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.

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

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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.

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

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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

Satellite precipitation estimation over the Tibetan Plateau

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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

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

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.

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

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

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.

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.

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

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.

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.

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)

Improving the Regional Applicability of Satellite Precipitation Products by Ensemble Algorithm

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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.

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

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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.

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

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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

A global satellite assisted precipitation climatology

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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

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.

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.

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

Science.gov (United States)

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

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

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

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

Science.gov (United States)

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.

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

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.

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.

PoPSat: The Polar Precipitation Satellite Mission

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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

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.

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

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

Science.gov (United States)

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.

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.

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%.

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.

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

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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.

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.

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

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.)

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

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

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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

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

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

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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.

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.

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

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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.

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

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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

Validation and Error Characterization for the Global Precipitation Measurement

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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

Geographically weighted regression based methods for merging satellite and gauge precipitation

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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.

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

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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.

Online Assessment of Satellite-Derived Global Precipitation Products

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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

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

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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

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.

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

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

2009-04-01

Operational Estimation of Accumulated Precipitation using Satellite Observation, by Eumetsat Satellite Application facility in Support to Hydrology (H-SAF Consortium). Cap. Attilio DI DIODATO(*), T.Col. Luigi DE LEONIBUS(*), T.Col Francesco ZAULI(*), Cap. Daniele BIRON(*), Ten. Davide Melfi(*) Satellite Application Facilities (SAFs) are specialised development and processing centres of the EUMETSAT Distributed Ground Segment. SAFs process level 1b data from meteorological satellites (geostationary and polar ones) in conjunction with all other relevant sources of data and appropriate models to generate services and level 2 products. Each SAF is a consortium of EUMETSAT European partners lead by a host institute responsible for the management of the complete SAF project. The Meteorological Service of Italian Air Force is the host Institute for the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF). HSAF has the commitment to develop and to provide, operationally after 2010, products regarding precipitation, soil moisture and snow. HSAF is going to provide information on error structure of its products and validation of the products via their impacts into Hydrological models. To that purpose it has been structured a specific subgroups. Accumulated precipitation is computed by temporal integration of the instantaneous rain rate achieved by the blended LEO/MW and GEO/IR precipitation rate products generated by Rapid Update method available every 15 minutes. The algorithm provides four outputs, consisting in accumulated precipitation in 3, 6, 12 and 24 hours, delivered every 3 hours at the synoptic hours. These outputs are our precipitation background fields. Satellite estimates can cover most of the globe, however, they suffer from errors due to lack of a direct relationship between observation parameters and precipitation, the poor sampling and algorithm imperfections. For this reason the 3 hours accumulated precipitation is

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

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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.

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

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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

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

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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.

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

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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.

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

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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

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...

The assessment of Global Precipitation Measurement estimates over the Indian subcontinent

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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.

Assessment of Precipitation Data Generated by GPM and TRMM Satellites

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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.

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

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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.

Variability of Evaporation and Precipitation over the Ocean from Satellite Data

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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.

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

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.

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.

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

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.

Satellite and ground measurements of latitude distribution of upper ionosphere parameters in the region of the main trough of ionization

International Nuclear Information System (INIS)

Filippov, V.M.; Alekseev, V.N.; Afonin, V.V.

1988-01-01

Results of simultaneous complex measurements of subauroral ionosphere structure at observations of charged-particle precipitation at Interkosmos-19 satellite, electron concentration and temperature at Kosmos-900 satellite, ionosphere parameters and plasma convection at Zhigansk (L∼4) and Jakutsk (L∼3) stations and 630.0 mm line luminescence by scanning photometer at Zhigansk station, carried out on the 26 - 27.03.1979, are presented. It is found, that the through polar edge is formed by low-energy electron precipitations in diffuse auroral zone. It is confirmed by spatial coincidence of diffuse precipitations equatorial boundary, determined by satellite and ground optical measurements, with the ionization main through polar edge, determined by ground ionospherical observation and satellite measurements Ne at Kosmos-900 satellite. Results of these complex experiments show as well, that one of the main mechanisms of main ionospherical through formation may be plasma convection peculiarities within F region at subauroral zone widthes

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.

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.

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.

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.

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...

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

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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.

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.

Performance of the Falling Snow Retrieval Algorithms for the Global Precipitation Measurement (GPM) Mission

Science.gov (United States)

Skofronick-Jackson, Gail; Munchak, Stephen J.; Ringerud, Sarah

2016-01-01

Retrievals of falling snow from space represent an important data set for understanding the Earth's atmospheric, hydrological, and energy cycles, especially during climate change. Estimates of falling snow must be captured to obtain the true global precipitation water cycle, snowfall accumulations are required for hydrological studies, and without knowledge of the frozen particles in clouds one cannot adequately understand the energy and radiation budgets. While satellite-based remote sensing provides global coverage of falling snow events, the science is relatively new and retrievals are still undergoing development with challenges remaining). This work reports on the development and testing of retrieval algorithms for the Global Precipitation Measurement (GPM) mission Core Satellite, launched February 2014.

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.

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.

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.

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

Global Precipitation Measurement (GPM) Core Observatory Falling Snow Estimates

Science.gov (United States)

Skofronick Jackson, G.; Kulie, M.; Milani, L.; Munchak, S. J.; Wood, N.; Levizzani, V.

2017-12-01

Retrievals of falling snow from space represent an important data set for understanding and linking the Earth's atmospheric, hydrological, and energy cycles. Estimates of falling snow must be captured to obtain the true global precipitation water cycle, snowfall accumulations are required for hydrological studies, and without knowledge of the frozen particles in clouds one cannot adequately understand the energy and radiation budgets. This work focuses on comparing the first stable falling snow retrieval products (released May 2017) for the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO), which was launched February 2014, and carries both an active dual frequency (Ku- and Ka-band) precipitation radar (DPR) and a passive microwave radiometer (GPM Microwave Imager-GMI). Five separate GPM-CO falling snow retrieval algorithm products are analyzed including those from DPR Matched (Ka+Ku) Scan, DPR Normal Scan (Ku), DPR High Sensitivity Scan (Ka), combined DPR+GMI, and GMI. While satellite-based remote sensing provides global coverage of falling snow events, the science is relatively new, the different on-orbit instruments don't capture all snow rates equally, and retrieval algorithms differ. Thus a detailed comparison among the GPM-CO products elucidates advantages and disadvantages of the retrievals. GPM and CloudSat global snowfall evaluation exercises are natural investigative pathways to explore, but caution must be undertaken when analyzing these datasets for comparative purposes. This work includes outlining the challenges associated with comparing GPM-CO to CloudSat satellite snow estimates due to the different sampling, algorithms, and instrument capabilities. We will highlight some factors and assumptions that can be altered or statistically normalized and applied in an effort to make comparisons between GPM and CloudSat global satellite falling snow products as equitable as possible.

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

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.

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

Science.gov (United States)

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.

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.

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.

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

Science.gov (United States)

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

Quantitative measurement of lightning-induced electron precipitation using VLF remote sensing

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Peter, William Bolton

This dissertation examines the detection of lightning-induced energetic electron precipitation via subionospheric Very Low Frequency (VLF) remote sensing. The primary measurement tool used is a distributed set of VLF observing sites, the Holographic Array for Ionospheric/Lightning Research (HAIL), located along the eastern side of the Rocky Mountains in the Central United States. Measurements of the VLF signal perturbations indicate that 90% of the precipitation occurs over a region ˜8 degrees in latitudinal extent, with the peak of the precipitation poleward displaced ˜7 degrees from the causative discharge. A comparison of the VLF signal perturbations recorded on the HAIL array with a comprehensive model of LEP events allows for the quantitative measurement of electron precipitation and ionospheric density enhancement with unprecedented quantitative detail. The model consists of three major components: a test-particle model of gyroresonant whistler-induced electron precipitation; a Monte Carlo simulation of energy deposition into the ionosphere; and a model of VLF subionospheric signal propagation. For the two representative LEP events studied, the model calculates peak VLF amplitude and phase perturbations within a factor of three of those observed, well within the expected variability of radiation belt flux levels. The modeled precipitated energy flux (E>45 keV) peaks at ˜1 x 10-2 [ergs s-1 cm -2], resulting in a peak loss of ˜0.001% from a single flux tube at L˜2.2, consistent with previous satellite measurements of LEP events. Metrics quantifying the ionospheric density enhancement (N ILDE) and the electron precipitation (Gamma) are strongly correlated with the VLF signal perturbations calculated by the model. A conversion ratio Psi relates VLF signal amplitude perturbations (DeltaA) to the time-integrated precipitation (100-300 keV) along the VLF path (Psi=Gamma / DeltaA). The total precipitation (100-300 keV) induced by one of the representative LEP

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.

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

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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

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

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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.

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

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

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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.

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

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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.

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.

The Day-1 GPM Combined Precipitation Algorithm: IMERG

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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

Measurement of precipitation using lysimeters

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Fank, Johann; Klammler, Gernot

2013-04-01

Austria's alpine foothill aquifers contain important drinking water resources, but are also used intensively for agricultural production. These groundwater bodies are generally recharged by infiltrating precipitation. A sustainable water resources management of these aquifers requires quantifying real evapotranspiration (ET), groundwater recharge (GR), precipitation (P) and soil water storage change (ΔS). While GR and ΔS can be directly measured by weighable lysimeters and P by separate precipitation gauges, ET is determined by solving the climatic water balance ET = P GR ± ΔS. According to WMO (2008) measurement of rainfall is strongly influenced by precipitation gauge errors. Most significant errors result from wind loss, wetting loss, evaporation loss, and due to in- and out-splashing of water. Measuring errors can be reduced by a larger area of the measuring gaugés surface and positioning the collecting vessel at ground level. Modern weighable lysimeters commonly have a surface of 1 m², are integrated into their typical surroundings of vegetation cover (to avoid oasis effects) and allow scaling the mass change of monolithic soil columns in high measuring accuracy (0.01 mm water equivalent) and high temporal resolution. Thus, also precipitation can be quantified by measuring the positive mass changes of the lysimeter. According to Meissner et al. (2007) also dew, fog and rime can be determined by means of highly precise weighable lysimeters. Furthermore, measuring precipitation using lysimeters avoid common measuring errors (WMO 2008) at point scale. Though, this method implicates external effects (background noise, influence of vegetation and wind) which affect the mass time series. While the background noise of the weighing is rather well known and can be filtered out of the mass time series, the influence of wind, which blows through the vegetation and affects measured lysimeter mass, cannot be corrected easily since there is no clear relation between

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.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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.

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

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.

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

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

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.

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.

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.

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.

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

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.

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.

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.

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)

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.

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

Errors and Correction of Precipitation Measurements in China

Institute of Scientific and Technical Information of China (English)

REN Zhihua; LI Mingqin

2007-01-01

In order to discover the range of various errors in Chinese precipitation measurements and seek a correction method, 30 precipitation evaluation stations were set up countrywide before 1993. All the stations are reference stations in China. To seek a correction method for wind-induced error, a precipitation correction instrument called the "horizontal precipitation gauge" was devised beforehand. Field intercomparison observations regarding 29,000 precipitation events have been conducted using one pit gauge, two elevated operational gauges and one horizontal gauge at the above 30 stations. The range of precipitation measurement errors in China is obtained by analysis of intercomparison measurement results. The distribution of random errors and systematic errors in precipitation measurements are studied in this paper.A correction method, especially for wind-induced errors, is developed. The results prove that a correlation of power function exists between the precipitation amount caught by the horizontal gauge and the absolute difference of observations implemented by the operational gauge and pit gauge. The correlation coefficient is 0.99. For operational observations, precipitation correction can be carried out only by parallel observation with a horizontal precipitation gauge. The precipitation accuracy after correction approaches that of the pit gauge. The correction method developed is simple and feasible.

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.

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

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.

