camera PSDs is good. To cross-validate PSD measurements, we compare MASC mean PSD (averaged over three cameras) with the collocated 2D Video Disdrometer, and observe good agreements of the two sets of results.

  19. Recent Trends of the Tropical Hydrological Cycle Inferred from Global Precipitation Climatology Project and International Satellite Cloud Climatology Project data

    Science.gov (United States)

    Zhou, Y. P.; Xu, Kuan-Man; Sud, Y. C.; Betts, A. K.

    2011-01-01

    Scores of modeling studies have shown that increasing greenhouse gases in the atmosphere impact the global hydrologic cycle; however, disagreements on regional scales are large, and thus the simulated trends of such impacts, even for regions as large as the tropics, remain uncertain. The present investigation attempts to examine such trends in the observations using satellite data products comprising Global Precipitation Climatology Project precipitation and International Satellite Cloud Climatology Project cloud and radiation. Specifically, evolving trends of the tropical hydrological cycle over the last 20-30 years were identified and analyzed. The results show (1) intensification of tropical precipitation in the rising regions of the Walker and Hadley circulations and weakening over the sinking regions of the associated overturning circulation; (2) poleward shift of the subtropical dry zones (up to 2deg/decade in June-July-August (JJA) in the Northern Hemisphere and 0.3-0.7deg/decade in June-July-August and September-October-November in the Southern Hemisphere) consistent with an overall broadening of the Hadley circulation; and (3) significant poleward migration (0.9-1.7deg/decade) of cloud boundaries of Hadley cell and plausible narrowing of the high cloudiness in the Intertropical Convergence Zone region in some seasons. These results support findings of some of the previous studies that showed strengthening of the tropical hydrological cycle and expansion of the Hadley cell that are potentially related to the recent global warming trends.

  20. Stochastic error model corrections to improve the performance of bottom-up precipitation products for hydrologic applications

    Science.gov (United States)

    Maggioni, V.; Massari, C.; Ciabatta, L.; Brocca, L.

    2016-12-01

    Accurate quantitative precipitation estimation is of great importance for water resources management, agricultural planning, and forecasting and monitoring of natural hazards such as flash floods and landslides. In situ observations are limited around the Earth, especially in remote areas (e.g., complex terrain, dense vegetation), but currently available satellite precipitation products are able to provide global precipitation estimates with an accuracy that depends upon many factors (e.g., type of storms, temporal sampling, season, etc.). The recent SM2RAIN approach proposes to estimate rainfall by using satellite soil moisture observations. As opposed to traditional satellite precipitation methods, which sense cloud properties to retrieve instantaneous estimates, this new bottom-up approach makes use of two consecutive soil moisture measurements for obtaining an estimate of the fallen precipitation within the interval between two satellite overpasses. As a result, the nature of the measurement is different and complementary to the one of classical precipitation products and could provide a different valid perspective to substitute or improve current rainfall estimates. However, uncertainties in the SM2RAIN product are still not well known and could represent a limitation in utilizing this dataset for hydrological applications. Therefore, quantifying the uncertainty associated with SM2RAIN is necessary for enabling its use. The study is conducted over the Italian territory for a 5-yr period (2010-2014). A number of satellite precipitation error properties, typically used in error modeling, are investigated and include probability of detection, false alarm rates, missed events, spatial correlation of the error, and hit biases. After this preliminary uncertainty analysis, the potential of applying the stochastic rainfall error model SREM2D to correct SM2RAIN and to improve its performance in hydrologic applications is investigated. The use of SREM2D for

  1. Surface Freshwater Storage Variations in the Orinoco Floodplains Using Multi-Satellite Observations

    Directory of Open Access Journals (Sweden)

    Frédéric Frappart

    2014-12-01

    Full Text Available Variations in surface water extent and storage are poorly characterized from regional to global scales. In this study, a multi-satellite approach is proposed to estimate the water stored in the floodplains of the Orinoco Basin at a monthly time-scale using remotely-sensed observations of surface water from the Global Inundation Extent Multi-Satellite (GIEMS and stages from Envisat radar altimetry. Surface water storage variations over 2003–2007 exhibit large interannual variability and a strong seasonal signal, peaking during summer, and associated with the flood pulse. The volume of surface water storage in the Orinoco Basin was highly correlated with the river discharge at Ciudad Bolivar (R = 0.95, the closest station to the mouth where discharge was estimated, although discharge lagged one month behind storage. The correlation remained high (R = 0.73 after removing seasonal effects. Mean annual variations in surface water volume represented ~170 km3, contributing to ~45% of the Gravity Recovery and Climate Experiment (GRACE-derived total water storage variations and representing ~13% of the total volume of water that flowed out of the Orinoco Basin to the Atlantic Ocean.

  2. Precipitation Estimation Using L-Band and C-Band Soil Moisture Retrievals

    Science.gov (United States)

    Koster, Randal D.; Brocca, Luca; Crow, Wade T.; Burgin, Mariko S.; De Lannoy, Gabrielle J. M.

    2016-01-01

    An established methodology for estimating precipitation amounts from satellite-based soil moisture retrievals is applied to L-band products from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterometer (ASCAT) mission. The precipitation estimates so obtained are evaluated against in situ (gauge-based) precipitation observations from across the globe. The precipitation estimation skill achieved using the L-band SMAP and SMOS data sets is higher than that obtained with the C-band product, as might be expected given that L-band is sensitive to a thicker layer of soil and thereby provides more information on the response of soil moisture to precipitation. The square of the correlation coefficient between the SMAP-based precipitation estimates and the observations (for aggregations to approximately100 km and 5 days) is on average about 0.6 in areas of high rain gauge density. Satellite missions specifically designed to monitor soil moisture thus do provide significant information on precipitation variability, information that could contribute to efforts in global precipitation estimation.

  3. A Metastatistical Approach to Satellite Estimates of Extreme Rainfall Events

    Science.gov (United States)

    Zorzetto, E.; Marani, M.

    2017-12-01

    The estimation of the average recurrence interval of intense rainfall events is a central issue for both hydrologic modeling and engineering design. These estimates require the inference of the properties of the right tail of the statistical distribution of precipitation, a task often performed using the Generalized Extreme Value (GEV) distribution, estimated either from a samples of annual maxima (AM) or with a peaks over threshold (POT) approach. However, these approaches require long and homogeneous rainfall records, which often are not available, especially in the case of remote-sensed rainfall datasets. We use here, and tailor it to remotely-sensed rainfall estimates, an alternative approach, based on the metastatistical extreme value distribution (MEVD), which produces estimates of rainfall extreme values based on the probability distribution function (pdf) of all measured `ordinary' rainfall event. This methodology also accounts for the interannual variations observed in the pdf of daily rainfall by integrating over the sample space of its random parameters. We illustrate the application of this framework to the TRMM Multi-satellite Precipitation Analysis rainfall dataset, where MEVD optimally exploits the relatively short datasets of satellite-sensed rainfall, while taking full advantage of its high spatial resolution and quasi-global coverage. Accuracy of TRMM precipitation estimates and scale issues are here investigated for a case study located in the Little Washita watershed, Oklahoma, using a dense network of rain gauges for independent ground validation. The methodology contributes to our understanding of the risk of extreme rainfall events, as it allows i) an optimal use of the TRMM datasets in estimating the tail of the probability distribution of daily rainfall, and ii) a global mapping of daily rainfall extremes and distributional tail properties, bridging the existing gaps in rain gauges networks.

  4. Development of a daily gridded precipitation data set for the Middle East

    Directory of Open Access Journals (Sweden)

    A. Yatagai

    2008-03-01

    Full Text Available We show an algorithm to construct a rain-gauge-based analysis of daily precipitation for the Middle East. One of the key points of our algorithm is to construct an accurate distribution of climatology. One possible advantage of this product is to validate high-resolution climate models and/or to diagnose the impact of climate changes on local hydrological resources. Many users are familiar with a monthly precipitation dataset (New et al., 1999 and a satellite-based daily precipitation dataset (Huffman et al., 2001, yet our data set, unlike theirs, clearly shows the effect of orography on daily precipitation and other extreme events, especially over the Fertile Crescent region. Currently the Middle-East precipitation analysis product is consisting of a 25-year data set for 1979–2003 based on more than 1300 stations.

  5. Error threshold inference from Global Precipitation Measurement (GPM) satellite rainfall data and interpolated ground-based rainfall measurements in Metro Manila

    Science.gov (United States)

    Ampil, L. J. Y.; Yao, J. G.; Lagrosas, N.; Lorenzo, G. R. H.; Simpas, J.

    2017-12-01

    The Global Precipitation Measurement (GPM) mission is a group of satellites that provides global observations of precipitation. Satellite-based observations act as an alternative if ground-based measurements are inadequate or unavailable. Data provided by satellites however must be validated for this data to be reliable and used effectively. In this study, the Integrated Multisatellite Retrievals for GPM (IMERG) Final Run v3 half-hourly product is validated by comparing against interpolated ground measurements derived from sixteen ground stations in Metro Manila. The area considered in this study is the region 14.4° - 14.8° latitude and 120.9° - 121.2° longitude, subdivided into twelve 0.1° x 0.1° grid squares. Satellite data from June 1 - August 31, 2014 with the data aggregated to 1-day temporal resolution are used in this study. The satellite data is directly compared to measurements from individual ground stations to determine the effect of the interpolation by contrast against the comparison of satellite data and interpolated measurements. The comparisons are calculated by taking a fractional root-mean-square error (F-RMSE) between two datasets. The results show that interpolation improves errors compared to using raw station data except during days with very small amounts of rainfall. F-RMSE reaches extreme values of up to 654 without a rainfall threshold. A rainfall threshold is inferred to remove extreme error values and make the distribution of F-RMSE more consistent. Results show that the rainfall threshold varies slightly per month. The threshold for June is inferred to be 0.5 mm, reducing the maximum F-RMSE to 9.78, while the threshold for July and August is inferred to be 0.1 mm, reducing the maximum F-RMSE to 4.8 and 10.7, respectively. The maximum F-RMSE is reduced further as the threshold is increased. Maximum F-RMSE is reduced to 3.06 when a rainfall threshold of 10 mm is applied over the entire duration of JJA. These results indicate that

  6. Impact of climate change on precipitation distribution and water availability in the Nile using CMIP5 GCM ensemble.

    Science.gov (United States)

    Mekonnen, Z. T.; Gebremichael, M.

    2017-12-01

    ABSTRACT In a basin like the Nile where millions of people depend on rainfed agriculture and surface water resources for their livelihoods, changes in precipitation will have tremendous social and economic consequences. General circulation models (GCMs) have been associated with high uncertainty in their projection of future precipitation for the Nile basin. Some studies tried to compare performance of different GCMs by doing a Multi-Model comparison for the region. Many indicated that there is no single model that gives the "best estimate" of precipitation for a very complex and large basin like the Nile. In this study, we used a combination of satellite and long term rain gauge precipitation measurements (TRMM and CenTrends) to evaluate the performance of 10 GCMs from the 5th Coupled Model Intercomparison Project (CMIP5) at different spatial and seasonal scales and produce a weighted ensemble projection. Our results confirm that there is no single model that gives best estimate over the region, hence the approach of creating an ensemble depending on how the model performed in specific areas and seasons resulted in an improved estimate of precipitation compared with observed values. Following the same approach, we created an ensemble of future precipitation projections for four different time periods (2000-2024, 2025-2049 and 2050-2100). The analysis showed that all the major sub-basins of the Nile will get will get more precipitation with time, even though the distribution with in the sub basin might be different. Overall the analysis showed a 15 % increase (125 mm/year) by the end of the century averaged over the area up to the Aswan dam. KEY WORDS: Climate Change, CMIP5, Nile, East Africa, CenTrends, Precipitation, Weighted Ensembles

  7. Engineering analysis of the two-stage trifluoride precipitation process

    International Nuclear Information System (INIS)

    Luerkens, D.w.W.

    1984-06-01

    An engineering analysis of two-stage trifluoride precipitation processes is developed. Precipitation kinetics are modeled using consecutive reactions to represent fluoride complexation. Material balances across the precipitators are used to model the time dependent concentration profiles of the main chemical species. The results of the engineering analysis are correlated with previous experimental work on plutonium trifluoride and cerium trifluoride

  8. AUTOMATIC CLOUD DETECTION FROM MULTI-TEMPORAL SATELLITE IMAGES: TOWARDS THE USE OF PLÉIADES TIME SERIES

    Directory of Open Access Journals (Sweden)

    N. Champion

    2012-08-01

    Full Text Available Contrary to aerial images, satellite images are often affected by the presence of clouds. Identifying and removing these clouds is one of the primary steps to perform when processing satellite images, as they may alter subsequent procedures such as atmospheric corrections, DSM production or land cover classification. The main goal of this paper is to present the cloud detection approach, developed at the French Mapping agency. Our approach is based on the availability of multi-temporal satellite images (i.e. time series that generally contain between 5 and 10 images and is based on a region-growing procedure. Seeds (corresponding to clouds are firstly extracted through a pixel-to-pixel comparison between the images contained in time series (the presence of a cloud is here assumed to be related to a high variation of reflectance between two images. Clouds are then delineated finely using a dedicated region-growing algorithm. The method, originally designed for panchromatic SPOT5-HRS images, is tested in this paper using time series with 9 multi-temporal satellite images. Our preliminary experiments show the good performances of our method. In a near future, the method will be applied to Pléiades images, acquired during the in-flight commissioning phase of the satellite (launched at the end of 2011. In that context, this is a particular goal of this paper to show to which extent and in which way our method can be adapted to this kind of imagery.

  9. Spatial Downscaling of TRMM Precipitation using MODIS product in the Korean Peninsula

    Science.gov (United States)

    Cho, H.; Choi, M.

    2013-12-01

    Precipitation is a major driving force in the water cycle. But, it is difficult to provide spatially distributed precipitation data from isolated individual in situ. The Tropical Rainfall Monitoring Mission (TRMM) satellite can provide precipitation data with relatively coarse spatial resolution (0.25° scale) at daily basis. In order to overcome the coarse spatial resolution of TRMM precipitation products, we conducted a downscaling technique using a scaling parameter from the Moderate Resolution Imaging Spectroradiometers (MODIS) sensor. In this study, statistical relations between precipitation estimates derived from the TRMM satellite and the normalized difference vegetation index (NDVI) which is obtained from the MODIS sensor in TERRA satellite are found for different spatial scales on the Korean peninsula in northeast Asia. We obtain the downscaled precipitation mapping by regression equation between yearly TRMM precipitations values and annual average NDVI aggregating 1km to 25 degree. The downscaled precipitation is validated using time series of the ground measurements precipitation dataset provided by Korea Meteorological Organization (KMO) from 2002 to 2005. To improve the spatial downscaling of precipitation, we will conduct a study about correlation between precipitation and land surface temperature, perceptible water and other hydrological parameters.

  10. Multi-Satellite Orbit Determination Using Interferometric Observables with RF Localization Applications

    Science.gov (United States)

    Geeraert, Jeroen L.

    Very long baseline interferometry (VLBI) specifically same-beam interferometry (SBI), and dual-satellite geolocation are two fields of research not previously connected. This is due to the different application of each field, SBI is used for relative interplanetary navigation of two satellites while dual-satellite geolocation is used to locate the source of a radio frequency (RF) signal. In this dissertation however, we leverage both fields to create a novel method for multi-satellite orbit determination (OD) using time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements. The measurements are double differenced between the satellites and the stations, in so doing, many of the common errors are canceled which can significantly improve measurement precision. Provided with this novel OD technique, the observability is first analyzed to determine the benefits and limitations of this method. In all but a few scenarios the measurements successfully reduce the covariance when examining the Cramer-Rao Lower Bound (CRLB). Reduced observability is encountered with geostationary satellites as their motion with respect to the stations is limited, especially when only one baseline is used. However, when using satellite pairs with greater relative motion with respect to the stations, even satellites that are close to, but not exactly in a geostationary orbit can be estimated accurately. We find that in a strong majority of cases the OD technique provides lower uncertainties and solutions far more accurate than using conventional OD observables such as range and range-rate while also not being affected by common errors and biases. We specifically examine GEO-GEO, GEO-MEO, and GEO-LEO dual-satellite estimation cases. The work is further extended by developing a relative navigation scenario where the chief satellite is assumed to have perfect knowledge, or some small amount of uncertainty considered but not estimated, while estimating the deputy

  11. Development of Mission and Spacecraft Dynamics Analysis System for Geostationary Communication Satellite

    Directory of Open Access Journals (Sweden)

    Hyeon Cheol Gong

    1998-06-01

    Full Text Available We consider the motion of the subsystems as separate bodies as well as the entire satellite for the attitude and orbit control of a communication satellite by multi-body modeling technique. Thus, the system can be applied to a general communication satellite as well as a specific communication satellite, i.e. Koreasat I, II. The simulation results can be viewed by two-dimensional graphics and three-dimensional animation. The graphical user interface (GUI makes its usage much simpler. We have simulated a couple of scenarios for Koreasat I, II which are being operated as geostationary communication satellites to verify the system performance.

  12. Improved candidate generation and coverage analysis methods for design optimization of symmetric multi-satellite constellations

    Science.gov (United States)

    Matossian, Mark G.

    1997-01-01

    Much attention in recent years has focused on commercial telecommunications ventures involving constellations of spacecraft in low and medium Earth orbit. These projects often require investments on the order of billions of dollars (US$) for development and operations, but surprisingly little work has been published on constellation design optimization for coverage analysis, traffic simulation and launch sequencing for constellation build-up strategies. This paper addresses the two most critical aspects of constellation orbital design — efficient constellation candidate generation and coverage analysis. Inefficiencies and flaws in the current standard algorithm for constellation modeling are identified, and a corrected and improved algorithm is presented. In the 1970's, John Walker and G. V. Mozhaev developed innovative strategies for continuous global coverage using symmetric non-geosynchronous constellations. (These are sometimes referred to as rosette, or Walker constellations. An example is pictured above.) In 1980, the late Arthur Ballard extended and generalized the work of Walker into a detailed algorithm for the NAVSTAR/GPS program, which deployed a 24 satellite symmetric constellation. Ballard's important contribution was published in his "Rosette Constellations of Earth Satellites."

  13. Constraining precipitation amount and distribution over cold regions using GRACE

    Science.gov (United States)

    Behrangi, A.; Reager, J. T., II; Gardner, A. S.; Fisher, J.

    2017-12-01

    Current quantitative knowledge on the amount and distribution of precipitation in high-elevation and high latitude regions is limited due to instrumental and retrieval shortcomings. Here we demonstrate how that satellite gravimetry (Gravity Recovery and Climate Experiment, GRACE) can be used to provide an independent estimate of monthly accumulated precipitation using mass balance. Results showed that the GRACE-based precipitation estimate has the highest agreement with most of the commonly used precipitation products in summer, but it deviates from them in cold months, when the other products are expected to have larger error. We also observed that as near surface temperature decreases products tend to underestimate accumulated precipitation retrieved from GRACE. The analysis performed using various products such as GPCP, GPCC, TRMM, and gridded station data over vast regions in high latitudes and two large endorheic basins in High Mountain Asia. Based on the analysis over High Mountain Asia it was found that most of the products capture about or less than 50% of the total precipitation estimated using GRACE in winter. Overall, GPCP showed better agreement with GRACE estimate than other products. Yet on average GRACE showed 30% more annual precipitation than GPCP in the study basin.

  14. Analysis of the Nonlinear Trends and Non-Stationary Oscillations of Regional Precipitation in Xinjiang, Northwestern China, Using Ensemble Empirical Mode Decomposition

    OpenAIRE

    Guo, Bin; Chen, Zhongsheng; Guo, Jinyun; Liu, Feng; Chen, Chuanfa; Liu, Kangli

    2016-01-01

    Changes in precipitation could have crucial influences on the regional water resources in arid regions such as Xinjiang. It is necessary to understand the intrinsic multi-scale variations of precipitation in different parts of Xinjiang in the context of climate change. In this study, based on precipitation data from 53 meteorological stations in Xinjiang during 1960–2012, we investigated the intrinsic multi-scale characteristics of precipitation variability using an adaptive method named ense...

  15. Global Precipitation Measurement. Report 1; Summary of the First GPM Partners Planning Workshop

    Science.gov (United States)

    Shepherd, J. Marshall; Mehta, Amita; Smith, Eric A. (Editor); Adams, W. James (Editor)

    2002-01-01

    This report provides a synopsis of the proceedings of the First Global Precipitation Measurement (GPM) Partners Planning Workshop held at the University of Maryland, College Park, from May 16 to 18, 2001. GPM consists of a multi-member global satellite constellation (i.e., an international set of satellite missions) and the accompanying scientific research program, with the main goal of providing frequent, accurate, and globally distributed precipitation measurements essential in understanding several fundamental issues associated with the global water and energy cycle (GWEC). The exchange of scientific and technical information at this and subsequent GPM workshops between representatives from around the world represents a key step in the formulation phase of GPM mission development. The U.S. National Aeronautics and Space Agency (NASA), the National Space Development Agency of Japan (NASDA), and other interested agencies from nations around the world seek to observe, understand, and model the Earth system to learn how it is changing and what consequences these changes have on life, particularly as they pertain to hydrological processes and the availability of fresh water resources. GWEN processes are central to a broader understanding of the Earth system.

  16. Mediterranean hurricanes: large-scale environment and convective and precipitating areas from satellite microwave observations

    Directory of Open Access Journals (Sweden)

    C. Claud

    2010-10-01

    Full Text Available Subsynoptic scale vortices that have been likened to tropical cyclones or polar lows (medicanes are occasionally observed over the Mediterranean Sea. Generated over the sea, they are usually associated with strong winds and heavy precipitation and thus can be highly destructive in islands and costal areas. Only an accurate forecasting of such systems could mitigate these effects. However, at the moment, the predictability of these systems remains limited.

    Due to the scarcity of conventional observations, use is made of NOAA/MetOp satellite observations, for which advantage can be taken of the time coverage differences between the platforms that carry it, to give a very complete temporal description of the disturbances. A combination of AMSU-B (Advanced Microwave Sounding Unit-B/MHS (Microwave Humidity Sounder observations permit to investigate precipitation associated with these systems while coincident AMSU-A (Advanced Microwave Sounding Unit-A observations give insights into the larger synoptic-scale environment in which they occur.

    Three different cases (in terms of intensity, location, trajectory, duration, and periods of the year – May, September and December, respectively were investigated. Throughout these time periods, AMSU-A observations show that the persisting deep outflow of cold air over the sea together with an upper-level trough upstream constituted a favourable environment for the development of medicanes. AMSU-B/MHS based diagnostics show that convection and precipitation areas are large in the early stage of the low, but significantly reduced afterwards. Convection is maximum just after the upper-level trough, located upstream of cold mid-tropospheric air, reached its maximum intensity and acquired a cyclonic orientation.

  17. A satellite observational and numerical study of precipitation characteristics in western North Atlantic tropical cyclones

    Science.gov (United States)

    Rodgers, Edward B.; Chang, Simon W.; Pierce, Harold F.

    1994-01-01

    Special Sensor Microwave/Imager (SSM/I) observations were used to examine the spatial and temporal changes of the precipitation characteristics of tropical cyclones. SSM/I observations were also combined with the results of a tropical cyclone numerical model to examine the role of inner-core diabatic heating in subsequent intensity changes of tropical cyclones. Included in the SSM/I observations were rainfall characteristics of 18 named western North Atlantic tropical cyclones between 1987 and 1989. The SSM/I rain-rate algorithm that employed the 85-GHz channel provided an analysis of the rain-rate distribution in greater detail. However, the SSM/I algorithm underestimated the rain rates when compared to in situ techniques but appeared to be comparable to the rain rates obtained from other satellite-borne passive microwave radiometers. The analysis of SSM/I observations found that more intense systems had higher rain rates, more latent heat release, and a greater contribution from heavier rain to the total tropical cyclone rainfall. In addition, regions with the heaviest rain rates were found near the center of the most intense tropical cyclones. Observational analysis from SSM/I also revealed that the greatest rain rates in the inner-core regions were found in the right half of fast-moving cyclones, while the heaviest rain rates in slow-moving tropical cyclones were found in the forward half. The combination of SSM/I observations and an interpretation of numerical model simulations revealed that the correlation between changes in the inner core diabetic heating and the subsequent intensity became greater as the tropical cyclones became more intense.

  18. Monitoring Powdery Mildew of Winter Wheat by Using Moderate Resolution Multi-Temporal Satellite Imagery

    Science.gov (United States)

    Zhang, Jingcheng; Pu, Ruiliang; Yuan, Lin; Wang, Jihua; Huang, Wenjiang; Yang, Guijun

    2014-01-01

    Powdery mildew is one of the most serious diseases that have a significant impact on the production of winter wheat. As an effective alternative to traditional sampling methods, remote sensing can be a useful tool in disease detection. This study attempted to use multi-temporal moderate resolution satellite-based data of surface reflectances in blue (B), green (G), red (R) and near infrared (NIR) bands from HJ-CCD (CCD sensor on Huanjing satellite) to monitor disease at a regional scale. In a suburban area in Beijing, China, an extensive field campaign for disease intensity survey was conducted at key growth stages of winter wheat in 2010. Meanwhile, corresponding time series of HJ-CCD images were acquired over the study area. In this study, a number of single-stage and multi-stage spectral features, which were sensitive to powdery mildew, were selected by using an independent t-test. With the selected spectral features, four advanced methods: mahalanobis distance, maximum likelihood classifier, partial least square regression and mixture tuned matched filtering were tested and evaluated for their performances in disease mapping. The experimental results showed that all four algorithms could generate disease maps with a generally correct distribution pattern of powdery mildew at the grain filling stage (Zadoks 72). However, by comparing these disease maps with ground survey data (validation samples), all of the four algorithms also produced a variable degree of error in estimating the disease occurrence and severity. Further, we found that the integration of MTMF and PLSR algorithms could result in a significant accuracy improvement of identifying and determining the disease intensity (overall accuracy of 72% increased to 78% and kappa coefficient of 0.49 increased to 0.59). The experimental results also demonstrated that the multi-temporal satellite images have a great potential in crop diseases mapping at a regional scale. PMID:24691435

  19. Retrieval of precipitable water using near infrared channels of Global Imager/Advanced Earth Observing Satellite-II (GLI/ADEOS-II)

    International Nuclear Information System (INIS)

    Kuji, M.; Uchiyama, A.

    2002-01-01

    Retrieval of precipitable water (vertically integrated water vapor amount) is proposed using near infrared channels og Global Imager onboard Advanced Earth Observing Satellite-II (GLI/ADEOS-II). The principle of retrieval algorithm is based upon that adopted with Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Earth Observing System (EOS) satellite series. Simulations were carried out with GLI Signal Simulator (GSS) to calculate the radiance ratio between water vapor absorbing bands and non-absorbing bands. As a result, it is found that for the case of high spectral reflectance background (a bright target) such as the land surface, the calibration curves are sensitive to the precipitable water variation. For the case of low albedo background (a dark target) such as the ocean surface, on the contrary, the calibration curve is not very sensitive to its variation under conditions of the large water vapor amount. It turns out that aerosol loading has little influence on the retrieval over a bright target for the aerosol optical thickness less than about 1.0 at 500nm. It is also anticipated that simultaneous retrieval of the water vapor amount using GLI data along with other channels will lead to improved accuracy of the determination of surface geophysical properties, such as vegetation, ocean color, and snow and ice, through the better atmospheric correction

  20. Multi-Satellite MIMO Communications at Ku-Band and Above: Investigations on Spatial Multiplexing for Capacity Improvement and Selection Diversity for Interference Mitigation

    Directory of Open Access Journals (Sweden)

    Liolis Konstantinos P

    2007-01-01

    Full Text Available This paper investigates the applicability of multiple-input multiple-output (MIMO technology to satellite communications at the Ku-band and above. After introducing the possible diversity sources to form a MIMO matrix channel in a satellite environment, particular emphasis is put on satellite diversity. Two specific different topics from the field of MIMO technology applications to satellite communications at these frequencies are further analyzed: (i capacity improvement achieved by MIMO spatial multiplexing systems and (ii interference mitigation achieved by MIMO diversity systems employing receive antenna selection. In the first case, a single-user capacity analysis of a satellite MIMO spatial multiplexing system is presented and a useful analytical closed form expression is derived for the outage capacity achieved. In the second case, a satellite MIMO diversity system with receive antenna selection is considered, adjacent satellite cochannel interference on its forward link is studied and an analytical model predicting the interference mitigation achieved is presented. In both cases, an appropriate physical MIMO channel model is assumed which takes into account the propagation phenomena related to the frequencies of interest, such as clear line-of-sight operation, high antenna directivity, the effect of rain fading, and the slant path lengths difference. Useful numerical results obtained through the analytical expressions derived are presented to compare the performance of multi-satellite MIMO systems to relevant single-input single-output (SISO ones.

  1. Recent Progress on the Second Generation CMORPH: LEO-IR Based Precipitation Estimates and Cloud Motion Vector

    Science.gov (United States)

    Xie, Pingping; Joyce, Robert; Wu, Shaorong

    2015-04-01

    cloud motion vectors from the GEO/LEO IR based precipitation estimates and the CFS Reanalysis (CFSR) precipitation fields. Motion vectors are first derived separately from the satellite IR based precipitation estimates and the CFSR precipitation fields. These individually derived motion vectors are then combined through a 2D-VAR technique to form an analyzed field of cloud motion vectors over the entire globe. Error function is experimented to best reflect the performance of the satellite IR based estimates and the CFSR in capturing the movements of precipitating cloud systems over different regions and for different seasons. Quantitative experiments are conducted to optimize the LEO IR based precipitation estimation technique and the 2D-VAR based motion vector analysis system. Detailed results will be reported at the EGU.

  2. GPM Mission Gridded Text Products Providing Surface Precipitation Retrievals

    Science.gov (United States)

    Stocker, Erich Franz; Kelley, Owen; Huffman, George; Kummerow, Christian

    2015-04-01

    In February 2015, the Global Precipitation Measurement (GPM) mission core satellite will complete its first year in space. The core satellite carries a conically scanning microwave imager called the GPM Microwave Imager (GMI), which also has 166 GHz and 183 GHz frequency channels. The GPM core satellite also carries a dual frequency radar (DPR) which operates at Ku frequency, similar to the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar), and a new Ka frequency. The precipitation processing system (PPS) is producing swath-based instantaneous precipitation retrievals from GMI, both radars including a dual-frequency product, and a combined GMI/DPR precipitation retrieval. These level 2 products are written in the HDF5 format and have many additional parameters beyond surface precipitation that are organized into appropriate groups. While these retrieval algorithms were developed prior to launch and are not optimal, these algorithms are producing very creditable retrievals. It is appropriate for a wide group of users to have access to the GPM retrievals. However, for reseachers requiring only surface precipitation, these L2 swath products can appear to be very intimidating and they certainly do contain many more variables than the average researcher needs. Some researchers desire only surface retrievals stored in a simple easily accessible format. In response, PPS has begun to produce gridded text based products that contain just the most widely used variables for each instrument (surface rainfall rate, fraction liquid, fraction convective) in a single line for each grid box that contains one or more observations. This paper will describe the gridded data products that are being produced and provide an overview of their content. Currently two types of gridded products are being produced: (1) surface precipitation retrievals from the core satellite instruments - GMI, DPR, and combined GMI/DPR (2) surface precipitation retrievals for the partner

  3. Shoreline change assessment using multi-temporal satellite images: a case study of Lake Sapanca, NW Turkey.

    Science.gov (United States)

    Duru, Umit

    2017-08-01

    The research summarized here determines historical shoreline changes along Lake Sapanca by using Remote Sensing (RS) and Geographical Information Systems (GIS). Six multi-temporal satellite images of Landsat Multispectral Scanner (L1-5 MMS), Enhanced Thematic Mapper Plus (L7 ETM+), and Operational Land Imager Sensors (L8 OLI), covering the period between 17 June 1975 and 15 July 2016, were used to monitor shoreline positions and estimate change rates along the coastal zone. After pre-possessing routines, the Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), and supervised classification techniques were utilized to extract six different shorelines. Digital Shoreline Analysis System (DSAS), a toolbox that enables transect-based computations of shoreline displacement, was used to compute historical shoreline change rates. The average rate of shoreline change for the entire cost was 2.7 m/year of progradation with an uncertainty of 0.2 m/year. While the great part of the lake shoreline remained stable, the study concluded that the easterly and westerly coasts and deltaic coasts are more vulnerable to shoreline displacements over the last four decades. The study also reveals that anthropogenic activities, more specifically over extraction of freshwater from the lake, cyclic variation in rainfall, and deposition of sediment transported by the surrounding creeks dominantly control spatiotemporal shoreline changes in the region. Monitoring shoreline changes using multi-temporal satellite images is a significant component for the coastal decision-making and management.

  4. An Image Matching Algorithm Integrating Global SRTM and Image Segmentation for Multi-Source Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Xiao Ling

    2016-08-01

    Full Text Available This paper presents a novel image matching method for multi-source satellite images, which integrates global Shuttle Radar Topography Mission (SRTM data and image segmentation to achieve robust and numerous correspondences. This method first generates the epipolar lines as a geometric constraint assisted by global SRTM data, after which the seed points are selected and matched. To produce more reliable matching results, a region segmentation-based matching propagation is proposed in this paper, whereby the region segmentations are extracted by image segmentation and are considered to be a spatial constraint. Moreover, a similarity measure integrating Distance, Angle and Normalized Cross-Correlation (DANCC, which considers geometric similarity and radiometric similarity, is introduced to find the optimal correspondences. Experiments using typical satellite images acquired from Resources Satellite-3 (ZY-3, Mapping Satellite-1, SPOT-5 and Google Earth demonstrated that the proposed method is able to produce reliable and accurate matching results.

  5. Global Precipitation Measurement (GPM) Mission Products and Services at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC)

    Science.gov (United States)

    Liu, Zhong; Ostrenga, D.; Vollmer, B.; Deshong, B.; Greene, M.; Teng, W.; Kempler, S. J.

    2015-01-01

    On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http:pmm.nasa.govGPM). The GPM mission consists of an international network of satellites in which a GPM Core Observatory satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data within the NASA Earth Observation System Data Information System (EOSDIS). The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). Over the past 16 years, the GES DISC has served the scientific as well as other communities with TRMM data and user-friendly services. During the GPM era, the GES DISC will continue to provide user-friendly data services and customer support to users around the world. GPM products currently and to-be available include the following: 1. Level-1 GPM Microwave Imager (GMI) and partner radiometer products. 2. Goddard Profiling Algorithm (GPROF) GMI and partner products. 3. Integrated Multi-satellitE Retrievals for GPM (IMERG) products. (early, late, and final)A dedicated Web portal (including user guides, etc.) has been developed for GPM data (http:disc.sci.gsfc.nasa.govgpm). Data services that are currently and to-be available include Google-like Mirador (http:mirador.gsfc.nasa.gov) for data search and access; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion into various formats (e.g., netCDF, HDF, KML (for Google Earth), ASCII); exploration, visualization, and statistical online analysis through Giovanni (http:giovanni.gsfc.nasa.gov); generation of value-added products; parameter and spatial subsetting; time aggregation; regridding; data

  6. Global Precipitation Measurement (GPM) Mission Products and Services at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC)

    Science.gov (United States)

    Ostrenga, D.; Liu, Z.; Vollmer, B.; Teng, W. L.; Kempler, S. J.

    2014-12-01

    On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http://pmm.nasa.gov/GPM). The GPM mission consists of an international network of satellites in which a GPM "Core Observatory" satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data within the NASA Earth Observation System Data Information System (EOSDIS). The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). Over the past 16 years, the GES DISC has served the scientific as well as other communities with TRMM data and user-friendly services. During the GPM era, the GES DISC will continue to provide user-friendly data services and customer support to users around the world. GPM products currently and to-be available include the following: Level-1 GPM Microwave Imager (GMI) and partner radiometer products Goddard Profiling Algorithm (GPROF) GMI and partner products Integrated Multi-satellitE Retrievals for GPM (IMERG) products (early, late, and final) A dedicated Web portal (including user guides, etc.) has been developed for GPM data (http://disc.sci.gsfc.nasa.gov/gpm). Data services that are currently and to-be available include Google-like Mirador (http://mirador.gsfc.nasa.gov/) for data search and access; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion into various formats (e.g., netCDF, HDF, KML (for Google Earth), ASCII); exploration, visualization, and statistical online analysis through Giovanni (http://giovanni.gsfc.nasa.gov); generation of value-added products; parameter and spatial subsetting; time aggregation; regridding

  7. Upper Blue Nile basin water budget from a multi-model perspective

    Science.gov (United States)

    Jung, Hahn Chul; Getirana, Augusto; Policelli, Frederick; McNally, Amy; Arsenault, Kristi R.; Kumar, Sujay; Tadesse, Tsegaye; Peters-Lidard, Christa D.