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

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.

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

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

Study of cloud properties using airborne and satellite measurements

Science.gov (United States)

Boscornea, Andreea; Stefan, Sabina; Vajaiac, Sorin Nicolae

2014-08-01

The present study investigates cloud microphysics properties using aircraft and satellite measurements. Cloud properties were drawn from data acquired both from in situ measurements with state of the art airborne instrumentation and from satellite products of the MODIS06 System. The used aircraft was ATMOSLAB - Airborne Laboratory for Environmental Atmospheric Research, property of the National Institute for Aerospace Research "Elie Carafoli" (INCAS), Bucharest, Romania, which is specially equipped for this kind of research. The main tool of the airborne laboratory is a Cloud, Aerosol and Precipitation Spectrometer - CAPS (30 bins, 0.51- 50 μm). The data was recorded during two flights during the winter 2013-2014, over a flat region in the south-eastern part of Romania (between Bucharest and Constanta). The analysis of cloud particle size variations and cloud liquid water content provided by CAPS can explain cloud processes, and can also indicate the extent of aerosols effects on clouds. The results, such as cloud coverage and/or cloud types, microphysical parameters of aerosols on the one side and the cloud microphysics parameters obtained from aircraft flights on the other side, was used to illustrate the importance of microphysics cloud properties for including the radiative effects of clouds in the regional climate models.

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

Ground-truth measurement systems

Science.gov (United States)

Serafin, R.; Seliga, T. A.; Lhermitte, R. M.; Nystuen, J. A.; Cherry, S.; Bringi, V. N.; Blackmer, R.; Heymsfield, G. M.

1981-01-01

Ground-truth measurements of precipitation and related weather events are an essential component of any satellite system designed for monitoring rainfall from space. Such measurements are required for testing, evaluation, and operations; they provide detailed information on the actual weather events, which can then be compared with satellite observations intended to provide both quantitative and qualitative information about them. Also, very comprehensive ground-truth observations should lead to a better understanding of precipitation fields and their relationships to satellite data. This process serves two very important functions: (a) aiding in the development and interpretation of schemes of analyzing satellite data, and (b) providing a continuing method for verifying satellite measurements.

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

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

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.

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.

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.

Precipitation and measurements of precipitation

NARCIS (Netherlands)

Schmidt, F.H.; Bruin, H.A.R. de; Attmannspacher, W.; Harrold, T.W.; Kraijenhoff van de Leur, D.A.

1977-01-01

In Western Europe, precipitation is normal phenomenon; it is of importance to all aspects of society, particularly to agriculture, in cattle breeding and, of course, it is a subject of hydrological research. Precipitation is an essential part in the hydrological cycle. How disastrous local

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.

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

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

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

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.

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.

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.)

Measurement of γ'precipitates in nimonic PE16

International Nuclear Information System (INIS)

Baker, C.; Lobb, R.C.

1977-09-01

γ' precipitates in Nimonic PE16 have been examined using bright and dark field imaging techniques in an electron microscope. The validity of these techniques to determine mean precipitate diameters, precipitate density and volume fraction is discussed. It is concluded that bright field imaging techniques are sufficiently accurate to measure γ' precipitate diameters but it is essential to use dark field imaging techniques to determine γ' precipitate density or volume fraction. (author)

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

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

Measurements of VLF-particle interactions at the South Atlantic Magnetic Anomaly on board a Brazilian geophysical satellite

International Nuclear Information System (INIS)

Gonzalez, W.D.; Pinto Junior, O.; Dutra, S.L.G.; Takahashi, H.

1988-01-01

A summary of the proposal for measurements of VLF wave-particle interactions, expected to occur at the South Atlantic magnetic anomaly, to be carried out on board a Brazilian geophysical satellite, will be presented. The expected domain of such interactions refers to electromagnetic VLF waves and to energetic-relativistic inner belt electrons, pitch angle diffusing into the atmosphere via cyclotron resonances. The detectors involve a tri-axial search coil magnetometer and a surface barrier silicon telescope. A modified and preliminary version of this proposed experiment will be carried out on board long duration balloon flights, well before the beginning of the intended satellite measurements. For the ballon flights the particle detector will be replaced by an x-ray detector, which can also monitor parameters related to the electron precipitation. (author) [pt

Detailed characteristics of radiation belt electrons revealed by CSSWE/REPTile measurements: Geomagnetic activity response and precipitation observation

Science.gov (United States)

Zhang, K.; Li, X.; Schiller, Q.; Gerhardt, D.; Zhao, H.; Millan, R.

2017-08-01

Earth's outer radiation belt electrons are highly dynamic. We study the detailed characteristics of relativistic electrons in the outer belt using measurements from the Colorado Student Space Weather Experiment (CSSWE) mission, a low Earth orbit (LEO) CubeSat, which traverses the radiation belt four times in one orbit ( 1.5 h) and has the advantage of measuring the dynamic activities of the electrons including their rapid precipitation. We focus on the measured electron response to geomagnetic activity for different energies to show that there are abundant sub-MeV electrons in the inner belt and slot region. These electrons are further enhanced during active times, while there is a lack of >1.63 MeV electrons in these regions. We also show that the variation of measured electron flux at LEO is strongly dependent on the local magnetic field strength, which is far from a dipole approximation. Moreover, a specific precipitation band, which happened on 19 January 2013, is investigated based on the conjunctive measurement of CSSWE, the Balloon Array for Radiation belt Relativistic Electron Losses, and one of the Polar Operational Environmental Satellites. In this precipitation band event, the net loss of the 0.58-1.63 MeV electrons (L = 3.5-6) is estimated to account for 6.8% of the total electron content.

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

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

Monitoring mass changes in the Volta River basin using GRACE satellite gravity and TRMM precipitation

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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.

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

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.

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

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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

Inter-Comparison and Evaluation of Remote Sensing Precipitation Products over China from 2005 to 2013

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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.

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

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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.

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

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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

Tropical Rainfall Measuring Mission (TRMM) Precipitation Data and Services for Research and Applications

Science.gov (United States)

Liu, Zhong; Ostrenga, Dana; Teng, William; Kempler, Steven

2012-01-01

Precipitation is a critical component of the Earth's hydrological cycle. Launched on 27 November 1997, TRMM is a joint U.S.-Japan satellite mission to provide the first detailed and comprehensive data set of the four-dimensional distribution of rainfall and latent heating over vastly under-sampled tropical and subtropical oceans and continents (40 S - 40 N). Over the past 14 years, TRMM has been a major data source for meteorological, hydrological and other research and application activities around the world. The purpose of this short article is to inform that the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides TRMM archive and near-real-time precipitation data sets and services for research and applications. TRMM data consist of orbital data from TRMM instruments at the sensor s resolution, gridded data at a range of spatial and temporal resolutions, subsets, ground-based instrument data, and ancillary data. Data analysis, display, and delivery are facilitated by the following services: (1) Mirador (data search and access); (2) TOVAS (TRMM Online Visualization and Analysis System); (3) OPeNDAP (Open-source Project for a Network Data Access Protocol); (4) GrADS Data Server (GDS); and (5) Open Geospatial Consortium (OGC) Web Map Service (WMS) for the GIS community. Precipitation data application services are available to support a wide variety of applications around the world. Future plans include enhanced and new services to address data related issues from the user community. Meanwhile, the GES DISC is preparing for the Global Precipitation Measurement (GPM) mission which is scheduled for launch in 2014.

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

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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

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

Using NDVI to measure precipitation in semi-arid landscapes

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Birtwhistle, Amy N.; Laituri, Melinda; Bledsoe, Brian; Friedman, Jonathan M.

2016-01-01

Measuring precipitation in semi-arid landscapes is important for understanding the processes related to rainfall and run-off; however, measuring precipitation accurately can often be challenging especially within remote regions where precipitation instruments are scarce. Typically, rain-gauges are sparsely distributed and research comparing rain-gauge and RADAR precipitation estimates reveal that RADAR data are often misleading, especially for monsoon season convective storms. This study investigates an alternative way to map the spatial and temporal variation of precipitation inputs along ephemeral stream channels using Normalized Difference Vegetation Index (NDVI) derived from Landsat Thematic Mapper imagery. NDVI values from 26 years of pre- and post-monsoon season Landsat imagery were derived across Yuma Proving Ground (YPG), a region covering 3,367 km2 of semiarid landscapes in southwestern Arizona, USA. The change in NDVI from a pre-to post-monsoon season image along ephemeral stream channels explained 73% of the variance in annual monsoonal precipitation totals from a nearby rain-gauge. In addition, large seasonal changes in NDVI along channels were useful in determining when and where flow events have occurred.

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

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

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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

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

Initial results of centralized autonomous orbit determination of the new-generation BDS satellites with inter-satellite link measurements

Science.gov (United States)

Tang, Chengpan; Hu, Xiaogong; Zhou, Shanshi; Liu, Li; Pan, Junyang; Chen, Liucheng; Guo, Rui; Zhu, Lingfeng; Hu, Guangming; Li, Xiaojie; He, Feng; Chang, Zhiqiao

2018-01-01

Autonomous orbit determination is the ability of navigation satellites to estimate the orbit parameters on-board using inter-satellite link (ISL) measurements. This study mainly focuses on data processing of the ISL measurements as a new measurement type and its application on the centralized autonomous orbit determination of the new-generation Beidou navigation satellite system satellites for the first time. The ISL measurements are dual one-way measurements that follow a time division multiple access (TDMA) structure. The ranging error of the ISL measurements is less than 0.25 ns. This paper proposes a derivation approach to the satellite clock offsets and the geometric distances from TDMA dual one-way measurements without a loss of accuracy. The derived clock offsets are used for time synchronization, and the derived geometry distances are used for autonomous orbit determination. The clock offsets from the ISL measurements are consistent with the L-band two-way satellite, and time-frequency transfer clock measurements and the detrended residuals vary within 0.5 ns. The centralized autonomous orbit determination is conducted in a batch mode on a ground-capable server for the feasibility study. Constant hardware delays are present in the geometric distances and become the largest source of error in the autonomous orbit determination. Therefore, the hardware delays are estimated simultaneously with the satellite orbits. To avoid uncertainties in the constellation orientation, a ground anchor station that "observes" the satellites with on-board ISL payloads is introduced into the orbit determination. The root-mean-square values of orbit determination residuals are within 10.0 cm, and the standard deviation of the estimated ISL hardware delays is within 0.2 ns. The accuracy of the autonomous orbits is evaluated by analysis of overlap comparison and the satellite laser ranging (SLR) residuals and is compared with the accuracy of the L-band orbits. The results indicate

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.

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

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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

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.

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

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.

How Consistent are Recent Variations in the Tropical Energy and Water Cycle Resolved by Satellite Measurements?

Science.gov (United States)

Robertson, F. R.; Lu, H.-I.

2004-01-01

One notable aspect of Earth's climate is that although the planet appears to be very close to radiative balance at top-of-atmosphere (TOA), the atmosphere itself and underlying surface are not. Profound exchanges of energy between the atmosphere and oceans, land and cryosphere occur over a range of time scales. Recent evidence from broadband satellite measurements suggests that even these TOA fluxes contain some detectable variations. Our ability to measure and reconstruct radiative fluxes at the surface and at the top of atmosphere is improving rapidly. One question is 'How consistent, physically, are these diverse remotely-sensed data sets'? The answer is of crucial importance to understanding climate processes, improving physical models, and improving remote sensing algorithms. In this work we will evaluate two recently released estimates of radiative fluxes, focusing primarily on surface estimates. The International Satellite Cloud Climatology Project 'FD' radiative flux profiles are available from mid-1983 to near present and have been constructed by driving the radiative transfer physics from the Goddard Institute for Space Studies (GISS) global model with ISCCP clouds and TOVS (TIROS Operational Vertical Sounder)thermodynamic profiles. Full and clear sky SW and LW fluxes are produced. A similar product from the NASA/GEWEX Surface Radiation Budget Project using different radiative flux codes and thermodynamics from the NASA/Goddard Earth Observing System (GEOS-1) assimilation model makes a similar calculation of surface fluxes. However this data set currently extends only through 1995. We also employ precipitation measurements from the Global Precipitation Climatology Project (GPCP) and the Tropical Rainfall Measuring Mission (TRMM). Finally, ocean evaporation estimates from the Special Sensor Microwave Imager (SSM/I) are considered as well as derived evaporation from the NCAR/NCEP Reanalysis. Additional information is included in the original extended

Comparison between POES energetic electron precipitation observations and riometer absorptions: Implications for determining true precipitation fluxes

Science.gov (United States)

Rodger, Craig J.; Kavanagh, Andrew J.; Clilverd, Mark A.; Marple, Steve R.

2013-12-01

electron precipitation (EEP) impacts the chemistry of the middle atmosphere with growing evidence of coupling to surface temperatures at high latitudes. To better understand this link, it is essential to have realistic observations to properly characterize precipitation and which can be incorporated into chemistry-climate models. The Polar-orbiting Operational Environmental Satellite (POES) detectors measure precipitating particles but only integral fluxes and only in a fraction of the bounce loss cone. Ground-based riometers respond to precipitation from the whole bounce loss cone; they measure the cosmic radio noise absorption (CNA), a qualitative proxy with scant direct information on the energy flux of EEP. POES observations should have a direct relationship with ΔCNA and comparing the two will clarify their utility in studies of atmospheric change. We determined ionospheric changes produced by the EEP measured by the POES spacecraft in ~250 overpasses of an imaging riometer in northern Finland. The ΔCNA modeled from the POES data is 10-15 times less than the observed ΔCNA when the >30 keV flux is reported as ground-based measurements. The discrepancy occurs mostly during periods of low geomagnetic activity, and we contend that weak diffusion is dominating the pitch angle scattering into the bounce loss cone at these times. A correction to the calculation using measurements of the trapped flux considerably reduces the discrepancy and provides further support to our hypothesis that weak diffusion leads to underestimates of the EEP.

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.

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

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.

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.

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

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

Relationships between particle precipitation and auroral forms

International Nuclear Information System (INIS)

Burch, J.L.; Winningham, J.D.

1978-01-01

The present state of knowledge on the relationships between high-latitude particle precipitation and the aurora is reviewed. Attention is focused on the largescale relationships between auroral forms and magnetospheric particle populations, on the relationships between satellite and sounding-rocket measurements, and on the interaction of auroral electrons with the atmosphere. While significant progress is being made in relating the largescale features of the aurora to magnetospheric plasma domains, and in understanding the way in which auroral electrons deposit their energy in the atmosphere, only slight progress has been made in relating satellite data to the small-scale phenomena associated with auroral arcs. (author)

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.

Improving precipitation measurement

Science.gov (United States)

Strangeways, Ian

2004-09-01

Although rainfall has been measured for centuries scientifically and in isolated brief episodes over millennia for agriculture, it is still not measured adequately even today for climatology, water resources, and other precise applications. This paper outlines the history of raingauges, their errors, and describes the field testing over 3 years of a first guess design for an aerodynamic rain collector proposed by Folland in 1988. Although shown to have aerodynamic advantage over a standard 5 gauge, the new rain collector was found to suffer from outsplash in heavy rain. To study this problem, and to derive general basic design rules for aerodynamic gauges, its performance was investigated in turbulent, real-world conditions rather than in the controlled and simplified environment of a wind tunnel or mathematical model as in the past. To do this, video records were made using thread tracers to indicate the path of the wind, giving new insight into the complex flow of natural wind around and within raingauges. A new design resulted, and 2 years of field testing have shown that the new gauge has good aerodynamic and evaporative characteristics and minimal outsplash, offering the potential for improved precipitation measurement.

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.

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

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

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.

Satellite Remote Sensing: Aerosol Measurements

Science.gov (United States)

Kahn, Ralph A.

2013-01-01

Aerosols are solid or liquid particles suspended in the air, and those observed by satellite remote sensing are typically between about 0.05 and 10 microns in size. (Note that in traditional aerosol science, the term "aerosol" refers to both the particles and the medium in which they reside, whereas for remote sensing, the term commonly refers to the particles only. In this article, we adopt the remote-sensing definition.) They originate from a great diversity of sources, such as wildfires, volcanoes, soils and desert sands, breaking waves, natural biological activity, agricultural burning, cement production, and fossil fuel combustion. They typically remain in the atmosphere from several days to a week or more, and some travel great distances before returning to Earth's surface via gravitational settling or washout by precipitation. Many aerosol sources exhibit strong seasonal variability, and most experience inter-annual fluctuations. As such, the frequent, global coverage that space-based aerosol remote-sensing instruments can provide is making increasingly important contributions to regional and larger-scale aerosol studies.

Rain detection over land surfaces using passive microwave satellite data

NARCIS (Netherlands)

Bauer, P.; Burose, D.; Schulz, J.

2002-01-01

An algorithm is presented for the detection of surface rainfall using passive microwave measurements by satellite radiometers. The technique consists of a two-stage approach to distinguish precipitation signatures from other effects: (1) Contributions from slowly varying parameters (surface type and

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

Global Precipitation Measurement Mission: Architecture and Mission Concept

Science.gov (United States)

Bundas, David

2005-01-01

The Global Precipitation Measurement (GPM) Mission is a collaboration between the National Aeronautics and Space Administration (NASA) and the Japanese Aerospace Exploration Agency (JAXA), and other partners, with the goal of monitoring the diurnal and seasonal variations in precipitation over the surface of the earth. These measurements will be used to improve current climate models and weather forecasting, and enable improved storm and flood warnings. This paper gives an overview of the mission architecture and addresses some of the key trades that have been completed, including the selection of the Core Observatory s orbit, orbit maintenance trades, and design issues related to meeting orbital debris requirements.

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

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.

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.

Land-mobile satellite excess path loss measurements

Science.gov (United States)

Hess, G. C.

1980-05-01

An experiment conducted with the ATS-6 satellite to determine the additional path loss over free-space loss experienced by land-mobile communication links is described. This excess path loss is measured as a function of 1) local environment, 2) vehicle heading, 3) link frequency, 4) satellite elevation angle, and 5) street side. A statistical description of excess loss developed from the data shows that the first two parameters dominate. Excess path loss on the order of 25 dB is typical in urban situations, but decreases to under 10 dB in suburban/rural areas. Spaced antenna selection diversity is found to provide only a slight decrease (4 dB, typically) in the urban excess path loss observed. Level crossing rates are depressed in satellite links relative to those of Rayleigh-faded terrestrial links, but increases in average fade durations tend to offset that advantage. The measurements show that the excess path loss difference between 860-MHz links and 1550-MHz links is generally negligible.

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

As reported at the EGU General Assembly of 2014, a prototype system was developed for the second generation CMORPH to produce global analyses of 30-min precipitation on a 0.05olat/lon grid over the entire globe from pole to pole through integration of information from satellite observations as well as numerical model simulations. The second generation CMORPH is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available low earth orbit (LEO) satellites, precipitation estimates derived from infrared (IR) observations of geostationary (GEO) as well as LEO platforms, and precipitation simulations from numerical global models. Key to the success of the 2nd generation CMORPH, among a couple of other elements, are the development of a LEO-IR based precipitation estimation to fill in the polar gaps and objectively analyzed cloud motion vectors to capture the cloud movements of various spatial scales over the entire globe. In this presentation, we report our recent work on the refinement for these two important algorithm components. The prototype algorithm for the LEO IR precipitation estimation is refined to achieve improved quantitative accuracy and consistency with PMW retrievals. AVHRR IR TBB data from all LEO satellites are first remapped to a 0.05olat/lon grid over the entire globe and in a 30-min interval. Temporally and spatially co-located data pairs of the LEO TBB and inter-calibrated combined satellite PMW retrievals (MWCOMB) are then collected to construct tables. Precipitation at a grid box is derived from the TBB through matching the PDF tables for the TBB and the MWCOMB. This procedure is implemented for different season, latitude band and underlying surface types to account for the variations in the cloud - precipitation relationship. At the meantime, a sub-system is developed to construct analyzed fields of

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

The possible direct use of satellite radiance measurements by the Atmospheric Radiation Measurement Program

International Nuclear Information System (INIS)

1993-03-01

The Atmospheric Radiation Measurement (ARM) Program is a major research program initiated by the Department of Energy to improve our understanding of radiative and cloud processes critical to predicting the Earth's climate and its changes. Central to this concept is the use of four to six intensively instrumented sites for long-term study and characterization of the processes of interest. The instrumentation suites will include ground-based, high-accuracy radiometers for measuring the short and longwave surface flux, as well as an extensive set of ground-and air-based instrumentation for characterizing the intervening atmospheric column. Satellite-based measurements are expected to play a very important role in providing top-of-the-atmosphere measurements. In this study, we examine the possibility of comparing ARM outputs directly with satellite measurements, thereby ensuring the independence of these two important data sets. Thus we focused on what do satellites really measure and how well do they measure it. On what can we do about the general lack of adequate visible channel calibration. On what is the best way for ARM to obtain near-real-time access to this unprocessed data. And on what is the optimum way for ARM to make use of satellite data

TRMM Precipitation Radar (PR) Level 2 Surface Cross-Section Product (TRMM Product 2A21) V7

Data.gov (United States)

National Aeronautics and Space Administration — The Tropical Rainfall Measuring Mission (TRMM) is a joint U.S.-Japan satellite mission to monitor tropical and subtropical precipitation and to estimate its...

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

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

Constraining relationships between rainfall and landsliding with satellite derived rainfall measurements and landslide inventories.

Science.gov (United States)

Marc, Odin; Malet, Jean-Philippe; Stumpf, Andre; Gosset, Marielle

2017-04-01

In mountainous and hilly regions, landslides are an important source of damage and fatalities. Landsliding correlates with extreme rainfall events and may increase with climate change. Still, how precipitation drives landsliding at regional scales is poorly understood quantitatively in part because constraining simultaneously landsliding and rainfall across large areas is challenging. By combining optical images acquired from satellite observation platforms and rainfall measurements from satellite constellations we are building a database of landslide events caused by with single storm events. We present results from storm-induced landslides from Brazil, Taiwan, Micronesia, Central America, Europe and the USA. We present scaling laws between rainfall metrics derived by satellites (total rainfall, mean intensity, antecedent rainfall, ...) and statistical descriptors of landslide events (total area and volume, size distribution, mean runout, ...). Total rainfall seems to be the most important parameter driving non-linearly the increase in total landslide number, and area and volume. The maximum size of bedrock landslides correlates with the total number of landslides, and thus with total rainfall, within the limits of available topographic relief. In contrast, the power-law scaling exponent of the size distribution, controlling the relative abundance of small and large landslides, appears rather independent of the rainfall metrics (intensity, duration and total rainfall). These scaling laws seem to explain both the intra-storm pattern of landsliding, at the scale of satellite rainfall measurements ( 25kmx25km), and the different impacts observed for various storms. Where possible, we evaluate the limits of standard rainfall products (TRMM, GPM, GSMaP) by comparing them to in-situ data. Then we discuss how slope distribution and other geomorphic factors (lithology, soil presence,...) modulate these scaling laws. Such scaling laws at the basin scale and based only on a

Satellite measurements of the earth's crustal magnetic field

Science.gov (United States)

Schnetzler, C. C.

1989-01-01

The literature associated with the Magsat mission has evaluated the capabilities and limitations of satellite measurements of the earth's crustal magnetic field, and demonstrated that there exists a 300-3000 km magnetic field, related to major features in the earth's crust, which is primarily caused by induction. Due to its scale and sensitivity, satellite data have been useful in the development of models for such large crustal features as subduction zones, submarine platforms, continental accretion boundaries, and rifts. Attention is presently given to the lack of agreement between laboratory and satellite estimates of lower crustal magnetization.