    2017-12-01

    Improved understanding of the water balance in the Blue Nile is of critical importance because of increasingly frequent hydroclimatic extremes under a changing climate. The intercomparison and evaluation of multiple land surface models (LSMs) associated with different meteorological forcing and precipitation datasets can offer a moderate range of water budget variable estimates. In this context, two LSMs, Noah version 3.3 (Noah3.3) and Catchment LSM version Fortuna 2.5 (CLSMF2.5) coupled with the Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme are used to produce hydrological estimates over the region. The two LSMs were forced with different combinations of two reanalysis-based meteorological datasets from the Modern-Era Retrospective analysis for Research and Applications datasets (i.e., MERRA-Land and MERRA-2) and three observation-based precipitation datasets, generating a total of 16 experiments. Modeled evapotranspiration (ET), streamflow, and terrestrial water storage estimates were evaluated against the Atmosphere-Land Exchange Inverse (ALEXI) ET, in-situ streamflow observations, and NASA Gravity Recovery and Climate Experiment (GRACE) products, respectively. Results show that CLSMF2.5 provided better representation of the water budget variables than Noah3.3 in terms of Nash-Sutcliffe coefficient when considering all meteorological forcing datasets and precipitation datasets. The model experiments forced with observation-based products, the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA), outperform those run with MERRA-Land and MERRA-2 precipitation. The results presented in this paper would suggest that the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System incorporate CLSMF2.5 and HyMAP routing scheme to better represent the water balance in this region.

  8. Investigation of precipitation and hardening response of maraging stainless steels 17-4 and 13-8+Mo during multi-pass welding

    Science.gov (United States)

    Hamlin, Robert J.

    Martensitic precipitation strengthened stainless steels 17-4 and 13-8+Mo are candidate alloys for high strength military applications. These applications will require joining by fusion welding processes thus, it is necessary to develop an understanding of microstructural and mechanical property changes that occur during welding. Previous investigations on these materials have demonstrated that significant softening occurs in the heat affected zone (HAZ) during welding, due to dissolution of the strengthen precipitates. It was also observed that post weld heat treatments (PWHT's) were required to restore the properties. However, PWHT's are expensive and cannot be applied when welding on a large scale or making a repair in the field. Thus, the purpose of the current work is to gain a fundamental understanding of the precipitation kinetics in these systems so that optimized welding procedures can be developed that do not require a PWHT. Multi-pass welding provides an opportunity to restore the strengthening precipitates that dissolve during primary weld passes using the heat from secondary weld passes. Thus, a preliminary investigation was performed to determine whether the times and temperatures associated with welding thermal cycles were sufficient to restore the strength in these systems. A Gleeble thermo-mechanical simulator was used to perform multi-pass welding simulations on samples of each material using a 1000 J/mm and 2000 J/mm heat input. Additionally, base metal and weld metal samples were used as starting conditions to evaluate the difference in precipitation response between each. Hardness measurements were used to estimate the extent of precipitate dissolution and growth. Microstructures were characterized using light optical microscopy (LOM), scanning electron microscopy (SEM), and energy dispersive spectrometry (EDS). It was determined that precipitate dissolution occurred during primary welding thermal cycles and that significant hardening could be

  9. Multi-satellites normalization of the FengYun-2s visible detectors by the MVP method

    Science.gov (United States)

    Li, Yuan; Rong, Zhi-guo; Zhang, Li-jun; Sun, Ling; Xu, Na

    2013-08-01

    After January 13, 2012, FY-2F had successfully launched, the total number of the in orbit operating FengYun-2 geostationary meteorological satellites reached three. For accurate and efficient application of multi-satellite observation data, the study of the multi-satellites normalization of the visible detector was urgent. The method required to be non-rely on the in orbit calibration. So as to validate the calibration results before and after the launch; calculate day updating surface bidirectional reflectance distribution function (BRDF); at the same time track the long-term decay phenomenon of the detector's linearity and responsivity. By research of the typical BRDF model, the normalization method was designed. Which could effectively solute the interference of surface directional reflectance characteristics, non-rely on visible detector in orbit calibration. That was the Median Vertical Plane (MVP) method. The MVP method was based on the symmetry of principal plane, which were the directional reflective properties of the general surface targets. Two geostationary satellites were taken as the endpoint of a segment, targets on the intersecting line of the segment's MVP and the earth surface could be used as a normalization reference target (NRT). Observation on the NRT by two satellites at the moment the sun passing through the MVP brought the same observation zenith, solar zenith, and opposite relative direction angle. At that time, the linear regression coefficients of the satellite output data were the required normalization coefficients. The normalization coefficients between FY-2D, FY-2E and FY-2F were calculated, and the self-test method of the normalized results was designed and realized. The results showed the differences of the responsivity between satellites could up to 10.1%(FY-2E to FY-2F); the differences of the output reflectance calculated by the broadcast calibration look-up table could up to 21.1%(FY-2D to FY-2F); the differences of the output

  10. Early drought detection by spectral analysis of satellite time series of precipitation and Normalized Difference Vegetation Index (NDVI)

    NARCIS (Netherlands)

    Van Hoek, Mattijn; Jia, Li; Zhou, J.; Zheng, Chaolei; Menenti, M.

    2016-01-01

    The time lag between anomalies in precipitation and vegetation activity plays a critical role in early drought detection as agricultural droughts are caused by precipitation shortages. The aim of this study is to explore a new approach to estimate the time lag between a forcing (precipitation)

  11. Geophysical analysis of coherent satellite scintillation data

    Science.gov (United States)

    Fremouw, E. J.; Lansinger, J. M.; Miller, D. A.

    1981-11-01

    In May of 1976, Air Force Satellite P76-5 was launched with the Defense Nuclear Agency's Wideband beacon, DNA-002, as its sole payload. Several researchers have employed the resulting data in studies of ionospheric structure and its effect on transionospheric radio communications. In the present work, recordings of amplitude and phase scintillation imposed on Wideband's VHF and UHF signals by the ionosphere have been used to study medium-scale structures in the auroral-zone F layer. Results include quantitative identification of a very close relationship between scintillation and solar/geomagnetic activity, together with lack of a seasonal variation in scintillation activity in the Alaskan sector. A surprisingly high correlation (90%) was found between monthly means of phase-scintillation index, on the one hand, and sunspot number and 10-cm solar radio flux, on the other. The high-latitude scintillation boundary was found to be very similar to the soft-electron precipitation boundary, including similarity in expansion rates with increasing magnetic activity. Interestingly, it is systematically shifted poleward of the precipitation boundary on the day side of the earth and equatorward on the night side. Taken together, the results of this research disclose a rather direct relationship between scintillation and soft-electron precipitation, with plasma convection likely playing an important role in generation of the scintillation-producing irregularities.

  12. Analysis of the Nonlinear Trends and Non-Stationary Oscillations of Regional Precipitation in Xinjiang, Northwestern China, Using Ensemble Empirical Mode Decomposition

    Directory of Open Access Journals (Sweden)

    Bin Guo

    2016-03-01

    Full Text Available Changes in precipitation could have crucial influences on the regional water resources in arid regions such as Xinjiang. It is necessary to understand the intrinsic multi-scale variations of precipitation in different parts of Xinjiang in the context of climate change. In this study, based on precipitation data from 53 meteorological stations in Xinjiang during 1960–2012, we investigated the intrinsic multi-scale characteristics of precipitation variability using an adaptive method named ensemble empirical mode decomposition (EEMD. Obvious non-linear upward trends in precipitation were found in the north, south, east and the entire Xinjiang. Changes in precipitation in Xinjiang exhibited significant inter-annual scale (quasi-2 and quasi-6 years and inter-decadal scale (quasi-12 and quasi-23 years. Moreover, the 2–3-year quasi-periodic fluctuation was dominant in regional precipitation and the inter-annual variation had a considerable effect on the regional-scale precipitation variation in Xinjiang. We also found that there were distinctive spatial differences in variation trends and turning points of precipitation in Xinjiang. The results of this study indicated that compared to traditional decomposition methods, the EEMD method, without using any a priori determined basis functions, could effectively extract the reliable multi-scale fluctuations and reveal the intrinsic oscillation properties of climate elements.

  13. Analysis of the Nonlinear Trends and Non-Stationary Oscillations of Regional Precipitation in Xinjiang, Northwestern China, Using Ensemble Empirical Mode Decomposition.

    Science.gov (United States)

    Guo, Bin; Chen, Zhongsheng; Guo, Jinyun; Liu, Feng; Chen, Chuanfa; Liu, Kangli

    2016-03-21

    Changes in precipitation could have crucial influences on the regional water resources in arid regions such as Xinjiang. It is necessary to understand the intrinsic multi-scale variations of precipitation in different parts of Xinjiang in the context of climate change. In this study, based on precipitation data from 53 meteorological stations in Xinjiang during 1960-2012, we investigated the intrinsic multi-scale characteristics of precipitation variability using an adaptive method named ensemble empirical mode decomposition (EEMD). Obvious non-linear upward trends in precipitation were found in the north, south, east and the entire Xinjiang. Changes in precipitation in Xinjiang exhibited significant inter-annual scale (quasi-2 and quasi-6 years) and inter-decadal scale (quasi-12 and quasi-23 years). Moreover, the 2-3-year quasi-periodic fluctuation was dominant in regional precipitation and the inter-annual variation had a considerable effect on the regional-scale precipitation variation in Xinjiang. We also found that there were distinctive spatial differences in variation trends and turning points of precipitation in Xinjiang. The results of this study indicated that compared to traditional decomposition methods, the EEMD method, without using any a priori determined basis functions, could effectively extract the reliable multi-scale fluctuations and reveal the intrinsic oscillation properties of climate elements.

  14. First Evaluation of the Climatological Calibration Algorithm in the Real-time TMPA Precipitation Estimates over Two Basins at High and Low Latitudes

    Science.gov (United States)

    Yong, Bin; Ren, Liliang; Hong, Yang; Gourley, Jonathan; Tian, Yudong; Huffman, George J.; Chen, Xi; Wang, Weiguang; Wen, Yixin

    2013-01-01

    The TRMM Multi-satellite Precipitation Analysis (TMPA) system underwent a crucial upgrade in early 2009 to include a climatological calibration algorithm (CCA) to its realtime product 3B42RT, and this algorithm will continue to be applied in the future Global Precipitation Measurement era constellation precipitation products. In this study, efforts are focused on the comparison and validation of the Version 6 3B42RT estimates before and after the climatological calibration is applied. The evaluation is accomplished using independent rain gauge networks located within the high-latitude Laohahe basin and the low-latitude Mishui basin, both in China. The analyses indicate the CCA can effectively reduce the systematic errors over the low-latitude Mishui basin but misrepresent the intensity distribution pattern of medium-high rain rates. This behavior could adversely affect TMPA's hydrological applications, especially for extreme events (e.g., floods and landslides). Results also show that the CCA tends to perform slightly worse, in particular, during summer and winter, over the high-latitude Laohahe basin. This is possibly due to the simplified calibration-processing scheme in the CCA that directly applies the climatological calibrators developed within 40 degrees latitude to the latitude belts of 40 degrees N-50 degrees N. Caution should therefore be exercised when using the calibrated 3B42RT for heavy rainfall-related flood forecasting (or landslide warning) over high-latitude regions, as the employment of the smooth-fill scheme in the CCA bias correction could homogenize the varying rainstorm characteristics. Finally, this study highlights that accurate detection and estimation of snow at high latitudes is still a challenging task for the future development of satellite precipitation retrievals.

  15. Quad-Tree Visual-Calculus Analysis of Satellite Coverage

    Science.gov (United States)

    Lo, Martin W.; Hockney, George; Kwan, Bruce

    2003-01-01

    An improved method of analysis of coverage of areas of the Earth by a constellation of radio-communication or scientific-observation satellites has been developed. This method is intended to supplant an older method in which the global-coverage-analysis problem is solved from a ground-to-satellite perspective. The present method provides for rapid and efficient analysis. This method is derived from a satellite-to-ground perspective and involves a unique combination of two techniques for multiresolution representation of map features on the surface of a sphere.

  16. Diurnal variations of summertime precipitation over the Tibetan Plateau in relation to orographically-induced regional circulations

    International Nuclear Information System (INIS)

    Liu Xiaodong; Bai Aijuan; Liu Changhai

    2009-01-01

    The diurnal patterns of variation of summertime precipitation over the Tibetan Plateau were first investigated using the TRMM multi-satellite precipitation analysis product for five summer seasons (i.e. June to August for 2002-2006). Both hourly precipitation amount and precipitation frequency exhibit pronounced daily variability with an overall late-afternoon-evening maximum and a dominant morning minimum. A notable exception is the prevalent nocturnal maximum around the periphery of the Plateau. In terms of the normalized harmonic amplitude, the diurnal signal shows significant regional contrast with the strongest manifestation over the central Plateau and the weakest near the periphery. This remarkable spatial dependence in daily rainfall cycles is clear evidence of orographic and heterogeneous land-surface impacts on convective development. Using six-hourly NCEP FNL data, we then examined the diurnal variability in the atmospheric circulation and thermodynamics in this region. The results show that the Plateau heats (cools) the overlying atmosphere during the day (night) more than the surrounding areas, and as a consequence a relatively stronger confluent circulation in this region occurs during the day than during the night, consistent with the diurnal rainfall cycles. Moreover, the regions with large low-level convergence and upper-level divergence correspond to the strong diurnal rainfall variations. The reversed daily alterations of convergence-divergence patterns in the vicinity of the Plateau edges are in agreement with the observed nighttime rainfall peak therein. This study further demonstrates the importance of the Tibetan Plateau in regulating regional circulation and precipitation.

  17. Evaluation of Uncertainty in Precipitation Datasets for New Mexico, USA

    Science.gov (United States)

    Besha, A. A.; Steele, C. M.; Fernald, A.

    2014-12-01

    Climate change, population growth and other factors are endangering water availability and sustainability in semiarid/arid areas particularly in the southwestern United States. Wide coverage of spatial and temporal measurements of precipitation are key for regional water budget analysis and hydrological operations which themselves are valuable tool for water resource planning and management. Rain gauge measurements are usually reliable and accurate at a point. They measure rainfall continuously, but spatial sampling is limited. Ground based radar and satellite remotely sensed precipitation have wide spatial and temporal coverage. However, these measurements are indirect and subject to errors because of equipment, meteorological variability, the heterogeneity of the land surface itself and lack of regular recording. This study seeks to understand precipitation uncertainty and in doing so, lessen uncertainty propagation into hydrological applications and operations. We reviewed, compared and evaluated the TRMM (Tropical Rainfall Measuring Mission) precipitation products, NOAA's (National Oceanic and Atmospheric Administration) Global Precipitation Climatology Centre (GPCC) monthly precipitation dataset, PRISM (Parameter elevation Regression on Independent Slopes Model) data and data from individual climate stations including Cooperative Observer Program (COOP), Remote Automated Weather Stations (RAWS), Soil Climate Analysis Network (SCAN) and Snowpack Telemetry (SNOTEL) stations. Though not yet finalized, this study finds that the uncertainty within precipitation estimates datasets is influenced by regional topography, season, climate and precipitation rate. Ongoing work aims to further evaluate precipitation datasets based on the relative influence of these phenomena so that we can identify the optimum datasets for input to statewide water budget analysis.

  18. Analysis of dual polarization images of precipitating clouds collected by the COSMO SkyMed constellation

    Science.gov (United States)

    Baldini, Luca; Roberto, Nicoletta; Gorgucci, Eugenio; Fritz, Jason; Chandrasekar, V.

    2014-07-01

    Currently, several satellite missions are employing X-band synthetic aperture radars (SAR) with polarimetric capabilities. In images collected over land by X-band SAR, precipitation results mainly in evident attenuation of the surface returns. Effects of precipitation in polarimetric SAR images and how to exploit them for precipitation studies are emerging topics of interest. This paper investigates polarimetric signatures of precipitation in images collected by the X-band SARs of the Italian Space Agency COSMO SkyMed constellation using the HH-VV alternate polarimetric mode. Analyzed images were collected in 2010 when the constellation was composed of three satellites and operated in the “tandem like” interferometric configuration, which allowed acquisition of the same scene with the same viewing geometry and a minimum decorrelation time of one day. Observations collected in Piedmont (Italy) and Tampa Bay (Florida, US) have been analyzed along with coincident observations collected by operational weather radars, used to reconstruct the component of SAR returns due to precipitation at horizontal and vertical polarization states. Different techniques are used depending on the different characteristics of terrestrial radars. SAR observations reconstructed from terrestrial measurements are in fairly good agreement with actual SAR observations. Results confirm that the attenuation signature in SAR images collected over land is particularly pronounced in the presence of precipitation cells and can be related to the radar reflectivity integrated along the same path. The difference between copolar HH and VV power measurements reveals a differential attenuation due to anisotropy of precipitation, whose range is limited when the SAR incidence angle is low. A specific feature observed in the CosmoSkyMed alternate polarization implementation is the presence of the scalloping effect, a periodic effect along the azimuth direction that cannot always be removed by standard de

  19. Development of Radar-Satellite Blended QPF (Quantitative Precipitation Forecast) Technique for heavy rainfall

    Science.gov (United States)

    Jang, Sangmin; Yoon, Sunkwon; Rhee, Jinyoung; Park, Kyungwon

    2016-04-01

    Due to the recent extreme weather and climate change, a frequency and size of localized heavy rainfall increases and it may bring various hazards including sediment-related disasters, flooding and inundation. To prevent and mitigate damage from such disasters, very short range forecasting and nowcasting of precipitation amounts are very important. Weather radar data very useful in monitoring and forecasting because weather radar has high resolution in spatial and temporal. Generally, extrapolation based on the motion vector is the best method of precipitation forecasting using radar rainfall data for a time frame within a few hours from the present. However, there is a need for improvement due to the radar rainfall being less accurate than rain-gauge on surface. To improve the radar rainfall and to take advantage of the COMS (Communication, Ocean and Meteorological Satellite) data, a technique to blend the different data types for very short range forecasting purposes was developed in the present study. The motion vector of precipitation systems are estimated using 1.5km CAPPI (Constant Altitude Plan Position Indicator) reflectivity by pattern matching method, which indicates the systems' direction and speed of movement and blended radar-COMS rain field is used for initial data. Since the original horizontal resolution of COMS is 4 km while that of radar is about 1 km, spatial downscaling technique is used to downscale the COMS data from 4 to 1 km pixels in order to match with the radar data. The accuracies of rainfall forecasting data were verified utilizing AWS (Automatic Weather System) observed data for an extreme rainfall occurred in the southern part of Korean Peninsula on 25 August 2014. The results of this study will be used as input data for an urban stream real-time flood early warning system and a prediction model of landslide. Acknowledgement This research was supported by a grant (13SCIPS04) from Smart Civil Infrastructure Research Program funded by

  20. Evaluation of CMIP5 continental precipitation simulations relative to satellite-based gauge-adjusted observations

    Science.gov (United States)

    Mehran, A.; AghaKouchak, A.; Phillips, T. J.

    2014-02-01

    The objective of this study is to cross-validate 34 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of precipitation against the Global Precipitation Climatology Project (GPCP) data, quantifying model pattern discrepancies, and biases for both entire distributions and their upper tails. The results of the volumetric hit index (VHI) analysis of the total monthly precipitation amounts show that most CMIP5 simulations are in good agreement with GPCP patterns in many areas but that their replication of observed precipitation over arid regions and certain subcontinental regions (e.g., northern Eurasia, eastern Russia, and central Australia) is problematical. Overall, the VHI of the multimodel ensemble mean and median also are superior to that of the individual CMIP5 models. However, at high quantiles of reference data (75th and 90th percentiles), all climate models display low skill in simulating precipitation, except over North America, the Amazon, and Central Africa. Analyses of total bias (B) in CMIP5 simulations reveal that most models overestimate precipitation over regions of complex topography (e.g., western North and South America and southern Africa and Asia), while underestimating it over arid regions. Also, while most climate model simulations show low biases over Europe, intermodel variations in bias over Australia and Amazonia are considerable. The quantile bias analyses indicate that CMIP5 simulations are even more biased at high quantiles of precipitation. It is found that a simple mean field bias removal improves the overall B and VHI values but does not make a significant improvement at high quantiles of precipitation.

  1. Research on the new type of multi-functional satellite system for space debris detection

    Science.gov (United States)

    Guo, Linghua; Fu, Qiang; Jiang, Huilin; Xu, Xihe

    2017-05-01

    With the rapid development of space exploration and utilization, orbital debris increases dramatically, leading to great threat to human space activities and spacecraft security. In this paper, a new type of multi-functional space debris satellite system (MSDS) was put forward, which shared main optical system, and possessed functions of multidimensional information detection, polarized remote sensing and high rate transmission. The MSDS system can meet the requirements of detection and identification for the small orbital debris which is 1000km faraway, as well as the requirements of the data transmission by 50 Mbps to 2.5 Gbps@200-1000 km. At the same time, by the method of satellite orbital maneuver and attitude adjusting, the orbital debris information that is real-time, complex and refined, allweather can be acquired and transmitted by the new system. Such new type of multifunctional satellite system can provide important and effective technology for international orbital debris detection.

  2. Precipitation from the GPM Microwave Imager and Constellation Radiometers

    Science.gov (United States)

    Kummerow, Christian; Randel, David; Kirstetter, Pierre-Emmanuel; Kulie, Mark; Wang, Nai-Yu

    2014-05-01

    Satellite precipitation retrievals from microwave sensors are fundamentally underconstrained requiring either implicit or explicit a-priori information to constrain solutions. The radiometer algorithm designed for the GPM core and constellation satellites makes this a-priori information explicit in the form of a database of possible rain structures from the GPM core satellite and a Bayesian retrieval scheme. The a-priori database will eventually come from the GPM core satellite's combined radar/radiometer retrieval algorithm. That product is physically constrained to ensure radiometric consistency between the radars and radiometers and is thus ideally suited to create the a-priori databases for all radiometers in the GPM constellation. Until a robust product exists, however, the a-priori databases are being generated from the combination of existing sources over land and oceans. Over oceans, the Day-1 GPM radiometer algorithm uses the TRMM PR/TMI physically derived hydrometer profiles that are available from the tropics through sea surface temperatures of approximately 285K. For colder sea surface temperatures, the existing profiles are used with lower hydrometeor layers removed to correspond to colder conditions. While not ideal, the results appear to be reasonable placeholders until the full GPM database can be constructed. It is more difficult to construct physically consistent profiles over land due to ambiguities in surface emissivities as well as details of the ice scattering that dominates brightness temperature signatures over land. Over land, the a-priori databases have therefore been constructed by matching satellite overpasses to surface radar data derived from the WSR-88 network over the continental United States through the National Mosaic and Multi-Sensor QPE (NMQ) initiative. Databases are generated as a function of land type (4 categories of increasing vegetation cover as well as 4 categories of increasing snow depth), land surface temperature and

  3. Controlling the number of walls in multi walled carbon nanotubes/alumina hybrid compound via ball milling of precipitate catalyst

    Energy Technology Data Exchange (ETDEWEB)

    Nosbi, Norlin [School of Materials and Mineral Resources Engineering, Engineering Campus, Universiti Sains Malaysia (USM), 14300 Nibong Tebal, Seberang Perai Selatan, Pulau Pinang (Malaysia); Akil, Hazizan Md, E-mail: hazizan@usm.my [School of Materials and Mineral Resources Engineering, Engineering Campus, Universiti Sains Malaysia (USM), 14300 Nibong Tebal, Seberang Perai Selatan, Pulau Pinang (Malaysia); Cluster for Polymer Composite (CPC), Science and Engineering Research Centre, Engineering Campus, Universiti Sains Malaysia (USM), 14300 Nibong Tebal, Seberang Perai Selatan, Pulau Pinang (Malaysia)

    2015-06-15

    Graphical abstract: - Highlights: • We report that, to manipulate carbon nanotubes geometry and number of walls are by controlling the precipitate catalyst size. • Number of walls and geometry effects depend on the milling time of the precipitate catalyst. • Increasing milling of time will decrease the carbon nanotubes number of walls. • Increasing milling of time will increase the carbon nanotubes thermal conductivity. - Abstract: This paper reports the influence of milling time on the structure and properties of the precipitate catalyst of multi walled carbon nanotubes (MWCNT)/alumina hybrid compound, produced through the chemical vapour deposition (CVD) process. For this purpose, light green precipitate consisted of aluminium, nickel(II) nitrate hexahydrate and sodium hydroxide mixture was placed in a planetary mill equipped with alumina vials using alumina balls at 300 rpm rotation speed for various milling time (5–15 h) prior to calcinations and CVD process. The compound was characterized using various techniques. Based on high-resolution transmission electron microscopy analysis, increasing the milling time up to 15 h decreased the diameter of MWCNT from 32.3 to 13.1 nm. It was noticed that the milling time had a significant effect on MWCNT wall thickness, whereby increasing the milling time from 0 to 15 h reduced the number of walls from 29 to 12. It was also interesting to note that the carbon content increased from 23.29 wt.% to 36.37 wt.% with increasing milling time.

  4. Merging bottom-up and top-down precipitation products using a stochastic error model

    Science.gov (United States)

    Maggioni, Viviana; Massari, Christian; Brocca, Luca; Ciabatta, Luca

    2017-04-01

    Accurate quantitative precipitation estimation is of great importance for water resources management, agricultural planning, and forecasting and monitoring of natural hazards such as flash floods and landslides. In situ observations are limited around the Earth, especially in remote areas (e.g., complex terrain, dense vegetation), but currently available satellite precipitation products are able to provide global precipitation estimates with an accuracy that depends upon many factors (e.g., type of storms, temporal sampling, season etc…). Recently, Brocca et al. (2014) have proposed an alternative approach (i.e., SM2RAIN) that allows to estimate rainfall from space by using satellite soil moisture observations. In contrast with classical satellite precipitation products which sense the cloud properties to retrieve the instantaneous precipitation, this new bottom-up approach makes use of two consecutive soil moisture measurements for obtaining an estimate of the fallen precipitation within the interval between two satellite passes. As a result, the nature of the measurement is different and complementary to the one of classical precipitation products and could provide a different valid perspective to improve current satellite rainfall estimates via appropriate integration between the products (i.e., SM2RAIN plus a classical satellite rainfall product). However, whether SM2RAIN is able or not to improve the performance of any state-of-the-art satellite rainfall product is much dependent upon an adequate quantification and characterization of the relative errors of the products. In this study, the stochastic rainfall error model SREM2D (Hossain et al. 2006) is used for characterizing the retrieval error of both SM2RAIN and a state-of-the-art satellite precipitation product (i.e., 3B42RT). The error characterization serves for an optimal integration between SM2RAIN and 3B42RT for enhancing the capability of the resulting integrated product (i.e. SM2RAIN+3B42RT) in

  5. A Prognostic Methodology for Precipitation Phase Detection using GPM Microwave Observations —With Focus on Snow Cover

    Science.gov (United States)

    Takbiri, Z.; Ebtehaj, A.; Foufoula-Georgiou, E.; Kirstetter, P.

    2017-12-01

    Improving satellite retrieval of precipitation requires increased understanding of its passive microwave signature over different land surfaces. Passive microwave signals over snow-covered surfaces are notoriously difficult to interpret because they record both emission from the land below and absorption/scattering from the liquid/ice crystals. Using data from the Global Precipitation Measurement (GPM) core satellite, we demonstrate that the microwave brightness temperatures of rain and snowfall shifts from a scattering to an emission regime from summer to winter, due to expansion of the less emissive snow cover underneath. We present evidence that the combination of low- (10-19 GHz) and high-frequency (89-166 GHz) channels provides the maximum amount of information for snowfall detection. The study also examines a prognostic nearest neighbor matching method for the detection of precipitation and its phase from passive microwave observations using GPM data. The nearest neighbor uses the weighted Euclidean distance metric to search through an a priori database that is populated with coincident GPM radiometer and radar data as well as ancillary snow cover fraction. The results demonstrate prognostic capabilities of the proposed method in detection of terrestrial snowfall. At the global scale, the average probability of hit and false alarm reaches to 0.80 and remains below 0.10, respectively. Surprisingly, the results show that the snow cover may help to better detect precipitation as the detection rate of terrestrial precipitation is increased from 0.75 (no snow cover) to 0.84 (snow-covered surfaces). For solid precipitation, this increased rate of detection is larger than its liquid counterpart by almost 8%. The main reasons are found to be related to the multi-frequency capabilities of the nearest neighbor matching that can properly isolate the atmospheric signal from the background emission and the fact that the precipitation can exhibit an emission-like (warmer

  6. Hydroclimatology of Lake Victoria region using hydrologic model and satellite remote sensing data

    Directory of Open Access Journals (Sweden)

    S. I. Khan

    2011-01-01

    Full Text Available Study of hydro-climatology at a range of temporal scales is important in understanding and ultimately mitigating the potential severe impacts of hydrological extreme events such as floods and droughts. Using daily in-situ data over the last two decades combined with the recently available multiple-years satellite remote sensing data, we analyzed and simulated, with a distributed hydrologic model, the hydro-climatology in Nzoia, one of the major contributing sub-basins of Lake Victoria in the East African highlands. The basin, with a semi arid climate, has no sustained base flow contribution to Lake Victoria. The short spell of high discharge showed that rain is the prime cause of floods in the basin. There is only a marginal increase in annual mean discharge over the last 21 years. The 2-, 5- and 10- year peak discharges, for the entire study period showed that more years since the mid 1990's have had high peak discharges despite having relatively less annual rain. The study also presents the hydrologic model calibration and validation results over the Nzoia basin. The spatiotemporal variability of the water cycle components were quantified using a hydrologic model, with in-situ and multi-satellite remote sensing datasets. The model is calibrated using daily observed discharge data for the period between 1985 and 1999, for which model performance is estimated with a Nash Sutcliffe Efficiency (NSCE of 0.87 and 0.23% bias. The model validation showed an error metrics with NSCE of 0.65 and 1.04% bias. Moreover, the hydrologic capability of satellite precipitation (TRMM-3B42 V6 is evaluated. In terms of reconstruction of the water cycle components the spatial distribution and time series of modeling results for precipitation and runoff showed considerable agreement with the monthly model runoff estimates and gauge observations. Runoff values responded to precipitation events that occurred across the catchment during the wet season from March to

  7. Computer-Aided Communication Satellite System Analysis and Optimization.

    Science.gov (United States)

    Stagl, Thomas W.; And Others

    Various published computer programs for fixed/broadcast communication satellite system synthesis and optimization are discussed. The rationale for selecting General Dynamics/Convair's Satellite Telecommunication Analysis and Modeling Program (STAMP) in modified form to aid in the system costing and sensitivity analysis work in the Program on…

  8. Passive Microwave Precipitation Retrieval Uncertainty Characterized based on Field Campaign Data over Complex Terrain

    Science.gov (United States)

    Derin, Y.; Anagnostou, E. N.; Anagnostou, M.; Kalogiros, J. A.; Casella, D.; Marra, A. C.; Panegrossi, G.; Sanò, P.

    2017-12-01

    Difficulties in representation of high rainfall variability over mountainous areas using ground based sensors make satellite remote sensing techniques attractive for hydrologic studies over these regions. Even though satellite-based rainfall measurements are quasi global and available at high spatial resolution, these products have uncertainties that necessitate use of error characterization and correction procedures based upon more accurate in situ rainfall measurements. Such measurements can be obtained from field campaigns facilitated by research quality sensors such as locally deployed weather radar and in situ weather stations. This study uses such high quality and resolution rainfall estimates derived from dual-polarization X-band radar (XPOL) observations from three field experiments in Mid-Atlantic US East Coast (NASA IPHEX experiment), the Olympic Peninsula of Washington State (NASA OLYMPEX experiment), and the Mediterranean to characterize the error characteristics of multiple passive microwave (PMW) sensor retrievals. The study first conducts an independent error analysis of the XPOL radar reference rainfall fields against in situ rain gauges and disdrometer observations available by the field experiments. Then the study evaluates different PMW precipitation products using the XPOL datasets (GR) over the three aforementioned complex terrain study areas. We extracted matchups of PMW/GR rainfall based on a matching methodology that identifies GR volume scans coincident with PMW field-of-view sampling volumes, and scaled GR parameters to the satellite products' nominal spatial resolution. The following PMW precipitation retrieval algorithms are evaluated: the NASA Goddard PROFiling algorithm (GPROF), standard and climatology-based products (V 3, 4 and 5) from four PMW sensors (SSMIS, MHS, GMI, and AMSR2), and the precipitation products based on the algorithms Cloud Dynamics and Radiation Database (CDRD) for SSMIS and Passive microwave Neural network

  9. Cloud-radiation-precipitation associations over the Asian monsoon region: an observational analysis

    Science.gov (United States)

    Li, Jiandong; Wang, Wei-Chyung; Dong, Xiquan; Mao, Jiangyu

    2017-11-01

    This study uses 2001-2014 satellite observations and reanalyses to investigate the seasonal characteristics of Cloud Radiative Effects (CREs) and their associations with cloud fraction (CF) and precipitation over the Asian monsoon region (AMR) covering Eastern China (EC) and South Asia (SA). The CREs exhibit strong seasonal variations but show distinctly different relationships with CFs and precipitation over the two regions. For EC, the CREs is dominated by shortwave (SW) cooling, with an annual mean value of - 40 W m- 2 for net CRE, and peak in summer while the presence of extensive and opaque low-level clouds contributes to large Top-Of-Atmosphere (TOA) albedo (>0.5) in winter. For SA, a weak net CRE exists throughout the year due to in-phase compensation of SWCRE by longwave (LW) CRE associated with the frequent occurrence of high clouds. For the entire AMR, SWCRE strongly correlates with the dominant types of CFs, although the cloud vertical structure plays important role particularly in summer. The relationships between CREs and precipitation are stronger in SA than in EC, indicating the dominant effect of monsoon circulation in the former region. SWCRE over EC is only partly related to precipitation and shows distinctive regional variations. Further studies need to pay more attention to vertical distributions of cloud micro- and macro-physical properties, and associated precipitation systems over the AMR.

  10. Physical retrieval of precipitation water contents from Special Sensor Microwave/Imager (SSM/I) data. Part 1: A cloud ensemble/radiative parameterization for sensor response (report version)

    Science.gov (United States)

    Olson, William S.; Raymond, William H.

    1990-01-01

    The physical retrieval of geophysical parameters based upon remotely sensed data requires a sensor response model which relates the upwelling radiances that the sensor observes to the parameters to be retrieved. In the retrieval of precipitation water contents from satellite passive microwave observations, the sensor response model has two basic components. First, a description of the radiative transfer of microwaves through a precipitating atmosphere must be considered, because it is necessary to establish the physical relationship between precipitation water content and upwelling microwave brightness temperature. Also the spatial response of the satellite microwave sensor (or antenna pattern) must be included in the description of sensor response, since precipitation and the associated brightness temperature field can vary over a typical microwave sensor resolution footprint. A 'population' of convective cells, as well as stratiform clouds, are simulated using a computationally-efficient multi-cylinder cloud model. Ensembles of clouds selected at random from the population, distributed over a 25 km x 25 km model domain, serve as the basis for radiative transfer calculations of upwelling brightness temperatures at the SSM/I frequencies. Sensor spatial response is treated explicitly by convolving the upwelling brightness temperature by the domain-integrated SSM/I antenna patterns. The sensor response model is utilized in precipitation water content retrievals.

  11. Network Configuration Analysis for Formation Flying Satellites

    Science.gov (United States)

    Knoblock, Eric J.; Wallett, Thomas M.; Konangi, Vijay K.; Bhasin, Kul B.

    2001-01-01

    The performance of two networks to support autonomous multi-spacecraft formation flying systems is presented. Both systems are comprised of a ten-satellite formation, with one of the satellites designated as the central or 'mother ship.' All data is routed through the mother ship to the terrestrial network. The first system uses a TCP/EP over ATM protocol architecture within the formation, and the second system uses the IEEE 802.11 protocol architecture within the formation. The simulations consist of file transfers using either the File Transfer Protocol (FTP) or the Simple Automatic File Exchange (SAFE) Protocol. The results compare the IP queuing delay, IP queue size and IP processing delay at the mother ship as well as end-to-end delay for both systems. In all cases, using IEEE 802.11 within the formation yields less delay. Also, the throughput exhibited by SAFE is better than FTP.

  12. Augmenting Satellite Precipitation Estimation with Lightning Information

    Energy Technology Data Exchange (ETDEWEB)

    Mahrooghy, Majid [Mississippi State University (MSU); Anantharaj, Valentine G [ORNL; Younan, Nicolas H. [Mississippi State University (MSU); Petersen, Walter A. [NASA Marshall Space Flight Center, Huntsville, AL; Hsu, Kuo-Lin [University of California, Irvine; Behrangi, Ali [Jet Propulsion Laboratory, Pasadena, CA; Aanstoos, James [Mississippi State University (MSU)

    2013-01-01

    We have used lightning information to augment the Precipitation Estimation from Remotely Sensed Imagery using an Artificial Neural Network - Cloud Classification System (PERSIANN-CCS). Co-located lightning data are used to segregate cloud patches, segmented from GOES-12 infrared data, into either electrified (EL) or non-electrified (NEL) patches. A set of features is extracted separately for the EL and NEL cloud patches. The features for the EL cloud patches include new features based on the lightning information. The cloud patches are classified and clustered using self-organizing maps (SOM). Then brightness temperature and rain rate (T-R) relationships are derived for the different clusters. Rain rates are estimated for the cloud patches based on their representative T-R relationship. The Equitable Threat Score (ETS) for daily precipitation estimates is improved by almost 12% for the winter season. In the summer, no significant improvements in ETS are noted.

  13. Mobility management in satellite networks

    Science.gov (United States)

    Johanson, Gary A.

    1995-01-01

    This paper addresses the methods used or proposed for use in multi-beam and/or multi-satellite networks designed to provide Mobile Satellite Services (MSS). Specific topics include beam crossover in the North American Mobile Satellite (MSAT) system as well as registration and live call hand-off for a multi-regional geosynchronous (GEO) satellite based system and a global coverage Low Earth Orbiting (LEO) system. In the MSAT system, the individual satellite beams cover very large geographic areas so the need for live call hand-off was not anticipated. This paper discusses the methods used to keep track of the beam location of the users so that incoming call announcements or other messages may be directed to them. Proposed new GEO systems with large numbers of beams will provide much smaller geographic coverage in individual beams and thus the need arises to keep track of the user's location as well as to provide live call hand-off as the user traverses from beam to beam. This situation also occurs in proposed LEO systems where the problems are worsened by the need for satellite to satellite hand-off as well as beam to beam hand-off within a single satellite. The paper discusses methods to accomplish these handoffs and proposes system architectures to address the various hand-off scenarios.

  14. Comparative Analysis of Satellite DNA in the Drosophila melanogaster Species Complex

    Directory of Open Access Journals (Sweden)

    Madhav Jagannathan

    2017-02-01

    Full Text Available Satellite DNAs are highly repetitive sequences that account for the majority of constitutive heterochromatin in many eukaryotic genomes. It is widely recognized that sequences and locations of satellite DNAs are highly divergent even in closely related species, contributing to the hypothesis that satellite DNA differences may underlie speciation. However, due to its repetitive nature, the mapping of satellite DNAs has been mostly left out of recent genomics analyses, hampering the use of molecular genetics techniques to better understand their role in speciation and evolution. Satellite DNAs are most extensively and comprehensively mapped in Drosophila melanogaster, a species that is also an excellent model system with which to study speciation. Yet the lack of comprehensive knowledge regarding satellite DNA identity and location in its sibling species (D. simulans, D. mauritiana, and D. sechellia has prevented the full utilization of D. melanogaster in studying speciation. To overcome this problem, we initiated the mapping of satellite DNAs on the genomes of the D. melanogaster species complex (D. melanogaster, D. simulans, D. mauritiana, and D. sechellia using multi-color fluorescent in situ hybridization (FISH probes. Our study confirms a striking divergence of satellite DNAs in the D. melanogaster species complex, even among the closely related species of the D. simulans clade (D. simulans, D. mauritiana, and D. sechellia, and suggests the presence of unidentified satellite sequences in these species.

  15. Analysis and modeling of tropical convection observed by CYGNSS

    Science.gov (United States)

    Lang, T. J.; Li, X.; Roberts, J. B.; Mecikalski, J. R.

    2017-12-01

    The Cyclone Global Navigation Satellite System (CYGNSS) is a multi-satellite constellation that utilizes Global Positioning System (GPS) reflectometry to retrieve near-surface wind speeds over the ocean. While CYGNSS is primarily aimed at measuring wind speeds in tropical cyclones, our research has established that the mission may also provide valuable insight into the relationships between wind-driven surface fluxes and general tropical oceanic convection. Currently, we are examining organized tropical convection using a mixture of CYGNSS level 1 through level 3 data, IMERG (Integrated Multi-satellite Retrievals for Global Precipitation Measurement), and other ancillary datasets (including buoys, GPM level 1 and 2 data, as well as ground-based radar). In addition, observing system experiments (OSEs) are being performed using hybrid three-dimensional variational assimilation to ingest CYGNSS observations into a limited-domain, convection-resolving model. Our focus for now is on case studies of convective evolution, but we will also report on progress toward statistical analysis of convection sampled by CYGNSS. Our working hypothesis is that the typical mature phase of organized tropical convection is marked by the development of a sharp gust-front boundary from an originally spatially broader but weaker wind speed change associated with precipitation. This increase in the wind gradient, which we demonstrate is observable by CYGNSS, likely helps to focus enhanced turbulent fluxes of convection-sustaining heat and moisture near the leading edge of the convective system where they are more easily ingested by the updraft. Progress on the testing and refinement of this hypothesis, using a mixture of observations and modeling, will be reported.

  16. Global Precipitation Measurement (GPM) L-6

    Science.gov (United States)

    Neeck, Steven P.; Kakar, Ramesh K.; Azarbarzin, Ardeshir A.; Hou, Arthur Y.

    2013-10-01

    The Global Precipitation Measurement (GPM) mission will advance the measurement of global precipitation, making possible high spatial resolution precipitation measurements. GPM will provide the first opportunity to calibrate measurements of global precipitation across tropical, mid-latitude, and polar regions. The GPM mission has the following scientific objectives: (1) Advance precipitation measurement capability from space through combined use of active and passive remote-sensing techniques; (2) Advance understanding of global water/energy cycle variability and fresh water availability; (3) Improve climate prediction by providing the foundation for better understanding of surface water fluxes, soil moisture storage, cloud/precipitation microphysics and latent heat release in the Earth's atmosphere; (4) Advance Numerical Weather Prediction (NWP) skills through more accurate and frequent measurements of instantaneous rain rates; and (5) Improve high impact natural hazard (flood/drought, landslide, and hurricane hazard) prediction capabilities. The GPM mission centers on the deployment of a Core Observatory carrying an advanced radar / radiometer system to measure precipitation from space and serve as a reference standard to unify precipitation measurements from a constellation of research and operational satellites. GPM, jointly led with the Japan Aerospace Exploration Agency (JAXA), involves a partnership with other international space agencies including the French Centre National d'Études Spatiales (CNES), the Indian Space Research Organisation (ISRO), the U.S. National Oceanic and Atmospheric Administration (NOAA), the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), and others. The GPM Core Observatory is currently being prepared for shipment to Japan for launch. Launch is scheduled for February 2014 from JAXA's Tanegashima Space Center on an H-IIA 202 launch vehicle.

  17. Remote Sensing of Clouds And Precipitation: Event-Based Characterization, Life Cycle Evolution, and Aerosol Influences

    Science.gov (United States)

    Esmaili, Rebekah Bradley

    Global climate models, numerical weather prediction, and flood models rely on accurate satellite precipitation products, which are the only datasets that are continuous in time and space across the globe. While there are more earth observing satellites than ever before, gaps in precipitation retrievals exist due to sensor and orbital limitations of low-earth (LEO) satellites, which are overcome by merging data from different sensors in satellite precipitation products (SPPs). Using cloud tracking at higher resolutions than the spatio-temporal scales of LEO satellites, this thesis examines how clouds typically form in the atmosphere, the rate that cloud size and temperature evolve over the life cycle, and the time of day that cloud development take place. This thesis found that cloud evolution was non-linear, which disagrees with the linear interpolation schemes used in SPPs. Longer lasting clouds tended to achieve their temperature and size maturity milestones at different times, while these stages often occurred simultaneously in shorter lasting clouds. Over the ocean, longer lasting clouds were found to occur more frequently at night, while shorter lasting clouds were more common during the daytime. This thesis also examines whether large-scale Saharan dust outbreaks can impact the trajectories and intensity of cloud clusters in the tropical Atlantic, which is predicted by modeling studies. The presented results show that proximity to Saharan dust outbreaks shifts Atlantic cloud development northward and intense storms becoming more common, whereas on days with low dust loading small-scale, warmer clouds are more common. A simplified view of cloud evolution in merged rainfall retrievals is a possible source of errors, which can propagate into higher level analysis. This thesis investigates the difference in the intensity, duration, and frequency of precipitation in IMERG, a next-generation satellite precipitation product with ground radar observations over the

  18. Analysis of Precipitation and Drought Data in Hexi Corridor, Northwest China

    Directory of Open Access Journals (Sweden)

    Xinyang Yu

    2017-05-01

    Full Text Available Precipitation data from nine meteorological stations in arid oases of Hexi Corridor, northwest China during 1970–2012 were analyzed to detect trends in precipitation and Standardized Precipitation Index (SPI at multiple time scales using linear regression, Mann–Kendall and Spearman’s Rho tests. The results found that annual precipitation in the observed stations was rare and fell into the arid region category according to the aridity index analysis. The monthly analysis of precipitation found that three stations showed significant increasing trends in different months, while on the annual level, only Yongchang station had a significant increasing trend. The analysis of SPI-12 found three main drought intervals, i.e., 1984–1987, 1991–1992 and 2008–2011, and an extremely dry year among the stations was recorded in 1986; the southeast and middle portions of the study area are expected to have more precipitation and less dry conditions.

  19. Acute Precipitants of Physical Elder Abuse: Qualitative Analysis of Legal Records From Highly Adjudicated Cases.

    Science.gov (United States)

    Rosen, Tony; Bloemen, Elizabeth M; LoFaso, Veronica M; Clark, Sunday; Flomenbaum, Neal E; Breckman, Risa; Markarian, Arlene; Riffin, Catherine; Lachs, Mark S; Pillemer, Karl

    2016-08-01

    Elder abuse is a common phenomenon with potentially devastating consequences for older adults. Although researchers have begun to identify predisposing risk factors for elder abuse victims and abusers, little is known about the acute precipitants that lead to escalation to physical violence. We analyzed legal records from highly adjudicated cases to describe these acute precipitants for physical elder abuse. In collaboration with a large, urban district attorney's office, we qualitatively evaluated legal records from 87 successfully prosecuted physical elder abuse cases from 2003 to 2015. We transcribed and analyzed narratives of the events surrounding physical abuse within victim statements, police reports, and prosecutor records. We identified major themes using content analysis. We identified 10 categories of acute precipitants that commonly triggered physical elder abuse, including victim attempting to prevent the abuser from entering or demanding that he or she leave, victim threatening or attempting to leave/escape, threat or perception that the victim would involve the authorities, conflict about a romantic relationship, presence during/intervention in ongoing family violence, issues in multi-generational child rearing, conflict about the abuser's substance abuse, confrontation about financial exploitation, dispute over theft/destruction of property, and disputes over minor household issues. Common acute precipitants of physical elder abuse may be identified. Improved understanding of these acute precipitants for escalation to physical violence and their contribution to elder abuse may assist in the development of prevention and management strategies.

  20. Evaluation of the TMPA-3B42 precipitation product using a high-density rain gauge network over complex terrain in northeastern Iberia

    KAUST Repository

    El Kenawy, Ahmed M.

    2015-08-29

    The performance of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA)-3B42 version 7 product is assessed over north-eastern Iberia, a region with considerable topographical gradients and complexity. Precipitation characteristics from a dense network of 656 rain gauges, spanning the period from 1998 to 2009, are used to evaluate TMPA-3B42 estimates on a daily scale. A set of accuracy estimators, including the relative bias, mean absolute error (MAE), root mean square error (RMSE) and Spearman coefficient was used to evaluate the results. The assessment indicates that TMPA-3B42 product is capable of describing the seasonal characteristics of the observed precipitation over most of the study domain. In particular, TMPA-3B42 precipitation agrees well with in situ measurements, with MAE less than 2.5mm.day-1, RMSE of 6.4mm.day-1 and Spearman correlation coefficients generally above 0.6. TMPA-3B42 provides improved accuracies in winter and summer, whereas it performs much worse in spring and autumn. Spatially, the retrieval errors show a consistent trend, with a general overestimation in regions of low altitude and underestimation in regions of heterogeneous terrain. TMPA-3B42 generally performs well over inland areas, while showing less skill in the coastal regions. A set of skill metrics, including a false alarm ratio [FAR], frequency bias index [FBI], the probability of detection [POD] and threat score [TS], is also used to evaluate TMPA performance under different precipitation thresholds (1, 5, 10, 25 and 50mm.day-1). The results suggest that TMPA-3B42 retrievals perform well in specifying moderate rain events (5-25mm.day-1), but show noticeably less skill in producing both light (<1mm.day-1) and heavy rainfall thresholds (more than 50mm.day-1). Given the complexity of the terrain and the associated high spatial variability of precipitation in north-eastern Iberia, the results reveal that TMPA-3B42 data provide an

  1. Evaluation of the TMPA-3B42 precipitation product using a high-density rain gauge network over complex terrain in northeastern Iberia

    KAUST Repository

    El Kenawy, Ahmed M.; Lopez-Moreno, Juan I.; McCabe, Matthew; Vicente-Serrano, Sergio M.

    2015-01-01

    The performance of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA)-3B42 version 7 product is assessed over north-eastern Iberia, a region with considerable topographical gradients and complexity. Precipitation characteristics from a dense network of 656 rain gauges, spanning the period from 1998 to 2009, are used to evaluate TMPA-3B42 estimates on a daily scale. A set of accuracy estimators, including the relative bias, mean absolute error (MAE), root mean square error (RMSE) and Spearman coefficient was used to evaluate the results. The assessment indicates that TMPA-3B42 product is capable of describing the seasonal characteristics of the observed precipitation over most of the study domain. In particular, TMPA-3B42 precipitation agrees well with in situ measurements, with MAE less than 2.5mm.day-1, RMSE of 6.4mm.day-1 and Spearman correlation coefficients generally above 0.6. TMPA-3B42 provides improved accuracies in winter and summer, whereas it performs much worse in spring and autumn. Spatially, the retrieval errors show a consistent trend, with a general overestimation in regions of low altitude and underestimation in regions of heterogeneous terrain. TMPA-3B42 generally performs well over inland areas, while showing less skill in the coastal regions. A set of skill metrics, including a false alarm ratio [FAR], frequency bias index [FBI], the probability of detection [POD] and threat score [TS], is also used to evaluate TMPA performance under different precipitation thresholds (1, 5, 10, 25 and 50mm.day-1). The results suggest that TMPA-3B42 retrievals perform well in specifying moderate rain events (5-25mm.day-1), but show noticeably less skill in producing both light (<1mm.day-1) and heavy rainfall thresholds (more than 50mm.day-1). Given the complexity of the terrain and the associated high spatial variability of precipitation in north-eastern Iberia, the results reveal that TMPA-3B42 data provide an

  2. Application of multi-scale wavelet entropy and multi-resolution Volterra models for climatic downscaling

    Science.gov (United States)

    Sehgal, V.; Lakhanpal, A.; Maheswaran, R.; Khosa, R.; Sridhar, Venkataramana

    2018-01-01

    This study proposes a wavelet-based multi-resolution modeling approach for statistical downscaling of GCM variables to mean monthly precipitation for five locations at Krishna Basin, India. Climatic dataset from NCEP is used for training the proposed models (Jan.'69 to Dec.'94) and are applied to corresponding CanCM4 GCM variables to simulate precipitation for the validation (Jan.'95-Dec.'05) and forecast (Jan.'06-Dec.'35) periods. The observed precipitation data is obtained from the India Meteorological Department (IMD) gridded precipitation product at 0.25 degree spatial resolution. This paper proposes a novel Multi-Scale Wavelet Entropy (MWE) based approach for clustering climatic variables into suitable clusters using k-means methodology. Principal Component Analysis (PCA) is used to obtain the representative Principal Components (PC) explaining 90-95% variance for each cluster. A multi-resolution non-linear approach combining Discrete Wavelet Transform (DWT) and Second Order Volterra (SoV) is used to model the representative PCs to obtain the downscaled precipitation for each downscaling location (W-P-SoV model). The results establish that wavelet-based multi-resolution SoV models perform significantly better compared to the traditional Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) based frameworks. It is observed that the proposed MWE-based clustering and subsequent PCA, helps reduce the dimensionality of the input climatic variables, while capturing more variability compared to stand-alone k-means (no MWE). The proposed models perform better in estimating the number of precipitation events during the non-monsoon periods whereas the models with clustering without MWE over-estimate the rainfall during the dry season.

  3. kCCA Transformation-Based Radiometric Normalization of Multi-Temporal Satellite Images

    Directory of Open Access Journals (Sweden)

    Yang Bai

    2018-03-01

    Full Text Available Radiation normalization is an essential pre-processing step for generating high-quality satellite sequence images. However, most radiometric normalization methods are linear, and they cannot eliminate the regular nonlinear spectral differences. Here we introduce the well-established kernel canonical correlation analysis (kCCA into radiometric normalization for the first time to overcome this problem, which leads to a new kernel method. It can maximally reduce the image differences among multi-temporal images regardless of the imaging conditions and the reflectivity difference. It also perfectly eliminates the impact of nonlinear changes caused by seasonal variation of natural objects. Comparisons with the multivariate alteration detection (CCA-based normalization and the histogram matching, on Gaofen-1 (GF-1 data, indicate that the kCCA-based normalization can preserve more similarity and better correlation between an image-pair and effectively avoid the color error propagation. The proposed method not only builds the common scale or reference to make the radiometric consistency among GF-1 image sequences, but also highlights the interesting spectral changes while eliminates less interesting spectral changes. Our method enables the application of GF-1 data for change detection, land-use, land-cover change detection etc.

  4. Comparison of Diurnal Characteristics of GPM-IMERG Precipitation Products with Hourly Rain Gauge Observations and TRMM-TMPA Products over Mainland China

    Science.gov (United States)

    Li, R.; Wang, K.; QI, D.

    2017-12-01

    The next generation global high resolutions precipitation products, the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) provide new insights into the global hydrometeorology studies. Although there are some previous works to evaluate it on daily scale or above, its performance on sub-daily scale is still limited. This study evaluates the diurnal characteristics of the half-hourly IMERG product with the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) data and the hourly rain gauge data from approximately 50000 automatic weather station (AWS) in China during 2014-2016. The results show that IMERG can roughly capture the diurnal cycle of precipitation amount with serial correlation for eight sub-regions ranging from 0.63 to 0.97, but less agreed in frequency (from 0.21 to 0.90) and intensity (from -0.22 to 0.83). IMERG can generally capture the nocturnal and early morning peak of amount, frequency and intensity, which it's a known issue unsolved by TMPA, partly due to the better detection of light rain in the morning. However as for the afternoon precipitation, overestimation of amount and frequency and underestimation of intensity still exist in IMERG product, which probably result from the overestimation of light and moderate rain. IMERG shows large bias in late morning (0900-1100 Beijing Time) and mid evening (2000-2200 Beijing Time). All these results highlight the cautions when using the IMERG sub-daily product and indicate the necessity of improved retrieval algorithm in the future.

  5. Satellite interference analysis and simulation using personal computers

    Science.gov (United States)

    Kantak, Anil

    1988-03-01

    This report presents the complete analysis and formulas necessary to quantify the interference experienced by a generic satellite communications receiving station due to an interfering satellite. Both satellites, the desired as well as the interfering satellite, are considered to be in elliptical orbits. Formulas are developed for the satellite look angles and the satellite transmit angles generally related to the land mask of the receiving station site for both satellites. Formulas for considering Doppler effect due to the satellite motion as well as the Earth's rotation are developed. The effect of the interfering-satellite signal modulation and the Doppler effect on the power received are considered. The statistical formulation of the interference effect is presented in the form of a histogram of the interference to the desired signal power ratio. Finally, a computer program suitable for microcomputers such as IBM AT is provided with the flowchart, a sample run, results of the run, and the program code.

  6. Calibration Plans for the Global Precipitation Measurement (GPM)

    Science.gov (United States)

    Bidwell, S. W.; Flaming, G. M.; Adams, W. J.; Everett, D. F.; Mendelsohn, C. R.; Smith, E. A.; Turk, J.

    2002-01-01

    The Global Precipitation Measurement (GPM) is an international effort led by the National Aeronautics and Space Administration (NASA) of the U.S.A. and the National Space Development Agency of Japan (NASDA) for the purpose of improving research into the global water and energy cycle. GPM will improve climate, weather, and hydrological forecasts through more frequent and more accurate measurement of precipitation world-wide. Comprised of U.S. domestic and international partners, GPM will incorporate and assimilate data streams from many spacecraft with varied orbital characteristics and instrument capabilities. Two of the satellites will be provided directly by GPM, the core satellite and a constellation member. The core satellite, at the heart of GPM, is scheduled for launch in November 2007. The core will carry a conical scanning microwave radiometer, the GPM Microwave Imager (GMI), and a two-frequency cross-track-scanning radar, the Dual-frequency Precipitation Radar (DPR). The passive microwave channels and the two radar frequencies of the core are carefully chosen for investigating the varying character of precipitation over ocean and land, and from the tropics to the high-latitudes. The DPR will enable microphysical characterization and three-dimensional profiling of precipitation. The GPM-provided constellation spacecraft will carry a GMI radiometer identical to that on the core spacecraft. This paper presents calibration plans for the GPM, including on-board instrument calibration, external calibration methods, and the role of ground validation. Particular emphasis is on plans for inter-satellite calibration of the GPM constellation. With its Unique instrument capabilities, the core spacecraft will serve as a calibration transfer standard to the GPM constellation. In particular the Dual-frequency Precipitation Radar aboard the core will check the accuracy of retrievals from the GMI radiometer and will enable improvement of the radiometer retrievals

  7. Scheduling algorithm for data relay satellite optical communication based on artificial intelligent optimization

    Science.gov (United States)

    Zhao, Wei-hu; Zhao, Jing; Zhao, Shang-hong; Li, Yong-jun; Wang, Xiang; Dong, Yi; Dong, Chen

    2013-08-01

    Optical satellite communication with the advantages of broadband, large capacity and low power consuming broke the bottleneck of the traditional microwave satellite communication. The formation of the Space-based Information System with the technology of high performance optical inter-satellite communication and the realization of global seamless coverage and mobile terminal accessing are the necessary trend of the development of optical satellite communication. Considering the resources, missions and restraints of Data Relay Satellite Optical Communication System, a model of optical communication resources scheduling is established and a scheduling algorithm based on artificial intelligent optimization is put forwarded. According to the multi-relay-satellite, multi-user-satellite, multi-optical-antenna and multi-mission with several priority weights, the resources are scheduled reasonable by the operation: "Ascertain Current Mission Scheduling Time" and "Refresh Latter Mission Time-Window". The priority weight is considered as the parameter of the fitness function and the scheduling project is optimized by the Genetic Algorithm. The simulation scenarios including 3 relay satellites with 6 optical antennas, 12 user satellites and 30 missions, the simulation result reveals that the algorithm obtain satisfactory results in both efficiency and performance and resources scheduling model and the optimization algorithm are suitable in multi-relay-satellite, multi-user-satellite, and multi-optical-antenna recourses scheduling problem.

  8. Performance of Optimally Merged Multisatellite Precipitation Products Using the Dynamic Bayesian Model Averaging Scheme Over the Tibetan Plateau

    Science.gov (United States)

    Ma, Yingzhao; Hong, Yang; Chen, Yang; Yang, Yuan; Tang, Guoqiang; Yao, Yunjun; Long, Di; Li, Changmin; Han, Zhongying; Liu, Ronghua

    2018-01-01

    Accurate estimation of precipitation from satellites at high spatiotemporal scales over the Tibetan Plateau (TP) remains a challenge. In this study, we proposed a general framework for blending multiple satellite precipitation data using the dynamic Bayesian model averaging (BMA) algorithm. The blended experiment was performed at a daily 0.25° grid scale for 2007-2012 among Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42RT and 3B42V7, Climate Prediction Center MORPHing technique (CMORPH), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR). First, the BMA weights were optimized using the expectation-maximization (EM) method for each member on each day at 200 calibrated sites and then interpolated to the entire plateau using the ordinary kriging (OK) approach. Thus, the merging data were produced by weighted sums of the individuals over the plateau. The dynamic BMA approach showed better performance with a smaller root-mean-square error (RMSE) of 6.77 mm/day, higher correlation coefficient of 0.592, and closer Euclid value of 0.833, compared to the individuals at 15 validated sites. Moreover, BMA has proven to be more robust in terms of seasonality, topography, and other parameters than traditional ensemble methods including simple model averaging (SMA) and one-outlier removed (OOR). Error analysis between BMA and the state-of-the-art IMERG in the summer of 2014 further proved that the performance of BMA was superior with respect to multisatellite precipitation data merging. This study demonstrates that BMA provides a new solution for blending multiple satellite data in regions with limited gauges.

  9. Contemporary ground-based and satellite precipitating system characterization for desertification studies in Southern Italy

    Directory of Open Access Journals (Sweden)

    M. Casazza

    2008-07-01

    Full Text Available During the research project RIADE (Ricerca Integrata per l'Applicazione di tecnologie e processi innovativi per la lotta alla DEsertificazione, devoted to the study on the potential risk of desertification in Southern Italy, a particular attention has been paid also to the analysis of precipitations from three surface stations (Licata, Sicily; Rotondella, Basilicata; Surigheddu, Sardinia in order to improve the knowledge derived from the most modern climatological studies related to this subject. The point of view adopted is to better define the precipitation microphysical properties (in particular, the Drop Size Distribution, DSD, and its moments, which are deeply related to the cloud system that generates the precipitation events. In particular we have used a newly introduced Convective Stratiform discrimination technique, that allowed us to observe a prevalence of events, concentrated along Winter (Wi season, of different microphysical nature. In fact the prevailing Stratiform nature is related to Licata station, while for Surigheddu and for Rotondella the nature is mainly Convective. This distinction is related to the presence of drops of bigger dimensions and more intense precipitations in the latter case, while, in the former case, a prevalence of smaller drops and a less intense precipitation is recorded. This confirms the distinctive belonging to three different climatic regions, as indicated in the study by Brunetti et al. (2006. Our findings are important in the framework of desertification studies, because the cause of desertification can be related either to fertile soils removal (in the case of Convective events or to lack of precipitated water (in the case of Stratiform events. We have also analysed a sub-set of ten events, with contemporary presence of data from VIS/IR channels of METEOSAT-7, SSM/I data from F13 and MODIS data from Terra platform. This has been done both to confirm the findings of PLUDIX data analysis (which

  10. Contemporary ground-based and satellite precipitating system characterization for desertification studies in Southern Italy

    Directory of Open Access Journals (Sweden)

    M. Casazza

    2008-07-01

    Full Text Available During the research project RIADE (Ricerca Integrata per l'Applicazione di tecnologie e processi innovativi per la lotta alla DEsertificazione, devoted to the study on the potential risk of desertification in Southern Italy, a particular attention has been paid also to the analysis of precipitations from three surface stations (Licata, Sicily; Rotondella, Basilicata; Surigheddu, Sardinia in order to improve the knowledge derived from the most modern climatological studies related to this subject. The point of view adopted is to better define the precipitation microphysical properties (in particular, the Drop Size Distribution, DSD, and its moments, which are deeply related to the cloud system that generates the precipitation events. In particular we have used a newly introduced Convective Stratiform discrimination technique, that allowed us to observe a prevalence of events, concentrated along Winter (Wi season, of different microphysical nature. In fact the prevailing Stratiform nature is related to Licata station, while for Surigheddu and for Rotondella the nature is mainly Convective. This distinction is related to the presence of drops of bigger dimensions and more intense precipitations in the latter case, while, in the former case, a prevalence of smaller drops and a less intense precipitation is recorded. This confirms the distinctive belonging to three different climatic regions, as indicated in the study by Brunetti et al. (2006. Our findings are important in the framework of desertification studies, because the cause of desertification can be related either to fertile soils removal (in the case of Convective events or to lack of precipitated water (in the case of Stratiform events. We have also analysed a sub-set of ten events, with contemporary presence of data from VIS/IR channels of METEOSAT-7, SSM/I data from F13 and MODIS data from Terra platform. This has been done both to confirm the findings of PLUDIX data analysis (which is

  11. Utilizing a suite of satellite missions to address poorly constrained hydrological fluxes

    Science.gov (United States)

    Singh, A.; Behrangi, A.; Fisher, J.; Reager, J. T., II; Gardner, A. S.

    2017-12-01

    The amount of water stored in a given region (total water storage) changes in response to changes in the hydrologic balance (inputs minus outputs). Closing this balance is exceedingly difficult due to the sparsity of field observation, large uncertainties in satellite derived estimates and model limitation. Different regions have distinct reliability on different hydrological parameters. For example, at a higher latitude precipitation is more uncertain than evapotranspiration (ET) while at lower/middle latitude the opposite is true. This study explores alternative estimates of regional hydrological fluxes by integrating the total water storage estimated by the GRACE gravity fields, and improved estimates lake storage variation by Landsat based land-water classification and satellite altimetry based water height measurements. In particular, an alternative ET estimate is generated for the Aral Sea region by integrating multi-sensor remote sensing data. In an endorheic lake like the Aral Sea, its volumetric variations are predominately governed by changes in inflow, evaporation from the water body and precipitation on the lake. The Aral Sea water volume is estimated at a monthly time step by the combination of Landsat land-water classification and ocean radar altimetry (Jason 1 and Jason 2) observations using truncated pyramid method. Considering gauge based river runoff as a true observation and given the fact that there is less variability between multiple precipitation datasets (TRMM, GPCP, GPCC, and ERA), ET can be considered as a most uncertain parameter in this region. The estimated lake volume acts as a controlling factor to estimate ET as the residual of the changes in TWS minus inflow plus precipitation. The estimated ET is compared with the MODIS-based evaporation observations.

  12. Comparison of TRMM and Global Precipitation Climatology Project (GPCP) Precipitation Analyses

    Science.gov (United States)

    Adler, Robert F.; Huffman, George J.; Bolvin, David; Nelkin, Eric; Curtis, Scott

    1999-01-01

    This paper describes recent results of using Tropical Rainfall Measuring Mission (TRMM) (launched in November 1997) information as the key calibration tool in a merged analysis on a 1 x 1' latitude/longitude monthly scale based on multiple satellite sources and raingauge analyses. The TRMM-based product is compared with the community-based Global Precipitation Climatology Project (GPCP) results. The long-term GPCP analysis is compared to the new TRMM-based analysis which uses the most accurate TRMM information to calibrate the estimates from the Special Sensor Microwave/Imager (SSM/I) and geosynchronous IR observations and merges those estimates together with the TRMM and gauge information to produce accurate rainfall estimates with the increased sampling provided by the combined satellite information. The comparison with TRMM results on a month-to-month basis should clarify the strengths and weaknesses of the long-term GPCP product in the tropics and point to how to improve the monitoring analysis. Preliminary results from the TRMM merged satellite analysis indicates fairly close agreement with the GPCP estimates. The GPCP analysis is done at 2.5 degree latitude/longitude resolution and interpolated to a 1 degree grid for comparison with the TRMM analysis. As expected the same features are evident in both panels, but there are subtle differences in the magnitudes. Focusing on the Pacific Ocean Inter-Tropical Convergence Zone (ITCZ) one can see the TRMM-based estimates having higher peak values and lower values in the ITCZ periphery. These attributes also show up in the statistics, where GPCP>TRMM at low values (below 10 mm/d) and TRMM>GPCP at high values (greater than 15 mm/d). The area in the Indian Ocean which shows consistently higher values of TRMM over GPCP needs to be examined carefully to determine if the lack of geosynchronous data has led to a difference in the two analyses. By the time of the meeting over a year of TRMM products will be available for

  13. Aerosols, Chemistry, and Radiative Forcing: A 3-D Model Analysis of Satellite and ACE-Asia data (ACMAP)

    Science.gov (United States)

    Chin, Mian; Ginoux, Paul; Torres, Omar; Zhao, Xue-Peng

    2005-01-01

    We propose a research project to incorporate a global 3-D model and satellite data into the multi-national Aerosol Characterization Experiment-Asia (ACE-Asia) mission. Our objectives are (1) to understand the physical, chemical, and optical properties of aerosols and the processes that control those properties over the Asian-Pacific region, (2) to investigate the interaction between aerosols and tropospheric chemistry, and (3) to determine the aerosol radiative forcing over the Asia-Pacific region. We will use the Georgia TecWGoddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model to link satellite observations and the ACE-Asia measurements. First, we will use the GOCART model to simulate aerosols and related species, and evaluate the model with satellite and in-situ observations. Second, the model generated aerosol vertical profiles and compositions will be used to validate the satellite products; and the satellite data will be used for during- and post- mission analysis. Third, we will use the model to analyze and interpret both satellite and ACE- Asia field campaign data and investigate the aerosol-chemistry interactions. Finally, we will calculate aerosol radiative forcing over the Asian-Pacific region, and assess the influence of Asian pollution in the global atmosphere. We propose a research project to incorporate a global 3-D model and satellite data into

  14. Coherent Uncertainty Analysis of Aerosol Measurements from Multiple Satellite Sensors

    Science.gov (United States)

    Petrenko, M.; Ichoku, C.

    2013-01-01

    Aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS altogether, a total of 11 different aerosol products were comparatively analyzed using data collocated with ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations within the Multi-sensor Aerosol Products Sampling System (MAPSS, http://giovanni.gsfc.nasa.gov/mapss/ and http://giovanni.gsfc.nasa.gov/aerostat/). The analysis was performed by comparing quality-screened satellite aerosol optical depth or thickness (AOD or AOT) retrievals during 2006-2010 to available collocated AERONET measurements globally, regionally, and seasonally, and deriving a number of statistical measures of accuracy. We used a robust statistical approach to detect and remove possible outliers in the collocated data that can bias the results of the analysis. Overall, the proportion of outliers in each of the quality-screened AOD products was within 12%. Squared correlation coefficient (R2) values of the satellite AOD retrievals relative to AERONET exceeded 0.6, with R2 for most of the products exceeding 0.7 over land and 0.8 over ocean. Root mean square error (RMSE) values for most of the AOD products were within 0.15 over land and 0.09 over ocean. We have been able to generate global maps showing regions where the different products present advantages over the others, as well as the relative performance of each product over different landcover types. It was observed that while MODIS, MISR, and SeaWiFS provide accurate retrievals over most of the landcover types, multi-angle capabilities make MISR the only sensor to retrieve reliable AOD over barren and snow / ice surfaces. Likewise, active sensing enables CALIOP to retrieve aerosol properties over bright-surface shrublands more accurately than the other sensors, while POLDER, which is the only one of the sensors capable of measuring polarized aerosols, outperforms other sensors in

  15. Large-scale assessment of soil erosion in Africa: satellites help to jointly account for dynamic rainfall and vegetation cover

    Science.gov (United States)

    Vrieling, Anton; Hoedjes, Joost C. B.; van der Velde, Marijn

    2015-04-01

    Efforts to map and monitor soil erosion need to account for the erratic nature of the soil erosion process. Soil erosion by water occurs on sloped terrain when erosive rainfall and consequent surface runoff impact soils that are not well-protected by vegetation or other soil protective measures. Both rainfall erosivity and vegetation cover are highly variable through space and time. Due to data paucity and the relative ease of spatially overlaying geographical data layers into existing models like USLE (Universal Soil Loss Equation), many studies and mapping efforts merely use average annual values for erosivity and vegetation cover as input. We first show that rainfall erosivity can be estimated from satellite precipitation data. We obtained average annual erosivity estimates from 15 yr of 3-hourly TRMM Multi-satellite Precipitation Analysis (TMPA) data (1998-2012) using intensity-erosivity relationships. Our estimates showed a positive correlation (r = 0.84) with long-term annual erosivity values of 37 stations obtained from literature. Using these TMPA erosivity retrievals, we demonstrate the large interannual variability, with maximum annual erosivity often exceeding two to three times the mean value, especially in semi-arid areas. We then calculate erosivity at a 10-daily time-step and combine this with vegetation cover development for selected locations in Africa using NDVI - normalized difference vegetation index - time series from SPOT VEGETATION. Although we do not integrate the data at this point, the joint analysis of both variables stresses the need for joint accounting for erosivity and vegetation cover for large-scale erosion assessment and monitoring.

  16. UC Irvine CHRS Real-time Global Satellite Precipitation Monitoring System (G-WADI PERSIANN-CCS GeoServer) for Hydrometeorological Applications

    Science.gov (United States)

    Sorooshian, S.; Hsu, K. L.; Gao, X.; Imam, B.; Nguyen, P.; Braithwaite, D.; Logan, W. S.; Mishra, A.

    2015-12-01

    The G-WADI Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) GeoServer has been successfully developed by the Center for Hydrometeorology and Remote Sensing (CHRS) at the University of California Irvine in collaboration with the UNESCO's International Hydrological Programme (IHP) and a number of its international centers. The system employs state-of-the-art technologies in remote sensing and artificial intelligence to estimate precipitation globally from satellite imagery in real-time and high spatiotemporal resolution (4km, hourly). It offers graphical tools and data service to help the user in emergency planning and management for natural disasters related to hydrological processes. The G-WADI PERSIANN-CCS GeoServer has been upgraded with new user-friendly functionalities. The precipitation data generated by the GeoServer is disseminated to the user community through support provided by ICIWaRM (The International Center for Integrated Water Resources Management), UNESCO and UC Irvine. Recently a number of new applications for mobile devices have been developed by our students. The RainMapper has been available on App Store and Google Play for the real-time PERSIANN-CCS observations. A global crowd sourced rainfall reporting system named iRain has also been developed to engage the public globally to provide qualitative information about real-time precipitation in their location which will be useful in improving the quality of the PERSIANN-CCS data. A number of recent examples of the application and use of the G-WADI PERSIANN-CCS GeoServer information will also be presented.

  17. The Canadian Precipitation Analysis (CaPA): Evaluation of the statistical interpolation scheme

    Science.gov (United States)

    Evans, Andrea; Rasmussen, Peter; Fortin, Vincent

    2013-04-01

    CaPA (Canadian Precipitation Analysis) is a data assimilation system which employs statistical interpolation to combine observed precipitation with gridded precipitation fields produced by Environment Canada's Global Environmental Multiscale (GEM) climate model into a final gridded precipitation analysis. Precipitation is important in many fields and applications, including agricultural water management projects, flood control programs, and hydroelectric power generation planning. Precipitation is a key input to hydrological models, and there is a desire to have access to the best available information about precipitation in time and space. The principal goal of CaPA is to produce this type of information. In order to perform the necessary statistical interpolation, CaPA requires the estimation of a semi-variogram. This semi-variogram is used to describe the spatial correlations between precipitation innovations, defined as the observed precipitation amounts minus the GEM forecasted amounts predicted at the observation locations. Currently, CaPA uses a single isotropic variogram across the entire analysis domain. The present project investigates the implications of this choice by first conducting a basic variographic analysis of precipitation innovation data across the Canadian prairies, with specific interest in identifying and quantifying potential anisotropy within the domain. This focus is further expanded by identifying the effect of storm type on the variogram. The ultimate goal of the variographic analysis is to develop improved semi-variograms for CaPA that better capture the spatial complexities of precipitation over the Canadian prairies. CaPA presently applies a Box-Cox data transformation to both the observations and the GEM data, prior to the calculation of the innovations. The data transformation is necessary to satisfy the normal distribution assumption, but introduces a significant bias. The second part of the investigation aims at devising a bias

  18. Prime mission results of the dual-frequency precipitation radar on the global precipitation measurement core spacecraft and the version 5 GPM standard products

    Science.gov (United States)

    Furukawa, K.; Nio, T.; Oki, R.; Kubota, T.; Iguchi, T.