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.

Accuracy of CHIRPS Satellite-Rainfall Products over Mainland China

Directory of Open Access Journals (Sweden)

Lei Bai

2018-02-01

Full Text Available Precipitation is the main component of global water cycle. At present, satellite quantitative precipitation estimates (QPEs are widely applied in the scientific community. However, the evaluations of satellite QPEs have some limitations in terms of the deficiency in observation, evaluation methodology, the selection of time windows for evaluation and short periods for evaluation. The objective of this work is to make some improvements by evaluating the spatio-temporal pattern of the long-terms Climate Hazard Group InfraRed Precipitation Satellite’s (CHIRPS’s QPEs over mainland China. In this study, we compared the daily precipitation estimates from CHIRPS with 2480 rain gauges across China and gridded observation using several statistical metrics in the long-term period of 1981–2014. The results show that there is significant difference between point evaluation and grid evaluation for CHIRPS. CHIRPS has better performance for a large amount of precipitation than it does for arid and semi-arid land. The change in good performance zones has strong relationship with monsoon’s movement. Therefore, CHIRPS performs better in river basins of southern China and exhibits poor performance in river basins in northwestern and northern China. Moreover, CHIRPS exhibits better in warm season than in Winter, owing to its limited ability to detect snowfall. Nevertheless, CHIRPS is moderately sensitive to the precipitation from typhoon weather systems. The limitations for CHIRPS result from the Tropical Rainfall Measuring Mission (TRMM 3B42 estimates’ accuracy and valid spatial coverage.

Introducing Multisensor Satellite Radiance-Based Evaluation for Regional Earth System Modeling

Science.gov (United States)

Matsui, T.; Santanello, J.; Shi, J. J.; Tao, W.-K.; Wu, D.; Peters-Lidard, C.; Kemp, E.; Chin, M.; Starr, D.; Sekiguchi, M.;

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

Spaceborne microwave cross-track scanning radiometers, originally developed for temperature and humidity sounding, have shown great capabilities to provide a significant contribution in precipitation monitoring both in terms of measurement quality and spatial/temporal coverage. The Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for cross-track scanning radiometers, originally developed for the Advanced Microwave Sounding Unit/Microwave Humidity Sounder (AMSU-A/MHS) radiometers (on board the European MetOp and U.S. NOAA satellites), was recently newly designed to exploit the Advanced Technology Microwave Sounder (ATMS) on board the Suomi-NPP satellite and the future JPSS satellites. The PNPR algorithm is based on the Artificial Neural Network (ANN) approach. The main PNPR-ATMS algorithm changes with respect to PNPR-AMSU/MHS are the design and implementation of a new ANN able to manage the information derived from the additional ATMS channels (respect to the AMSU-A/MHS radiometer) and a new screening procedure for not-precipitating pixels. In order to achieve maximum consistency of the retrieved surface precipitation, both PNPR algorithms are based on the same physical foundation. The PNPR is optimized for the European and the African area. The neural network was trained using a cloud-radiation database built upon 94 cloud-resolving simulations over Europe and the Mediterranean and over the African area and radiative transfer model simulations of TB vectors consistent with the AMSU-A/MHS and ATMS channel frequencies, viewing angles, and view-angle dependent IFOV sizes along the scan projections. As opposed to other ANN precipitation retrieval algorithms, PNPR uses a unique ANN that retrieves the surface precipitation rate for all types of surface backgrounds represented in the training database, i.e., land (vegetated or arid), ocean, snow/ice or coast. This approach prevents different precipitation estimates from being inconsistent with one

CalWater 2 - Precipitation, Aerosols, and Pacific Atmospheric Rivers Experiment

Science.gov (United States)

Spackman, Ryan; Ralph, Marty; Prather, Kim; Cayan, Dan; DeMott, Paul; Dettinger, Mike; Fairall, Chris; Leung, Ruby; Rosenfeld, Daniel; Rutledge, Steven; Waliser, Duane; White, Allen

2014-05-01

Emerging research has identified two phenomena that play key roles in the variability of the water supply and the incidence of extreme precipitation events along the West Coast of the United States. These phenomena include the role of (1) atmospheric rivers (ARs) in delivering much of the precipitation associated with major storms along the U.S. West Coast, and (2) aerosols—from local sources as well as those transported from remote continents—and their modulating effects on western U.S. precipitation. A better understanding of these processes is needed to reduce uncertainties in weather predictions and climate projections of extreme precipitation and its effects, including the provision of beneficial water supply. This presentation summarizes science gaps associated with (1) the evolution and structure of ARs including cloud and precipitation processes and air-sea interaction, and (2) aerosol interaction with ARs and the impact on precipitation, including locally-generated aerosol effects on orographic precipitation along the U.S. West Coast. Observations are proposed for multiple winter seasons as part of a 5-year broad interagency vision referred to as CalWater 2 to address these science gaps (http://esrl.noaa.gov/psd/calwater). In the near term, a science investigation is being planned including a targeted set of aircraft and ship-based measurements and associated evaluation of data in near-shore regions of California and in the eastern Pacific for an intensive observing period between January 2015 and March 2015. DOE's Atmospheric Radiation Measurement (ARM) program and NOAA are coordinating on deployment of airborne and ship-borne facilities for this period in a DOE-sponsored study called ACAPEX (ARM Cloud Aerosol and Precipitation Experiment) to complement CalWater 2. The motivation for this major study is based on findings that have emerged in the last few years from airborne and ground-based studies including CalWater and NOAA's HydroMeterology Testbed

Vegetation responses to sagebrush-reduction treatments measured by satellites

Science.gov (United States)

Johnston, Aaron; Beever, Erik; Merkle, Jerod A.; Chong, Geneva W.

2018-01-01

Time series of vegetative indices derived from satellite imagery constitute tools to measure ecological effects of natural and management-induced disturbances to ecosystems. Over the past century, sagebrush-reduction treatments have been applied widely throughout western North America to increase herbaceous vegetation for livestock and wildlife. We used indices from satellite imagery to 1) quantify effects of prescribed-fire, herbicide, and mechanical treatments on vegetative cover, productivity, and phenology, and 2) describe how vegetation changed over time following these treatments. We hypothesized that treatments would increase herbaceous cover and accordingly shift phenologies towards those typical of grass-dominated systems. We expected prescribed burns would lead to the greatest and most-prolonged effects on vegetative cover and phenology, followed by herbicide and mechanical treatments. Treatments appeared to increase herbaceous cover and productivity, which coincided with signs of earlier senescence − signals expected of grass-dominated systems, relative to sagebrush-dominated systems. Spatial heterogeneity for most phenometrics was lower in treated areas relative to controls, which suggested treatment-induced homogenization of vegetative communities. Phenometrics that explain spring migrations of ungulates mostly were unaffected by sagebrush treatments. Fire had the strongest effect on vegetative cover, and yielded the least evidence for sagebrush recovery. Overall, treatment effects were small relative to those reported from field-based studies for reasons most likely related to sagebrush recovery, treatment specification, and untreated patches within mosaicked treatment applications. Treatment effects were also small relative to inter-annual variation in phenology and productivity that was explained by temperature, snowpack, and growing-season precipitation. Our results indicated that cumulative NDVI, late-season phenometrics, and spatial

GPM GROUND VALIDATION ENVIRONMENT CANADA (EC) MANUAL PRECIPITATION MEASUREMENTS GCPEX V1

Data.gov (United States)

National Aeronautics and Space Administration — The GPM Ground Validation Environment Canada (EC) Manual Precipitation Measurements GCPEx dataset was collected during the GPM Cold-season Precipitation Experiment...

In-place measurement of specific electric resistance during precipitation of γ'-precipitating Ni base alloys

International Nuclear Information System (INIS)

Silomon, M.

1991-01-01

During precipitation and coarsening of a second phase, the electric resistance of an alloy changes. Continuous resistance measurement is possible during heat treatment and can be conducted with limited experimental effort; any metallographic determination of the temperature and time dependencies of structural changes, however, requires very high effort. For this reason, an instrument was set up which permits continuous measurement of the resistance at precipitation temperature and during heating or cooling, while providing sufficient resolution for minor changes. Both measuring methods are conducted on technologically relevant alloys such as Nimonic PE 16 and those based on Ni-20 At.% Cr with deliberately varied additions of Al and Ti (accompanying investigations: TEM, SANS, and calorimetry). Their usefulness for alloy development is discussed within the scope of current concepts of demixing kinetics and resistance of alloys. Essential results concern the matrix/γ'-phase mismatch, the Ni 2 Cr short range order, and determination of the γ'-solvus temperature. (orig.) With 53 figs., 4 tabs [de

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.

A New Satellite System for Measuring BRDF from Space

Science.gov (United States)

Wiscombe, W.; Kaufman, Y.; Herman, J.

1999-01-01

Formation flying of satellites is at the beginning of an explosive growth curve. Spacecraft buses are shrinking to the point where we will soon be able to launch 10 micro-satellites or 100 nano-satellites on a single launch vehicle. Simultaneously, spectrometers are just beginning to be flown in space by both the U.S. and Europe. On-board programmable band aggregation will soon allow exactly the spectral bands desired to be returned to Earth. Further efforts are being devoted to radically shrink spectrometers both in size and weight. And GPS positioning and attitude determination, plus new technologies for attitude control, will allow fleets of satellites to all point at the same Earth target. All these advances, in combination, make possible for the first time the proper measurement of Bidirectional Reflectance Distribution (BRDF) form space. Previously space BDRF's were mere composites, built up over time by viewing different types of scenes at different times, then creating catalogs of BDRF functions whose use relied upon correct "scene identification" --the weak link. Formation-flying micro-satellites, carrying programmable spectrometers and precision-pointing at the same Earth target, can measure the full BDRF simultaneously, in real time. This talk will review these technological advances and discuss an actual proposed concept, based on these advances, to measure Earth-target BDRF's (clouds as well as surface) across the full solar spectrum in the 2010 timeframe. This concept is part of a larger concept called Leonardo for properly measuring the radiative forcing of Earth for climate purposes; lack of knowing of BDRF and of diurnal cycle are at present the two limiting factors preventing improved estimates of this forcing.

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

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)

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.

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

Using GRACE to constrain precipitation amount over cold mountainous basins

Science.gov (United States)

Behrangi, Ali; Gardner, Alex S.; Reager, John T.; Fisher, Joshua B.

2017-01-01

Despite the importance for hydrology and climate-change studies, current quantitative knowledge on the amount and distribution of precipitation in mountainous and high-elevation regions is limited due to instrumental and retrieval shortcomings. Here by focusing on two large endorheic basins in High Mountain Asia, we show that satellite gravimetry (Gravity Recovery and Climate Experiment (GRACE)) can be used to provide an independent estimate of monthly accumulated precipitation using mass balance equation. 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 errors. It was found that most of the products capture about or less than 50% of the total precipitation estimated using GRACE in winter. Overall, Global Precipitation Climatology Project (GPCP) showed better agreement with GRACE estimate than other products. Yet on average GRACE showed 30% more annual precipitation than GPCP in the study basins. In basins of appropriate size with an absence of dense ground measurements, as is a typical case in cold mountainous regions, we find GRACE can be a viable alternative to constrain monthly and seasonal precipitation estimates from other remotely sensed precipitation products that show large bias.

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

OpenAIRE

Ayehu, Getachew Tesfaye; Tadesse, Tsegaye; Gessesse, Berhan; Dinku, Tufa

2018-01-01

Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor) ground observations) or through...

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.

Satellite measurements of aerosol mass and transport

Energy Technology Data Exchange (ETDEWEB)

Fraser, R.S.; Kaufman, Y.J.; Mahoney, R.L.

1984-01-01

The aerosol optical thickness over land is derived from satellite measurements of the radiance of scattered sunlight. These data are used to estimate the columnar mass density of particulate sulfur on a day with a large amount of sulfur. The horizontal transport of the particulate sulfur is calculated using wing vectors measured with rawins. 33 references, 7 figures, 1 table.

Geometric model of pseudo-distance measurement in satellite location systems

Science.gov (United States)

Panchuk, K. L.; Lyashkov, A. A.; Lyubchinov, E. V.

2018-04-01

The existing mathematical model of pseudo-distance measurement in satellite location systems does not provide a precise solution of the problem, but rather an approximate one. The existence of such inaccuracy, as well as bias in measurement of distance from satellite to receiver, results in inaccuracy level of several meters. Thereupon, relevance of refinement of the current mathematical model becomes obvious. The solution of the system of quadratic equations used in the current mathematical model is based on linearization. The objective of the paper is refinement of current mathematical model and derivation of analytical solution of the system of equations on its basis. In order to attain the objective, geometric analysis is performed; geometric interpretation of the equations is given. As a result, an equivalent system of equations, which allows analytical solution, is derived. An example of analytical solution implementation is presented. Application of analytical solution algorithm to the problem of pseudo-distance measurement in satellite location systems allows to improve the accuracy such measurements.

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

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.

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.

Measurement-based perturbation theory and differential equation parameter estimation with applications to satellite gravimetry

Science.gov (United States)

Xu, Peiliang

2018-06-01

The numerical integration method has been routinely used by major institutions worldwide, for example, NASA Goddard Space Flight Center and German Research Center for Geosciences (GFZ), to produce global gravitational models from satellite tracking measurements of CHAMP and/or GRACE types. Such Earth's gravitational products have found widest possible multidisciplinary applications in Earth Sciences. The method is essentially implemented by solving the differential equations of the partial derivatives of the orbit of a satellite with respect to the unknown harmonic coefficients under the conditions of zero initial values. From the mathematical and statistical point of view, satellite gravimetry from satellite tracking is essentially the problem of estimating unknown parameters in the Newton's nonlinear differential equations from satellite tracking measurements. We prove that zero initial values for the partial derivatives are incorrect mathematically and not permitted physically. The numerical integration method, as currently implemented and used in mathematics and statistics, chemistry and physics, and satellite gravimetry, is groundless, mathematically and physically. Given the Newton's nonlinear governing differential equations of satellite motion with unknown equation parameters and unknown initial conditions, we develop three methods to derive new local solutions around a nominal reference orbit, which are linked to measurements to estimate the unknown corrections to approximate values of the unknown parameters and the unknown initial conditions. Bearing in mind that satellite orbits can now be tracked almost continuously at unprecedented accuracy, we propose the measurement-based perturbation theory and derive global uniformly convergent solutions to the Newton's nonlinear governing differential equations of satellite motion for the next generation of global gravitational models. Since the solutions are global uniformly convergent, theoretically speaking

Measurement of Precipitation in the Alps Using Dual-Polarization C-Band Ground-Based Radars, the GPM Spaceborne Ku-Band Radar, and Rain Gauges

Directory of Open Access Journals (Sweden)

Marco Gabella

2017-11-01

Full Text Available The complex problem of quantitative precipitation estimation in the Alpine region is tackled from four different points of view: (1 the modern MeteoSwiss network of automatic telemetered rain gauges (GAUGE; (2 the recently upgraded MeteoSwiss dual-polarization Doppler, ground-based weather radar network (RADAR; (3 a real-time merging of GAUGE and RADAR, implemented at MeteoSwiss, in which a technique based on co-kriging with external drift (CombiPrecip is used; (4 spaceborne observations, acquired by the dual-wavelength precipitation radar on board the Global Precipitation Measuring (GPM core satellite. There are obviously large differences in these sampling modes, which we have tried to minimize by integrating synchronous observations taken during the first 2 years of the GPM mission. The data comprises 327 “wet” overpasses of Switzerland, taken after the launch of GPM in February 2014. By comparing the GPM radar estimates with the MeteoSwiss products, a similar performance was found in terms of bias. On average (whole country, all days and seasons, both solid and liquid phases, underestimation is as large as −3.0 (−3.4 dB with respect to RADAR (GAUGE. GPM is not suitable for assessing what product is the best in terms of average precipitation over the Alps. GPM can nevertheless be used to evaluate the dispersion of the error around the mean, which is a measure of the geographical distribution of the error inside the country. Using 221 rain-gauge sites, the result is clear both in terms of correlation and in terms of scatter (a robust, weighted measure of the dispersion of the multiplicative error around the mean. The best agreement was observed between GPM and CombiPrecip, and, next, between GPM and RADAR, whereas a larger disagreement was found between GPM and GAUGE. Hence, GPM confirms that, for precipitation mapping in the Alpine region, the best results are obtained by combining ground-based radar with rain-gauge measurements using

Global Precipitation Measurement (GPM) Mission Core Spacecraft Systems Engineering Challenges

Science.gov (United States)

Bundas, David J.; ONeill, Deborah; Field, Thomas; Meadows, Gary; Patterson, Peter

2006-01-01

The Global Precipitation Measurement (GPM) Mission is a collaboration between the National Aeronautics and Space Administration (NASA) and the Japanese Aerospace Exploration Agency (JAXA), and other US and international partners, with the goal of monitoring the diurnal and seasonal variations in precipitation over the surface of the earth. These measurements will be used to improve current climate models and weather forecasting, and enable improved storm and flood warnings. This paper gives an overview of the mission architecture and addresses the status of some key trade studies, including the geolocation budgeting, design considerations for spacecraft charging, and design issues related to the mitigation of orbital debris.

Variations of Precipitation Structure and Microwave Tbs During the Evolution of a Hailstorm from TRMM Observations

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

In this paper, a hailstorm occurring on 9 May 1999 in Huanghuai region was studied by using the combined data from the precipitation radar (PR), microwave image (TMI), and visible infrared scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) satellite. According to the 3-orbit observations of 5-h duration from the TRMM satellite, the variation characteristics of the precipitation structures as well as cloud top temperature and microwave signals of the precipitating cloud were comprehensively analyzed during the evolution of hailstorm. The results show that the precipitation is obviously converted from early hail cloud with strong convection into the later storm cloud with weak convection. For hail cloud, there exists some strong convective cells, and the heavy solid precipitation is shown at the middle-top levels so that the contribution of rainfall amount above the freezing-layer to the column precipitation amount is rather larger than that within the melting-layer. However, for storm cloud, the convective cells are surrounded by the large area of stratiform precipitation, and the precipitation thickness gradually decreases, and the rainfall above the freezing-layer obviously reduces and the contribution of rainfall amount within the melting-layer rapidly increases. Therefore, the larger ratio of rainfall amount above the freezing layer to column precipitation amount is, the more convective the cloud is; reversely, the larger proportion of rainfall below the melting layer is, the more stable the stratiform cloud is. The different changing trends of microwave signals at different precipitation stages show that it is better to consider the structures and stages of precipitating cloud to choose the optimal microwave channels to retrieve surface rainfall.

Precipitation measurements for earth-space communications: Accuracy requirements and ground-truth techniques

Science.gov (United States)

Ippolito, L. J.; Kaul, R.

1981-01-01

Rainfall which is regarded as one of the more important observations for the measurements of this most variable parameter was made continuously, across large areas and over the sea. Ships could not provide the needed resolution nor could available radars provide the needed breadth of coverage. Microwave observations from the Nimbus-5 satellite offered some hope. Another possibility was suggested by the results of many comparisons between rainfall and the clouds seen in satellite pictures. Sequences of pictures from the first geostationary satellites were employed and a general correspondence between rain and the convective clouds visible in satellite pictures was found. It was demonstrated that the agreement was best for growing clouds. The development methods to infer GATE rainfall from geostationary satellite images are examined.

Spatial downscaling algorithm of TRMM precipitation based on multiple high-resolution satellite data for Inner Mongolia, China

Science.gov (United States)

Duan, Limin; Fan, Keke; Li, Wei; Liu, Tingxi

2017-12-01

Daily precipitation data from 42 stations in Inner Mongolia, China for the 10 years period from 1 January 2001 to 31 December 2010 was utilized along with downscaled data from the Tropical Rainfall Measuring Mission (TRMM) with a spatial resolution of 0.25° × 0.25° for the same period based on the statistical relationships between the normalized difference vegetation index (NDVI), meteorological variables, and digital elevation models (https://en.wikipedia.org/wiki/Digital_elevation_model) (DEM) using the leave-one-out (LOO) cross validation method and multivariate step regression. The results indicate that (1) TRMM data can indeed be used to estimate annual precipitation in Inner Mongolia and there is a linear relationship between annual TRMM and observed precipitation; (2) there is a significant relationship between TRMM-based precipitation and predicted precipitation, with a spatial resolution of 0.50° × 0.50°; (3) NDVI and temperature are important factors influencing the downscaling of TRMM precipitation data for DEM and the slope is not the most significant factor affecting the downscaled TRMM data; and (4) the downscaled TRMM data reflects spatial patterns in annual precipitation reasonably well, showing less precipitation falling in west Inner Mongolia and more in the south and southeast. The new approach proposed here provides a useful alternative for evaluating spatial patterns in precipitation and can thus be applied to generate a more accurate precipitation dataset to support both irrigation management and the conservation of this fragile grassland ecosystem.

Correlative studies of satellite ozone sensor measurements

International Nuclear Information System (INIS)

Lovill, J.E.; Ellis, J.S.

1983-01-01

Comparisons are made between total ozone measurements made by four satellite ozone sensors (TOMS, SBUV, TOVS and MFR). The comparisons were made during July 1979 when all sensors were operating simultaneously. The TOMS and SBUV sensors were observed to measure less total ozone than the MFR sensor, 10 and 15 Dobson units (DU) respectively. The MFR and TOMS sensors measured less ozone than the TOVS sensor, 19 an 28 DU, respectively. Latitudinal variability of the total ozone comparisons is discussed

Using High Energy Precipitation for Magnetic Mapping in the Nightside Transition Region During Dynamic Events

Science.gov (United States)

Spanswick, E.

2017-12-01

Identifying the magnetic footprint of a satellite can be done using the in situ observations together with some ionospheric or low-altitude satellite observation to argue that the two measurements were made on the same field line. Nishimura et al. [2011], e.g., correlated a time series of chorus wave power near the magnetic equator with the time series of intensities of every pixel of a is roughly magnetically conjugate ASI. Often, the pattern of correlation shows a well-defined peak at the location of the satellite's magnetic footprint. Their results cannot be replicated during dynamic events (e.g., substorms), because the required auroral forms do not occur at such times. It would be important if we could make mappings with such confidence during active times. The Transition Region Explorer (TREx), which is presently being implemented, is a new ground-based facility that will remote sense electron precipitation across 3 hours of MLT and 12 degrees of magnetic latitude spanning the auroral zone in western Canada. TREx includes the world's first imaging riometers array with a contiguous field of view large enough to seamlessly track the spatio-temporal evolution of high energy electron precipitation at mesoscales. Two studies motivated the TREx riometers array. First, Baker et al. [1981] demonstrated riometer absorption is an excellent proxy for the electron energy flux integrated from 30 keV to 200keV keV at the magnetic equator on the flux tube corresponding to the location of that riometers. Second, Spanswick et al. [2007] showed the correlation between the riometers absorption and the integrated electron energy flux near the magnetic equator peaked when the satellite was nearest to conjugate to the riometers. Here we present observations using CANOPUS single beam riometers and CRRES MEB to illustrate how the relative closeness of the footpoint of an equatorial spacecraft can be assessed using high energy precipitation. As well, we present the capabilities of

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

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.