    2017-09-01

    The Dual-frequency Precipitation Radar (DPR) on the Global Precipitation Measurement (GPM) core satellite was developed by Japan Aerospace Exploration Agency (JAXA) and National Institute of Information and Communications Technology (NICT). The objective of the GPM mission is to observe global precipitation more frequently and accurately. The GPM core satellite is a joint product of National Aeronautics and Space Administration (NASA), JAXA and NICT. NASA developed the satellite bus and the GPM Microwave Imager (GMI), and JAXA and NICT developed the DPR. The inclination of the GPM core satellite is 65 degrees, and the nominal flight altitude is 407 km. The non-sunsynchronous circular orbit is necessary for measuring the diurnal change of rainfall. The DPR consists of two radars, which are Ku-band precipitation radar (KuPR) and Ka-band precipitation radar (KaPR). GPM core observatory was successfully launched by H2A launch vehicle on Feb. 28, 2014. DPR orbital check out was completed in May 2014. DPR products were released to the public on Sep. 2, 2014 and Normal Observation Operation period was started. JAXA is continuing DPR trend monitoring, calibration and validation operations to confirm that DPR keeps its function and performance on orbit. The results of DPR trend monitoring, calibration and validation show that DPR kept its function and performance on orbit during the 3 years and 2 months prime mission period. The DPR Prime mission period was completed in May 2017. The version 5 GPM products were released to the public in 2017. JAXA confirmed that GPM/DPR total system performance and the GPM version 5 products achieved the success criteria and the performance indicators that were defined for the JAXA GPM/DPR mission.

  19. A Multi-stage Method to Extract Road from High Resolution Satellite Image

    International Nuclear Information System (INIS)

    Zhijian, Huang; Zhang, Jinfang; Xu, Fanjiang

    2014-01-01

    Extracting road information from high-resolution satellite images is complex and hardly achieves by exploiting only one or two modules. This paper presents a multi-stage method, consisting of automatic information extraction and semi-automatic post-processing. The Multi-scale Enhancement algorithm enlarges the contrast of human-made structures with the background. The Statistical Region Merging segments images into regions, whose skeletons are extracted and pruned according to geometry shape information. Setting the start and the end skeleton points, the shortest skeleton path is constructed as a road centre line. The Bidirectional Adaptive Smoothing technique smoothens the road centre line and adjusts it to right position. With the smoothed line and its average width, a Buffer algorithm reconstructs the road region easily. Seen from the last results, the proposed method eliminates redundant non-road regions, repairs incomplete occlusions, jumps over complete occlusions, and reserves accurate road centre lines and neat road regions. During the whole process, only a few interactions are needed

  20. Analysis on Precipitation Variation in Anyang and Nanyang in Recent 57 Years

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    [Objective] The aim was to analyze precipitation variation in Anyang and Nanyang in recent 57 years. [Method] Based on the data of annual precipitation in Anyang and Nanyang from 1953 to 2009, the changes of precipitation in Anyang and Nanyang were compared by means of mathematical statistics, regression analysis and wavelet analysis. [Result] In recent 57 years, annual precipitation in Anyang and Nanyang showed decrease trend, especially Anyang with obvious decrease trend; from seasonal variation, average ...

  1. Assessing the fitness-for-purpose of satellite multi-mission ocean color climate data records: A protocol applied to OC-CCI chlorophyll-a data.

    Science.gov (United States)

    Mélin, F; Vantrepotte, V; Chuprin, A; Grant, M; Jackson, T; Sathyendranath, S

    2017-12-15

    In this work, trend estimates are used as indicators to compare the multi-annual variability of different satellite chlorophyll- a (Chl a ) data and to assess the fitness-for-purpose of multi-mission Chl a products as climate data records (CDR). Under the assumption that single-mission products are free from spurious temporal artifacts and can be used as benchmark time series, multi-mission CDRs should reproduce the main trend patterns observed by single-mission series when computed over their respective periods. This study introduces and applies quantitative metrics to compare trend distributions from different data records. First, contingency matrices compare the trend diagnostics associated with two satellite products when expressed in binary categories such as existence, significance and signs of trends. Contingency matrices can be further summarized by metrics such as Cohen's κ index that rates the overall agreement between the two distributions of diagnostics. A more quantitative measure of the discrepancies between trends is provided by the distributions of differences between trend slopes. Thirdly, maps of the level of significance P of a t -test quantifying the degree to which two trend estimates differ provide a statistical, spatially-resolved, evaluation. The proposed methodology is applied to the multi-mission Ocean Colour-Climate Change Initiative (OC-CCI) Chl a data. The agreement between trend distributions associated with OC-CCI data and single-mission products usually appears as good as when single-mission products are compared. As the period of analysis is extended beyond 2012 to 2015, the level of agreement tends to be degraded, which might be at least partly due to the aging of the MODIS sensor on-board Aqua. On the other hand, the trends displayed by the OC-CCI series over the short period 2012-2015 are very consistent with those observed with VIIRS. These results overall suggest that the OC-CCI Chl a data can be used for multi-annual time

  2. Monitoring soil wetness variations by means of satellite passive microwave observations: the HYDROPTIMET study cases

    Directory of Open Access Journals (Sweden)

    T. Lacava

    2005-01-01

    Full Text Available Soil moisture is an important component of the hydrological cycle. In the framework of modern flood warning systems, the knowledge of soil moisture is crucial, due to the influence on the soil response in terms of infiltration-runoff. Precipitation-runoff processes, in fact, are related to catchment's hydrological conditions before the precipitation. Thus, an estimation of these conditions is of significant importance to improve the reliability of flood warning systems. Combining such information with other weather-related satellite products (i.e. rain rate estimation might represent a useful exercise in order to improve our capability to handle (and possibly mitigate or prevent hydro-geological hazards. Remote sensing, in the last few years, has supported several techniques for soil moisture/wetness monitoring. Most of the satellite-based techniques use microwave data, thanks to the all-weather and all-time capability of these data, as well as to their high sensitivity to water content in the soil. On the other hand, microwave data are unfortunately highly affected by the presence of surface roughness or vegetation coverage within the instantaneous satellite field of view (IFOV. Those problems, consequently, strongly limit the efficiency and the reliability of traditional satellite techniques. Recently, using data coming from AMSU (Advanced Microwave Sounding Unit, flying aboard NOAA (National Oceanic and Atmospheric Administration satellites, a new methodology for soil wetness estimation has been proposed. The proposed index, called Soil Wetness Variation Index (SWVI, developed by a multi-temporal analysis of AMSU records, seems able to reduce the problems related to vegetation and/or roughness effects. Such an approach has been tested, with promising results, on the analysis of some flooding events which occurred in Europe in the past. In this study, results achieved for the HYDROPTIMET test cases will be analysed and discussed in detail

  3. Relationship between satellite microwave radiometric data, antecedent precipitation index, and regional soil moisture

    International Nuclear Information System (INIS)

    Teng, W.L.; Wang, J.R.; Doraiswamy, P.C.

    1993-01-01

    Satellite microwave brightness temperatures (TB 'S) have been shown, in previous studies for semi-arid environments, to correlate well with the antecedent precipitation index (API), a soil moisture indicator. The current study, using the Special Sensor Microwave/Imager (SSM/I), continued this work for parts of the U.S. Corn and Wheat Belts, which included areas with a more humid climate, a denser natural vegetation cover, and a different mix of agricultural crop types. Four years (1987-1990) of SSM/I data at 19 and 37GHz, daily precipitation and temperature data from weather stations, and API calculated from the weather data were processed, geo-referenced, and averaged to equation pending latitude-longitude grid quadrants. Correlation results between TB at 19 GHz and API were highly dependent on geographical location. Correlation coefficients (r values) ranged from —0-6 to —0-85 for the semi-arid parts of the study area and from —03 to —0-7 for the more humid and more densely vegetated parts. R values were also higher for the very dry and very wet years (—0-5 to —085) than for the 'normal’ year (—0-3 to —0-65). Similar to previous results, the Microwave Polarization Difference Index (MPDI), based on the 37 GHz data, was found to correspond to variations in vegetation cover. The MPDI was used to develop a linear regression model to estimate API from TB . Correlation between estimated and calculated APIs was also geographically and time dependent. Comparison of API with some field soil moisture measurements showed a similar trend, which provided some degree of confidence in using API as an indicator of soil moisture

  4. On the Land-Ocean Contrast of Tropical Convection and Microphysics Statistics Derived from TRMM Satellite Signals and Global Storm-Resolving Models

    Science.gov (United States)

    Matsui, Toshihisa; Chern, Jiun-Dar; Tao, Wei-Kuo; Lang, Stephen E.; Satoh, Masaki; Hashino, Tempei; Kubota, Takuji

    2016-01-01

    A 14-year climatology of Tropical Rainfall Measuring Mission (TRMM) collocated multi-sensor signal statistics reveal a distinct land-ocean contrast as well as geographical variability of precipitation type, intensity, and microphysics. Microphysics information inferred from the TRMM precipitation radar and Microwave Imager (TMI) show a large land-ocean contrast for the deep category, suggesting continental convective vigor. Over land, TRMM shows higher echo-top heights and larger maximum echoes, suggesting taller storms and more intense precipitation, as well as larger microwave scattering, suggesting the presence of morelarger frozen convective hydrometeors. This strong land-ocean contrast in deep convection is invariant over seasonal and multi-year time-scales. Consequently, relatively short-term simulations from two global storm-resolving models can be evaluated in terms of their land-ocean statistics using the TRMM Triple-sensor Three-step Evaluation via a satellite simulator. The models evaluated are the NASA Multi-scale Modeling Framework (MMF) and the Non-hydrostatic Icosahedral Cloud Atmospheric Model (NICAM). While both simulations can represent convective land-ocean contrasts in warm precipitation to some extent, near-surface conditions over land are relatively moisture in NICAM than MMF, which appears to be the key driver in the divergent warm precipitation results between the two models. Both the MMF and NICAM produced similar frequencies of large CAPE between land and ocean. The dry MMF boundary layer enhanced microwave scattering signals over land, but only NICAM had an enhanced deep convection frequency over land. Neither model could reproduce a realistic land-ocean contrast in in deep convective precipitation microphysics. A realistic contrast between land and ocean remains an issue in global storm-resolving modeling.

  5. Multi-source Geospatial Data Analysis with Google Earth Engine

    Science.gov (United States)

    Erickson, T.

    2014-12-01

    The Google Earth Engine platform is a cloud computing environment for data analysis that combines a public data catalog with a large-scale computational facility optimized for parallel processing of geospatial data. The data catalog is a multi-petabyte archive of georeferenced datasets that include images from Earth observing satellite and airborne sensors (examples: USGS Landsat, NASA MODIS, USDA NAIP), weather and climate datasets, and digital elevation models. Earth Engine supports both a just-in-time computation model that enables real-time preview and debugging during algorithm development for open-ended data exploration, and a batch computation mode for applying algorithms over large spatial and temporal extents. The platform automatically handles many traditionally-onerous data management tasks, such as data format conversion, reprojection, and resampling, which facilitates writing algorithms that combine data from multiple sensors and/or models. Although the primary use of Earth Engine, to date, has been the analysis of large Earth observing satellite datasets, the computational platform is generally applicable to a wide variety of use cases that require large-scale geospatial data analyses. This presentation will focus on how Earth Engine facilitates the analysis of geospatial data streams that originate from multiple separate sources (and often communities) and how it enables collaboration during algorithm development and data exploration. The talk will highlight current projects/analyses that are enabled by this functionality.https://earthengine.google.org

  6. Scientific analysis of satellite ranging data

    Science.gov (United States)

    Smith, David E.

    1994-01-01

    A network of satellite laser ranging (SLR) tracking systems with continuously improving accuracies is challenging the modelling capabilities of analysts worldwide. Various data analysis techniques have yielded many advances in the development of orbit, instrument and Earth models. The direct measurement of the distance to the satellite provided by the laser ranges has given us a simple metric which links the results obtained by diverse approaches. Different groups have used SLR data, often in combination with observations from other space geodetic techniques, to improve models of the static geopotential, the solid Earth, ocean tides, and atmospheric drag models for low Earth satellites. Radiation pressure models and other non-conservative forces for satellite orbits above the atmosphere have been developed to exploit the full accuracy of the latest SLR instruments. SLR is the baseline tracking system for the altimeter missions TOPEX/Poseidon, and ERS-1 and will play an important role in providing the reference frame for locating the geocentric position of the ocean surface, in providing an unchanging range standard for altimeter calibration, and for improving the geoid models to separate gravitational from ocean circulation signals seen in the sea surface. However, even with the many improvements in the models used to support the orbital analysis of laser observations, there remain systematic effects which limit the full exploitation of SLR accuracy today.

  7. GNSS global real-time augmentation positioning: Real-time precise satellite clock estimation, prototype system construction and performance analysis

    Science.gov (United States)

    Chen, Liang; Zhao, Qile; Hu, Zhigang; Jiang, Xinyuan; Geng, Changjiang; Ge, Maorong; Shi, Chuang

    2018-01-01

    Lots of ambiguities in un-differenced (UD) model lead to lower calculation efficiency, which isn't appropriate for the high-frequency real-time GNSS clock estimation, like 1 Hz. Mixed differenced model fusing UD pseudo-range and epoch-differenced (ED) phase observations has been introduced into real-time clock estimation. In this contribution, we extend the mixed differenced model for realizing multi-GNSS real-time clock high-frequency updating and a rigorous comparison and analysis on same conditions are performed to achieve the best real-time clock estimation performance taking the efficiency, accuracy, consistency and reliability into consideration. Based on the multi-GNSS real-time data streams provided by multi-GNSS Experiment (MGEX) and Wuhan University, GPS + BeiDou + Galileo global real-time augmentation positioning prototype system is designed and constructed, including real-time precise orbit determination, real-time precise clock estimation, real-time Precise Point Positioning (RT-PPP) and real-time Standard Point Positioning (RT-SPP). The statistical analysis of the 6 h-predicted real-time orbits shows that the root mean square (RMS) in radial direction is about 1-5 cm for GPS, Beidou MEO and Galileo satellites and about 10 cm for Beidou GEO and IGSO satellites. Using the mixed differenced estimation model, the prototype system can realize high-efficient real-time satellite absolute clock estimation with no constant clock-bias and can be used for high-frequency augmentation message updating (such as 1 Hz). The real-time augmentation message signal-in-space ranging error (SISRE), a comprehensive accuracy of orbit and clock and effecting the users' actual positioning performance, is introduced to evaluate and analyze the performance of GPS + BeiDou + Galileo global real-time augmentation positioning system. The statistical analysis of real-time augmentation message SISRE is about 4-7 cm for GPS, whlile 10 cm for Beidou IGSO/MEO, Galileo and about 30 cm

  8. Search for Best Astronomical Observatory Sites in the MENA Region using Satellite Measurements

    International Nuclear Information System (INIS)

    Abdelaziz, G; Guebsi, R; Flamant, C; Guessoum, N

    2017-01-01

    We perform a systematic search for astronomical observatory sites in the MENA (Middle-East and North Africa) region using space-based data for all the relevant factors, i.e. altitude (DEM), cloud fraction (CF), light pollution (NTL), precipitable water vapor (PWV), aerosol optical depth (AOD), relative humidity (RH), wind speed (WS), Richardson Number (RN), and diurnal temperature range (DTR). We look for the best locations overall even where altitudes are low (the threshold that we normally consider being 1,500 m) or where the combination of the afore-mentioned determining factors had previously excluded all locations in a given country. In this aim, we use the rich data that Earth-observing satellites provide, e.g. the Terra and Aqua multi-national NASA research satellites, with their MODIS (Moderate Resolution Imaging Spectroradiometer) and AIRS (Atmospheric Infrared Sounder) instruments, the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS), and other products from climate diagnostics archives (e.g. MERRA). We present preliminary results on the best locations for the region. (paper)

  9. Search for Best Astronomical Observatory Sites in the MENA Region using Satellite Measurements

    Science.gov (United States)

    Abdelaziz, G.; Guebsi, R.; Guessoum, N.; Flamant, C.

    2017-06-01

    We perform a systematic search for astronomical observatory sites in the MENA (Middle-East and North Africa) region using space-based data for all the relevant factors, i.e. altitude (DEM), cloud fraction (CF), light pollution (NTL), precipitable water vapor (PWV), aerosol optical depth (AOD), relative humidity (RH), wind speed (WS), Richardson Number (RN), and diurnal temperature range (DTR). We look for the best locations overall even where altitudes are low (the threshold that we normally consider being 1,500 m) or where the combination of the afore-mentioned determining factors had previously excluded all locations in a given country. In this aim, we use the rich data that Earth-observing satellites provide, e.g. the Terra and Aqua multi-national NASA research satellites, with their MODIS (Moderate Resolution Imaging Spectroradiometer) and AIRS (Atmospheric Infrared Sounder) instruments, the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS), and other products from climate diagnostics archives (e.g. MERRA). We present preliminary results on the best locations for the region.

  10. Validation of Satellite Precipitation Products Using Local Rain Gauges to Support Water Assessment in Cochabamba, Bolivia

    Science.gov (United States)

    Saavedra, O.

    2017-12-01

    The metropolitan region of Cochabamba has been struggling for a consistent water supply master plan for years. The limited precipitation intensities and growing water demand have led to severe water conflicts since 2000 when the fight for water had international visibility. A new dam has just placed into operation, located at the mountain range north of the city, which is the hope to fulfill partially water demand in the region. Looking for feasible water sources and projects are essential to fulfill demand. However, the limited monitoring network composed by conventional rain gauges are not enough to come up with the proper aerial precipitation patterns. This study explores the capabilities of GSMaP-GPM satellite products combined with local rain gauge network to obtain an enhanced product with spatial and temporal resolution. A simple methodology based on penalty factors is proposed to adjust GSMaP-GPM intensities on grid-by-grid basis. The distance of an evaluated grid to the surrounding rain gauges was taken into account. The final correcting factors were obtained by iteration, at this particular case of study four iterations were enough to reduce the relative error. A distributed hydrological model was forced with the enhanced precipitation product to simulate the inflow to the new operating dam. Once the model parameters were calibrated and validated, forecast simulations were run. For the short term, the precipitation trend was projected using exponential equation. As for the long term projection, precipitation and temperature from the hadGEM2 and MIROC global circulation model outputs were used where the last one was found in closer agreement of predictions in the past. Overall, we found out that the amount of 1000 l/s for water supply to the region should be possible to fulfill till 2030. Beyond this year, the intake of two neighboring basins should be constructed to increase the stored volume. This is study was found particularly useful to forecast river

  11. Geospatial Information from Satellite Imagery for Geovisualisation of Smart Cities in India

    Science.gov (United States)

    Mohan, M.

    2016-06-01

    In the recent past, there have been large emphasis on extraction of geospatial information from satellite imagery. The Geospatial information are being processed through geospatial technologies which are playing important roles in developing of smart cities, particularly in developing countries of the world like India. The study is based on the latest geospatial satellite imagery available for the multi-date, multi-stage, multi-sensor, and multi-resolution. In addition to this, the latest geospatial technologies have been used for digital image processing of remote sensing satellite imagery and the latest geographic information systems as 3-D GeoVisualisation, geospatial digital mapping and geospatial analysis for developing of smart cities in India. The Geospatial information obtained from RS and GPS systems have complex structure involving space, time and presentation. Such information helps in 3-Dimensional digital modelling for smart cities which involves of spatial and non-spatial information integration for geographic visualisation of smart cites in context to the real world. In other words, the geospatial database provides platform for the information visualisation which is also known as geovisualisation. So, as a result there have been an increasing research interest which are being directed to geospatial analysis, digital mapping, geovisualisation, monitoring and developing of smart cities using geospatial technologies. However, the present research has made an attempt for development of cities in real world scenario particulary to help local, regional and state level planners and policy makers to better understand and address issues attributed to cities using the geospatial information from satellite imagery for geovisualisation of Smart Cities in emerging and developing country, India.

  12. A multi-sensor data-driven methodology for all-sky passive microwave inundation retrieval

    Science.gov (United States)

    Takbiri, Zeinab; Ebtehaj, Ardeshir M.; Foufoula-Georgiou, Efi

    2017-06-01

    We present a multi-sensor Bayesian passive microwave retrieval algorithm for flood inundation mapping at high spatial and temporal resolutions. The algorithm takes advantage of observations from multiple sensors in optical, short-infrared, and microwave bands, thereby allowing for detection and mapping of the sub-pixel fraction of inundated areas under almost all-sky conditions. The method relies on a nearest-neighbor search and a modern sparsity-promoting inversion method that make use of an a priori dataset in the form of two joint dictionaries. These dictionaries contain almost overlapping observations by the Special Sensor Microwave Imager and Sounder (SSMIS) on board the Defense Meteorological Satellite Program (DMSP) F17 satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua and Terra satellites. Evaluation of the retrieval algorithm over the Mekong Delta shows that it is capable of capturing to a good degree the inundation diurnal variability due to localized convective precipitation. At longer timescales, the results demonstrate consistency with the ground-based water level observations, denoting that the method is properly capturing inundation seasonal patterns in response to regional monsoonal rain. The calculated Euclidean distance, rank-correlation, and also copula quantile analysis demonstrate a good agreement between the outputs of the algorithm and the observed water levels at monthly and daily timescales. The current inundation products are at a resolution of 12.5 km and taken twice per day, but a higher resolution (order of 5 km and every 3 h) can be achieved using the same algorithm with the dictionary populated by the Global Precipitation Mission (GPM) Microwave Imager (GMI) products.

  13. A multi-sensor data-driven methodology for all-sky passive microwave inundation retrieval

    Directory of Open Access Journals (Sweden)

    Z. Takbiri

    2017-06-01

    Full Text Available We present a multi-sensor Bayesian passive microwave retrieval algorithm for flood inundation mapping at high spatial and temporal resolutions. The algorithm takes advantage of observations from multiple sensors in optical, short-infrared, and microwave bands, thereby allowing for detection and mapping of the sub-pixel fraction of inundated areas under almost all-sky conditions. The method relies on a nearest-neighbor search and a modern sparsity-promoting inversion method that make use of an a priori dataset in the form of two joint dictionaries. These dictionaries contain almost overlapping observations by the Special Sensor Microwave Imager and Sounder (SSMIS on board the Defense Meteorological Satellite Program (DMSP F17 satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS on board the Aqua and Terra satellites. Evaluation of the retrieval algorithm over the Mekong Delta shows that it is capable of capturing to a good degree the inundation diurnal variability due to localized convective precipitation. At longer timescales, the results demonstrate consistency with the ground-based water level observations, denoting that the method is properly capturing inundation seasonal patterns in response to regional monsoonal rain. The calculated Euclidean distance, rank-correlation, and also copula quantile analysis demonstrate a good agreement between the outputs of the algorithm and the observed water levels at monthly and daily timescales. The current inundation products are at a resolution of 12.5 km and taken twice per day, but a higher resolution (order of 5 km and every 3 h can be achieved using the same algorithm with the dictionary populated by the Global Precipitation Mission (GPM Microwave Imager (GMI products.

  14. The retrieval of cloud microphysical properties using satellite measurements and an in situ database

    Directory of Open Access Journals (Sweden)

    C. Poix

    1996-01-01

    Full Text Available By combining AVHRR data from the NOAA satellites with information from a database of in situ measurements, large-scale maps can be generated of the microphysical parameters most immediately significant for the modelling of global circulation and climate. From the satellite data, the clouds can be classified into cumuliform, stratiform and cirrus classes and then into further sub-classes by cloud top temperature. At the same time a database of in situ measurements made by research aircraft is classified into the same sub-classes and a statistical analysis is used to derive relationships between the sub-classes and the cloud microphysical properties. These two analyses are then linked to give estimates of the microphysical properties of the satellite observed clouds. Examples are given of the application of this technique to derive maps of the probability of occurrence of precipitating clouds and of precipitating water content derived from a case study within the International Cirrus Experiment (ICE held in 1989 over the North Sea.

  15. The retrieval of cloud microphysical properties using satellite measurements and an in situ database

    Directory of Open Access Journals (Sweden)

    Christophe Poix

    Full Text Available By combining AVHRR data from the NOAA satellites with information from a database of in situ measurements, large-scale maps can be generated of the microphysical parameters most immediately significant for the modelling of global circulation and climate. From the satellite data, the clouds can be classified into cumuliform, stratiform and cirrus classes and then into further sub-classes by cloud top temperature. At the same time a database of in situ measurements made by research aircraft is classified into the same sub-classes and a statistical analysis is used to derive relationships between the sub-classes and the cloud microphysical properties. These two analyses are then linked to give estimates of the microphysical properties of the satellite observed clouds. Examples are given of the application of this technique to derive maps of the probability of occurrence of precipitating clouds and of precipitating water content derived from a case study within the International Cirrus Experiment (ICE held in 1989 over the North Sea.

  16. Multi-annual changes of NOx emissions in megacity regions: nonlinear trend analysis of satellite measurement based estimates

    Directory of Open Access Journals (Sweden)

    J. P. Burrows

    2010-09-01

    Full Text Available Hazardous impact of air pollutant emissions from megacities on atmospheric composition on regional and global scales is currently an important issue in atmospheric research. However, the quantification of emissions and related effects is frequently a difficult task, especially in the case of developing countries, due to the lack of reliable data and information. This study examines possibilities to retrieve multi-annual NOx emissions changes in megacity regions from satellite measurements of nitrogen dioxide and to quantify them in terms of linear and nonlinear trends. By combining the retrievals of the GOME and SCIAMACHY satellite instrument data with simulations performed by the CHIMERE chemistry transport model, we obtain the time series of NOx emission estimates for the 12 largest urban agglomerations in Europe and the Middle East in the period from 1996 to 2008. We employ then a novel method allowing estimation of a nonlinear trend in a noisy time series of an observed variable. The method is based on the probabilistic approach and the use of artificial neural networks; it does not involve any quantitative a priori assumptions. As a result, statistically significant nonlinearities in the estimated NOx emission trends are detected in 5 megacities (Bagdad, Madrid, Milan, Moscow and Paris. Statistically significant upward linear trends are detected in Istanbul and Tehran, while downward linear trends are revealed in Berlin, London and the Ruhr agglomeration. The presence of nonlinearities in NOx emission changes in Milan, Paris and Madrid is confirmed by comparison of simulated NOx concentrations with independent air quality monitoring data. A good quantitative agreement between the linear trends in the simulated and measured near surface NOx concentrations is found in London.

  17. Global precipitations and climate change. Proceedings

    International Nuclear Information System (INIS)

    Desbois, M.; Desalmand, F.

    1994-01-01

    The workshop reviewed the present status of knowledge concerning the past and present evolution of the distribution of precipitations at global scale, related to climate evolution at different time scales. This review was intended to assess the availability and quality of data which could help, through validation and initialization of model studies, to improve our understanding of the processes determining these precipitation changes. On another hand, the modelling specialists presented their actual use of precipitation data. Exchanges of views between the modelling and observing communities were thus made possible, leading to a set of recommendations for future studies. Sessions were then devoted to specific themes: 1) Paleoclimatology, 2) data collection, history and statistics, programmes, 3) methodologies and accuracy of large scale estimation of precipitation from conventional data, 4) estimation of precipitation from satellite data, 5) modelling studies. (orig.)

  18. Monitoring mass changes in the Volta River basin using GRACE satellite gravity and TRMM precipitation

    Directory of Open Access Journals (Sweden)

    Vagner G. Ferreira

    Full Text Available GRACE satellite gravity data was used to estimate mass changes within the Volta River basin in West African for the period of January, 2005 to December, 2010. We also used the precipitation data from the Tropical Rainfall Measurement Mission (TRMM to determine relative contributions source to the seasonal hydrological balance within the Volta River basin. We found out that the seasonal mass change tends to be detected by GRACE for periods from 1 month in the south to 4 months in the north of the basin after the rainfall events. The results suggested a significant gain in water storage in the basin at reference epoch 2007.5 and a dominant annual cycle for the period under consideration for both in the mass changes and rainfall time series. However, there was a low correlation between mass changes and rainfall implying that there must be other processes which cause mass changes without rainfall in the upstream of the Volta River basin.

  19. Ganga floods of 2010 in Uttar Pradesh, north India: a perspective analysis using satellite remote sensing data

    Directory of Open Access Journals (Sweden)

    C.M. Bhatt

    2016-03-01

    Full Text Available The present study focuses on the unprecedented flood situation captured through multi-temporal satellite images, witnessed along the Ganga River in Uttar Pradesh during September 2010. At three gauge stations (Kannauj, Ankinghat and Kanpur, river water level exceeded the previous high-flood level attained by river more than a decade ago. The present communication with the aid of pre- and post-flood satellite images, coupled with hydrological (river water level and meteorological (rainfall data, explains about the unprecedented flood situation. In the latter part of the study, a novel and cost-effective method for building a library of flood inundation extents based on historical satellite data analysis and tagging the inundation layer with observed water level is demonstrated. During flood season, based on the forecasted water level, the library can be accessed to fetch the spatial inundation layer corresponding to the forecasted stage and anticipate in advance, likely spatial inundation pattern and submergence of villages and hence in alerting the habitation at risk. This method can be helpful in anticipating the areas to be affected in situations where satellite images cannot be effectively utilized due to cloud cover and also for providing information about the areas being partially covered in satellite data.

  20. Analysis of the Effect of Interior Nudging on Temperature and Precipitation Distributions of Multi-year Regional Climate Simulations

    Science.gov (United States)

    Nolte, C. G.; Otte, T. L.; Bowden, J. H.; Otte, M. J.

    2010-12-01

    There is disagreement in the regional climate modeling community as to the appropriateness of the use of internal nudging. Some investigators argue that the regional model should be minimally constrained and allowed to respond to regional-scale forcing, while others have noted that in the absence of interior nudging, significant large-scale discrepancies develop between the regional model solution and the driving coarse-scale fields. These discrepancies lead to reduced confidence in the ability of regional climate models to dynamically downscale global climate model simulations under climate change scenarios, and detract from the usability of the regional simulations for impact assessments. The advantages and limitations of interior nudging schemes for regional climate modeling are investigated in this study. Multi-year simulations using the WRF model driven by reanalysis data over the continental United States at 36km resolution are conducted using spectral nudging, grid point nudging, and for a base case without interior nudging. The means, distributions, and inter-annual variability of temperature and precipitation will be evaluated in comparison to regional analyses.

  1. Precipitation and Phase Transformations in 2101 Lean Duplex Stainless Steel During Isothermal Aging

    Science.gov (United States)

    Maetz, Jean-Yves; Cazottes, Sophie; Verdu, Catherine; Kleber, Xavier

    2016-01-01

    The effect of isothermal aging at 963 K (690 °C) on the microstructure of a 2101 lean duplex stainless steel, with the composition Fe-21.5Cr-5Mn-1.6Ni-0.22N-0.3Mo, was investigated using a multi-technique and multi-scale approach. The kinetics of phase transformation and precipitation was followed from a few minutes to thousands of hours using thermoelectric power measurements; based on these results, certain aging states were selected for electron microscopy characterization. Scanning electron microscopy, electron back-scattered diffraction, and transmission electron microscopy were used to quantitatively describe the microstructural evolution through crystallographic analysis, chemical analysis, and volume fraction measurements from the macroscopic scale down to the nanometric scale. During aging, the precipitation of M23C6 carbides, Cr2N nitrides, and σ phase as well as the transformation of ferrite into austenite and austenite into martensite was observed. These complex microstructural changes are controlled by Cr volume diffusion. The precipitation and phase transformation mechanisms are described.

  2. Future Temperatures and Precipitations in the Arid Northern-Central Chile: A Multi-Model Downscaling Approach

    Science.gov (United States)

    Souvignet, M.; Heinrich, J.

    2010-03-01

    Downscaling of global climate outputs is necessary to transfer projections of potential climate change scenarios to local levels. This is of special interest to dry mountainous areas, which are particularly vulnerable to climate change due to risks of reduced freshwater availability. These areas play a key role for hydrology since they usually receive the highest local precipitation rates stored in form of snow and glaciers. In the central-northern Chile (Norte Chico, 26-33ºS), where agriculture still serves as a backbone of the economy as well as ensures the well being of people, the knowledge of water resources availability is essential. The region is characterised by a semiarid climate with a mean annual precipitation inferior to 100mm. Moreover, the local climate is also highly influenced by the ENSO phenomenon, which accounts for the strong inter-annual variability in precipitation patterns. Although historical and spatially extensive precipitation data in the headwaters of the basins in this region are not readily available, records at coastal stations show worrisome trends. For instance, the average precipitation in La Serena, the most important city located in the Coquimbo Region, has decreased dramatically in the past 100 years. The 30-year monthly average has decreased from 170 mm in the early 20th century to values less than 80 mm nowadays. Climate Change is expected to strengthen this pattern in the region, and therefore strongly influence local hydrological patterns. The objectives of this study are i) to develop climate change scenarios (2046-2099) for the Norte Chico using multi-model predictions in terms of temperatures and precipitations, and ii) to compare the efficiency of two downscaling techniques in arid mountainous regions. In addition, this study aims at iii) providing decision makers with sound analysis of potential impact of Climate Change on streamflow in the region. For the present study, future local climate scenarios were developed

  3. NESDIS Blended Total Precipitable Water (TPW) Products

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The blended Total Precipitable Water (TPW) product is derived from multiple sensors/satellites. The Percentage of TPW normal (PCT), or TPW anomaly, shows the...

  4. Temperature-dependent daily variability of precipitable water in special sensor microwave/imager observations

    Science.gov (United States)

    Gutowski, William J.; Lindemulder, Elizabeth A.; Jovaag, Kari

    1995-01-01

    We use retrievals of atmospheric precipitable water from satellite microwave observations and analyses of near-surface temperature to examine the relationship between these two fields on daily and longer time scales. The retrieval technique producing the data used here is most effective over the open ocean, so the analysis focuses on the southern hemisphere's extratropics, which have an extensive ocean surface. For both the total and the eddy precipitable water fields, there is a close correspondence between local variations in the precipitable water and near-surface temperature. The correspondence appears particularly strong for synoptic and planetary scale transient eddies. More specifically, the results support a typical modeling assumption that transient eddy moisture fields are proportional to transient eddy temperature fields under the assumption f constant relative humidity.

  5. The Lightning Mapping Imager (LMI) on the FY-4 satellite and a typical application experiment using the LMI data

    Science.gov (United States)

    Huang, F.; Hui, W.; Li, X.; Liu, R.; Zhang, Z.; Zheng, Y.; Kang, N.

    2017-12-01

    The Lightning Mapping Imager (LMI) on the FY-4A satellite, which was launched successfully in December 2016, is the first satellite-based lightning detector from space independently developed in China, and one of the world's first two stationary satellite LMIs. The optical imaging technique with a 400x600 CCD array plane and a frequency of 500 frames/s is adopted in the FY-4A LMI to perform real-time and continuous observation of total lightening in the Chinese mainland and adjacent areas. As of July 2017, the in-orbit test shows that the lightening observation date could be accurately obtained by the FY-4A LMI, and that the geo-location could be verified by the ground lightening observation network over China. Since the beginning of the 2017 flood season, every process of strong thunderstorms has been monitored by the FY-4A LMI throughout the various areas of China, and of these are used as a typical application case in this talk. On April 8 and 9, 2017, a strong convective precipitation process occurred in the middle-lower reaches of the Yangtze River, China. The observation data of the FY-4A LMI are used to monitor the occurrence, development, shift and extinction of the thunderstorm track. By means of analyzing the station's synchronous precipitation observation data, it is indicated that the moving track of the thunderstorm is not completely consistent with that of the precipitation center, and while the distribution areas of thunderstorm and precipitation are consistent to a certain extent, a significant difference also exists. This difference is mainly caused by the convective precipitation and stratus precipitation area during the precipitation process. Through comparative analysis, the preliminary satellite and foundation lightening observation data show a higher consistency. However, the time of lightening activity observed by satellite is one hour earlier than that of the ground observation, which is likely related to the total lightning observation by

  6. CDRD and PNPR passive microwave precipitation retrieval algorithms: verification study over Africa and Southern Atlantic

    Science.gov (United States)

    Panegrossi, Giulia; Casella, Daniele; Cinzia Marra, Anna; Petracca, Marco; Sanò, Paolo; Dietrich, Stefano

    2015-04-01

    to all available PMW radiometers in the GPM constellation of satellites (including NPP Suomi ATMS, and GMI). Three years of SSMIS and AMSU/MHS data have been considered to carry out a verification study over Africa of the retrievals from the CDRD and PNPR algorithms. The precipitation products from the TRMM ¬Precipitation radar (PR) (TRMM product 2A25 and 2A23) have been used as ground truth. The results of this study aimed at assessing the accuracy of the precipitation retrievals in different climatic regions and precipitation regimes will be presented. Particular emphasis will be given to the analysis of the level of coherence of the precipitation estimates and patterns between the two algorithms exploiting different radiometers. Recent developments aimed at the full exploitation of the GPM constellation of satellites for optimal precipitation/drought monitoring will be also presented.

  7. Spatiotemporal Analysis of Extreme Hourly Precipitation Patterns in Hainan Island, South China

    Directory of Open Access Journals (Sweden)

    Wenjie Chen

    2015-05-01

    Full Text Available To analyze extreme precipitation patterns in Hainan Island, hourly precipitation datasets from 18 stations, for the period from 1967 to 2012, were investigated. Two precipitation concentration indices (PCI and 11 extreme precipitation indices (EPI were chosen. PCI1 indicated a moderate seasonality in yearly precipitation and PCI2 showed that at least 80% of the total precipitation fell in 20% of the rainiest hours. Furthermore, the spatial variations of PCI1 and PCI2 differed. Linear regression indicated increasing trends in 11 of the calculated EPI. Principal component analysis found that the first recalculated principal component represented the 11 EPI. The recalculated principal component revealed an increasing trend in precipitation extremes for the whole island (except the interior section. Trend stability analysis of several of EPI suggested that the southern parts of Hainan Island, and especially the city of Sanya, should receive more attention to establish the drainage facilities necessary to prevent waterlogging.

  8. Global Precipitation Climatology Project (GPCP) Climate Data Record (CDR), Version 2.3 (Monthly)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Precipitation Climatology Project (GPCP) consists of monthly satellite-gauge and associated precipitation error estimates and covers the period January...

  9. Diagnosis of inconsistencies in multi-year gridded precipitation data over mountainous areas and related impacts on hydrologic simulations

    Science.gov (United States)

    Mizukami, N.; Smith, M. B.

    2010-12-01

    It is common for the error characteristics of long-term precipitation data to change over time due to various factors such as gauge relocation and changes in data processing methods. The temporal consistency of precipitation data error characteristics is as important as data accuracy itself for hydrologic model calibration and subsequent use of the calibrated model for streamflow prediction. In mountainous areas, the generation of precipitation grids relies on sparse gage networks, the makeup of which often varies over time. This causes a change in error characteristics of the long-term precipitation data record. We will discuss the diagnostic analysis of the consistency of gridded precipitation time series and illustrate the adverse effect of inconsistent precipitation data on a hydrologic model simulation. We used hourly 4 km gridded precipitation time series over a mountainous basin in the Sierra Nevada Mountains of California from October 1988 through September 2006. The basin is part of the broader study area that served as the focus of the second phase of the Distributed Model Intercomparison Project (DMIP-2), organized by the U.S. National Weather Service (NWS) of the National Oceanographic and Atmospheric Administration (NOAA). To check the consistency of the gridded precipitation time series, double mass analysis was performed using single pixel and basin mean areal precipitation (MAP) values derived from gridded DMIP-2 and Parameter-Elevation Regressions on Independent Slopes Model (PRISM) precipitation data. The analysis leads to the conclusion that over the entire study time period, a clear change in error characteristics in the DMIP-2 data occurred in the beginning of 2003. This matches the timing of one of the major gage network changes. The inconsistency of two MAP time series computed from the gridded precipitation fields over two elevation zones was corrected by adjusting hourly values based on the double mass analysis. We show that model

  10. Bias Correction of Satellite Precipitation Products (SPPs) using a User-friendly Tool: A Step in Enhancing Technical Capacity

    Science.gov (United States)

    Rushi, B. R.; Ellenburg, W. L.; Adams, E. C.; Flores, A.; Limaye, A. S.; Valdés-Pineda, R.; Roy, T.; Valdés, J. B.; Mithieu, F.; Omondi, S.

    2017-12-01

    SERVIR, a joint NASA-USAID initiative, works to build capacity in Earth observation technologies in developing countries for improved environmental decision making in the arena of: weather and climate, water and disasters, food security and land use/land cover. SERVIR partners with leading regional organizations in Eastern and Southern Africa, Hindu Kush-Himalaya, Mekong region, and West Africa to achieve its objectives. SERVIR develops hydrological applications to address specific needs articulated by key stakeholders and daily rainfall estimates are a vital input for these applications. Satellite-derived rainfall is subjected to systemic biases which need to be corrected before it can be used for any hydrologic application such as real-time or seasonal forecasting. SERVIR and the SWAAT team at the University of Arizona, have co-developed an open-source and user friendly tool of rainfall bias correction approaches for SPPs. Bias correction tools were developed based on Linear Scaling and Quantile Mapping techniques. A set of SPPs, such as PERSIANN-CCS, TMPA-RT, and CMORPH, are bias corrected using Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data which incorporates ground based precipitation observations. This bias correction tools also contains a component, which is included to improve monthly mean of CHIRPS using precipitation products of the Global Surface Summary of the Day (GSOD) database developed by the National Climatic Data Center (NCDC). This tool takes input from command-line which makes it user-friendly and applicable in any operating platform without prior programming skills. This presentation will focus on this bias-correction tool for SPPs, including application scenarios.

  11. Under which climate and soil conditions the plant productivity-precipitation relationship is linear or nonlinear?

    Science.gov (United States)

    Ye, Jian-Sheng; Pei, Jiu-Ying; Fang, Chao

    2018-03-01

    Understanding under which climate and soil conditions the plant productivity-precipitation relationship is linear or nonlinear is useful for accurately predicting the response of ecosystem function to global environmental change. Using long-term (2000-2016) net primary productivity (NPP)-precipitation datasets derived from satellite observations, we identify >5600pixels in the North Hemisphere landmass that fit either linear or nonlinear temporal NPP-precipitation relationships. Differences in climate (precipitation, radiation, ratio of actual to potential evapotranspiration, temperature) and soil factors (nitrogen, phosphorous, organic carbon, field capacity) between the linear and nonlinear types are evaluated. Our analysis shows that both linear and nonlinear types exhibit similar interannual precipitation variabilities and occurrences of extreme precipitation. Permutational multivariate analysis of variance suggests that linear and nonlinear types differ significantly regarding to radiation, ratio of actual to potential evapotranspiration, and soil factors. The nonlinear type possesses lower radiation and/or less soil nutrients than the linear type, thereby suggesting that nonlinear type features higher degree of limitation from resources other than precipitation. This study suggests several factors limiting the responses of plant productivity to changes in precipitation, thus causing nonlinear NPP-precipitation pattern. Precipitation manipulation and modeling experiments should combine with changes in other climate and soil factors to better predict the response of plant productivity under future climate. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Advantages of Using Microwave Satellite Soil Moisture over Gridded Precipitation Products and Land Surface Model Output in Assessing Regional Vegetation Water Availability and Growth Dynamics for a Lateral Inflow Receiving Landscape

    NARCIS (Netherlands)

    Chen, T.; McVicar, T.R.; Wang, G.J.; Chen, X.; de Jeu, R.A.M.; Liu, Y.; Shen, H.; Zhang, F.; Dolman, A.J.

    2016-01-01

    To improve the understanding of water-vegetation relationships, direct comparative studies assessing the utility of satellite remotely sensed soil moisture, gridded precipitation products, and land surface model output are needed. A case study was investigated for a water-limited, lateral inflow

  13. Is precipitation a predictor of mortality in Bangladesh? A multi-stratified analysis in a South Asian monsoon climate.

    Science.gov (United States)

    Burkart, Katrin; Kinney, Patrick

    2016-05-15

    While numerous studies have assessed the association between temperature and mortality in various locations, few have addressed the relationship between precipitation and mortality. Given the high amounts of rainfall in many tropical monsoon areas and the often seasonally pronounced differences, there might be a potentially strong impact on health outcomes and death. In this study, we investigated the association between precipitation and daily death counts in Bangladesh from 2003 to 2007 using regression models with a quasipoisson distribution adjusting for long-term time and seasonal trends, day of the month, age and perceived temperature. Effects were assessed for all ages, the elderly and by gender. During the dry season a sharp increase in death risk was found at very high precipitation amounts which are most likely to be cyclone-related. This cyclone effect was most pronounced for females at the immediate day with an increase of 18.7% (3.8-35.6%) in non-external cause mortality per mm precipitation above 5mm. At longer lags we found a negative association between precipitation and mortality indicating some kind of dry effect which was more pronounced for the elderly with a mortality increase of 4.4% (2.6-6.2%) per mm decrease in precipitation. During the rainy season, we observed a protective effect of rainfall which was strongest during periods of seasonally high equivalent temperatures with a decrease in mortality of 4.0% (2.3-5.6%) per mm increase in precipitation on the immediate day. The observed associations between precipitation and mortality differed by season, age and gender. Generally, a strong short-term increase in mortality was associated with cyclonic activity during the dry season, while ongoing low rainfall seemed to have an adverse impact at higher lags. During the rainy season, precipitation seemed to mitigate heat effects. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Evaluation of Remotely Sensed Precipitation and its Performance for Streamflow Simulations in Basins of the Southeast Tibetan Plateau

    DEFF Research Database (Denmark)

    Wang, Sheng; Liu, Suxia; Mo, Xingguo

    2015-01-01

    along with the CMORPH gauge–satellite blended version (C-ga), which is virtually C-adj in precipitation ungauged regions and is controlled by gauge analysis over regions of a dense station network, were intercompared with daily streamflow predicted by the distributed vegetation interface processes (VIP...

  15. Precipitation-generated oscillations in open cellular cloud fields.

    Science.gov (United States)

    Feingold, Graham; Koren, Ilan; Wang, Hailong; Xue, Huiwen; Brewer, Wm Alan

    2010-08-12

    Cloud fields adopt many different patterns that can have a profound effect on the amount of sunlight reflected back to space, with important implications for the Earth's climate. These cloud patterns can be observed in satellite images of the Earth and often exhibit distinct cell-like structures associated with organized convection at scales of tens of kilometres. Recent evidence has shown that atmospheric aerosol particles-through their influence on precipitation formation-help to determine whether cloud fields take on closed (more reflective) or open (less reflective) cellular patterns. The physical mechanisms controlling the formation and evolution of these cells, however, are still poorly understood, limiting our ability to simulate realistically the effects of clouds on global reflectance. Here we use satellite imagery and numerical models to show how precipitating clouds produce an open cellular cloud pattern that oscillates between different, weakly stable states. The oscillations are a result of precipitation causing downward motion and outflow from clouds that were previously positively buoyant. The evaporating precipitation drives air down to the Earth's surface, where it diverges and collides with the outflows of neighbouring precipitating cells. These colliding outflows form surface convergence zones and new cloud formation. In turn, the newly formed clouds produce precipitation and new colliding outflow patterns that are displaced from the previous ones. As successive cycles of this kind unfold, convergence zones alternate with divergence zones and new cloud patterns emerge to replace old ones. The result is an oscillating, self-organized system with a characteristic cell size and precipitation frequency.

  16. Multi-satellite climatologies of fundamental atmospheric variables from Radio Occulation and their validation

    International Nuclear Information System (INIS)

    Pirscher, B.

    2010-01-01

    Monitoring of global climate change requires high quality observations not only on the Earths surface but also in the free atmosphere. Global Positioning System (GPS) Radio Occultation (RO) observations are known to have the potential to deliver very accurate, precise, and long-term stable measurements between about 8 km and 30 km altitude.This thesis investigates the suitability of RO observations to serve as climate benchmark record by validating the consistency of RO data provided by different satellites. The main focus lies on systematic differences of RO climatologies, originating from different data processing, data quality, spatio-temporal sampling, and particular orbit characteristics. Data of six RO satellite missions (including one multi-satellite constellation) are analyzed. Largest disagreements of RO climatologies are observed when comparing data provided by different processing centers. Mean absolute temperature differences between 8 km and 30 km altitude amount to 0.5 K, while climate time series of temperature changes agree much closer.Utilizing RO data from the same data center and considering space-temporal sampling yields remarkable consistency of temperature climatologies with mean differences being smaller than 0.1 K. Disagreements are found to be largest at 35 km, where they exceed 0.2 K. This results from different data quality and its utilization within the processing scheme. Climatologies, which are derived from data with the same quality agree to within 0.02 K also at high altitudes. The measurements local time, which depends on the satellites orbit, has a minor but clearly understandable influence on differences in RO climatologies. The results underline the utility of RO data for long-term monitoring of the global climate. (author) [de

  17. Space environment monitoring by low-altitude operational satellites

    International Nuclear Information System (INIS)

    Kroehl, H.W.

    1982-01-01

    The primary task of the Defense Meteorological Satellite Program (DMSP) is the acquisition of meteorological data in the visual and infrared spectral regions. The Air Weather Service operates two satellites in low-altitude, sun-synchronous, polar orbits at 850 km altitude, 98.7 deg inclination, 101.5 minute period and dawn-dusk or noon-midnight equatorial crossing times. Special DMSP sensors of interest to the space science community are the precipitating electron spectrometer, the terrestrial noise receiver, and the topside ionosphere plasma monitor. Data from low-altitude, meteorological satellites can be used to build empirical models of precipitating electron characteristics of the auroral zone and polar cap. The Tiros-NOAA satellite program complements the DMSP program. The orbital elements are the same as DMSP's, except for the times of equatorial crossing, and the tilt of the orbital plane. The Tiros-NOAA program meets the civilian community's needs for meteorological data as the DMSP program does for the military

  18. GEOSPATIAL INFORMATION FROM SATELLITE IMAGERY FOR GEOVISUALISATION OF SMART CITIES IN INDIA

    Directory of Open Access Journals (Sweden)

    M. Mohan

    2016-06-01

    Full Text Available In the recent past, there have been large emphasis on extraction of geospatial information from satellite imagery. The Geospatial information are being processed through geospatial technologies which are playing important roles in developing of smart cities, particularly in developing countries of the world like India. The study is based on the latest geospatial satellite imagery available for the multi-date, multi-stage, multi-sensor, and multi-resolution. In addition to this, the latest geospatial technologies have been used for digital image processing of remote sensing satellite imagery and the latest geographic information systems as 3-D GeoVisualisation, geospatial digital mapping and geospatial analysis for developing of smart cities in India. The Geospatial information obtained from RS and GPS systems have complex structure involving space, time and presentation. Such information helps in 3-Dimensional digital modelling for smart cities which involves of spatial and non-spatial information integration for geographic visualisation of smart cites in context to the real world. In other words, the geospatial database provides platform for the information visualisation which is also known as geovisualisation. So, as a result there have been an increasing research interest which are being directed to geospatial analysis, digital mapping, geovisualisation, monitoring and developing of smart cities using geospatial technologies. However, the present research has made an attempt for development of cities in real world scenario particulary to help local, regional and state level planners and policy makers to better understand and address issues attributed to cities using the geospatial information from satellite imagery for geovisualisation of Smart Cities in emerging and developing country, India.

  19. Regional model simulation of the North Atlantic cyclone "Caroline" and comparisons with satellite data

    Directory of Open Access Journals (Sweden)

    E. Keup-Thiel

    2003-03-01

    Full Text Available An individual regional model simulation of cyclone "Caroline" has been carried out to study water cycle components over the North Atlantic Ocean. The uncertainties associated with quantitative estimates of the water cycle components are highlighted by a comparison of the model results with SSM/I (Special Sensor Microwave Imager satellite data. The vertically integrated water vapor of the REgional MOdel REMO is in good agreement with the SSM/I satellite data. The simulation results for other water budget components like the vertically integrated liquid water content and precipitation compare also reasonably well within the frontal system. However, the high precipitation rate in the cold air outbreak on the backside of the cold front derived from SSM/I satellite data is generally underestimated by REMO. This results in a considerable deficit of the total precipitation amount accumulated for the cyclone "Caroline". While REMO simulates 24.3 108 m3 h-1 for 09:00 UTC, the total areal precipitation from SSM/I satellite data amounts to 54.7 08 m3 h-1.Key words. Meteorology and atmospheric dynamics (precipitation; mesoscale meteorology – Radio science (remote sensing

  20. Wildfire Dynamics and Occasional Precipitation during Active Fire Season in Tropical Lowland of Nepal

    Directory of Open Access Journals (Sweden)

    Krishna Bahadur Bhujel

    2017-10-01

    Full Text Available Occasional precipitation plays a vital role in reducing the effect of wildfire. This precipitation is especially important for countries like Nepal, where wildfires are a common seasonal event. Approximately 0.1 million hectare of forest area is affected annually due to wildfires in active fire season. The study on the relation of these forms of occasional precipitation with wildfire incidence is still lacking. This research was objectively carried out to examine the correlation of occasional precipitation with wildfire incidence and burnt area. The Moderate Resolution Imaging Spector-Radiometer (MODIS satellite images and precipitation records for 15 years gathered from Department of Hydrology and Metrology were used as input data for this study. The images were analyzed by using ArcGIS function while the precipitation records were analyzed by using Statistical Package for the Social Science (SPSS program. The linear regression model was applied to find correlation of occasional precipitation with wildfire incidence and burnt area. Analysis revealed decreasing trend of precipitation in study area. We found significant correlation (p<0.05 of precipitation with wildfire incidence and burnt area. Findings will be useful for policy makers, implementers and researchers to manage wildfire in sustainable basis.

  1. Geospatial analysis of creeks evolution in the Indus Delta, Pakistan using multi sensor satellite data

    Science.gov (United States)

    Ijaz, Muhammad Wajid; Mahar, Rasool Bux; Siyal, Altaf Ali; Anjum, Muhammad Naveed

    2018-01-01

    Sea level rise (SLR) in response to looming climate change is being considered as a major impediment to coastal areas. Acute wave activities and tidal propagations of semi-diurnal to mixed type are impairing the morphology of the Indus Delta in Pakistan. In this study a synthetic approach has been adopted using multi sensor satellite and ground data in order to integrate the individual effect of topography, oceanic activities and vegetative canopy for deduction of a synergic impact over the morphology of the Indus Delta creeks system from 1972 to 2017. Geomorphologic anomalies in the planform of fourteen major creeks were explored. Spatiotemporal variations suggested that a substantial amount of the delta alluvium had been engulfed by the Arabian Sea. On average, the creeks located on the right side of the Indus River were relatively less wide (3.9 km) than those of on the left side (5.2 km). Zonal statistics calculated with topographic position index (TPI) enabled to understand the tide induced inundation extents. The mangrove canopy on the right side was found greater, which is why tidal basins on that side experienced less erosive activities. Thus, it could be maintained that the coastal sedimentary processes may be monitored effectively with the remotely sensed data and temporal pattern of changes can be quantified for future planning and mitigation of adverse effects.

  2. Opportunities and challenges for evaluating precipitation estimates during GPM mission

    Energy Technology Data Exchange (ETDEWEB)

    Amitai, E. [George Mason Univ. and NASA Goddard Space Flight Center, Greenbelt, MD (United States); NASA Goddard Space Flight Center, Greenbelt, MD (United States); Llort, X.; Sempere-Torres, D. [GRAHI/Univ. Politecnica de Catalunya, Barcelona (Spain)

    2006-10-15

    Data assimilation in conjunction with numerical weather prediction and a variety of hydrologic applications now depend on satellite observations of precipitation. However, providing values of precipitation is not sufficient unless they are accompanied by the associated uncertainty estimates. The main approach of quantifying satellite precipitation uncertainties generally requires establishment of reliable uncertainty estimates for the ground validation rainfall products. This paper discusses several of the relevant validation concepts evolving from the tropical rainfall measuring mission (TRMM) era to the global precipitation measurement mission (GPM) era in the context of determining and reducing uncertainties of ground and space-based radar rainfall estimates. From comparisons of probability distribution functions of rain rates derived from TRMM precipitation radar and co-located ground based radar data - using the new NASA TRMM radar rainfall products (version 6) - this paper provides (1) a brief review of the importance of comparing pdfs of rain rate for statistical and physical verification of space-borne radar estimates of precipitation; (2) a brief review of how well the ground validation estimates compare to the TRMM radar retrieved estimates; and (3) discussion on opportunities and challenges to determine and reduce the uncertainties in space-based and ground-based radar estimates of rain rate distributions. (orig.)

  3. Application of Satellite Observations to Manage Natural Disasters in the Lake Victoria Basin

    Science.gov (United States)

    Habib, Shahid; Policelli, F.; Irwin, D.; Korme, Tesfaye; Adler, Bob; Hong, Yang

    2010-01-01

    Lake Victoria, the second largest fresh water lake in the Eastern part of Africa is a vital natural resource for the economic well being and prosperity of over 30 million people located in riparian regions of Uganda, Kenya and Tanzania. It covers a large area of about 68,870 km2 and produces a GDP of about US $30 billion per year. The region is also very much prone to natural disasters such as severe floods during heavy precipitation periods in the Eastern part of Africa. In addition to floods, the precipitation also produces large infestations of mosquito larvae due to the standing water in many areas. This further causes multiple vector borne diseases such as Malaria, Rift Valley Fever and more. These problems are of serious concern and require active and aggressive surveillance and management to minimize the loss of human and animal lives and property damage. Satellite imagery and observations along with the in situ measurements provide a great tool to analyze and study this area and inform the policy makers to make calculated policy decisions which are more beneficial to the environment. Recently, NASA and USAID have joined forces with the Regional Center for Mapping of Resources for Development (RCMRD) located in Nairobi, Kenya to utilize multiple NASA sensors such as TRMM, SRTM and MODIS to develop flood potential maps for the Lake Victoria Basin. The idea is to generate a flood forecasts and "nowcasts" that can be sent to the disaster management organizations of Uganda, Kenya, and Tanzania. Post flood event satellite imagery is becoming a common tool to assess the areas inundated by flooding. However, this work is unique undertaking by utilizing land imaging and atmospheric satellites to build credible flood potential maps. At same time, we are also studying the potential occurrence and spread of Rift Valley Fever disease based on the short term climate records and precipitation data. These activities require multi-nation coordination and agreements and

  4. Scoping Study of Machine Learning Techniques for Visualization and Analysis of Multi-source Data in Nuclear Safeguards

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Yonggang

    2018-05-07

    In implementation of nuclear safeguards, many different techniques are being used to monitor operation of nuclear facilities and safeguard nuclear materials, ranging from radiation detectors, flow monitors, video surveillance, satellite imagers, digital seals to open source search and reports of onsite inspections/verifications. Each technique measures one or more unique properties related to nuclear materials or operation processes. Because these data sets have no or loose correlations, it could be beneficial to analyze the data sets together to improve the effectiveness and efficiency of safeguards processes. Advanced visualization techniques and machine-learning based multi-modality analysis could be effective tools in such integrated analysis. In this project, we will conduct a survey of existing visualization and analysis techniques for multi-source data and assess their potential values in nuclear safeguards.

  5. Sensitivity of Distributed Hydrologic Simulations to Ground and Satellite Based Rainfall Products

    Directory of Open Access Journals (Sweden)

    Singaiah Chintalapudi

    2014-05-01

    Full Text Available In this study, seven precipitation products (rain gauges, NEXRAD MPE, PERSIANN 0.25 degree, PERSIANN CCS-3hr, PERSIANN CCS-1hr, TRMM 3B42V7, and CMORPH were used to force a physically-based distributed hydrologic model. The model was driven by these products to simulate the hydrologic response of a 1232 km2 watershed in the Guadalupe River basin, Texas. Storm events in 2007 were used to analyze the precipitation products. Comparison with rain gauge observations reveals that there were significant biases in the satellite rainfall products and large variations in the estimated amounts. The radar basin average precipitation compared very well with the rain gauge product while the gauge-adjusted TRMM 3B42V7 precipitation compared best with observed rainfall among all satellite precipitation products. The NEXRAD MPE simulated streamflows matched the observed ones the best yielding the highest Nash-Sutcliffe Efficiency correlation coefficient values for both the July and August 2007 events. Simulations driven by TRMM 3B42V7 matched the observed streamflow better than other satellite products for both events. The PERSIANN coarse resolution product yielded better runoff results than the higher resolution product. The study reveals that satellite rainfall products are viable alternatives when rain gauge or ground radar observations are sparse or non-existent.

  6. Challenge and opportunities of space-based precipitation radar for spatio-temporal hydrology analysis in tropical maritime influenced catchment: Case study on the hilly tropical watershed of Peninsular Malaysia

    International Nuclear Information System (INIS)

    Mahmud, M R; Numata, S; Matsuyama, H; Hashim, M; Hosaka, T

    2014-01-01

    This paper highlights two critical issues regarding hilly watershed in Peninsular Malaysia; (1) current status of spatio-temporal condition of rain gauge based measurement, and (2) potential of space-based precipitation radar to study the rainfall dynamics. Two analyses were carried out represent each issue consecutively. First, the spatial distribution and efficiency of rain gauge in hilly watershed Peninsular Malaysia is evaluated with respect to the land use and elevation information using Geographical Information System (GIS) approach. Second, the spatial pattern of rainfall changes is analysed using the Tropical Rainfall Measuring Mission (TRMM) satellite information. The spatial analysis revealed that the rain gauge distribution had sparse coverage on hilly watershed and possessed inadequate efficiency for effective spatial based assessment. Significant monthly rainfall changes identified by TRMM satellite on the upper part of the watershed had occurred occasionally in 1999, 2000, 2001, 2006, and 2009 went undetected by conventional rain gauge. This study informed the potential and opportunities of space-based precipitation radar to fill the gaps of knowledge on spatio-temporal rainfall patterns for hydrology and related fields in tropical region

  7. Evaluation of Hyperspectral Multi-Band Indices to Estimate Chlorophyll-A Concentration Using Field Spectral Measurements and Satellite Data in Dianshan Lake, China

    Directory of Open Access Journals (Sweden)

    Linna Li

    2013-04-01

    Full Text Available Chlorophyll-a (Chl-a concentration is considered as a key indicator of the eutrophic status of inland water bodies. Various algorithms have been developed for estimating Chl-a in order to improve the accuracy of predictive models. The objective of this study is to assess the potential of hyperspectral multi-band indices to estimate the Chl-a concentration in Dianshan Lake, which is the largest lake in Shanghai, an international metropolis of China. Based on field spectral measurements and in-situ Chl-a concentration collected on 7–8 September 2010, hyperspectral multi-band indices were calibrated to estimate the Chl-a concentration with optimal wavelengths selected by model tuning. A three-band index accounts for 87.36% (R2 = 0.8736 of the Chl-a variation. A four-band index, which adds a wavelength in the near infrared (NIR region, results in a higher R2 (0.8997 by removing the absorption and backscattering effects of suspended solids. To test the applicability of the proposed indices for routinely monitoring of Chl-a in inland lakes, simulated Hyperion and real HJ-1A satellite data were selected to estimate the Chl-a concentration. The results show that the explanatory powers of these satellite hyperspectral multi-band indices are relatively high with R2 = 0.8559, 0.8945, 0.7969, and 0.8241 for simulated Hyperion and real HJ-1A satellite data, respectively. All of the results provide strong evidence that hyperspectral multi-band indices are promising and applicable to estimate Chl-a in eutrophic inland lakes.

  8. Evaluation of NASA's MERRA Precipitation Product in Reproducing the Observed Trend and Distribution of Extreme Precipitation Events in the United States

    Science.gov (United States)

    Ashouri, Hamed; Sorooshian, Soroosh; Hsu, Kuo-Lin; Bosilovich, Michael G.; Lee, Jaechoul; Wehner, Michael F.; Collow, Allison

    2016-01-01

    This study evaluates the performance of NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) precipitation product in reproducing the trend and distribution of extreme precipitation events. Utilizing the extreme value theory, time-invariant and time-variant extreme value distributions are developed to model the trends and changes in the patterns of extreme precipitation events over the contiguous United States during 1979-2010. The Climate Prediction Center (CPC) U.S.Unified gridded observation data are used as the observational dataset. The CPC analysis shows that the eastern and western parts of the United States are experiencing positive and negative trends in annual maxima, respectively. The continental-scale patterns of change found in MERRA seem to reasonably mirror the observed patterns of change found in CPC. This is not previously expected, given the difficulty in constraining precipitation in reanalysis products. MERRA tends to overestimate the frequency at which the 99th percentile of precipitation is exceeded because this threshold tends to be lower in MERRA, making it easier to be exceeded. This feature is dominant during the summer months. MERRA tends to reproduce spatial patterns of the scale and location parameters of the generalized extreme value and generalized Pareto distributions. However, MERRA underestimates these parameters, particularly over the Gulf Coast states, leading to lower magnitudes in extreme precipitation events. Two issues in MERRA are identified: 1) MERRA shows a spurious negative trend in Nebraska and Kansas, which is most likely related to the changes in the satellite observing system over time that has apparently affected the water cycle in the central United States, and 2) the patterns of positive trend over the Gulf Coast states and along the East Coast seem to be correlated with the tropical cyclones in these regions. The analysis of the trends in the seasonal precipitation extremes indicates that

  9. GPS Estimates of Integrated Precipitable Water Aid Weather Forecasters

    Science.gov (United States)

    Moore, Angelyn W.; Gutman, Seth I.; Holub, Kirk; Bock, Yehuda; Danielson, David; Laber, Jayme; Small, Ivory

    2013-01-01

    Global Positioning System (GPS) meteorology provides enhanced density, low-latency (30-min resolution), integrated precipitable water (IPW) estimates to NOAA NWS (National Oceanic and Atmospheric Adminis tration Nat ional Weather Service) Weather Forecast Offices (WFOs) to provide improved model and satellite data verification capability and more accurate forecasts of extreme weather such as flooding. An early activity of this project was to increase the number of stations contributing to the NOAA Earth System Research Laboratory (ESRL) GPS meteorology observing network in Southern California by about 27 stations. Following this, the Los Angeles/Oxnard and San Diego WFOs began using the enhanced GPS-based IPW measurements provided by ESRL in the 2012 and 2013 monsoon seasons. Forecasters found GPS IPW to be an effective tool in evaluating model performance, and in monitoring monsoon development between weather model runs for improved flood forecasting. GPS stations are multi-purpose, and routine processing for position solutions also yields estimates of tropospheric zenith delays, which can be converted into mm-accuracy PWV (precipitable water vapor) using in situ pressure and temperature measurements, the basis for GPS meteorology. NOAA ESRL has implemented this concept with a nationwide distribution of more than 300 "GPSMet" stations providing IPW estimates at sub-hourly resolution currently used in operational weather models in the U.S.

  10. Assessment of Observational Uncertainty in Extreme Precipitation Events over the Continental United States

    Science.gov (United States)

    Slinskey, E. A.; Loikith, P. C.; Waliser, D. E.; Goodman, A.

    2017-12-01

    Extreme precipitation events are associated with numerous societal and environmental impacts. Furthermore, anthropogenic climate change is projected to alter precipitation intensity across portions of the Continental United States (CONUS). Therefore, a spatial understanding and intuitive means of monitoring extreme precipitation over time is critical. Towards this end, we apply an event-based indicator, developed as a part of NASA's support of the ongoing efforts of the US National Climate Assessment, which assigns categories to extreme precipitation events based on 3-day storm totals as a basis for dataset intercomparison. To assess observational uncertainty across a wide range of historical precipitation measurement approaches, we intercompare in situ station data from the Global Historical Climatology Network (GHCN), satellite-derived precipitation data from NASA's Tropical Rainfall Measuring Mission (TRMM), gridded in situ station data from the Parameter-elevation Regressions on Independent Slopes Model (PRISM), global reanalysis from NASA's Modern Era Retrospective-Analysis version 2 (MERRA 2), and regional reanalysis with gauge data assimilation from NCEP's North American Regional Reanalysis (NARR). Results suggest considerable variability across the five-dataset suite in the frequency, spatial extent, and magnitude of extreme precipitation events. Consistent with expectations, higher resolution datasets were found to resemble station data best and capture a greater frequency of high-end extreme events relative to lower spatial resolution datasets. The degree of dataset agreement varies regionally, however all datasets successfully capture the seasonal cycle of precipitation extremes across the CONUS. These intercomparison results provide additional insight about observational uncertainty and the ability of a range of precipitation measurement and analysis products to capture extreme precipitation event climatology. While the event category threshold is fixed

  11. Optimal ranking regime analysis of U.S. climate variablility. Part II: Precipitation and streamflow

    Science.gov (United States)

    In a preceding companion paper the Optimal Ranking Regime (ORR) method was used to identify intra- to multi-decadal (IMD) regimes in U.S. climate division temperature data during 1896-2012. Here, the method is used to test for annual and seasonal precipitation regimes during that same period. In add...

  12. A two-component generalized extreme value distribution for precipitation frequency analysis

    Czech Academy of Sciences Publication Activity Database

    Rulfová, Zuzana; Buishand, A.; Roth, M.; Kyselý, Jan

    2016-01-01

    Roč. 534, March (2016), s. 659-668 ISSN 0022-1694 R&D Projects: GA ČR(CZ) GA14-18675S Institutional support: RVO:68378289 Keywords : precipitation extremes * two-component extreme value distribution * regional frequency analysis * convective precipitation * stratiform precipitation * Central Europe Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 3.483, year: 2016 http://www.sciencedirect.com/science/article/pii/S0022169416000500

  13. Comparison of satellite-derived LAI and precipitation anomalies over Brazil with a thermal infrared-based Evaporative Stress Index for 2003-2013

    Science.gov (United States)

    Anderson, Martha C.; Zolin, Cornelio A.; Hain, Christopher R.; Semmens, Kathryn; Tugrul Yilmaz, M.; Gao, Feng

    2015-07-01

    Shortwave vegetation index (VI) and leaf area index (LAI) remote sensing products yield inconsistent depictions of biophysical response to drought and pluvial events that have occurred in Brazil over the past decade. Conflicting reports of severity of drought impacts on vegetation health and functioning have been attributed to cloud and aerosol contamination of shortwave reflectance composites, particularly over the rainforested regions of the Amazon basin which are subject to prolonged periods of cloud cover and episodes of intense biomass burning. This study compares timeseries of satellite-derived maps of LAI from the Moderate Resolution Imaging Spectroradiometer (MODIS) and precipitation from the Tropical Rainfall Mapping Mission (TRMM) with a diagnostic Evaporative Stress Index (ESI) retrieved using thermal infrared remote sensing over South America for the period 2003-2013. This period includes several severe droughts and floods that occurred both over the Amazon and over unforested savanna and agricultural areas in Brazil. Cross-correlations between absolute values and standardized anomalies in monthly LAI and precipitation composites as well as the actual-to-reference evapotranspiration (ET) ratio used in the ESI were computed for representative forested and agricultural regions. The correlation analyses reveal strong apparent anticorrelation between MODIS LAI and TRMM precipitation anomalies over the Amazon, but better coupling over regions vegetated with shorter grass and crop canopies. The ESI was more consistently correlated with precipitation patterns over both landcover types. Temporal comparisons between ESI and TRMM anomalies suggest longer moisture buffering timescales in the deeper rooted rainforest systems. Diagnostic thermal-based retrievals of ET and ET anomalies, such as used in the ESI, provide independent information on the impacts of extreme hydrologic events on vegetation health in comparison with VI and precipitation-based drought

  14. Does extreme precipitation intensity depend on the emissions scenario?

    Science.gov (United States)

    Pendergrass, Angeline; Lehner, Flavio; Sanderson, Benjamin; Xu, Yangyang

    2016-04-01

    The rate of increase of global-mean precipitation per degree surface temperature increase differs for greenhouse gas and aerosol forcings, and therefore depends on the change in composition of the emissions scenario used to drive climate model simulations for the remainder of the century. We investigate whether or not this is also the case for extreme precipitation simulated by a multi-model ensemble driven by four realistic emissions scenarios. In most models, the rate of increase of maximum annual daily rainfall per degree global warming in the multi-model ensemble is statistically indistinguishable across the four scenarios, whether this extreme precipitation is calculated globally, over all land, or over extra-tropical land. These results indicate that, in most models, extreme precipitation depends on the total amount of warming and does not depend on emissions scenario, in contrast to mean precipitation.

  15. Monitoring Global Precipitation through UCI CHRS's RainMapper App on Mobile Devices

    Science.gov (United States)

    Nguyen, P.; Huynh, P.; Braithwaite, D.; Hsu, K. L.; Sorooshian, S.

    2014-12-01

    The Water and Development Information for Arid Lands-a Global Network (G-WADI) Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks—Cloud Classification System (PERSIANN-CCS) GeoServer has been developed through a collaboration between the Center for Hydrometeorology and Remote Sensing (CHRS) at the University of California, Irvine (UCI) and the UNESCO's International Hydrological Program (IHP). G-WADI PERSIANN-CCS GeoServer provides near real-time high resolution (0.04o, approx 4km) global (60oN - 60oS) satellite precipitation estimated by the PERSIANN-CCS algorithm developed by the scientists at CHRS. The G-WADI PERSIANN-CCS GeoServer utilizes the open-source MapServer software from the University of Minnesota to provide a user-friendly web-based mapping and visualization of satellite precipitation data. Recent efforts have been made by the scientists at CHRS to provide free on-the-go access to the PERSIANN-CCS precipitation data through an application named RainMapper for mobile devices. RainMapper provides visualization of global satellite precipitation of the most recent 3, 6, 12, 24, 48 and 72-hour periods overlaid with various basemaps. RainMapper uses the Google maps application programing interface (API) and embedded global positioning system (GPS) access to better monitor the global precipitation data on mobile devices. Functionalities include using geographical searching with voice recognition technologies make it easy for the user to explore near real-time precipitation in a certain location. RainMapper also allows for conveniently sharing the precipitation information and visualizations with the public through social networks such as Facebook and Twitter. RainMapper is available for iOS and Android devices and can be downloaded (free) from the App Store and Google Play. The usefulness of RainMapper was demonstrated through an application in tracking the evolution of the recent Rammasun Typhoon over the

  16. Surface Freshwater Storage and Variability in the Amazon Basin from Multi-Satellite Observations, 1993-2007

    Science.gov (United States)

    Papa, Fabrice; Frappart, Frederic; Guntner, Andreas; Prigent, Catherine; Aires, Filipe; Getirana, Augusto; Maurer, Raffael

    2013-01-01

    The amount of water stored and moving through the surface water bodies of large river basins (river, floodplains, wetlands) plays a major role in the global water and biochemical cycles and is a critical parameter for water resources management. However, the spatio-temporal variations of these freshwater reservoirs are still widely unknown at the global scale. Here, we propose a hypsographic curve approach to estimate surface freshwater storage variations over the Amazon basin combining surface water extent from a multi-satellite-technique with topographic data from the Global Digital Elevation Model (GDEM) from Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Monthly surface water storage variations for 1993-2007 are presented, showing a strong seasonal and interannual variability, and are evaluated against in situ river discharge and precipitation. The basin-scale mean annual amplitude of approx. 1200 cu km is in the range of previous estimates and contributes to about half of the Gravity Recovery And Climate Experiment (GRACE) total water storage variations. For the first time, we map the surface water volume anomaly during the extreme droughts of 1997 (October-November) and 2005 (September-October) and found that during these dry events the water stored in the river and flood-plains of the Amazon basin was, respectively, approx. 230 (approx. 40%) and 210 (approx. 50%) cu km below the 1993-2007 average. This new 15year data set of surface water volume represents an unprecedented source of information for future hydrological or climate modeling of the Amazon. It is also a first step toward the development of such database at the global scale.