The effect of energetic electron precipitation on the nitric oxide density in the lower thermosphere

International Nuclear Information System (INIS)

Saetre, Camilla

2006-12-01

The objective of this thesis has been the study of the chemical effects of the electron precipitation in the upper atmosphere, and mainly the increase of thermospheric nitric oxide (NO). NO plays an important role in the temperature balance for the mesosphere and thermosphere.In this project auroral electron precipitation data, derived from the Polar Ionospheric X-ray Imaging Experiment (PIXIE) and the Ultraviolet Imager (UVI) on board the Polar satellite, have been used together with NO density measurements from the Student Nitric Oxide Explorer (SNOE)

Analysis of precipitation teleconnections in CMIP models as a measure of model fidelity in simulating precipitation

Science.gov (United States)

Langenbrunner, B.; Neelin, J.; Meyerson, J.

2011-12-01

The accurate representation of precipitation is a recurring issue in global climate models, especially in the tropics. Poor skill in modeling the variability and climate teleconnections associated with El Niño/Southern Oscillation (ENSO) also persisted in the latest Climate Model Intercomparison Project (CMIP) campaigns. Observed ENSO precipitation teleconnections provide a standard by which we can judge a given model's ability to reproduce precipitation and dynamic feedback processes originating in the tropical Pacific. Using CMIP3 Atmospheric Model Intercomparison Project (AMIP) runs as a baseline, we compare precipitation teleconnections between models and observations, and we evaluate these results against available CMIP5 historical and AMIP runs. Using AMIP simulations restricts evaluation to the atmospheric response, as sea surface temperatures (SSTs) in AMIP are prescribed by observations. We use a rank correlation between ENSO SST indices and precipitation to define teleconnections, since this method is robust to outliers and appropriate for non-Gaussian data. Spatial correlations of the modeled and observed teleconnections are then evaluated. We look at these correlations in regions of strong precipitation teleconnections, including equatorial S. America, the "horseshoe" region in the western tropical Pacific, and southern N. America. For each region and season, we create a "normalized projection" of a given model's teleconnection pattern onto that of the observations, a metric that assesses the quality of regional pattern simulations while rewarding signals of correct sign over the region. Comparing this to an area-averaged (i.e., more generous) metric suggests models do better when restrictions on exact spatial dependence are loosened and conservation constraints apply. Model fidelity in regional measures remains far from perfect, suggesting intrinsic issues with the models' regional sensitivities in moist processes.

Interpretation of Spectrometric Measurements of Active Geostationary Satellites

Science.gov (United States)

Bedard, D.; Wade, G.

2014-09-01

Over 5000 visible near-infrared (VNIR) spectrometric measurements of active geostationary satellites have been collected with the National Research Council (NRC) 1.8m Plaskett telescope located at the Dominion Astrophysical Observatory (DAO) in Victoria, Canada. The objective of this ongoing experiment is to study how reflectance spectroscopy can be used to reliably identify specific material types on the surface of artificial Earth-orbiting objects. Active geostationary satellites were selected as the main subjects for this experiment since their orientation is stable and can be estimated to a high-level of confidence throughout a night of observation. Furthermore, for most geostationary satellites, there is a wide variety of sources that can provide some level of information as to their external surface composition. Notwithstanding the high number of measurements that have been collected to date, it was assumed that the experimenters would have a much greater success rate in material identification given the choice experimental subjects. To date, only the presence of aluminum has been confidently identified in some of the reflectance spectra that have been collected. Two additional material types, namely photovoltaic cells and polyimide film, the first layer of multi-layer insulation (MLI), have also been possibly identified. However uncertainties in the reduced spectral measurements prevent any definitive conclusion with respect to these materials at this time. The surprising lack of results with respect to material identification have forced the experimenters to use other data interpretation methods to characterize the spectral scattering characteristics of the studied satellites. The results from this study have already led to improvements in the ways that reflectance spectra from spacecraft are collected and analysed. Equally important, the data interpretation techniques elaborated over the course of this experiment will also serve to increase the body of

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.)

Precipitation and Hydrology Experiment Counter-Flow Spectrometer and Impactor Field Campaign Report

Energy Technology Data Exchange (ETDEWEB)

Poellot, Michael [University of North Dakota

2016-03-01

The U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility Aerial Facility (ARM AAF) counter-flow spectrometer and impactor (CSI) probe was flown on the University of North Dakota Cessna Citation research aircraft during the Integrated Precipitation and Hydrology Experiment (IPHEX). The field campaign took place during May and June of 2014 over North Carolina and its coastal waters as part of a National Aeronautics and Space Administration (NASA) Global Precipitation Measurement validation campaign. The CSI was added to the Citation instrument suite to support the involvement of Jay Mace through the NASA Advanced Composition Explorer (ACE) satellite program and flights of the NASA ER-2 aircraft, which is a civilian version of the Air Force’s U2-S reconnaissance platform. The ACE program funded extra ER-2 flights to focus on clouds that are weakly precipitating, which are also of interest to the Atmospheric System Research program sponsored by DOE.

Rainfall Imprint on Sea Surface Salinity in the ITCZ: new satellite perspectives

Science.gov (United States)

Boutin, J.; Viltard, N.; Supply, A.; Martin, N.; Vergely, J. L.; Hénocq, C.; Reverdin, G. P.

2016-02-01

The European Soil Moisture and Ocean Salinity (SMOS) satellite mission monitors sea surface salinity (SSS) over the global ocean for more than 5 years since 2010. The MADRAS microwave radiometer carried by the French (CNES) Indian (ISRO) satellite mission Megha-Tropiques sampled the 30° N-30° S region end of 2011 and in 2012, very complementary to other Global Precipitation Measurement(GPM) missions. In tropical regions, SMOS SSS contains a large imprint of atmospheric rainfall, but is also likely affected by oceanographic processes (advection and diffusion). At local and short time scales, Boutin et al. (2013, 2014) have shown that the spatio-temporal variability of SSS is dominated by rainfall as detected by satellite microwave radiometers and have demonstrated a close to linear relationship between SMOS SSS freshening under rain cells and satellite rain rate. The order of magnitude is in remarkable agreement with the theoretical renewal model of Schlussel et al. (1997) and compatible with AQUARIUS SSS observations, as well as with in situ drifters observations although the latter are local and taken at 45cm depth while satellite L-band SSS roughly correspond to the top 1cm depth and are spatially integrated over 43-150km. It is thus expected that the combined information of satellite rain rates and satellite SSS brings new constraints on the precipitation budget. We first look at the consistency between the spatial structures of SMOS SSS decrease and of rain rates derived either from the MADRAS microwave radiometer or from the CMORPH combined products that do not use MADRAS rain rates. This provides an indirect validation of the rain rates estimates. We then investigate the impact of rain history and of wind speed on the observed SMOS freshening. Based on these results, we discuss the precision on various precipitation estimates over 2012 in the ITCZ region and the major sources of uncertainties that the SPURS2 campaign could help to resolve.

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...

Beryllium-7 and 210Pb atmospheric deposition measured in moss and dependence on cumulative precipitation

International Nuclear Information System (INIS)

Krmar, M.; Mihailović, D.T.; Arsenić, I.; Radnović, D.; Pap, I.

2016-01-01

This paper focuses on analysis of the time series of 7 Be and 210 Pb activity measured in moss, and the amount, as well as duration of precipitation, to gain a better understanding of the possible relationships between airborne radionuclide deposition and precipitation. Here we consider whether the amount of these airborne radionuclides in moss samples is a cumulative measure of radionuclide deposition and decay, and a new approach for analyses of the relationships between precipitation and moss activity concentrations is suggested. Through these analyses it was shown that comparison of cumulative activity measured at one location using moss, normalized by values of cumulative amount or duration of precipitation, showed different regimes of airborne radionuclide deposition. - Graphical abstract: Correlation between cumulative activity of 7 Be and 210 Pb measured in moss samples normalized by the cumulative precipitation. - Highlights: • Use of mosses in measurement of airborne radionuclides deposition was investigated • Prior work indicated 7 Be and 210 Pb activities were not correlated with precipitation • This is unusual since radionuclides moss tissues depends on depositional fluxes. • A new method for study of 7 Be and 210 Pb depositional dynamics was developed • Different seasonal regimes of 7 Be deposition are more noticeable in new technique

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

The ongoing NASA/JAXA Global Precipitation Measurement mission (GPM) requires the full exploitation of the complete constellation of passive microwave (PMW) radiometers orbiting around the globe for global precipitation monitoring. In this context the coherence of the estimates of precipitation using different passive microwave radiometers is a crucial need. We have developed two different passive microwave precipitation retrieval algorithms: one is the Cloud Dynamics Radiation Database algorithm (CDRD), a physically ¬based Bayesian algorithm for conically scanning radiometers (i.e., DMSP SSMIS); the other one is the Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for cross¬-track scanning radiometers (i.e., NOAA and MetOp¬A/B AMSU-¬A/MHS, and NPP Suomi ATMS). The algorithms, originally created for application over Europe and the Mediterranean basin, and used operationally within the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF, http://hsaf.meteoam.it), have been recently modified and extended to Africa and Southern Atlantic for application to the MSG full disk area. The two algorithms are based on the same physical foundation, i.e., the same cloud-radiation model simulations as a priori information in the Bayesian solver and as training dataset in the neural network approach, and they also use similar procedures for identification of frozen background surface, detection of snowfall, and determination of a pixel based quality index of the surface precipitation retrievals. In addition, similar procedures for the screening of not ¬precipitating pixels are used. A novel algorithm for the detection of precipitation in tropical/sub-tropical areas has been developed. The precipitation detection algorithm shows a small rate of false alarms (also over arid/desert regions), a superior detection capability in comparison with other widely used screening algorithms, and it is applicable

Quantitative measurement for the microstructural parameters of nano-precipitates in Al-Mg-Si-Cu alloys

Energy Technology Data Exchange (ETDEWEB)

Li, Kai [School of Metallurgy and Environment, Central South University, Changsha 410083 (China); Electron Microscopy for Materials Science (EMAT), University of Antwerp, Antwerp B-2020 (Belgium); State Key Laboratory of Powder Metallurgy, Central South University, Changsha 410083 (China); Idrissi, Hosni [Electron Microscopy for Materials Science (EMAT), University of Antwerp, Antwerp B-2020 (Belgium); Institute of Mechanics, Materials and Civil Engineering (iMMC), Université catholique de Louvain, Place Sainte Barbe 2, B-1348 Louvain-la-Neuve (Belgium); Sha, Gang [Gleiter Institute of Nano-science, Nanjing University of Science and Technology, Nanjing 210094 (China); Song, Min, E-mail: msong@csu.edu.cn [State Key Laboratory of Powder Metallurgy, Central South University, Changsha 410083 (China); Lu, Jiangbo [Electron Microscopy for Materials Science (EMAT), University of Antwerp, Antwerp B-2020 (Belgium); Electronic Materials Research Laboratory, Key Laboratory of the Ministry of Education and International Center for Dielectric Research, Xi' an Jiaotong University, Xi' an 710049 (China); Shi, Hui [Electron Microscopy for Materials Science (EMAT), University of Antwerp, Antwerp B-2020 (Belgium); ArcelorMittal Global R& D Gent, Pres. J.F. Kennedylaan 3 Zelzate, Ghent B-9060 (Belgium); Wang, Wanlin [School of Metallurgy and Environment, Central South University, Changsha 410083 (China); Ringer, Simon P. [Australian Institute for Nanoscale Science and Technology, The University of Sydney, NSW 2006 (Australia); School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, NSW 2006 (Australia); Du, Yong [State Key Laboratory of Powder Metallurgy, Central South University, Changsha 410083 (China); Schryvers, Dominique [Electron Microscopy for Materials Science (EMAT), University of Antwerp, Antwerp B-2020 (Belgium)

2016-08-15

Size, number density and volume fraction of nano-precipitates are important microstructural parameters controlling the strengthening of materials. In this work a widely accessible, convenient, moderately time efficient method with acceptable accuracy and precision has been provided for measurement of volume fraction of nano-precipitates in crystalline materials. The method is based on the traditional but highly accurate technique of measuring foil thickness via convergent beam electron diffraction. A new equation is proposed and verified with the aid of 3-dimensional atom probe (3DAP) analysis, to compensate for the additional error resulted from the hardly distinguishable contrast of too short incomplete precipitates cut by the foil surface. The method can be performed on a regular foil specimen with a modern LaB{sub 6} or field-emission-gun transmission electron microscope. Precisions around ± 16% have been obtained for precipitate volume fractions of needle-like β″/C and Q precipitates in an aged Al-Mg-Si-Cu alloy. The measured number density is close to that directly obtained using 3DAP analysis by a misfit of 4.5%, and the estimated precision for number density measurement is about ± 11%. The limitations of the method are also discussed. - Highlights: •A facile method for measuring volume fraction of nano-precipitates based on CBED •An equation to compensate for small invisible precipitates, with 3DAP verification •Precisions around ± 16% for volume fraction and ± 11% for number density.