  17. A satellite simulator for TRMM PR applied to climate model simulations

    Science.gov (United States)

    Spangehl, T.; Schroeder, M.; Bodas-Salcedo, A.; Hollmann, R.; Riley Dellaripa, E. M.; Schumacher, C.

    2017-12-01

    Climate model simulations have to be compared against observation based datasets in order to assess their skill in representing precipitation characteristics. Here we use a satellite simulator for TRMM PR in order to evaluate simulations performed with MPI-ESM (Earth system model of the Max Planck Institute for Meteorology in Hamburg, Germany) performed within the MiKlip project (https://www.fona-miklip.de/, funded by Federal Ministry of Education and Research in Germany). While classical evaluation methods focus on geophysical parameters such as precipitation amounts, the application of the satellite simulator enables an evaluation in the instrument's parameter space thereby reducing uncertainties on the reference side. The CFMIP Observation Simulator Package (COSP) provides a framework for the application of satellite simulators to climate model simulations. The approach requires the introduction of sub-grid cloud and precipitation variability. Radar reflectivities are obtained by applying Mie theory, with the microphysical assumptions being chosen to match the atmosphere component of MPI-ESM (ECHAM6). The results are found to be sensitive to the methods used to distribute the convective precipitation over the sub-grid boxes. Simple parameterization methods are used to introduce sub-grid variability of convective clouds and precipitation. In order to constrain uncertainties a comprehensive comparison with sub-grid scale convective precipitation variability which is deduced from TRMM PR observations is carried out.

  18. Shoreline change after 12 years of tsunami in Banda Aceh, Indonesia: a multi-resolution, multi-temporal satellite data and GIS approach

    Science.gov (United States)

    Sugianto, S.; Heriansyah; Darusman; Rusdi, M.; Karim, A.

    2018-04-01

    The Indian Ocean Tsunami event on the 26 December 2004 has caused severe damage of some shorelines in Banda Aceh City, Indonesia. Tracing back the impact can be seen using remote sensing data combined with GIS. The approach is incorporated with image processing to analyze the extent of shoreline changes with multi-temporal data after 12 years of tsunami. This study demonstrates multi-resolution and multi-temporal satellite images of QuickBird and IKONOS to demarcate the shoreline of Banda Aceh shoreline from before and after tsunami. The research has demonstrated a significant change to the shoreline in the form of abrasion between 2004 and 2005 from few meters to hundred meters’ change. The change between 2004 and 2011 has not returned to the previous stage of shoreline before the tsunami, considered post tsunami impact. The abrasion occurs between 18.3 to 194.93 meters. Further, the change in 2009-2011 shows slowly change of shoreline of Banda Aceh, considered without impact of tsunami e.g. abrasion caused by ocean waves that erode the coast and on specific areas accretion occurs caused by sediment carried by the river flow into the sea near the shoreline of the study area.

  19. Terrestrial precipitation and soil moisture: A case study over southern Arizona and data development

    Science.gov (United States)

    Stillman, Susan

    Quantifying climatological precipitation and soil moisture as well as interannual variability and trends requires extensive observation. This work focuses on the analysis of available precipitation and soil moisture data and the development of new ways to estimate these quantities. Precipitation and soil moisture characteristics are highly dependent on the spatial and temporal scales. We begin at the point scale, examining hourly precipitation and soil moisture at individual gauges. First, we focus on the Walnut Gulch Experimental Watershed (WGEW), a 150 km2 area in southern Arizona. The watershed has been measuring rainfall since 1956 with a very high density network of approximately 0.6 gauges per km2. Additionally, there are 19 soil moisture probes at 5 cm depth with data starting in 2002. In order to extend the measurement period, we have developed a water balance model which estimates monsoon season (Jul-Sep) soil moisture using only precipitation for input, and calibrated so that the modeled soil moisture fits best with the soil moisture measured by each of the 19 probes from 2002-2012. This observationally constrained soil moisture is highly correlated with the collocated probes (R=0.88), and extends the measurement period from 10 to 56 years and the number of gauges from 19 to 88. Then, we focus on the spatiotemporal variability within the watershed and the ability to estimate area averaged quantities. Spatially averaged precipitation and observationally constrained soil moisture from the 88 gauges is then used to evaluate various gridded datasets. We find that gauge-based precipitation products perform best followed by reanalyses and then satellite-based products. Coupled Model Intercomparison Project Phase 5 (CMIP5) models perform the worst and overestimate cold season precipitation while offsetting the monsoon peak precipitation forward or backward by a month. Satellite-based soil moisture is the best followed by land data assimilation systems and

  20. Scaling Analysis of Ocean Surface Turbulent Heterogeneities from Satellite Remote Sensing: Use of 2D Structure Functions.

    Directory of Open Access Journals (Sweden)

    P R Renosh

    Full Text Available Satellite remote sensing observations allow the ocean surface to be sampled synoptically over large spatio-temporal scales. The images provided from visible and thermal infrared satellite observations are widely used in physical, biological, and ecological oceanography. The present work proposes a method to understand the multi-scaling properties of satellite products such as the Chlorophyll-a (Chl-a, and the Sea Surface Temperature (SST, rarely studied. The specific objectives of this study are to show how the small scale heterogeneities of satellite images can be characterised using tools borrowed from the fields of turbulence. For that purpose, we show how the structure function, which is classically used in the frame of scaling time series analysis, can be used also in 2D. The main advantage of this method is that it can be applied to process images which have missing data. Based on both simulated and real images, we demonstrate that coarse-graining (CG of a gradient modulus transform of the original image does not provide correct scaling exponents. We show, using a fractional Brownian simulation in 2D, that the structure function (SF can be used with randomly sampled couple of points, and verify that 1 million of couple of points provides enough statistics.

  1. Evaluating the Performance of the Goddard Multi-Scale Modeling Framework against GPM, TRMM and CloudSat/CALIPSO Products

    Science.gov (United States)

    Chern, J. D.; Tao, W. K.; Lang, S. E.; Matsui, T.; Mohr, K. I.

    2014-12-01

    Four six-month (March-August 2014) experiments with the Goddard Multi-scale Modeling Framework (MMF) were performed to study the impacts of different Goddard one-moment bulk microphysical schemes and large-scale forcings on the performance of the MMF. Recently a new Goddard one-moment bulk microphysics with four-ice classes (cloud ice, snow, graupel, and frozen drops/hail) has been developed based on cloud-resolving model simulations with large-scale forcings from field campaign observations. The new scheme has been successfully implemented to the MMF and two MMF experiments were carried out with this new scheme and the old three-ice classes (cloud ice, snow graupel) scheme. The MMF has global coverage and can rigorously evaluate microphysics performance for different cloud regimes. The results show MMF with the new scheme outperformed the old one. The MMF simulations are also strongly affected by the interaction between large-scale and cloud-scale processes. Two MMF sensitivity experiments with and without nudging large-scale forcings to those of ERA-Interim reanalysis were carried out to study the impacts of large-scale forcings. The model simulated mean and variability of surface precipitation, cloud types, cloud properties such as cloud amount, hydrometeors vertical profiles, and cloud water contents, etc. in different geographic locations and climate regimes are evaluated against GPM, TRMM, CloudSat/CALIPSO satellite observations. The Goddard MMF has also been coupled with the Goddard Satellite Data Simulation Unit (G-SDSU), a system with multi-satellite, multi-sensor, and multi-spectrum satellite simulators. The statistics of MMF simulated radiances and backscattering can be directly compared with satellite observations to assess the strengths and/or deficiencies of MMF simulations and provide guidance on how to improve the MMF and microphysics.

  2. Comparison and evaluation of satellite derived precipitation products for hydrological modeling of the Zambezi River Basin

    Directory of Open Access Journals (Sweden)

    T. Cohen Liechti

    2012-02-01

    Full Text Available In the framework of the African DAms ProjecT (ADAPT, an integrated water resource management study in the Zambezi Basin is currently under development. In view of the sparse gauging network for rainfall monitoring, the observations from spaceborne instrumentation currently produce the only available rainfall data for a large part of the basin.

    Three operational and acknowledged high resolution satellite derived estimates: the Tropical Rainfall Measuring Mission product 3B42 (TRMM 3B42, the Famine Early Warning System product 2.0 (FEWS RFE2.0 and the National Oceanic and Atmospheric Administration/Climate Prediction Centre (NOAA/CPC morphing technique (CMORPH are analyzed in terms of spatial and temporal repartition of the precipitations. They are compared to ground data for the wet seasons of the years 2003 to 2009 on a point to pixel basis at daily, 10-daily and monthly time steps and on a pixel to pixel basis for the wet seasons of the years 2003 to 2007 at monthly time steps.

    The general North-South gradient of precipitation is captured by all the analyzed products. Regarding the spatial heterogeneity, FEWS pixels are much more inter-correlated than TRMM and CMORPH pixels. For a rainfall homogeneity threshold criterion of 0.5 global mean correlation coefficient, the area of each sub-basin should not exceed a circle of 2.5° latitude/longitude radius for FEWS and a circle of 0.75° latitude/longitude radius for TRMM and CMORPH considering rectangular meshes.

    In terms of reliability, the correspondence of all estimates with ground data increases with the time step chosen for the analysis. The volume ratio computation indicates that CMORPH is overestimating the rainfall by nearly 50%. The statistics of TRMM and FEWS estimates show quite similar results.

    Due to its lower inter-correlation and longer data set, the TRMM 3B42 product is chosen as input for the hydraulic-hydrologic model of the basin.

  3. Satellite network robust QoS-aware routing

    CERN Document Server

    Long, Fei

    2014-01-01

    Satellite Network Robust QoS-aware Routing presents a novel routing strategy for satellite networks. This strategy is useful for the design of multi-layered satellite networks as it can greatly reduce the number of time slots in one system cycle. The traffic prediction and engineering approaches make the system robust so that the traffic spikes can be handled effectively. The multi-QoS optimization routing algorithm can satisfy various potential user requirements. Clear and sufficient illustrations are also presented in the book. As the chapters cover the above topics independently, readers from different research backgrounds in constellation design, multi-QoS routing, and traffic engineering can benefit from the book.   Fei Long is a senior engineer at Beijing R&D Center of 54th Research Institute of China Electronics Technology Group Corporation.

  4. Spatiotemporal Patterns of Precipitation-Modulated Landslide Deformation From Independent Component Analysis of InSAR Time Series

    Science.gov (United States)

    Cohen-Waeber, J.; Bürgmann, R.; Chaussard, E.; Giannico, C.; Ferretti, A.

    2018-02-01

    Long-term landslide deformation is disruptive and costly in urbanized environments. We rely on TerraSAR-X satellite images (2009-2014) and an improved data processing algorithm (SqueeSAR™) to produce an exceptionally dense Interferometric Synthetic Aperture Radar ground deformation time series for the San Francisco East Bay Hills. Independent and principal component analyses of the time series reveal four distinct spatial and temporal surface deformation patterns in the area around Blakemont landslide, which we relate to different geomechanical processes. Two components of time-dependent landslide deformation isolate continuous motion and motion driven by precipitation-modulated pore pressure changes controlled by annual seasonal cycles and multiyear drought conditions. Two components capturing more widespread seasonal deformation separate precipitation-modulated soil swelling from annual cycles that may be related to groundwater level changes and thermal expansion of buildings. High-resolution characterization of landslide response to precipitation is a first step toward improved hazard forecasting.

  5. Precipitation in Madeira island and atmospheric rivers in the winter seasons

    Science.gov (United States)

    Couto, Flavio T.; Salgado, Rui; João Costa, Maria; Prior, Victor

    2016-04-01

    This study aims to analyse the distribution of the daily accumulated precipitation in the Madeira's highlands over a 10-year period, as well as the main characteristics associated with atmospheric rivers (ARs) affecting the island during 10 winter seasons, and their impact in the rainfall amounts recorded near the mountain crest in the south-eastern part of the island. The period between September 2002 and November 2012 is considered for the analysis. The ARs have been identified from the total precipitable water vapour field extracted from the Atmospheric Infrared Sounder (AIRS). The AIRS observations were downloaded for a domain covering large part of the North Atlantic Ocean. The precipitable water vapour field from the European Centre for Medium-range Weather Forecasts (ECMWF) analysis was also used aiming to support the AIRS data when there was no satellite information over the island. The daily accumulated precipitation at surface showed generally drier summers, while the highest accumulated precipitation are recorded mainly during the winter, although some significant events may occur also in autumn and spring seasons. The patterns of the precipitable water vapour field when ARs reach the island were investigated, and even if great part of the atmospheric rivers reaches the island in a dissipation stage, some rivers are heavy enough to reach the Madeira Island. In this situation, the water vapour transport could be observed in two main configurations and transporting significant water vapour amounts toward the Madeira from the tropical region. This study lead to conclude that the atmospheric rivers, when associated to high values of precipitable water vapour over the island can provide favourable conditions to the development of precipitation, sometimes associated with high amounts. However, it was also found that many cases of high to extreme accumulated precipitation at the surface were not associated to this kind of moisture transport.

  6. Regional model simulation of the North Atlantic cyclone "Caroline" and comparisons with satellite data

    Directory of Open Access Journals (Sweden)

    E. Keup-Thiel

    Full Text Available An individual regional model simulation of cyclone "Caroline" has been carried out to study water cycle components over the North Atlantic Ocean. The uncertainties associated with quantitative estimates of the water cycle components are highlighted by a comparison of the model results with SSM/I (Special Sensor Microwave Imager satellite data.

    The vertically integrated water vapor of the REgional MOdel REMO is in good agreement with the SSM/I satellite data. The simulation results for other water budget components like the vertically integrated liquid water content and precipitation compare also reasonably well within the frontal system. However, the high precipitation rate in the cold air outbreak on the backside of the cold front derived from SSM/I satellite data is generally underestimated by REMO. This results in a considerable deficit of the total precipitation amount accumulated for the cyclone "Caroline". While REMO simulates 24.3 108 m3 h-1 for 09:00 UTC, the total areal precipitation from SSM/I satellite data amounts to 54.7 08 m3 h-1.

    Key words. Meteorology and atmospheric dynamics (precipitation; mesoscale meteorology – Radio science (remote sensing

  7. Validation and Error Characterization for the Global Precipitation Measurement

    Science.gov (United States)

    Bidwell, Steven W.; Adams, W. J.; Everett, D. F.; Smith, E. A.; Yuter, S. E.

    2003-01-01

    The Global Precipitation Measurement (GPM) is an international effort to increase scientific knowledge on the global water cycle with specific goals of improving the understanding and the predictions of climate, weather, and hydrology. These goals will be achieved through several satellites specifically dedicated to GPM along with the integration of numerous meteorological satellite data streams from international and domestic partners. The GPM effort is led by the National Aeronautics and Space Administration (NASA) of the United States and the National Space Development Agency (NASDA) of Japan. In addition to the spaceborne assets, international and domestic partners will provide ground-based resources for validating the satellite observations and retrievals. This paper describes the validation effort of Global Precipitation Measurement to provide quantitative estimates on the errors of the GPM satellite retrievals. The GPM validation approach will build upon the research experience of the Tropical Rainfall Measuring Mission (TRMM) retrieval comparisons and its validation program. The GPM ground validation program will employ instrumentation, physical infrastructure, and research capabilities at Supersites located in important meteorological regimes of the globe. NASA will provide two Supersites, one in a tropical oceanic and the other in a mid-latitude continental regime. GPM international partners will provide Supersites for other important regimes. Those objectives or regimes not addressed by Supersites will be covered through focused field experiments. This paper describes the specific errors that GPM ground validation will address, quantify, and relate to the GPM satellite physical retrievals. GPM will attempt to identify the source of errors within retrievals including those of instrument calibration, retrieval physical assumptions, and algorithm applicability. With the identification of error sources, improvements will be made to the respective calibration

  8. The Passive Microwave Neural Network Precipitation Retrieval (PNPR) for AMSU/MHS and ATMS cross-track scanning radiometers

    Science.gov (United States)

    Sano', Paolo; Casella, Daniele; Panegrossi, Giulia; Cinzia Marra, Anna; Dietrich, Stefano

    2016-04-01

    another when an observed precipitation system extends over two or more types of surfaces. As input data, the PNPR algorithm incorporates the TBs from selected channels, and various additional TBs-derived variables. Ancillary geographical/geophysical inputs (i.e., latitude, terrain height, surface type, season) are also considered during the training phase. The PNPR algorithm outputs consist of both the surface precipitation rate (along with the information on precipitation phase: liquid, mixed, solid) and a pixel-based quality index. We will illustrate the main features of the PNPR algorithm and will show results of a verification study over Europe and Africa. The study is based on the available ground-based radar and/or rain gauge network observations over the European area. In addition, results of the comparison with rainfall products available from the NASA/JAXA Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) (over the African area) and Global Precipitation Measurement (GPM) Dual frequency Precipitation Radar (DPR) will be shown. The analysis is built upon a two-years coincidence dataset of AMSU/MHS and ATMS observations with PR (2013-2014) and DPR (2014-2015). The PNPR is developed within the EUMETSAT H/SAF program (Satellite Application Facility for Operational Hydrology and Water Management), where it is used operationally towards the full exploitation of all microwave radiometers available in the GPM era. The algorithm will be tailored to the future European Microwave Sounder (MWS) onboard the MetOp-Second Generation (MetOp-SG) satellites.

  9. Voltage Stability Analysis of Muscat Power System During Summer Weather Conditions

    Directory of Open Access Journals (Sweden)

    K. Ellithy

    2000-12-01

    Full Text Available A systematic and general formulation of a Propagation Simulation Program (PSP is developed for the coherent field of microwave and millimeter wave carrier signals traversing intermediate layered precipitation media taking into account the random behavior of particle size, orientation, shape and concentration distributions.  Based on a rigorous solution of the volumetric multiple-scattering integral equations, the formalism offers the capability of treating the potential transmission impairments on satellite-earth links and radar remote sensing generated by composite atmospheric layers of precipitation in conjunction with the finite polarization isolation of dual-polarized transmitting and receiving antennas. A multi-layered formulation is employed which encompasses an ensemble of discrete particles comprising an arbitrary mixture of ice crystals, melting snow and raindrops that may exist simultaneously along satellite-earth communication paths.

  10. Intensive time series data exploitation: the Multi-sensor Evolution Analysis (MEA) platform

    Science.gov (United States)

    Mantovani, Simone; Natali, Stefano; Folegani, Marco; Scremin, Alessandro

    2014-05-01

    The monitoring of the temporal evolution of natural phenomena must be performed in order to ensure their correct description and to allow improvements in modelling and forecast capabilities. This assumption, that is obvious for ground-based measurements, has not always been true for data collected through space-based platforms: except for geostationary satellites and sensors, that allow providing a very effective monitoring of phenomena with geometric scale from regional to global; smaller phenomena (with characteristic dimension lower than few kilometres) have been monitored with instruments that could collect data only with a time interval in the order of several days; bi-temporal techniques have been the most used ones for years, in order to characterise temporal changes and try identifying specific phenomena. The more the number of flying sensor has grown and their performance improved, the more their capability of monitoring natural phenomena at a smaller geographic scale has grown: we can now count on tenth of years of remotely sensed data, collected by hundreds of sensors that are now accessible from a wide users' community, and the techniques for data processing have to be adapted to move toward a data intensive exploitation. Starting from 2008, the European Space Agency has initiated the development of the Multi-sensor Evolution Analysis (MEA) platform (https://mea.eo.esa.int), whose first aim was to permit the access and exploitation of long term remotely sensed satellite data from different platforms: 15 years of global (A)ATSR data together with 5 years of regional AVNIR-2 data were loaded into the system and were used, through a web-based graphic user interface, for land cover change analysis. The MEA data availability has grown during years integrating multi-disciplinary data that feature spatial and temporal dimensions: so far tenths of Terabytes of data in the land and atmosphere domains are available and can be visualized and exploited, keeping the

  11. Short-range quantitative precipitation forecasting using Deep Learning approaches

    Science.gov (United States)

    Akbari Asanjan, A.; Yang, T.; Gao, X.; Hsu, K. L.; Sorooshian, S.

    2017-12-01

    Predicting short-range quantitative precipitation is very important for flood forecasting, early flood warning and other hydrometeorological purposes. This study aims to improve the precipitation forecasting skills using a recently developed and advanced machine learning technique named Long Short-Term Memory (LSTM). The proposed LSTM learns the changing patterns of clouds from Cloud-Top Brightness Temperature (CTBT) images, retrieved from the infrared channel of Geostationary Operational Environmental Satellite (GOES), using a sophisticated and effective learning method. After learning the dynamics of clouds, the LSTM model predicts the upcoming rainy CTBT events. The proposed model is then merged with a precipitation estimation algorithm termed Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) to provide precipitation forecasts. The results of merged LSTM with PERSIANN are compared to the results of an Elman-type Recurrent Neural Network (RNN) merged with PERSIANN and Final Analysis of Global Forecast System model over the states of Oklahoma, Florida and Oregon. The performance of each model is investigated during 3 storm events each located over one of the study regions. The results indicate the outperformance of merged LSTM forecasts comparing to the numerical and statistical baselines in terms of Probability of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), RMSE and correlation coefficient especially in convective systems. The proposed method shows superior capabilities in short-term forecasting over compared methods.

  12. Evaluation of modeled changes in extreme precipitation in Europe and the Rhine basin

    NARCIS (Netherlands)

    Haren, van R.; Oldenborgh, van G.J.; Lenderink, G.; Hazeleger, W.

    2013-01-01

    In this study, we investigate the change in multi-day precipitation extremes in late winter in Europe using observations and climate models. The objectives of the analysis are to determine whether climate models can accurately reproduce observed trends and, if not, to find the causes of the

  13. A Decadal Historical Satellite Data and Rainfall Trend Analysis (2001–2016 for Flood Hazard Mapping in Sri Lanka

    Directory of Open Access Journals (Sweden)

    Niranga Alahacoon

    2018-03-01

    Full Text Available Critical information on a flood-affected area is needed in a short time frame to initiate rapid response operations and develop long-term flood management strategies. This study combined rainfall trend analysis using Asian Precipitation—Highly Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE gridded rainfall data with flood maps derived from Synthetic Aperture Radar (SAR and multispectral satellite to arrive at holistic spatio-temporal patterns of floods in Sri Lanka. Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR data were used to map flood extents for emergency relief operations while eight-day Moderate Resolution Imaging Spectroradiometer (MODIS surface reflectance data for the time period from 2001 to 2016 were used to map long term flood-affected areas. The inundation maps produced for rapid response were published within three hours upon the availability of satellite imagery in web platforms, with the aim of supporting a wide range of stakeholders in emergency response and flood relief operations. The aggregated time series of flood extents mapped using MODIS data were used to develop a flood occurrence map (2001–2016 for Sri Lanka. Flood hotpots identified using both optical and synthetic aperture average of 325 km2 for the years 2006–2015 and exceptional flooding in 2016 with inundation extent of approximately 1400 km2. The time series rainfall data explains increasing trend in the extreme rainfall indices with similar observation derived from satellite imagery. The results demonstrate the feasibility of using multi-sensor flood mapping approaches, which will aid Disaster Management Center (DMC and other multi-lateral agencies involved in managing rapid response operations and preparing mitigation measures.

  14. Security Concepts for Satellite Links

    Science.gov (United States)

    Tobehn, C.; Penné, B.; Rathje, R.; Weigl, A.; Gorecki, Ch.; Michalik, H.

    2008-08-01

    The high costs to develop, launch and maintain a satellite network makes protecting the assets imperative. Attacks may be passive such as eavesdropping on the payload data. More serious threat are active attacks that try to gain control of the satellite, which may lead to the total lost of the satellite asset. To counter these threats, new satellite and ground systems are using cryptographic technologies to provide a range of services: confidentiality, entity & message authentication, and data integrity. Additionally, key management cryptographic services are required to support these services. This paper describes the key points of current satellite control and operations, that are authentication of the access to the satellite TMTC link and encryption of security relevant TM/TC data. For payload data management the key points are multi-user ground station access and high data rates both requiring frequent updates and uploads of keys with the corresponding key management methods. For secure satellite management authentication & key negotiation algorithms as HMAC-RIPEMD160, EC- DSA and EC-DH are used. Encryption of data uses algorithms as IDEA, AES, Triple-DES, or other. A channel coding and encryption unit for payload data provides download data rates up to Nx250 Mbps. The presented concepts are based on our experience and heritage of the security systems for all German MOD satellite projects (SATCOMBw2, SAR-Lupe multi- satellite system and German-French SAR-Lupe-Helios- II systems inter-operability) as well as for further international (KOMPSAT-II Payload data link system) and ESA activities (TMTC security and GMES).

  15. Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

    Science.gov (United States)

    Dubovik, O; Herman, M.; Holdak, A.; Lapyonok, T.; Taure, D.; Deuze, J. L.; Ducos, F.; Sinyuk, A.

    2011-01-01

    The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL microsatellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.

  16. Satellite Radio

    Indian Academy of Sciences (India)

    Satellites have been a highly effective platform for multi- form broadcasts. This has led to a ... diversity offormats, languages, genre, and a universal reach that cannot be met by .... programs can be delivered to whom it is intended. In the case of.

  17. The geomorphological evidences of subsidence in the Nile Delta: Analysis of high resolution topographic DEM and multi-temporal satellite images

    Science.gov (United States)

    El Bastawesy, M.; Cherif, O. H.; Sultan, M.

    2017-12-01

    This paper investigates the relevance of landforms to the subsidence of the Nile Delta using a high resolution topographic digital elevation model (DEM) and sets of multi-temporal Landsat satellite images. 195 topographic map sheets produced in 1946 at 1:25,000 scale were digitized, and the DEM was interpolated. The undertaken processing techniques have distinguished all the natural low-lying closed depressions from the artificial errors induced by the interpolation of the DEM. The local subsidence of these depressions from their surroundings reaches a maximum depth of 2.5 m. The regional subsidence of the Nile Delta has developed inverted topography, where the tracts occupied by the contemporary distributary channels are standing at higher elevations than the areas in between. This inversion could be related to the differences in the hydrological and sedimentological properties of underlying sediments, as the channels are underlain by water-saturated sands while the successions of clay and silt on flood plains are prone to compaction. Furthermore, the analysis of remote sensing and topographic data clearly show significant changes in the land cover and land use, particularly in the northern lagoons and adjacent sabkhas, which are dominated by numerous low subsiding depressions. The areas covered by water logging and ponds are increasing on the expense of agricultural areas, and aquaculture have been practiced instead. The precise estimation of subsidence rates and distribution should be worked out to evaluate probable changes in land cover and land use.

  18. Evaluating Climate Causation of Conflict in Darfur Using Multi-temporal, Multi-resolution Satellite Image Datasets With Novel Analyses

    Science.gov (United States)

    Brown, I.; Wennbom, M.

    2013-12-01

    Climate change, population growth and changes in traditional lifestyles have led to instabilities in traditional demarcations between neighboring ethic and religious groups in the Sahel region. This has resulted in a number of conflicts as groups resort to arms to settle disputes. Such disputes often centre on or are justified by competition for resources. The conflict in Darfur has been controversially explained by resource scarcity resulting from climate change. Here we analyse established methods of using satellite imagery to assess vegetation health in Darfur. Multi-decadal time series of observations are available using low spatial resolution visible-near infrared imagery. Typically normalized difference vegetation index (NDVI) analyses are produced to describe changes in vegetation ';greenness' or ';health'. Such approaches have been widely used to evaluate the long term development of vegetation in relation to climate variations across a wide range of environments from the Arctic to the Sahel. These datasets typically measure peak NDVI observed over a given interval and may introduce bias. It is furthermore unclear how the spatial organization of sparse vegetation may affect low resolution NDVI products. We develop and assess alternative measures of vegetation including descriptors of the growing season, wetness and resource availability. Expanding the range of parameters used in the analysis reduces our dependence on peak NDVI. Furthermore, these descriptors provide a better characterization of the growing season than the single NDVI measure. Using multi-sensor data we combine high temporal/moderate spatial resolution data with low temporal/high spatial resolution data to improve the spatial representativity of the observations and to provide improved spatial analysis of vegetation patterns. The approach places the high resolution observations in the NDVI context space using a longer time series of lower resolution imagery. The vegetation descriptors

  19. Impacts of Pacific SSTs on California Winter Precipitation

    Science.gov (United States)

    Myoung, B.; Kafatos, M.

    2017-12-01

    Consecutive below-normal precipitation years and resulted multi-year droughts are critical issues as the recent 2012-2015 drought of California caused tremendous socio-economic damages. However, studies on the causes of the multi-year droughts lack. In this study, focusing on the three multi-year droughts (1999-2002, 2007-2009, and 2012-2015) in California during the last two decades, we investigated the atmospheric and oceanic characteristics of the three drought events for winter (December-February, DJF) in order to understand large-scale circulations that are responsible for initiation, maintenance, and termination of the droughts. It was found that abnormally developed upper-tropospheric ridges over the North Pacific are primarily responsible for precipitation deficits and then droughts. These ridges developed when negative sea surface temperature anomalies (SSTs) including La Niña events are pervasive in the tropical Pacific. After 3 or 4 years, the droughts ended under the opposite conditions; upper-tropospheric troughs in the North Pacific with El Niño events in the tropics. Results of Empirical Orthogonal Function (EOF) analysis for the 41-year (1974/75-2014/15) 500 hPa geopotential height in DJF revealed that, during the drought periods, the positive phases of the first and second EOF mode (EOF1+ and EOF2+, respectively) were active one by one, positioning upper-tropospheric ridges over the North Pacific. While EOF1+ is associated with cold tropical central Pacific and negative Pacific Decadal Oscillation (PDO), EOF2+ is associated with the tropical east-west SST dipole pattern (i.e., warm western tropical Pacific and cool eastern tropical Pacific near the southern Peru). Based on these results, we developed a regression model for winter precipitation. While dominant SST factors differ by decades, for the recent two decades (1994/1995-2014/2015), 56% variability of DJF precipitation is explained by the tropical east-west SST dipole pattern and PDO (NINO3

  20. Large-Scale Covariability Between Aerosol and Precipitation Over the 7-SEAS Region: Observations and Simulations

    Science.gov (United States)

    Huang, Jingfeng; Hsu, N. Christina; Tsay, Si-Chee; Zhang, Chidong; Jeong, Myeong Jae; Gautam, Ritesh; Bettenhausen, Corey; Sayer, Andrew M.; Hansell, Richard A.; Liu, Xiaohong; hide

    2012-01-01

    One of the seven scientific areas of interests of the 7-SEAS field campaign is to evaluate the impact of aerosol on cloud and precipitation (http://7-seas.gsfc.nasa.gov). However, large-scale covariability between aerosol, cloud and precipitation is complicated not only by ambient environment and a variety of aerosol effects, but also by effects from rain washout and climate factors. This study characterizes large-scale aerosol-cloud-precipitation covariability through synergy of long-term multi ]sensor satellite observations with model simulations over the 7-SEAS region [10S-30N, 95E-130E]. Results show that climate factors such as ENSO significantly modulate aerosol and precipitation over the region simultaneously. After removal of climate factor effects, aerosol and precipitation are significantly anti-correlated over the southern part of the region, where high aerosols loading is associated with overall reduced total precipitation with intensified rain rates and decreased rain frequency, decreased tropospheric latent heating, suppressed cloud top height and increased outgoing longwave radiation, enhanced clear-sky shortwave TOA flux but reduced all-sky shortwave TOA flux in deep convective regimes; but such covariability becomes less notable over the northern counterpart of the region where low ]level stratus are found. Using CO as a proxy of biomass burning aerosols to minimize the washout effect, large-scale covariability between CO and precipitation was also investigated and similar large-scale covariability observed. Model simulations with NCAR CAM5 were found to show similar effects to observations in the spatio-temporal patterns. Results from both observations and simulations are valuable for improving our understanding of this region's meteorological system and the roles of aerosol within it. Key words: aerosol; precipitation; large-scale covariability; aerosol effects; washout; climate factors; 7- SEAS; CO; CAM5

  1. Estimating and forecasting the precipitable water vapor from GOES satellite data at high altitude sites

    Science.gov (United States)

    Marín, Julio C.; Pozo, Diana; Curé, Michel

    2015-01-01

    In this work, we describe a method to estimate the precipitable water vapor (PWV) from Geostationary Observational Environmental Satellite (GOES) data at high altitude sites. The method was applied at Atacama Pathfinder Experiment (APEX) and Cerro Toco sites, located above 5000 m altitude in the Chajnantor plateau, in the north of Chile. It was validated using GOES-12 satellite data over the range 0-1.2 mm since submillimeter/millimeter astronomical observations are only useful within this PWV range. The PWV estimated from GOES and the Final Analyses (FNL) at APEX for 2007 and 2009 show root mean square error values of 0.23 mm and 0.36 mm over the ranges 0-0.4 mm and 0.4-1.2 mm, respectively. However, absolute relative errors of 51% and 33% were shown over these PWV ranges, respectively. We recommend using high-resolution thermodynamic profiles from the Global Forecast System (GFS) model to estimate the PWV from GOES data since they are available every three hours and at an earlier time than the FNL data. The estimated PWV from GOES/GFS agrees better with the observed PWV at both sites during night time. The largest errors are shown during daytime. Short-term PWV forecasts were implemented at both sites, applying a simple persistence method to the PWV estimated from GOES/GFS. The 12 h and 24 h PWV forecasts evaluated from August to October 2009 indicates that 25% of them show a very good agreement with observations whereas 50% of them show reasonably good agreement with observations. Transmission uncertainties calculated for PWV estimations and forecasts over the studied sites are larger over the range 0-0.4 mm than over the range 0.4-1.2 mm. Thus, the method can be used over the latter interval with more confidence.

  2. MSU (Microwave Sounding Unit) Daily Troposphere Temperatures and Precipitation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of two MSU tropospheric temperatures levels and precipitation which are described in detail below. The NOAA satellites contributing to this...

  3. Northwestcape-induced Electron Precipitation and Theoretica Simulation

    Science.gov (United States)

    Zhang, Z.; Li, X.; Wang, C.; Chen, L.

    2017-12-01

    Enhancement of the electron fluxes in the inner radiation belt, which is induced by the powerful North West Cape (NWC) very-low-frequency (VLF) transmitter, have been observed and analyzed by several research groups. However, all of the previous publications have focused on NWC-induced > 100-keV electrons only, based on observations from the Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions (DEMETER) and the Geostationary Operational Environmental Satellite (GOES) satellites. Here, we present flux enhancements with 30-100-keV electrons related to NWC transmitter for the first time, which were observed by the GOES satellite at night. Similar to the 100- 300-keV precipitated-electron behavior, the low energy 30-100-keV electron precipitation is primarily located east of the transmitter. However, the latter does not drift eastward to the same extent as the former, possibly because of the lower electron velocity. The 30-100-keV electrons are distributed in the L = 1.8-2.1 L-shell range, in contrast to the 100-300-keVelectronswhichareatL=1.67-1.9. ThisisconsistentwiththeperspectivethattheenergyoftheVLF-waveinducedelectronfluxenhancementdecreaseswithhigherL-shellvalues. Weexpandupontherationalityofthesimultaneous enhancementofthe30-100-and100-300-keVelectronfluxesthroughcomparisonwiththecyclotronresonancetheoryfor the quasi-linear wave-particle interaction. In addition, we interpret the asymmetry characteristics of NWC electric power distribution in northand south hemisphere by ray tracing model. Finally, we present considerable discussionand showthat good agreement exists between the observation of satellites and theory.

  4. Dependence of Energetic Electron Precipitation on the Geomagnetic Index Kp and Electron Energy

    Directory of Open Access Journals (Sweden)

    Mi-Young Park

    2013-12-01

    Full Text Available It has long been known that the magnetospheric particles can precipitate into the atmosphere of the Earth. In this paper we examine such precipitation of energetic electrons using the data obtained from low-altitude polar orbiting satellite observations. We analyze the precipitating electron flux data for many periods selected from a total of 84 storm events identified for 2001-2012. The analysis includes the dependence of precipitation on the Kp index and the electron energy, for which we use three energies E1 > 30 keV, E2 > 100 keV, E3 > 300 keV. We find that the precipitation is best correlated with Kp after a time delay of < 3 hours. Most importantly, the correlation with Kp is notably tighter for lower energy than for higher energy in the sense that the lower energy precipitation flux increases more rapidly with Kp than does the higher energy precipitation flux. Based on this we suggest that the Kp index reflects excitation of a wave that is responsible for scattering of preferably lower energy electrons. The role of waves of other types should become increasingly important for higher energy, for which we suggest to rely on other indicators than Kp if one can identify such an indicator.