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...

GPM Precipitation Estimates over the Walnut Gulch Experimental Watershed/LTAR site in Southeastern Arizona

Science.gov (United States)

Goodrich, D. C.; Tan, J.; Petersen, W. A.; Unkrich, C. C.; Demaria, E. M.; Hazenberg, P.; Lakshmi, V.

2017-12-01

Precipitation profiles from the GPM Core Observatory Dual-frequency Precipitation Radar (DPR) form part of the a priori database used in GPM Goddard Profiling (GPROF) algorithm passive microwave radiometer retrievals of rainfall. The GPROF retrievals are in turn used as high quality precipitation estimates in gridded products such as IMERG. Due to the variability in and high surface emissivity of land surfaces, GPROF performs precipitation retrievals as a function of surface classes. As such, different surface types may possess different error characteristics, especially over arid regions where high quality ground measurements are often lacking. Importantly, the emissive properties of land also result in GPROF rainfall estimates being driven primarily by the higher frequency radiometer channels (e.g., > 89 GHz) where precipitation signals are most sensitive to coupling between the ice-phase and rainfall production. In this study, we evaluate the rainfall estimates from the Ku channel of the DPR as well as GPROF estimates from various passive microwave sensors. Our evaluation is conducted at the level of individual satellite pixels (5 to 15 km in diameter), against a dense network of weighing rain gauges (90 in 150 km2) in the USDA-ARS Walnut Gulch Experimental Watershed and Long-Term Agroecosystem Research (LTAR) site in southeastern Arizona. The multiple gauges in each satellite pixel and precise accumulation about the overpass time allow a spatially and temporally representative comparison between the satellite estimates and ground reference. Over Walnut Gulch, both the Ku and GPROF estimates are challenged to delineate between rain and no-rain. Probabilities of detection are relatively high, but false alarm ratios are also high. The rain intensities possess a negative bias across nearly all sensors. It is likely that storm types, arid conditions and the highly variable precipitation regime present a challenge to both rainfall retrieval algorithms. An array of

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.

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

Science.gov (United States)

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.

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

Using satellite-based measurements to explore ...

Science.gov (United States)

New particle formation (NPF) can potentially alter regional climate by increasing aerosol particle (hereafter particle) number concentrations and ultimately cloud condensation nuclei. The large scales on which NPF is manifest indicate potential to use satellite-based (inherently spatially averaged) measurements of atmospheric conditions to diagnose the occurrence of NPF and NPF characteristics. We demonstrate the potential for using satellite-measurements of insolation (UV), trace gas concentrations (sulfur dioxide (SO2), nitrogen dioxide (NO2), ammonia (NH3), formaldehyde (HCHO), ozone (O3)), aerosol optical properties (aerosol optical depth (AOD), Ångström exponent (AE)), and a proxy of biogenic volatile organic compound emissions (leaf area index (LAI), temperature (T)) as predictors for NPF characteristics: formation rates, growth rates, survival probabilities, and ultrafine particle (UFP) concentrations at five locations across North America. NPF at all sites is most frequent in spring, exhibits a one-day autocorrelation, and is associated with low condensational sink (AOD×AE) and HCHO concentrations, and high UV. However, there are important site-to-site variations in NPF frequency and characteristics, and in which of the predictor variables (particularly gas concentrations) significantly contribute to the explanatory power of regression models built to predict those characteristics. This finding may provide a partial explanation for the reported spatia

Estimations of natural variability between satellite measurements of trace species concentrations

Science.gov (United States)

Sheese, P.; Walker, K. A.; Boone, C. D.; Degenstein, D. A.; Kolonjari, F.; Plummer, D. A.; von Clarmann, T.

2017-12-01

In order to validate satellite measurements of atmospheric states, it is necessary to understand the range of random and systematic errors inherent in the measurements. On occasions where the measurements do not agree within those errors, a common "go-to" explanation is that the unexplained difference can be chalked up to "natural variability". However, the expected natural variability is often left ambiguous and rarely quantified. This study will look to quantify the expected natural variability of both O3 and NO2 between two satellite instruments: ACE-FTS (Atmospheric Chemistry Experiment - Fourier Transform Spectrometer) and OSIRIS (Optical Spectrograph and Infrared Imaging System). By sampling the CMAM30 (30-year specified dynamics simulation of the Canadian Middle Atmosphere Model) climate chemistry model throughout the upper troposphere and stratosphere at times and geolocations of coincident ACE-FTS and OSIRIS measurements at varying coincidence criteria, height-dependent expected values of O3 and NO2 variability will be estimated and reported on. The results could also be used to better optimize the coincidence criteria used in satellite measurement validation studies.

Overview of Boundary Layer Clouds Using Satellite and Ground-Based Measurements

Science.gov (United States)

Xi, B.; Dong, X.; Wu, P.; Qiu, S.

2017-12-01

A comprehensive summary of boundary layer clouds properties based on our few recently studies will be presented. The analyses include the global cloud fractions and cloud macro/micro- physical properties based on satellite measurements using both CERES-MODIS and CloudSat/Caliposo data products,; the annual/seasonal/diurnal variations of stratocumulus clouds over different climate regions (mid-latitude land, mid-latitude ocean, and Arctic region) using DOE ARM ground-based measurements over Southern great plain (SGP), Azores (GRW), and North slope of Alaska (NSA) sites; the impact of environmental conditions to the formation and dissipation process of marine boundary layer clouds over Azores site; characterizing Arctice mixed-phase cloud structure and favorable environmental conditions for the formation/maintainess of mixed-phase clouds over NSA site. Though the presentation has widely spread topics, we will focus on the representation of the ground-based measurements over different climate regions; evaluation of satellite retrieved cloud properties using these ground-based measurements, and understanding the uncertainties of both satellite and ground-based retrievals and measurements.

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.

Mapping Precipitation in the Lower Mekong River Basin and the U.S. Affiliated Pacific Islands

Science.gov (United States)

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

2017-12-01

Mapping and quantifying precipitation across varying temporal and spatial scales is of utmost importance in understanding, monitoring, and predicting flooding and drought. While there exists many in-situ precipitation gages that can accurately estimate precipitation in a given location, there are still many areas that lack in-situ gages. Many of these locations do not have precipitation gages because they are rural and/or topographically complex. The purpose of our research was to compare different remotely sensed satellite precipitation estimates with in-situ estimates across topographically complex and rural terrain within the United States Affiliated Pacific Islands (USAPI) and the Lower Mekong River Basin (LMRB). We utilize the publicly available Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) Climate Data Record (CDR) from NOAA and two remotely sensed precipitation products from NASA; the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Measurement (GPM). These precipitation estimates were compared with each other and to the available in-situ precipitation estimates from station gages. We also utilize NASA Landsat data to determine the land cover types of these study areas. Using the precipitation estimates, topography, and the land cover of the study areas, we were able to show areas experiencing differing amounts of rainfall and their agreement with in-situ estimates. Additionally, we study the seasonal and spatial trends in precipitation. These analyses can be used to help understand areas that are experience frequent flood or drought.

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.

First evidence for correlations between electron fluxes measured by NOAA-POES satellites and large seismic events

International Nuclear Information System (INIS)

Battiston, Roberto; Vitale, Vincenzo

2013-01-01

We present the result for the search of correlations between the precipitation of low energy electrons (E>0.3MeV) trapped within the Van Allen Belts and earthquakes with magnitude above 5 Richter scale. We used the electron data measured by the NOAA POES 15,16,17 and 18 satellites collected during a period of 13 years, corresponding to about 18 thousands M>5 earthquakes registered in the NEIC catalog of the U.S. Geological Survey. We defined Particle Burst (PB) the fluctuations of electrons counting rate having a probability −6 of being a statistical fluctuation. The observed correlation involves about 1.410 −3 of the earthquakes in that period of time. It provides the first statistically convincing evidence for the existence of a detectable coupling mechanism between the lithosphere and the magnetosphere having well defined time characteristics

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

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

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

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

Estimating Next Primary Productivity using Satellite and Ancillary Data

Science.gov (United States)

Choudhury, B. J.

The net primary productivity (C) or annual rate of carbon accumulation per unit ground area by terrestrial plant communities is the difference of the rate of gross photosynthesis (Ag) and autotrophic respiration (R) per unit ground area. Although available observations show that R is a large and variable fraction of Ag, viz., 0.3 to 0.7, it is generally recognized that much uncertainties exist in this fraction due to difficulties associated with the needed measurements. Additional uncertainties arise when these measurements are extrapolated to regional or global land surface using empirical equations, for example, using regression equations relating C to mean annual precipitation and air temperature. Here, a process- based approach has been taken to calculate Ag and R using satellite and ancillary data. Ag has been expressed as a product of radiation use efficiency, magnitude of intercepted photosynthetically active radiation (PAR), and normalized by stresses due to soil water shortage and air temperature away from the optimum range. A biophysical model has been used to determine the radiation use efficiency from the maximum rate of carbon assimilation by a leaf, foliage temperature, and the fraction of diffuse PAR incident on a canopy. All meteorological data (PAR, air temperature, precipitation, etc.) needed for the calculation are derived from satellite observations, while a land use, land cover data (based on satellite and ground measurements) have been used to assess the maximum rate of carbon assimilation by a leaf of varied cover type based on field measurements. R has been calculated as the sum of maintenance and growth components. The maintenance respiration of foliage and live fine roots at a standard temperature of different land cover has been determined from their nitrogen content using field and satellite measurements, while that of living fraction of woody stem (viz., sapwood) from the seasonal maximum leaf area index as determined from satellite

Study the Precipitation of Radiation Belt Electrons during the Rapid Dropout Events

Science.gov (United States)

Tu, W.; Cunningham, G.; Li, X.; Chen, Y.

2015-12-01

During the main phase of storms, the relativistic electron flux in the radiation belt can drop by orders of magnitude on timescales of a few hours. Where do the electrons go? This is one of the most important outstanding questions in radiation belt studies. Radiation belt electrons can be lost either by transport across the magnetopause into interplanetary space or by precipitation into the atmosphere. In this work we first conduct a survey of the MeV electron dropouts using the Van Allen Probes data in conjunction with the low-altitude measurements of precipitating electrons by 6 NOAA/POES satellites. The dropout events are categorized into three types: precipitation-loss dominant, outward radial diffusion dominant, or with contributions from both mechanisms. The survey results suggest the relative importance of precipitation and outward radial diffusion to the fast dropouts of radiation belt electrons, and their extent in L-shell and electron energy. Then, for specific events identified as dominated by precipitation loss, we use the Drift-Diffusion model, which includes the effects of azimuthal drift and pitch angle diffusion, to simulate both the electron dropout observed by Van Allen Probes and the distributions of drift-loss-cone electrons observed by multiple low-earth-orbit satellites (6 POES and the Colorado Student Space Weather Experiment). The model quantifies the electron precipitation loss and pitch angle diffusion coefficient, Dxx, with high temporal and spatial resolution. Finally, by comparing the Dxx derived from the model with those estimated from the quasi-linear theory using wave data from Van Allen Probes and other event-specific wave models, we are able to test the validity of quasi-linear theory and seek direct evidence of the wave-particle interactions during the dropouts.