  5. Multi-Satellite Air Quality Sulfur Dioxide (SO2) Database Long-Term L4 Global V1 (MSAQSO2L4) at GES DISC

    Data.gov (United States)

    National Aeronautics and Space Administration — These data are a part of Multi-Decadal Sulfur Dioxide Climatology from Satellite Instrument (MEaSUREs-12-0022 project). The catalogue MSAQSO2L4 file contains the...

  6. Seasonal and annual precipitation time series trend analysis in North Carolina, United States

    Science.gov (United States)

    Sayemuzzaman, Mohammad; Jha, Manoj K.

    2014-02-01

    The present study performs the spatial and temporal trend analysis of the annual and seasonal time-series of a set of uniformly distributed 249 stations precipitation data across the state of North Carolina, United States over the period of 1950-2009. The Mann-Kendall (MK) test, the Theil-Sen approach (TSA) and the Sequential Mann-Kendall (SQMK) test were applied to quantify the significance of trend, magnitude of trend, and the trend shift, respectively. Regional (mountain, piedmont and coastal) precipitation trends were also analyzed using the above-mentioned tests. Prior to the application of statistical tests, the pre-whitening technique was used to eliminate the effect of autocorrelation of precipitation data series. The application of the above-mentioned procedures has shown very notable statewide increasing trend for winter and decreasing trend for fall precipitation. Statewide mixed (increasing/decreasing) trend has been detected in annual, spring, and summer precipitation time series. Significant trends (confidence level ≥ 95%) were detected only in 8, 7, 4 and 10 nos. of stations (out of 249 stations) in winter, spring, summer, and fall, respectively. Magnitude of the highest increasing (decreasing) precipitation trend was found about 4 mm/season (- 4.50 mm/season) in fall (summer) season. Annual precipitation trend magnitude varied between - 5.50 mm/year and 9 mm/year. Regional trend analysis found increasing precipitation in mountain and coastal regions in general except during the winter. Piedmont region was found to have increasing trends in summer and fall, but decreasing trend in winter, spring and on an annual basis. The SQMK test on "trend shift analysis" identified a significant shift during 1960 - 70 in most parts of the state. Finally, the comparison between winter (summer) precipitations with the North Atlantic Oscillation (Southern Oscillation) indices concluded that the variability and trend of precipitation can be explained by the

  7. Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images

    Directory of Open Access Journals (Sweden)

    Marc Wieland

    2014-03-01

    Full Text Available In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS and very high resolution (WorldView-2, Quickbird, Ikonos multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognition tasks. Four classification algorithms, Normal Bayes, K Nearest Neighbors, Random Trees and Support Vector Machines, which represent different concepts in machine learning (probabilistic, nearest neighbor, tree-based, function-based, have been selected and implemented on a free and open-source basis. Particular focus is given to assess the generalization ability of machine learning algorithms and the transferability of trained learning machines between different image types and image scenes. Moreover, the influence of the number and choice of training data, the influence of the size and composition of the feature vector and the effect of image segmentation on the classification accuracy is evaluated.

  8. A Satellite Mortality Study to Support Space Systems Lifetime Prediction

    Science.gov (United States)

    Fox, George; Salazar, Ronald; Habib-Agahi, Hamid; Dubos, Gregory

    2013-01-01

    Estimating the operational lifetime of satellites and spacecraft is a complex process. Operational lifetime can differ from mission design lifetime for a variety of reasons. Unexpected mortality can occur due to human errors in design and fabrication, to human errors in launch and operations, to random anomalies of hardware and software or even satellite function degradation or technology change, leading to unrealized economic or mission return. This study focuses on data collection of public information using, for the first time, a large, publically available dataset, and preliminary analysis of satellite lifetimes, both operational lifetime and design lifetime. The objective of this study is the illustration of the relationship of design life to actual lifetime for some representative classes of satellites and spacecraft. First, a Weibull and Exponential lifetime analysis comparison is performed on the ratio of mission operating lifetime to design life, accounting for terminated and ongoing missions. Next a Kaplan-Meier survivor function, standard practice for clinical trials analysis, is estimated from operating lifetime. Bootstrap resampling is used to provide uncertainty estimates of selected survival probabilities. This study highlights the need for more detailed databases and engineering reliability models of satellite lifetime that include satellite systems and subsystems, operations procedures and environmental characteristics to support the design of complex, multi-generation, long-lived space systems in Earth orbit.

  9. The Mediterranean Moisture Contribution to Climatological and Extreme Monthly Continental Precipitation

    Directory of Open Access Journals (Sweden)

    Danica Ciric

    2018-04-01

    Full Text Available Moisture transport from its sources to surrounding continents is one of the most relevant topics in hydrology, and its role in extreme events is crucial for understanding several processes such as intense precipitation and flooding. In this study, we considered the Mediterranean Sea as the main water source and estimated its contribution to the monthly climatological and extreme precipitation events over the surrounding continental areas. To assess the effect of the Mediterranean Sea on precipitation, we used the Multi-Source Weighted-Ensemble Precipitation (MSWEP database to characterize precipitation. The Lagrangian dispersion model known as FLEXPART was used to estimate the moisture contribution of this source. This contribution was estimated by tracking particles that leave the Mediterranean basin monthly and then calculating water loss (E − P < 0 over the continental region, which was modelled by FLEXPART. The analysis was conducted using data from 1980 to 2015 with a spatial resolution of 0.25°. The results showed that, in general, the spatial pattern of the Mediterranean source’s contribution to precipitation, unlike climatology, is similar during extreme precipitation years in the regions under study. However, while the Mediterranean Sea is usually not an important source of climatological precipitation for some European regions, it is a significant source during extreme precipitation years.

  10. Multi-Temporal Multi-Sensor Analysis of Urbanization and Environmental/Climate Impact in China for Sustainable Urban Development

    Science.gov (United States)

    Ban, Yifang; Gong, Peng; Gamba, Paolo; Taubenbock, Hannes; Du, Peijun

    2016-08-01

    The overall objective of this research is to investigate multi-temporal, multi-scale, multi-sensor satellite data for analysis of urbanization and environmental/climate impact in China to support sustainable planning. Multi- temporal multi-scale SAR and optical data have been evaluated for urban information extraction using innovative methods and algorithms, including KTH- Pavia Urban Extractor, Pavia UEXT, and an "exclusion- inclusion" framework for urban extent extraction, and KTH-SEG, a novel object-based classification method for detailed urban land cover mapping. Various pixel- based and object-based change detection algorithms were also developed to extract urban changes. Several Chinese cities including Beijing, Shanghai and Guangzhou are selected as study areas. Spatio-temporal urbanization patterns and environmental impact at regional, metropolitan and city core were evaluated through ecosystem service, landscape metrics, spatial indices, and/or their combinations. The relationship between land surface temperature and land-cover classes was also analyzed.The urban extraction results showed that urban areas and small towns could be well extracted using multitemporal SAR data with the KTH-Pavia Urban Extractor and UEXT. The fusion of SAR data at multiple scales from multiple sensors was proven to improve urban extraction. For urban land cover mapping, the results show that the fusion of multitemporal SAR and optical data could produce detailed land cover maps with improved accuracy than that of SAR or optical data alone. Pixel-based and object-based change detection algorithms developed with the project were effective to extract urban changes. Comparing the urban land cover results from mulitemporal multisensor data, the environmental impact analysis indicates major losses for food supply, noise reduction, runoff mitigation, waste treatment and global climate regulation services through landscape structural changes in terms of decreases in service area, edge

  11. Coupling meteorology, metal concentrations, and Pb isotopes for source attribution in archived precipitation samples.

    Science.gov (United States)

    Graney, Joseph R; Landis, Matthew S

    2013-03-15

    A technique that couples lead (Pb) isotopes and multi-element concentrations with meteorological analysis was used to assess source contributions to precipitation samples at the Bondville, Illinois USA National Trends Network (NTN) site. Precipitation samples collected over a 16month period (July 1994-October 1995) at Bondville were parsed into six unique meteorological flow regimes using a minimum variance clustering technique on back trajectory endpoints. Pb isotope ratios and multi-element concentrations were measured using high resolution inductively coupled plasma-sector field mass spectrometry (ICP-SFMS) on the archived precipitation samples. Bondville is located in central Illinois, ~250km downwind from smelters in southeast Missouri. The Mississippi Valley Type ore deposits in Missouri provided a unique multi-element and Pb isotope fingerprint for smelter emissions which could be contrasted to industrial emissions from the Chicago and Indianapolis urban areas (~125km north and east, of Bondville respectively) and regional emissions from electric utility facilities. Differences in Pb isotopes and element concentrations in precipitation corresponded to flow regime. Industrial sources from urban areas, and thorogenic Pb from coal use, could be differentiated from smelter emissions from Missouri by coupling Pb isotopes with variations in element ratios and relative mass factors. Using a three endmember mixing model based on Pb isotope ratio differences, industrial processes in urban airsheds contributed 56±19%, smelters in southeast Missouri 26±13%, and coal combustion 18±7%, of the Pb in precipitation collected in Bondville in the mid-1990s. Copyright © 2012 Elsevier B.V. All rights reserved.

  12. Analysis on Climatic Characteristics of the Precipitation Anomaly in Southwest China in Recent 60 Years

    Institute of Scientific and Technical Information of China (English)

    ZHANG; Rong; PANG; Jing; QIN; Jun

    2012-01-01

    [Objective]The research aimed to analyze temporal-spatial distribution characteristics of the precipitation anomaly in southwest China from 1951 to 2010. [Method] Based on monthly precipitation data at 44 stations of southwest China and 160 stations of China from 1951 to 2010, by using EOF analysis, wavelet analysis and composite analysis, monthly and seasonal change rules of the precipitation in southwest China were analyzed. Corresponding spatial-temporal distribution characteristics of the precipitation in drought and flood years were studied. Temporal-spatial distribution characteristics of the precipitation anomaly in southwest China in recent 60 years were revealed. [Result]Seasonal distribution of the precipitation in southwest China was uneven and was typical single-peak type. Precipitation concentrated from May to September, and peak appeared in July. In recent years, rainfall in autumn significantly became less, while that in other seasons had no obvious change. Precipitation in summer had the cycle of 14 years, another for 6 years and 3-4 years of periodic oscillations. In wet years, precipitation in southwest China had same phase with that in southern China, and anti-phase with that in the junction of Qinghai, Gansu, Xinjiang and Tibet. In dry years, precipitation in southwest China had same phase with that in the eastern part of northwest China and northern China. [Conclusion]The research provided reference basis for prediction and pre-warning of the precipitation in the zone.

  13. ULF waves associated with enhanced subauroral proton precipitation

    Science.gov (United States)

    Immel, Thomas J.; Mende, S. B.; Frey, H. U.; Patel, J.; Bonnell, J. W.; Engebretson, M. J.; Fuselier, S. A.

    Several types of sub-auroral proton precipitation events have been identified using the Spectrographic Imager (SI) onboard the NASA-IMAGE satellite, including dayside subauroral proton flashes and detached proton arcs in the dusk sector. These have been observed at various levels of geomagnetic activity and solar wind conditions and the mechanism driving the precipitation has often been assumed to be scattering of protons into the loss cone by enhancement of ion-cyclotron waves in the interaction of the thermal plasmaspheric populations and more energetic ring current particles. Indeed, recent investigation of the detached arcs using the MPA instruments aboard the LANL geosynchronous satellites has shown there are nearly always heightened densities of cold plasma on high-altitude field lines which map down directly to the sub-auroral precipitation. If the ion-cyclotron instability is a causative mechanism, the enhancement of wave activity at ion-cyclotron frequencies should be measurable. It is here reported that magnetic pulsations in the Pc1 range occur in the vicinity of each of 4 detached arcs observed in 2000-2002, though with widely varying signatures. Additionally, longer period pulsations in the Pc5 ranges are also observed in the vicinity of the arcs, leading to the conclusion that a bounce-resonance of ring-current protons with the azimuthal Pc5 wave structure may also contribute to the detached precipitation.

  14. Antecedent precipitation index determined from CST estimates of rainfall

    Science.gov (United States)

    Martin, David W.

    1992-01-01

    This paper deals with an experimental calculation of a satellite-based antecedent precipitation index (API). The index is also derived from daily rain images produced from infrared images using an improved version of GSFC's Convective/Stratiform Technique (CST). API is a measure of soil moisture, and is based on the notion that the amount of moisture in the soil at a given time is related to precipitation at earlier times. Four different CST programs as well as the Geostationary Operational Enviroment Satellite (GOES) Precipitation Index developed by Arkin in 1979 are compared to experimental results, for the Mississippi Valley during the month of July. Rain images are shown for the best CST code and the ARK program. Comparisons are made as to the accuracy and detail of the results for the two codes. This project demonstrates the feasibility of running the CST on a synoptic scale. The Mississippi Valley case is well suited for testing the feasibility of monitoring soil moisture by means of CST. Preliminary comparisons of CST and ARK indicate significant differences in estimates of rain amount and distribution.

  15. Implications of a decrease in the precipitation area for the past and the future

    Science.gov (United States)

    Benestad, Rasmus E.

    2018-04-01

    The total area with 24 hrs precipitation has shrunk by 7% between 50°S–50°N over the period 1998–2016, according to the satellite-based Tropical Rain Measurement Mission data. A decrease in the daily precipitation area is an indication of profound changes in the hydrological cycle, where the global rate of precipitation is balanced by the global rate of evaporation. This decrease was accompanied by increases in total precipitation, evaporation, and wet-day mean precipitation. If these trends are real, then they suggest increased drought frequencies and more intense rainfall. Satellite records, however, may be inhomogeneous because they are synthesised from a number of individual missions with improved technology over time. A linear dependency was also found between the global mean temperature and the 50°S–50°N daily precipitation area with a slope value of ‑17 × 106 km 2/°C. This dependency was used with climate model simulations to make future projections which suggested a continued decrease that will strengthen in the future. The precipitation area evolves differently when the precipitation is accumulated over short and long time scales, however, and there has been a slight increase in the monthly precipitation area while the daily precipitation area decreased. An increase on monthly scale may indicate more pronounced variations in the rainfall patterns due to migrating rain-producing phenomena.

  16. EPSAT-SG: a satellite method for precipitation estimation; its concepts and implementation for the AMMA experiment

    Directory of Open Access Journals (Sweden)

    J. C. Bergès

    2010-01-01

    Full Text Available This paper presents a new rainfall estimation method, EPSAT-SG which is a frame for method design. The first implementation has been carried out to meet the requirement of the AMMA database on a West African domain. The rainfall estimation relies on two intermediate products: a rainfall probability and a rainfall potential intensity. The first one is computed from MSG/SEVIRI by a feed forward neural network. First evaluation results show better properties than direct precipitation intensity assessment by geostationary satellite infra-red sensors. The second product can be interpreted as a conditional rainfall intensity and, in the described implementation, it is extracted from GPCP-1dd. Various implementation options are discussed and comparison of this embedded product with 3B42 estimates demonstrates the importance of properly managing the temporal discontinuity. The resulting accumulated rainfall field can be presented as a GPCP downscaling. A validation based on ground data supplied by AGRHYMET (Niamey indicates that the estimation error has been reduced in this process. The described method could be easily adapted to other geographical area and operational environment.

  17. The GNSS polarimetric radio-occultation technique to sense precipitation events: a new concept to be tested aboard PAZ Low Earth Satellite

    Science.gov (United States)

    Tomás, Sergio; Oliveras, Santi; Cardellach, Estel; Rius, Antonio

    2013-04-01

    The Radio Occultation and Heavy Precipitation (ROHP) experiment, to be conducted aboard the Spanish PAZ satellite, consists of a radio occultation (RO) mission provided with dual-polarization capabilities. The research with polarimetric RO data has the goal of assessing the capabilities and limitations of this technique to infer profiles of heavy precipitation. The technique aims to provide vertical profiles of precipitation simultaneously to the vertical profiles of thermodynamic parameters (standard RO products) perfectly collocated both in space and time. If successful, the polarimetric RO will represent the first technique able to provide these complementary information on precipitation. This is a relevant input for studies on heavy and violent rainfall events, which being poorly represented by the current-generation of Numerical Weather Prediction and General Circulation Models appear to be difficult to forecast on all time-scales. The Low Earth Orbiter hosting this experiment, to be launched in 2013, will orbit at 500 km altitude in a near-Polar orbit. The Radio Occulation payload includes a RO GNSS receiver and a dual polarization (H/V) limb oriented antenna to capture the signals of setting GNSS transmitters. NOAA and UCAR participate in the ground-segment of the radiometric experiment to enable near-real time dissemination of the level-1 standard RO products. The space-based GNSS RO technique scans the atmosphere vertically at fine resolution (close to 300 meter in the troposphere) by precisely measure the delay between a GNSS transmitter and a GNSS receiver aboard a Low Earth Orbiter, when the former is setting below or rising above the Earth limb. The standard, thermodynamical, products are extracted from the excess delay induced by the atmosphere at different layers. This presentation will not focus on this well-established application, but a novel concept using polarimetry to also retrieve rain information. The precipitation-measurement principle is

  18. Using Satellite Data and Land Surface Models to Monitor and Forecast Drought Conditions in Africa and Middle East

    Science.gov (United States)

    Arsenault, K. R.; Shukla, S.; Getirana, A.; Peters-Lidard, C. D.; Kumar, S.; McNally, A.; Zaitchik, B. F.; Badr, H. S.; Funk, C. C.; Koster, R. D.; Narapusetty, B.; Jung, H. C.; Roningen, J. M.

    2017-12-01

    Drought and water scarcity are among the important issues facing several regions within Africa and the Middle East. In addition, these regions typically have sparse ground-based data networks, where sometimes remotely sensed observations may be the only data available. Long-term satellite records can help with determining historic and current drought conditions. In recent years, several new satellites have come on-line that monitor different hydrological variables, including soil moisture and terrestrial water storage. Though these recent data records may be considered too short for the use in identifying major droughts, they do provide additional information that can better characterize where water deficits may occur. We utilize recent satellite data records of Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) and the European Space Agency's Advanced Scatterometer (ASCAT) soil moisture retrievals. Combining these records with land surface models (LSMs), NASA's Catchment and the Noah Multi-Physics (MP), is aimed at improving the land model states and initialization for seasonal drought forecasts. The LSMs' total runoff is routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics, which can provide an additional means of validation against in situ streamflow data. The NASA Land Information System (LIS) software framework drives the LSMs and HyMAP and also supports the capability to assimilate these satellite retrievals, such as soil moisture and TWS. The LSMs are driven for 30+ years with NASA's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS/UCSB Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) rainfall dataset. The seasonal water deficit forecasts are generated using downscaled and bias-corrected versions of NASA's Goddard Earth Observing System Model (GEOS-5), and NOAA's Climate Forecast System (CFSv2) forecasts

  19. Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System

    Science.gov (United States)

    Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.

    2011-01-01

    The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.

  20. Automated invariant alignment to improve canonical variates in image fusion of satellite and weather radar data

    DEFF Research Database (Denmark)

    Vestergaard, Jacob Schack; Nielsen, Allan Aasbjerg

    2013-01-01

    Canonical correlation analysis (CCA) maximizes correlation between two sets of multivariate data. We applied CCA to multivariate satellite data and univariate radar data in order to produce a subspace descriptive of heavily precipitating clouds. A misalignment, inherent to the nature of the two...... data sets, was observed, corrupting the subspace. A method for aligning the two data sets is proposed, in order to overcome this issue and render a useful subspace projection. The observed corruption of the subspace gives rise to the hypothesis that the optimal correspondence, between a heavily...... precipitating cloud in the radar data and the associated cloud top registered in the satellite data, is found by a scale, rotation and translation invariant transformation together with a temporal displacement. The method starts by determining a conformal transformation of the radar data at the time of maximum...

  1. Thermoelectrical power analysis of precipitation in 6013 aluminum alloy

    International Nuclear Information System (INIS)

    Abdala, M.R.W.S.; Garcia de Blas, J.C.; Barbosa, C.; Acselrad, O.

    2008-01-01

    The 6013 aluminum alloy was first developed for application in the aircraft industry and, more recently, as a replacement option for the use of the 6061 alloy in the automotive industry. The present work describes the evolution of the process of formation and dissolution of different kinds of precipitates in 6013 aluminum alloy, subjected to different conditions of heat treatment, using for this purpose measurements of thermoelectrical power, Vickers microhardness and differential scanning calorimeter (DSC). Although in the last years many works have been published on the use of thermoelectrical power (TEP) measurements for the analysis of precipitation process in traditional alloys such as 6061, there is still little information related to 6013 alloy. The results obtained are compared with a previous characterization work on the same alloy using transmission electron microscopy. It was observed that TEP measurements are very sensitive to precipitation phenomena in this alloy, and it has been found that there is an inverse relation between TEP and Vickers microhardness values, which allowed proposing a precipitation sequence for 6013 aluminum alloy

  2. Environmental Testing Philosophy for a Sandia National Laboratories' Small Satellite Project - A Retrospective

    Energy Technology Data Exchange (ETDEWEB)

    CAP,JEROME S.

    2000-08-24

    Sandia has recently completed the flight certification test series for the Multi-Spectral Thermal Imaging satellite (MTI), which is a small satellite for which Sandia was the system integrator. A paper was presented at the 16th Aerospace Testing Seminar discussing plans for performing the structural dynamics certification program for that satellite. The testing philosophy was originally based on a combination of system level vibroacoustic tests and component level shock and vibration tests. However, the plans evolved to include computational analyses using both Finite Element Analysis and Statistical Energy Analysis techniques. This paper outlines the final certification process and discuss lessons learned including both things that went well and things that should/could have been done differently.

  3. Condensing Massive Satellite Datasets For Rapid Interactive Analysis

    Science.gov (United States)

    Grant, G.; Gallaher, D. W.; Lv, Q.; Campbell, G. G.; Fowler, C.; LIU, Q.; Chen, C.; Klucik, R.; McAllister, R. A.

    2015-12-01

    Our goal is to enable users to interactively analyze massive satellite datasets, identifying anomalous data or values that fall outside of thresholds. To achieve this, the project seeks to create a derived database containing only the most relevant information, accelerating the analysis process. The database is designed to be an ancillary tool for the researcher, not an archival database to replace the original data. This approach is aimed at improving performance by reducing the overall size by way of condensing the data. The primary challenges of the project include: - The nature of the research question(s) may not be known ahead of time. - The thresholds for determining anomalies may be uncertain. - Problems associated with processing cloudy, missing, or noisy satellite imagery. - The contents and method of creation of the condensed dataset must be easily explainable to users. The architecture of the database will reorganize spatially-oriented satellite imagery into temporally-oriented columns of data (a.k.a., "data rods") to facilitate time-series analysis. The database itself is an open-source parallel database, designed to make full use of clustered server technologies. A demonstration of the system capabilities will be shown. Applications for this technology include quick-look views of the data, as well as the potential for on-board satellite processing of essential information, with the goal of reducing data latency.

  4. An adaptive spatial model for precipitation data from multiple satellites over large regions

    KAUST Repository

    Chakraborty, Avishek; De, Swarup; Bowman, Kenneth P.; Sang, Huiyan; Genton, Marc G.; Mallick, Bani K.

    2015-01-01

    South America that has information from two satellites. We develop a flexible hierarchical model to combine instantaneous rainrate measurements from those satellites while accounting for their potential heterogeneity. Conceptually, we envision

  5. Satellite remote sensing of harmful algal blooms: A new multi-algorithm method for detecting the Florida Red Tide (Karenia brevis)

    Science.gov (United States)

    Carvalho, Gustavo A.; Minnett, Peter J.; Fleming, Lora E.; Banzon, Viva F.; Baringer, Warner

    2010-01-01

    In a continuing effort to develop suitable methods for the surveillance of Harmful Algal Blooms (HABs) of Karenia brevis using satellite radiometers, a new multi-algorithm method was developed to explore whether improvements in the remote sensing detection of the Florida Red Tide was possible. A Hybrid Scheme was introduced that sequentially applies the optimized versions of two pre-existing satellite-based algorithms: an Empirical Approach (using water-leaving radiance as a function of chlorophyll concentration) and a Bio-optical Technique (using particulate backscatter along with chlorophyll concentration). The long-term evaluation of the new multi-algorithm method was performed using a multi-year MODIS dataset (2002 to 2006; during the boreal Summer-Fall periods – July to December) along the Central West Florida Shelf between 25.75°N and 28.25°N. Algorithm validation was done with in situ measurements of the abundances of K. brevis; cell counts ≥1.5×104 cells l−1 defined a detectable HAB. Encouraging statistical results were derived when either or both algorithms correctly flagged known samples. The majority of the valid match-ups were correctly identified (~80% of both HABs and non-blooming conditions) and few false negatives or false positives were produced (~20% of each). Additionally, most of the HAB-positive identifications in the satellite data were indeed HAB samples (positive predictive value: ~70%) and those classified as HAB-negative were almost all non-bloom cases (negative predictive value: ~86%). These results demonstrate an excellent detection capability, on average ~10% more accurate than the individual algorithms used separately. Thus, the new Hybrid Scheme could become a powerful tool for environmental monitoring of K. brevis blooms, with valuable consequences including leading to the more rapid and efficient use of ships to make in situ measurements of HABs. PMID:21037979

  6. HEPD on NEXTSat-1: A High Energy Particle Detector for Measurements of Precipitating Radiation Belt Electrons

    Science.gov (United States)

    Sohn, Jongdae; Lee, Jaejin; Min, Kyoungwook; Lee, Junchan; Lee, Seunguk; Lee, Daeyoung; Jo, Gyeongbok; Yi, Yu; Na, Gowoon; Kang, Kyung-In; Shin, Goo-Hwan

    2018-05-01

    Radiation belt particles of the inner magnetosphere precipitate into the atmosphere in the subauroral regions when they are pitch-angle scattered into the loss cone by wave-particle interactions. Such particle precipitations are known to be especially enhanced during space storms, though they can also occur during quiet times. The observed characteristics of precipitating electrons can be distinctively different, in their time series as well as in their spectra, depending on the waves involved. The present paper describes the High Energy Particle Detector (HEPD) on board the Next Generation Small Satellite-1 (NEXTSat-1), which will measure these radiation belt electrons from a low-Earth polar orbit satellite to study the mechanisms related to electron precipitation in the sub-auroral regions. The HEPD is based on silicon barrier detectors and consists of three telescopes that are mounted on the satellite to have angles of 0°. 45°, and 90°, respectively with the local geomagnetic field during observations. With a high time resolution of 32 Hz and a high spectral resolution of 11 channels over the energy range from 350 keV to 2 MeV, together with the pitch angle information provided by the three telescopes, HEPD is capable of identifying physical processes, such as microbursts and dust-side relativistic electron precipitation (DREP) events associated with electron precipitations. NextSat-1 is scheduled for launch in early 2018.

  7. Climate network analysis of regional precipitation extremes: The true story told by event synchronization

    Science.gov (United States)

    Odenweller, Adrian; Donner, Reik V.

    2017-04-01

    Over the last decade, complex network methods have been frequently used for characterizing spatio-temporal patterns of climate variability from a complex systems perspective, yielding new insights into time-dependent teleconnectivity patterns and couplings between different components of the Earth climate. Among the foremost results reported, network analyses of the synchronicity of extreme events as captured by the so-called event synchronization have been proposed to be powerful tools for disentangling the spatio-temporal organization of particularly extreme rainfall events and anticipating the timing of monsoon onsets or extreme floodings. Rooted in the analysis of spike train synchrony analysis in the neurosciences, event synchronization has the great advantage of automatically classifying pairs of events arising at two distinct spatial locations as temporally close (and, thus, possibly statistically - or even dynamically - interrelated) or not without the necessity of selecting an additional parameter in terms of a maximally tolerable delay between these events. This consideration is conceptually justified in case of the original application to spike trains in electroencephalogram (EEG) recordings, where the inter-spike intervals show relatively narrow distributions at high temporal sampling rates. However, in case of climate studies, precipitation extremes defined by daily precipitation sums exceeding a certain empirical percentile of their local distribution exhibit a distinctively different type of distribution of waiting times between subsequent events. This raises conceptual concerns if event synchronization is still appropriate for detecting interlinkages between spatially distributed precipitation extremes. In order to study this problem in more detail, we employ event synchronization together with an alternative similarity measure for event sequences, event coincidence rates, which requires a manual setting of the tolerable maximum delay between two

  8. CHARACTERISTICS OF MEI-YU PRECIPITATION AND SVD ANALYSIS OF PRECIPITATION OVER THE YANGTZE-HUAIHE RIVERS VALLEYS AND THE SEA SURFACE TEMPERATURE IN THE NORTHERN PACIFIC OCEAN

    Institute of Scientific and Technical Information of China (English)

    MAO Wen-shu; WANG Qian-qian; PENG Jun; LI Yong-hua

    2008-01-01

    Based on the precipitation data of Meiyu at 37 stations in the valleys of Yangtze and Huaihe Rivers from 1954 to 2001, the temporal-spatial characteristics of Meiyu precipitation and their relationships with the sea surface temperature in northern Pacific are investigated using such methods as harmonic analysis, empirical orthogonal function (EOF), composite analysis and singular value decomposition (SVD). The results show that the temporal evolution and spatial distribution of Meiyu precipitation are not homogeneous in the Yangtze-Huaihe Rivers basins but with prominent inter-annual and inter-decadal variabilities. The key region between the anomalies of Meiyu precipitation and the monthly sea surface temperature anomalies (SSTA) lies in the west wind drift of North Pacific, which influences the precipitation anomaly of Meiyu precipitation over a key period of time from January to March in the same year. When the SST in the North Pacific west wind drift is warmer (colder) than average during these months, Meiyu precipitation anomalously increases (decreases) in the concurrent year. Results of SVD are consistent with those of composite analysis which pass the significance test of Monte-Carlo at 0.05.

  9. Mid-latitude electron precipitation into the atmosphere and related geophysical phenomena

    International Nuclear Information System (INIS)

    Chang, Y.C.

    1976-01-01

    Balloon observations of the x-ray flux of photons with energies greater than 25 keV, measured at an atmospheric depth of 8 g/cm at Roberval, Quebec (L=4.2) and satellite observations of the flux of electrons with energies greater than 35 keV in the dawn sector from L=4.2 to L=5.3 were analyzed. A differently structured cross-correlation curve was found during the first five minutes immediately after the onset of enhancement of the X-ray intensity. The technique of power spectral analysis was used to investigate periodicities in the flux. A dominant peak at the period of 0.83 second was found in the power spectral density of the counting rate of the greater than 200 keV channel during a relatively quiet-period of time from the point of view of electron precipitation. The precipitation of intermediate energy (250-500 keV) electrons responsible for the greater than 200 keV X rays was modulated at the bounce period of low energy (65-90 keV) electrons. The mechanism for the precipitation was pitch angle diffusion due to the electron-whistler mode wave interaction. Waves generated by low energy electrons in the equatorial region propagated outside of the region of growth. These waves could interact with higher energy electrons and modulate the flux of these electrons. A correlation study of the enhancement seen in the low energy channels of the S 3 satellite electron detector with the enhancement of X-ray fluxes during a substorm was made. The satellite data were used to locate where and when the injections occurred. Two sets of enhancements observed by the satellite were found to be injected at different local times at the same time which was within a few minutes of the onset of geomagnetic bays at several near-midnight ground stations. A model based on convection due to a static westward electric field and azimuthal drift due to the gradient and curvature of B was used to explain the energy dispersion and time delay of the substorm associated observations

  10. Inter-Comparison and Evaluation of Remote Sensing Precipitation Products over China from 2005 to 2013

    Directory of Open Access Journals (Sweden)

    Qiaolin Zeng

    2018-01-01

    Full Text Available Precipitation is a key aspect of the climate system. In this paper, the dependability of five satellite precipitation products (TRMM [Tropical Rainfall Measuring Mission] 3BV42, PERSIANN [Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks] CDR, GSMaP [Global Satellite Mapping of Precipitation] RENALYSIS, CMORPH [Climate Prediction Center’s morphing technique] BLD and CMORPH_RAW were compared with in situ measurements over China for the period of 2005 to 2013. To completely evaluate these precipitation products, the annual, seasonal and monthly precipitation averages were calculated. Overall, the Huaihe River and Qinlin mountains are shown to have heavy precipitation to the southeast and lighter precipitation to the northwest. The comparison results indicate that Gauge correction (CMORPH_BLD improves the quality of the original satellite products (CMORPH_RAW, resulting in the higher correlation coefficient (CC, the low relative bias (BIAS and root mean square error (RMSE. Over China, the GSMaP_RENALYSIS outperforms other products and shows the highest CC (0.91 and lowest RMSE (0.85 mm/day and all products except for PERSIANN_CDR exhibit underestimation. GSMaP_RENALYSIS gives the highest of probability of detection (81%, critical success index (63% and lowest false alarm ratio (36% while TRMM3BV42 gives the highest of frequency bias index (1.00. Over Tibetan Plateau, CMORPH_RAW demonstrates the poorest performance with the biggest BIAS (4.2 mm/month and lowest CC (0.22 in December 2013. GSMaP_RENALYSIS displays quite consistent with in situ measurements in summer. However, GSMaP_RENALYSIS and CMORPH_RAW underestimate precipitation over South China. CMORPH_BLD and TRMM3BV42 show consistent with high CC (>0.8 but relatively large RMSE in summer.

  11. GPM GROUND VALIDATION SATELLITE SIMULATED ORBITS LPVEX V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The Satellite Simulator database is available for several campaigns: Light Precipitation Evaluation Experiment (LPVEX), Midlatitude Continental Convective Clouds...

  12. Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations

    Science.gov (United States)

    Qi, W.; Zhang, C.; Fu, G.; Sweetapple, C.; Zhou, H.

    2016-02-01

    The applicability of six fine-resolution precipitation products, including precipitation radar, infrared, microwave and gauge-based products, using different precipitation computation recipes, is evaluated using statistical and hydrological methods in northeastern China. In addition, a framework quantifying uncertainty contributions of precipitation products, hydrological models, and their interactions to uncertainties in ensemble discharges is proposed. The investigated precipitation products are Tropical Rainfall Measuring Mission (TRMM) products (TRMM3B42 and TRMM3B42RT), Global Land Data Assimilation System (GLDAS)/Noah, Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and a Global Satellite Mapping of Precipitation (GSMAP-MVK+) product. Two hydrological models of different complexities, i.e. a water and energy budget-based distributed hydrological model and a physically based semi-distributed hydrological model, are employed to investigate the influence of hydrological models on simulated discharges. Results show APHRODITE has high accuracy at a monthly scale compared with other products, and GSMAP-MVK+ shows huge advantage and is better than TRMM3B42 in relative bias (RB), Nash-Sutcliffe coefficient of efficiency (NSE), root mean square error (RMSE), correlation coefficient (CC), false alarm ratio, and critical success index. These findings could be very useful for validation, refinement, and future development of satellite-based products (e.g. NASA Global Precipitation Measurement). Although large uncertainty exists in heavy precipitation, hydrological models contribute most of the uncertainty in extreme discharges. Interactions between precipitation products and hydrological models can have the similar magnitude of contribution to discharge uncertainty as the hydrological models. A

  13. Classification and global distribution of ocean precipitation types based on satellite passive microwave signatures

    Science.gov (United States)

    Gautam, Nitin

    The main objectives of this thesis are to develop a robust statistical method for the classification of ocean precipitation based on physical properties to which the SSM/I is sensitive and to examine how these properties vary globally and seasonally. A two step approach is adopted for the classification of oceanic precipitation classes from multispectral SSM/I data: (1)we subjectively define precipitation classes using a priori information about the precipitating system and its possible distinct signature on SSM/I data such as scattering by ice particles aloft in the precipitating cloud, emission by liquid rain water below freezing level, the difference of polarization at 19 GHz-an indirect measure of optical depth, etc.; (2)we then develop an objective classification scheme which is found to reproduce the subjective classification with high accuracy. This hybrid strategy allows us to use the characteristics of the data to define and encode classes and helps retain the physical interpretation of classes. The classification methods based on k-nearest neighbor and neural network are developed to objectively classify six precipitation classes. It is found that the classification method based neural network yields high accuracy for all precipitation classes. An inversion method based on minimum variance approach was used to retrieve gross microphysical properties of these precipitation classes such as column integrated liquid water path, column integrated ice water path, and column integrated min water path. This classification method is then applied to 2 years (1991-92) of SSM/I data to examine and document the seasonal and global distribution of precipitation frequency corresponding to each of these objectively defined six classes. The characteristics of the distribution are found to be consistent with assumptions used in defining these six precipitation classes and also with well known climatological patterns of precipitation regions. The seasonal and global

  14. Using constructed analogs to improve the skill of National Multi-Model Ensemble March–April–May precipitation forecasts in equatorial East Africa

    International Nuclear Information System (INIS)

    Shukla, Shraddhanand; Funk, Christopher; Hoell, Andrew

    2014-01-01

    In this study we implement and evaluate a simple ‘hybrid’ forecast approach that uses constructed analogs (CA) to improve the National Multi-Model Ensemble’s (NMME) March–April–May (MAM) precipitation forecasts over equatorial eastern Africa (hereafter referred to as EA, 2°S to 8°N and 36°E to 46°E). Due to recent declines in MAM rainfall, increases in population, land degradation, and limited technological advances, this region has become a recent epicenter of food insecurity. Timely and skillful precipitation forecasts for EA could help decision makers better manage their limited resources, mitigate socio-economic losses, and potentially save human lives. The ‘hybrid approach’ described in this study uses the CA method to translate dynamical precipitation and sea surface temperature (SST) forecasts over the Indian and Pacific Oceans (specifically 30°S to 30°N and 30°E to 270°E) into terrestrial MAM precipitation forecasts over the EA region. In doing so, this approach benefits from the post-1999 teleconnection that exists between precipitation and SSTs over the Indian and tropical Pacific Oceans (Indo-Pacific) and EA MAM rainfall. The coupled atmosphere-ocean dynamical forecasts used in this study were drawn from the NMME. We demonstrate that while the MAM precipitation forecasts (initialized in February) skill of the NMME models over the EA region itself is negligible, the ranked probability skill score of hybrid CA forecasts based on Indo-Pacific NMME precipitation and SST forecasts reach up to 0.45. (letter)

  15. Mutual information registration of multi-spectral and multi-resolution images of DigitalGlobe's WorldView-3 imaging satellite

    Science.gov (United States)

    Miecznik, Grzegorz; Shafer, Jeff; Baugh, William M.; Bader, Brett; Karspeck, Milan; Pacifici, Fabio

    2017-05-01

    WorldView-3 (WV-3) is a DigitalGlobe commercial, high resolution, push-broom imaging satellite with three instruments: visible and near-infrared VNIR consisting of panchromatic (0.3m nadir GSD) plus multi-spectral (1.2m), short-wave infrared SWIR (3.7m), and multi-spectral CAVIS (30m). Nine VNIR bands, which are on one instrument, are nearly perfectly registered to each other, whereas eight SWIR bands, belonging to the second instrument, are misaligned with respect to VNIR and to each other. Geometric calibration and ortho-rectification results in a VNIR/SWIR alignment which is accurate to approximately 0.75 SWIR pixel at 3.7m GSD, whereas inter-SWIR, band to band registration is 0.3 SWIR pixel. Numerous high resolution, spectral applications, such as object classification and material identification, require more accurate registration, which can be achieved by utilizing image processing algorithms, for example Mutual Information (MI). Although MI-based co-registration algorithms are highly accurate, implementation details for automated processing can be challenging. One particular challenge is how to compute bin widths of intensity histograms, which are fundamental building blocks of MI. We solve this problem by making the bin widths proportional to instrument shot noise. Next, we show how to take advantage of multiple VNIR bands, and improve registration sensitivity to image alignment. To meet this goal, we employ Canonical Correlation Analysis, which maximizes VNIR/SWIR correlation through an optimal linear combination of VNIR bands. Finally we explore how to register images corresponding to different spatial resolutions. We show that MI computed at a low-resolution grid is more sensitive to alignment parameters than MI computed at a high-resolution grid. The proposed modifications allow us to improve VNIR/SWIR registration to better than ¼ of a SWIR pixel, as long as terrain elevation is properly accounted for, and clouds and water are masked out.

  16. Statistical investigation of the efficiency of EMIC waves in precipitating relativistic electrons

    Science.gov (United States)

    Hudson, M. K.; Qin, M.; Millan, R. M.; Woodger, L. A.; Shekhar, S.

    2017-12-01

    Electromagnetic ion cyclotron (EMIC) waves have been proposed as an effective way to scatter relativistic electrons into the atmospheric loss cone. In our study, however, among the total 399 coincidence events when NOAA satellites goes through the region of EMIC wave activity, only 103 are associated with Relativistic Electron Precipitation (REP) events, which indicates that the link between EMIC waves and relativistic electrons is much weaker than expected. Most of the studies so far have been focused on the He+ band EMIC waves, and H+ band EMIC waves have been regarded as less important to the precipitation of electrons. In our study, we demonstrate that among the 103 EMIC wave events detected by Van Allen Probes that are in close conjunction with relativistic electron precipitation observed by POES satellites, the occurrence rate of H+ and He+ band EMIC waves coincident with REP is comparable, suggesting closer examination of the range of ΔL and ΔMLT used to determine coincidence between Van Allen Probes EMIC waves and POES precipitation observation.

  17. Effect of wine dilution on the reliability of tannin analysis by protein precipitation

    DEFF Research Database (Denmark)

    Jensen, Jacob Skibsted; Werge, Hans Henrik Malmborg; Egebo, Max

    2008-01-01

    A reported analytical method for tannin quantification relies on selective precipitation of tannins with bovine serum albumin. The reliability of tannin analysis by protein precipitation on wines having variable tannin levels was evaluated by measuring the tannin concentration of various dilutions...... of five commercial red wines. Tannin concentrations of both very diluted and concentrated samples were systematically underestimated, which could be explained by a precipitation threshold and insufficient protein for precipitation, respectively. Based on these findings, we have defined a valid range...... of the tannin response in the protein precipitation-tannin assay, which suffers minimally from these problems....

  18. Monitoring drought using multi-sensor remote sensing data in cropland of Gansu Province

    International Nuclear Information System (INIS)

    Zeng, Linglin; Shan, Jie; Xiang, Daxiang

    2014-01-01

    Various drought monitoring models have been developed from different perspectives, as drought is impacted by various factors (precipitation, evaporation, runoff) and usually reflected in various aspects (vegetation condition, temperature). Cloud not only plays an important role in the earth's energy balance and climate change, but also directly impacts the regional precipitation and evaporation. As a result, the change of cloud cover and cloud type can be used to monitor drought. This paper proposes a new drought composite index, the Drought Composite Index (DCI), for drought monitoring based on multi-sensor remote sensing data in cropland of Gansu Province. This index combines the cloud classification data (CLS) from FY satellite and Vegetation Condition Index (VCI) which was calculated using the maximum and minimum NDVI values for the same time period from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Pearson correlation was performed to correlate NDVI, VCI, CLS and DCI values to precipitation data and soil moisture (SM) data collected from 20 meteorological stations during the growing season of 2011 and 2012. Better agreement was observed between DCI and precipitation as compared with that between NDVI/VCI and precipitation, especially the one-month precipitation, and there is an obvious time lag in the response of vegetation to precipitation. In addition, the results indicated that DCI well reflected precipitation fluctuations in the study area promising a possibility for early drought awareness necessary and near real-time drought monitoring

  19. CEOS precipitation constellation

    Science.gov (United States)

    Neeck, Steven P.; Oki, Riko

    2007-10-01

    The outcomes of the 19th Committee on Earth Observing Satellites (CEOS) Plenary held in London in November 2005, recognized that the CEOS Implementation Plan for Space-Based Observations for Global Earth Observation System of Systems (GEOSS) should: - identify the supply of space-based observations required to satisfy the requirements expressed by the 10-year implementation plan for GEOSS; and - propose an innovative process whereby the many disparate types of Earth observing programs funded by CEOS Member agencies might contribute to the supply of the required observations. The CEOS Task Force charged with drafting the CEOS Implementation Plan for Space-Based Observations for GEOSS focused its early efforts on the creation of a 'new planning process' which would satisfy the various criteria demanded by member space agencies, and which would hopefully encourage a new phase of specificity and focus in the multi-lateral co-operation efforts undertaken by space agencies under the CEOS umbrella - resulting in improved engagement of all CEOS Members and real implementation results. The CEOS Constellations is the title given to this new process, and four pilot studies have been initiated in order to pioneer and test the concept. The Japan Aerospace Exploration Agency (JAXA) and the National Aeronautics and Space Administration (NASA) were selected as the lead agencies for the study of the development of a CEOS Precipitation Constellation with the support of other CEOS space agency and user community participants. The goals, approach, and anticipated outcomes for the study will be discussed.

  20. Object-Based Greenhouse Horticultural Crop Identification from Multi-Temporal Satellite Imagery: A Case Study in Almeria, Spain

    Directory of Open Access Journals (Sweden)

    Manuel A. Aguilar

    2015-06-01

    Full Text Available Greenhouse detection and mapping via remote sensing is a complex task, which has already been addressed in numerous studies. In this research, the innovative goal relies on the identification of greenhouse horticultural crops that were growing under plastic coverings on 30 September 2013. To this end, object-based image analysis (OBIA and a decision tree classifier (DT were applied to a set consisting of eight Landsat 8 OLI images collected from May to November 2013. Moreover, a single WorldView-2 satellite image acquired on 30 September 2013, was also used as a data source. In this approach, basic spectral information, textural features and several vegetation indices (VIs derived from Landsat 8 and WorldView-2 multi-temporal satellite data were computed on previously segmented image objects in order to identify four of the most popular autumn crops cultivated under greenhouse in Almería, Spain (i.e., tomato, pepper, cucumber and aubergine. The best classification accuracy (81.3% overall accuracy was achieved by using the full set of Landsat 8 time series. These results were considered good in the case of tomato and pepper crops, being significantly worse for cucumber and aubergine. These results were hardly improved by adding the information of the WorldView-2 image. The most important information for correct classification of different crops under greenhouses was related to the greenhouse management practices and not the spectral properties of the crops themselves.

  1. Detecting quasi-oscillations in the monthly precipitation regimes of the Iberian Peninsula

    Directory of Open Access Journals (Sweden)

    L. Morala

    2003-03-01

    Full Text Available A spectral analysis of the time series corresponding to the main monthly precipitation regimes of the Iberian Peninsula was performed using two methods, the Multi-Taper Method and Monte Carlo Singular Spectrum Analysis. The Multi-Taper Method gave a preliminary view of the presence of signals in some of the time series. Monte Carlo Singular Spectrum Analysis discriminated between potential oscillations and noise. From the results of the two methods it is concluded that there exist three significant quasi-oscillations at the 95% level of confidence: a 5.0 year quasi-oscillation and a long-term trend in the Atlantic pattern of March, a 3.2 year quasi-oscillation in the Cantabrian pattern of January, and a 4.0 year quasi-oscillation in the Catalonian pattern of February. These quasi-oscillations might be related to climatic variations with similar periodicities over the North Atlantic Ocean. The possible simultaneity of high values of precipitation generated by the significant quasi-oscillations and high sea–level pressures was studied by means of composite maps. It was found that high values of precipitation generated by the oscillations of the Atlantic patterns of January and March exist simultaneously with a specific high pressure structure over the North Atlantic Ocean, that allow cyclonic perturbations to cross the Iberian Peninsula. During the non-wet years, this high pressure structure moves northwards, keeping the track of the low pressure centers to the north, far from the Iberian Peninsula. On the other hand, high values of precipitation generated by the oscillation of the Cantabrian pattern of January exist simultaneously with a high pressure structure over the Galicia region and the Cantabrian Sea, that allow a northerly flow over the region. Also, a positive trend in the NAO index for March has been found, starting in the sixties, which is not evident for other winter months. This trend agrees with the decreasing trend found in the

  2. Multisensor satellite data for water quality analysis and water pollution risk assessment: decision making under deep uncertainty with fuzzy algorithm in framework of multimodel approach

    Science.gov (United States)

    Kostyuchenko, Yuriy V.; Sztoyka, Yulia; Kopachevsky, Ivan; Artemenko, Igor; Yuschenko, Maxim

    2017-10-01

    Multi-model approach for remote sensing data processing and interpretation is described. The problem of satellite data utilization in multi-modeling approach for socio-ecological risks assessment is formally defined. Observation, measurement and modeling data utilization method in the framework of multi-model approach is described. Methodology and models of risk assessment in framework of decision support approach are defined and described. Method of water quality assessment using satellite observation data is described. Method is based on analysis of spectral reflectance of aquifers. Spectral signatures of freshwater bodies and offshores are analyzed. Correlations between spectral reflectance, pollutions and selected water quality parameters are analyzed and quantified. Data of MODIS, MISR, AIRS and Landsat sensors received in 2002-2014 have been utilized verified by in-field spectrometry and lab measurements. Fuzzy logic based approach for decision support in field of water quality degradation risk is discussed. Decision on water quality category is making based on fuzzy algorithm using limited set of uncertain parameters. Data from satellite observations, field measurements and modeling is utilizing in the framework of the approach proposed. It is shown that this algorithm allows estimate water quality degradation rate and pollution risks. Problems of construction of spatial and temporal distribution of calculated parameters, as well as a problem of data regularization are discussed. Using proposed approach, maps of surface water pollution risk from point and diffuse sources are calculated and discussed.

  3. Hourly Comparison of GPM-IMERG-Final-Run and IMERG-Real-Time (V-03) over a Dense Surface Network in Northeastern Austria

    Science.gov (United States)

    Sharifi, Ehsan; Steinacker, Reinhold; Saghafian, Bahram

    2017-04-01

    Accurate quantitative daily precipitation estimation is key to meteorological and hydrological applications in hazards forecast and management. In-situ observations over mountainous areas are mostly limited, however, currently available satellite precipitation products can potentially provide the precipitation estimation needed for meteorological and hydrological applications. Over the years, blended methods that use multi-satellites and multi-sensors have been developed for estimating of global precipitation. One of the latest satellite precipitation products is GPM-IMERG (Global Precipitation Measurement with 30-minute temporal and 0.1-degree spatial resolutions) which consists of three products: Final-Run (aimed for research), Real-Time early run, and Real-Time late run. The Integrated Multisatellite Retrievals for GPM (IMERG) products built upon the success of TRMM's Multisatellite Precipitation Analysis (TMPA) products continue to make improvements in spatial and temporal resolutions and snowfall estimates. Recently, researchers who evaluated IMERG-Final-Run V-03 and other precipitation products indicated better performance for IMERG-Final-Run against other similar products. In this study two GPM-IMERG products, namely final run and real time-late run, were evaluated against a dense synoptic stations network (62 stations) over Northeastern Austria for mid-March 2015 to end of January 2016 period at hourly time-scale. Both products were examined against the reference data (stations) in capturing the occurrence of precipitation and statistical characteristics of precipitation intensity. Both satellite precipitation products underestimated precipitation events of 0.1 mm/hr to 0.4 mm/hr in intensity. For precipitations 0.4 mm/hr and greater, the trend was reversed and both satellite products overestimated than station recorded data. IMERG-RT outperformed IMERG-FR for precipitation intensity in the range of 0.1 mm/hr to 0.4 mm/hr while in the range of 1.1 to 1.8 mm

  4. Interfering line in trace analysis by X-ray spectrometry: Radiative auger satellites

    International Nuclear Information System (INIS)

    Maeda, Kuniko; Kawai, Jun.

    1994-01-01

    Strong characteristic X-ray lines (e.g. Kα and Kβ) are accompanied by broad low-energy satellites caused by the radiative Auger effect (RAE). In order to prove how the RAE satellites interfere the analysis of minor elements, low-energy side spectra of Ca and Ti Kβ, and Ca-Fe Kα were measured. The obtained RAE intensities are summarized together with published experimental and theoretical data. The integrated intensities of satellites due to K → MM, K → LM and K → LL RAE relative to that of Kα are determined to be of the order of 0.01-0.1%. This warns that the neglecting of the RAE satellites will introduce a serious error in trace analysis. (author)

  5. Spatial analysis of precipitation time series over the Upper Indus Basin

    Science.gov (United States)

    Latif, Yasir; Yaoming, Ma; Yaseen, Muhammad

    2018-01-01

    The upper Indus basin (UIB) holds one of the most substantial river systems in the world, contributing roughly half of the available surface water in Pakistan. This water provides necessary support for agriculture, domestic consumption, and hydropower generation; all critical for a stable economy in Pakistan. This study has identified trends, analyzed variability, and assessed changes in both annual and seasonal precipitation during four time series, identified herein as: (first) 1961-2013, (second) 1971-2013, (third) 1981-2013, and (fourth) 1991-2013, over the UIB. This study investigated spatial characteristics of the precipitation time series over 15 weather stations and provides strong evidence of annual precipitation by determining significant trends at 6 stations (Astore, Chilas, Dir, Drosh, Gupis, and Kakul) out of the 15 studied stations, revealing a significant negative trend during the fourth time series. Our study also showed significantly increased precipitation at Bunji, Chitral, and Skardu, whereas such trends at the rest of the stations appear insignificant. Moreover, our study found that seasonal precipitation decreased at some locations (at a high level of significance), as well as periods of scarce precipitation during all four seasons. The observed decreases in precipitation appear stronger and more significant in autumn; having 10 stations exhibiting decreasing precipitation during the fourth time series, with respect to time and space. Furthermore, the observed decreases in precipitation appear robust and more significant for regions at high elevation (>1300 m). This analysis concludes that decreasing precipitation dominated the UIB, both temporally and spatially including in the higher areas.

  6. Synoptic Disturbances Found in Precipitable Water Fields North of Equatorial Africa

    National Research Council Canada - National Science Library

    Patla, Jason

    1999-01-01

    The origin and structure of tropical synoptic scale precipitable water (PW) anomalies estimated from TOVS satellite observations are analyzed as they propagate eastward across northern Africa during MAM 1988...

  7. Improving multisensor estimation of heavy-to-extreme precipitation via conditional bias-penalized optimal estimation

    Science.gov (United States)

    Kim, Beomgeun; Seo, Dong-Jun; Noh, Seong Jin; Prat, Olivier P.; Nelson, Brian R.

    2018-01-01

    A new technique for merging radar precipitation estimates and rain gauge data is developed and evaluated to improve multisensor quantitative precipitation estimation (QPE), in particular, of heavy-to-extreme precipitation. Unlike the conventional cokriging methods which are susceptible to conditional bias (CB), the proposed technique, referred to herein as conditional bias-penalized cokriging (CBPCK), explicitly minimizes Type-II CB for improved quantitative estimation of heavy-to-extreme precipitation. CBPCK is a bivariate version of extended conditional bias-penalized kriging (ECBPK) developed for gauge-only analysis. To evaluate CBPCK, cross validation and visual examination are carried out using multi-year hourly radar and gauge data in the North Central Texas region in which CBPCK is compared with the variant of the ordinary cokriging (OCK) algorithm used operationally in the National Weather Service Multisensor Precipitation Estimator. The results show that CBPCK significantly reduces Type-II CB for estimation of heavy-to-extreme precipitation, and that the margin of improvement over OCK is larger in areas of higher fractional coverage (FC) of precipitation. When FC > 0.9 and hourly gauge precipitation is > 60 mm, the reduction in root mean squared error (RMSE) by CBPCK over radar-only (RO) is about 12 mm while the reduction in RMSE by OCK over RO is about 7 mm. CBPCK may be used in real-time analysis or in reanalysis of multisensor precipitation for which accurate estimation of heavy-to-extreme precipitation is of particular importance.

  8. A Coupled GCM-Cloud Resolving Modeling System, and a Regional Scale Model to Study Precipitation Processes

    Science.gov (United States)

    Tao, Wei-Kuo

    2007-01-01

    Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a superparameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (2ICE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generatio11 regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

  9. Multi-sensor satellite and in situ monitoring of phytoplankton development in a eutrophic-mesotrophic lake.

    Science.gov (United States)

    Dörnhöfer, Katja; Klinger, Philip; Heege, Thomas; Oppelt, Natascha

    2018-01-15

    Phytoplankton indicated by its photosynthetic pigment chlorophyll-a is an important pointer on lake ecology and a regularly monitored parameter within the European Water Framework Directive. Along with eutrophication and global warming cyanobacteria gain increasing importance concerning human health aspects. Optical remote sensing may support both the monitoring of horizontal distribution of phytoplankton and cyanobacteria at the lake surface and the reduction of spatial uncertainties associated with limited water sample analyses. Temporal and spatial resolution of using only one satellite sensor, however, may constrain its information value. To discuss the advantages of a multi-sensor approach the sensor-independent, physically based model MIP (Modular Inversion and Processing System) was applied at Lake Kummerow, Germany, and lake surface chlorophyll-a was derived from 33 images of five different sensors (MODIS-Terra, MODIS-Aqua, Landsat 8, Landsat 7 and Sentinel-2A). Remotely sensed lake average chlorophyll-a concentration showed a reasonable development and varied between 2.3±0.4 and 35.8±2.0mg·m -3 from July to October 2015. Match-ups between in situ and satellite chlorophyll-a revealed varying performances of Landsat 8 (RMSE: 3.6 and 19.7mg·m -3 ), Landsat 7 (RMSE: 6.2mg·m -3 ), Sentinel-2A (RMSE: 5.1mg·m -3 ) and MODIS (RMSE: 12.8mg·m -3 ), whereas an in situ data uncertainty of 48% needs to be respected. The temporal development of an index on harmful algal blooms corresponded well with the cyanobacteria biomass development during summer months. Satellite chlorophyll-a maps allowed to follow spatial patterns of chlorophyll-a distribution during a phytoplankton bloom event. Wind conditions mainly explained spatial patterns. Integrating satellite chlorophyll-a into trophic state assessment resulted in different trophic classes. Our study endorsed a combined use of satellite and in situ chlorophyll-a data to alleviate weaknesses of both approaches and

  10. Black carbon and West African Monsoon precipitation. Observations and simulations

    International Nuclear Information System (INIS)

    Huang, J.; Adams, A.; Zhang, C.; Wang, C.

    2009-01-01

    We have recently investigated large-scale co-variability between aerosol and precipitation and other meteorological variables in the West African Monsoon (WAM) region using long term satellite observations and reanalysis data. In this study we compared the observational results to a global model simulation including only direct radiative forcing of black carbon (BC). From both observations and model simulations we found that in boreal cold seasons anomalously high African aerosols are associated with significant reductions in cloud amount, cloud top height, and surface precipitation. These results suggest that the observed precipitation reduction in the WAM region is caused by radiative effect of BC. The result also suggests that the BC effect on precipitation is nonlinear. (orig.)

  11. Polarbrdf: A General Purpose Python Package for Visualization Quantitative Analysis of Multi-Angular Remote Sensing Measurements

    Science.gov (United States)

    Singh, Manoj K.; Gautam, Ritesh; Gatebe, Charles K.; Poudyal, Rajesh

    2016-01-01

    The Bidirectional Reflectance Distribution Function (BRDF) is a fundamental concept for characterizing the reflectance property of a surface, and helps in the analysis of remote sensing data from satellite, airborne and surface platforms. Multi-angular remote sensing measurements are required for the development and evaluation of BRDF models for improved characterization of surface properties. However, multi-angular data and the associated BRDF models are typically multidimensional involving multi-angular and multi-wavelength information. Effective visualization of such complex multidimensional measurements for different wavelength combinations is presently somewhat lacking in the literature, and could serve as a potentially useful research and teaching tool in aiding both interpretation and analysis of BRDF measurements. This article describes a newly developed software package in Python (PolarBRDF) to help visualize and analyze multi-angular data in polar and False Color Composite (FCC) forms. PolarBRDF also includes functionalities for computing important multi-angular reflectance/albedo parameters including spectral albedo, principal plane reflectance and spectral reflectance slope. Application of PolarBRDF is demonstrated using various case studies obtained from airborne multi-angular remote sensing measurements using NASA's Cloud Absorption Radiometer (CAR). Our visualization program also provides functionalities for untangling complex surface/atmosphere features embedded in pixel-based remote sensing measurements, such as the FCC imagery generation of BRDF measurements of grasslands in the presence of wild fire smoke and clouds. Furthermore, PolarBRDF also provides quantitative information of the angular distribution of scattered surface/atmosphere radiation, in the form of relevant BRDF variables such as sunglint, hotspot and scattering statistics.

  12. Links between North Atlantic atmospheric blocking and recent trends in European winter precipitation

    Science.gov (United States)

    Ummenhofer, Caroline; Seo, Hyodae; Kwon, Young-Oh; Joyce, Terrence

    2015-04-01

    European precipitation has sustained robust trends during wintertime (January - March) over recent decades. Central, western, and northern Europe have become wetter by an average 0.1-0.3% per annum for the period 1901-2010, while southern Europe, including the Iberian Peninsula, much of Italy and the Balkan States, has sustained drying of -0.2% per annum or more over the same period. The overall pattern is consistent across different observational precipitation products, while the magnitude of the precipitation trends varies amongst data sets. Using cluster analysis, which identifies recurrent states (or regimes) of European winter precipitation by grouping them according to an objective similarity criterion, changes in the frequency of dominant winter precipitation patterns over the past century are evaluated. Considerable multi-decadal variability exists in the frequency of dominant winter precipitation patterns: more recent decades are characterised by significantly fewer winters with anomalous wet conditions over southern, western, and central Europe. In contrast, winters with dry conditions in western and southern Europe, but above-average rainfall in western Scandinavia and the northern British Isles, have been more common recently. We evaluate the associated multi-decadal large-scale circulation changes across the broader extratropical North Atlantic region, which accompany the observed wintertime precipitation variability using the 20th Century reanalysis product. Some influence of the North Atlantic Oscillation (NAO) is apparent in modulating the frequency of dominant precipitation patterns. However, recent trends in the characteristics of atmospheric blocking across the North Atlantic sector indicate a change in the dominant blocking centres (near Greenland, the British Isles, and west of the Iberian Peninsula). Associated changes in sea level pressure, storm track position and strength, and oceanic heat fluxes across the North Atlantic region are also

  13. Analysis on BDS Satellite Internal Multipath and Its Impact on Wide-lane FCB Estimation

    Directory of Open Access Journals (Sweden)

    RUAN Rengui

    2017-08-01

    Full Text Available To the issue of the satellite internal multipath (SIMP of BeiDou satellites, it proposed and emphasized that the SIMP model should be established as a function of the nadir angle with respect to the observed satellite rather than the elevation of the measurement, so that it can be used for receivers at various altitude. BDS data from global distributed stations operated by the International Monitoring and Assessment System (iGMAS and the Multi-GNSS Experiment (MGEX of the International GNSS Service (IGS are collected and a new SIMP model as a piece-wise linear function of the nadir angle is released for the IGSO-and MEO-satellite groups and for B1, B2 and B3 frequency band individually. The SIMP of GEO,IGSO and MEO satellites is further analyzed with B1/B2 dual-frequency data onboard the FengYun-3 C(FY3C satellite at an altitude of~830 km, and it showed that, for nadir angles smaller than 7°, the SIMP values for GEO is quite close to the IGSO's, especially for B2, which may suggest that the SIMP model for IGSO satellites possibly also works for GEO satellites. It also demonstrated that, when the nadir angle is smaller than 12°for the MEO and 7°for the IGSO, the estimated SIMP model with data from FY3C is considerable consistent with that estimated with data collected at ground stations. Experiments are carried out to investigate the impacts of the SIMP on wide-lane fractional cycle bias (FCB estimation for BDS satellites. The result indicates that, with the correction of the estimated SIMP, the repeatability of the FCB series is significantly improved by more than 60% for all satellites. Specifically, for the MEO and IGSO satellites, the repeatability is smaller than 0.05 cycle; the repeatability of 0.023 and 0.068 cycles achieved for GEO satellites C01 and C02 respectively with the estimated SIMP model for IGSO satellites.

  14. The Climate Hazards group InfraRed Precipitation (CHIRP) with Stations (CHIRPS): Development and Validation

    Science.gov (United States)

    Peterson, P.; Funk, C. C.; Husak, G. J.; Pedreros, D. H.; Landsfeld, M.; Verdin, J. P.; Shukla, S.

    2013-12-01

    CHIRP and CHIRPS are new quasi-global precipitation products with daily to seasonal time scales, a 0.05° resolution, and a 1981 to near real-time period of record. Developed by the Climate Hazards Group at UCSB and scientists at the U.S. Geological Survey Earth Resources Observation and Science Center specifically for drought early warning and environmental monitoring, CHIRPS provides moderate latency precipitation estimates that place observed hydrologic extremes in their historic context. Three main types of information are used in the CHIRPS: (1) global 0.05° precipitation climatologies, (2) time-varying grids of satellite-based precipitation estimates, and (3) in situ precipitation observations. CHIRP: The global grids of long-term (1980-2009) average precipitation were estimated for each month based on station data, averaged satellite observations, and physiographic parameters. 1981-present time-varying grids of satellite precipitation were derived from spatially varying regression models based on pentadal cold cloud duration (CCD) values and TRMM V7 training data. The CCD time-series were derived from the CPC and NOAA B1 datasets. Pentadal CCD-percent anomaly values were multiplied by pentadal climatology fields to produce low bias pentadal precipitation estimates. CHIRPS: The CHG station blending procedure uses the satellite-observed spatial covariance structure to assign relative weights to neighboring stations and the CHIRP values. The CHIRPS blending procedure is based on the expected correlation between precipitation at a given target location and precipitation at the locations of the neighboring observation stations. These correlations are estimated using the CHIRP fields. The CHG has developed an extensive archive of in situ daily, pentadal and monthly precipitation totals. The CHG database has over half a billion daily rainfall observations since 1980 and another half billion before 1980. Most of these observations come from four sets of global

  15. STABILITY OF SATELLITES IN CLOSELY PACKED PLANETARY SYSTEMS

    International Nuclear Information System (INIS)

    Payne, Matthew J.; Holman, Matthew J.; Deck, Katherine M.; Perets, Hagai B.

    2013-01-01

    We perform numerical integrations of four-body (star, planet, planet, satellite) systems to investigate the stability of satellites in planetary systems with tightly packed inner planets (STIPs). We find that the majority of closely spaced stable two-planet systems can stably support satellites across a range of parameter-space which is only slightly decreased compared to that seen for the single-planet case. In particular, circular prograde satellites remain stable out to ∼0.4 R H (where R H is the Hill radius) as opposed to 0.5 R H in the single-planet case. A similarly small restriction in the stable parameter-space for retrograde satellites is observed, where planetary close approaches in the range 2.5-4.5 mutual Hill radii destabilize most satellites orbits only if a ∼ 0.65 R H . In very close planetary pairs (e.g., the 12:11 resonance) the addition of a satellite frequently destabilizes the entire system, causing extreme close approaches and the loss of satellites over a range of circumplanetary semi-major axes. The majority of systems investigated stably harbored satellites over a wide parameter-space, suggesting that STIPs can generally offer a dynamically stable home for satellites, albeit with a slightly smaller stable parameter-space than the single-planet case. As we demonstrate that multi-planet systems are not a priori poor candidates for hosting satellites, future measurements of satellite occurrence rates in multi-planet systems versus single-planet systems could be used to constrain either satellite formation or past periods of strong dynamical interaction between planets

  16. Sampling of Atmospheric Precipitation and Deposits for Analysis of Atmospheric Pollution

    OpenAIRE

    Skarżyńska, K.; Polkowska, Ż; Namieśnik, J.

    2006-01-01

    This paper reviews techniques and equipment for collecting precipitation samples from the atmosphere (fog and cloud water) and from atmospheric deposits (dew, hoarfrost, and rime) that are suitable for the evaluation of atmospheric pollution. It discusses the storage and preparation of samples for analysis and also presents bibliographic information on the concentration ranges of inorganic and organic compounds in the precipitation and atmospheric deposit samples.

  17. Asia-MIP: Multi Model-data Synthesis of Terrestrial Carbon Cycles in Asia

    Science.gov (United States)

    Ichii, K.; Kondo, M.; Ito, A.; Kang, M.; Sasai, T.; SATO, H.; Ueyama, M.; Kobayashi, H.; Saigusa, N.; Kim, J.

    2013-12-01

    Asia, which is characterized by monsoon climate and intense human activities, is one of the prominent understudied regions in terms of terrestrial carbon budgets and mechanisms of carbon exchange. To better understand terrestrial carbon cycle in Asia, we initiated multi-model and data intercomparison project in Asia (Asia-MIP). We analyzed outputs from multiple approaches: satellite-based observations (AVHRR and MODIS) and related products, empirically upscaled estimations (Support Vector Regression) using eddy-covariance observation network in Asia (AsiaFlux, CarboEastAsia, FLUXNET), ~10 terrestrial biosphere models (e.g. BEAMS, Biome-BGC, LPJ, SEIB-DGVM, TRIFFID, VISIT models), and atmospheric inversion analysis (e.g. TransCom models). We focused on the two difference temporal coverage: long-term (30 years; 1982-2011) and decadal (10 years; 2001-2010; data intensive period) scales. The regions of covering Siberia, Far East Asia, East Asia, Southeast Asia and South Asia (60-80E, 10S-80N), was analyzed in this study for assessing the magnitudes, interannual variability, and key driving factors of carbon cycles. We will report the progress of synthesis effort to quantify terrestrial carbon budget in Asia. First, we analyzed the recent trends in Gross Primary Productivities (GPP) using satellite-based observation (AVHRR) and multiple terrestrial biosphere models. We found both model outputs and satellite-based observation consistently show an increasing trend in GPP in most of the regions in Asia. Mechanisms of the GPP increase were analyzed using models, and changes in temperature and precipitation play dominant roles in GPP increase in boreal and temperate regions, whereas changes in atmospheric CO2 and precipitation are important in tropical regions. However, their relative contributions were different. Second, in the decadal analysis (2001-2010), we found that the negative GPP and carbon uptake anomalies in 2003 summer in Far East Asia is one of the largest

  18. Landslide mapping with multi-scale object-based image analysis – a case study in the Baichi watershed, Taiwan

    Directory of Open Access Journals (Sweden)

    T. Lahousse

    2011-10-01

    Full Text Available We developed a multi-scale OBIA (object-based image analysis landslide detection technique to map shallow landslides in the Baichi watershed, Taiwan, after the 2004 Typhoon Aere event. Our semi-automated detection method selected multiple scales through landslide size statistics analysis for successive classification rounds. The detection performance achieved a modified success rate (MSR of 86.5% with the training dataset and 86% with the validation dataset. This performance level was due to the multi-scale aspect of our methodology, as the MSR for single scale classification was substantially lower, even after spectral difference segmentation, with a maximum of 74%. Our multi-scale technique was capable of detecting landslides of varying sizes, including very small landslides, up to 95 m2. The method presented certain limitations: the thresholds we established for classification were specific to the study area, to the landslide type in the study area, and to the spectral characteristics of the satellite image. Because updating site-specific and image-specific classification thresholds is easy with OBIA software, our multi-scale technique is expected to be useful for mapping shallow landslides at watershed level.

  19. Vegetation anomalies caused by antecedent precipitation in most of the world

    Science.gov (United States)

    Papagiannopoulou, C.; Miralles, D. G.; Dorigo, W. A.; Verhoest, N. E. C.; Depoorter, M.; Waegeman, W.

    2017-07-01

    Quantifying environmental controls on vegetation is critical to predict the net effect of climate change on global ecosystems and the subsequent feedback on climate. Following a non-linear Granger causality framework based on a random forest predictive model, we exploit the current wealth of multi-decadal satellite data records to uncover the main drivers of monthly vegetation variability at the global scale. Results indicate that water availability is the most dominant factor driving vegetation globally: about 61% of the vegetated surface was primarily water-limited during 1981-2010. This included semiarid climates but also transitional ecoregions. Intra-annually, temperature controls Northern Hemisphere deciduous forests during the growing season, while antecedent precipitation largely dominates vegetation dynamics during the senescence period. The uncovered dependency of global vegetation on water availability is substantially larger than previously reported. This is owed to the ability of the framework to (1) disentangle the co-linearities between radiation/temperature and precipitation, and (2) quantify non-linear impacts of climate on vegetation. Our results reveal a prolonged effect of precipitation anomalies in dry regions: due to the long memory of soil moisture and the cumulative, non-linear, response of vegetation, water-limited regions show sensitivity to the values of precipitation occurring three months earlier. Meanwhile, the impacts of temperature and radiation anomalies are more immediate and dissipate shortly, pointing to a higher resilience of vegetation to these anomalies. Despite being infrequent by definition, hydro-climatic extremes are responsible for up to 10% of the vegetation variability during the 1981-2010 period in certain areas, particularly in water-limited ecosystems. Our approach is a first step towards a quantitative comparison of the resistance and resilience signature of different ecosystems, and can be used to benchmark Earth

  20. Anticipated Improvements in Precipitation Physics and Understanding of Water Cycle from GPM Mission

    Science.gov (United States)

    Smith, Eric A.

    2003-01-01

    The GPM mission is currently planned for start in the late-2007 to early-2008 time frame. Its main scientific goal is to help answer pressing scientific problems arising within the context of global and regional water cycles. These problems cut across a hierarchy of scales and include climate-water cycle interactions, techniques for improving weather and climate predictions, and better methods for combining observed precipitation with hydrometeorological prediction models for applications to hazardous flood-producing storms, seasonal flood/draught conditions, and fresh water resource assessments. The GPM mission will expand the scope of precipitation measurement through the use of a constellation of some 9 satellites, one of which will be an advanced TRMM-like core satellite carrying a dual-frequency Ku-Ka band precipitation radar and an advanced, multifrequency passive microwave radiometer with vertical-horizontal polarization discrimination. The other constellation members will include new dedicated satellites and co-existing operational/research satellites carrying similar (but not identical) passive microwave radiometers. The goal of the constellation is to achieve approximately 3-hour sampling at any spot on the globe -- continuously. The constellation s orbit architecture will consist of a mix of sun-synchronous and non-sun-synchronous satellites with the core satellite providing measurements of cloud-precipitation microphysical processes plus calibration-quality rainrate retrievals to be used with the other retrieval information to ensure bias-free constellation coverage. GPM is organized internationally, involving existing, pending, projected, and under-study partnerships which will link NASA and NOAA in the US, NASDA in Japan, ESA in Europe, ISRO in India, CNES in France, and possibly AS1 in Italy, KARI in South Korea, CSA in Canada, and AEB in Brazil. Additionally, the program is actively pursuing agreements with other international collaborators and