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

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

Sensitivity of Distributed Hydrologic Simulations to Ground and Satellite Based Rainfall Products

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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.

Assessment of Observational Uncertainty in Extreme Precipitation Events over the Continental United States

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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

Application of Vision Metrology to In-Orbit Measurement of Large Reflector Onboard Communication Satellite for Next Generation Mobile Satellite Communication

Science.gov (United States)

Akioka, M.; Orikasa, T.; Satoh, M.; Miura, A.; Tsuji, H.; Toyoshima, M.; Fujino, Y.

2016-06-01

Satellite for next generation mobile satellite communication service with small personal terminal requires onboard antenna with very large aperture reflector larger than twenty meters diameter because small personal terminal with lower power consumption in ground base requires the large onboard reflector with high antenna gain. But, large deployable antenna will deform in orbit because the antenna is not a solid dish but the flexible structure with fine cable and mesh supported by truss. Deformation of reflector shape deteriorate the antenna performance and quality and stability of communication service. However, in case of digital beam forming antenna with phased array can modify the antenna beam performance due to adjustment of excitation amplitude and excitation phase. If we can measure the reflector shape precisely in orbit, beam pattern and antenna performance can be compensated with the updated excitation amplitude and excitation phase parameters optimized for the reflector shape measured every moment. Softbank Corporation and National Institute of Information and Communications Technology has started the project "R&D on dynamic beam control technique for next generation mobile communication satellite" as a contracted research project sponsored by Ministry of Internal Affairs and Communication of Japan. In this topic, one of the problem in vision metrology application is a strong constraints on geometry for camera arrangement on satellite bus with very limited space. On satellite in orbit, we cannot take many images from many different directions as ordinary vision metrology measurement and the available area for camera positioning is quite limited. Feasibility of vision metrology application and general methodology to apply to future mobile satellite communication satellite is to be found. Our approach is as follows: 1) Development of prototyping simulator to evaluate the expected precision for network design in zero order and first order 2) Trial

Defense meteorological satellite measurements of total ozone

International Nuclear Information System (INIS)

Lovill, J.E.; Ellis, J.S.; Luther, F.M.; Sullivan, R.J.; Weichel, R.L.

1992-01-01

A multichannel filter radiometer (MFR) on Defense Meteorological Satellites (DMS) that measured total ozone on a global-scale from March 1977 - February 1980 is described. The total ozone data measured by the MFR were compared with total ozone data taken by surfaced-based Dobson spectrophotometers. When comparisons were made for five months, the Dobson spectrophotometer measured 2-5% more total ozone than the MFR. Comparisons between the Dobson spectrophotometer and the MFR showed a reduced RMS difference as the comparisons were made at closer proximity. A Northern Hemisphere total ozone distribution obtained from MFR data is presented

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

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

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

Satellite Soil Moisture and Water Storage Observations Identify Early and Late Season Water Supply Influencing Plant Growth in the Missouri Watershed

Science.gov (United States)

A, G.; Velicogna, I.; Kimball, J. S.; Du, J.; Kim, Y.; Colliander, A.; Njoku, E. G.

2017-12-01

We employ an array of continuously overlapping global satellite sensor observations including combined surface soil moisture (SM) estimates from SMAP, AMSR-E and AMSR-2, GRACE terrestrial water storage (TWS), and satellite precipitation measurements, to characterize seasonal timing and inter-annual variations of the regional water supply pattern and its associated influence on vegetation growth estimates from MODIS enhanced vegetation index (EVI), AMSR-E/2 vegetation optical depth (VOD) and GOME-2 solar-induced florescence (SIF). Satellite SM is used as a proxy of plant-available water supply sensitive to relatively rapid changes in surface condition, GRACE TWS measures seasonal and inter-annual variations in regional water storage, while precipitation measurements represent the direct water input to the analyzed ecosystem. In the Missouri watershed, we find surface SM variations are the dominant factor controlling vegetation growth following the peak of the growing season. Water supply to growth responds to both direct precipitation inputs and groundwater storage carry-over from prior seasons (winter and spring), depending on land cover distribution and regional climatic condition. For the natural grassland in the more arid central and northwest watershed areas, an early season anomaly in precipitation or surface temperature can have a lagged impact on summer vegetation growth by affecting the surface SM and the underlying TWS supplies. For the croplands in the more humid eastern portions of the watershed, the correspondence between surface SM and plant growth weakens. The combination of these complementary remote-sensing observations provides an effective means for evaluating regional variations in the timing and availability of water supply influencing vegetation growth.

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

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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.

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

Precipitation and total power consumption in the ionosphere: Global MHD simulation results compared with Polar and SNOE observations

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M. Palmroth

2006-05-01

Full Text Available We compare the ionospheric electron precipitation morphology and power from a global MHD simulation (GUMICS-4 with direct measurements of auroral energy flux during a pair of substorms on 28-29 March 1998. The electron precipitation power is computed directly from global images of auroral light observed by the Polar satellite ultraviolet imager (UVI. Independent of the Polar UVI measurements, the electron precipitation energy is determined from SNOE satellite observations on the thermospheric nitric oxide (NO density. We find that the GUMICS-4 simulation reproduces the spatial variation of the global aurora rather reliably in the sense that the onset of the substorm is shown in GUMICS-4 simulation as enhanced precipitation in the right location at the right time. The total integrated precipitation power in the GUMICS-4 simulation is in quantitative agreement with the observations during quiet times, i.e., before the two substorm intensifications. We find that during active times the GUMICS-4 integrated precipitation is a factor of 5 lower than the observations indicate. However, we also find factor of 2-3 differences in the precipitation power among the three different UVI processing methods tested here. The findings of this paper are used to complete an earlier objective, in which the total ionospheric power deposition in the simulation is forecasted from a mathematical expression, which is a function of solar wind density, velocity and magnetic field. We find that during this event, the correlation coefficient between the outcome of the forecasting expression and the simulation results is 0.83. During the event, the simulation result on the total ionospheric power deposition agrees with observations (correlation coefficient 0.8 and the AE index (0.85.

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.

Study of sea-surface slope distribution and its effect on radar backscatter based on Global Precipitation Measurement Ku-band precipitation radar measurements

Science.gov (United States)

Yan, Qiushuang; Zhang, Jie; Fan, Chenqing; Wang, Jing; Meng, Junmin

2018-01-01

The collocated normalized radar backscattering cross-section measurements from the Global Precipitation Measurement (GPM) Ku-band precipitation radar (KuPR) and the winds from the moored buoys are used to study the effect of different sea-surface slope probability density functions (PDFs), including the Gaussian PDF, the Gram-Charlier PDF, and the Liu PDF, on the geometrical optics (GO) model predictions of the radar backscatter at low incidence angles (0 deg to 18 deg) at different sea states. First, the peakedness coefficient in the Liu distribution is determined using the collocations at the normal incidence angle, and the results indicate that the peakedness coefficient is a nonlinear function of the wind speed. Then, the performance of the modified Liu distribution, i.e., Liu distribution using the obtained peakedness coefficient estimate; the Gaussian distribution; and the Gram-Charlier distribution is analyzed. The results show that the GO model predictions with the modified Liu distribution agree best with the KuPR measurements, followed by the predictions with the Gaussian distribution, while the predictions with the Gram-Charlier distribution have larger differences as the total or the slick filtered, not the radar filtered, probability density is included in the distribution. The best-performing distribution changes with incidence angle and changes with wind speed.

Comparison and evaluation of satellite derived precipitation products for hydrological modeling of the Zambezi River Basin

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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.

Monsoon Convection during the South China Sea Monsoon Experiment Observed from Shipboard Radar and the TRMM Satellite

Science.gov (United States)

Rickenbach, Tom; Cifelli, Rob; Halverson, Jeff; Kucera, Paul; Atkinson, Lester; Fisher, Brad; Gerlach, John; Harris, Kathy; Kaufman, Cristina; Liu, Ching-Hwang;

Analyzing coastal precipitation using TRMM observations

Directory of Open Access Journals (Sweden)

R. H. Heiblum

2011-12-01

Full Text Available The interaction between breezes and synoptic gradient winds, and surface friction increase in transition from sea to land can create persistent convergence zones nearby coastlines. The low level convergence of moist air promotes the dynamical and microphysical processes responsible for the formation of clouds and precipitation.

Our work focuses on the winter seasons of 1998–2011 in the Eastern Mediterranean. During the winter the Mediterranean sea is usually warmer than the adjacent land, resulting in frequent occurrence of land breeze that opposes the common synoptic winds. Using rain-rate vertical profiles from the Tropical Rainfall Measurement Mission (TRMM satellite, we examined the spatial and temporal distribution of average hydrometeor mass in clouds as a function of the distance from coastlines.

Results show that coastlines in the Eastern Mediterranean are indeed favored areas for precipitation formation. The intra-seasonal and diurnal changes in the distribution of hydrometeor mass indicate that the land breeze may likely be the main responsible mechanism behind our results.

Regional model simulation of the North Atlantic cyclone "Caroline" and comparisons with satellite data

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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

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

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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�

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.

Global distribution of pauses observed with satellite measurements

Indian Academy of Sciences (India)

Here we study the commonality and differences observed in the variability of all the pauses. We also examined how good other datasets will represent these features among (and in between) different satellite measurements, re-analysis, and model data. Hemispheric differences observed in all the pauses are also reported.

Total ozone retrieval from satellite multichannel filter radiometer measurements

International Nuclear Information System (INIS)

Lovill, J.E.; Sullivan, T.J.; Weichel, R.L.; Ellis, J.S.; Huebel, J.G.; Korver, J.; Weidhaas, P.P.; Phelps, F.A.

1978-01-01

A total ozone retrieval model has been developed to process radiance data gathered by a satellite-mounted multichannel filter radiometer (MFR). Extensive effort went into theoretical radiative transfer modeling, a retrieval scheme was developed, and the technique was applied to the MFR radiance measurements. The high quality of the total ozone retrieval results was determined through comparisons with Dobson measurements. Included in the report are global total ozone maps for 20 days between May 12 and July 5, 1977. A comparison of MFR results for 13 days in June 1977 with Dobson spectrophotometer measurements of ozone for the same period showed good agreement: there was a root-mean-square difference of 6.2% (equivalent to 20.2 m.atm.cm). The estimated global total ozone value for June 1977 (296 m.atm.cm) was in good agreement with satellite backscatter ultraviolet data for June 1970 (304 m.atm.cm) and June 1971

Energetic electron precipitation characteristics observed from Antarctica during a flux dropout event

Science.gov (United States)

Clilverd, Mark A.; Cobbett, Neil; Rodger, Craig J.; Brundell, James B.; Denton, Michael H.; Hartley, David P.; Rodriguez, Juan V.; Danskin, Donald; Raita, Tero; Spanswick, Emma L.

2013-11-01

from two autonomous VLF radio receiver systems installed in a remote region of the Antarctic in 2012 is used to take advantage of the juxtaposition of the L = 4.6 contour, and the Hawaii-Halley, Antarctica, great circle path as it passes over thick Antarctic ice shelf. The ice sheet conductivity leads to high sensitivity to changing D region conditions, and the quasi constant L shell highlights outer radiation belt processes. The ground-based instruments observed several energetic electron precipitation events over a moderately active 24 h period, during which the outer radiation belt electron flux declined at most energies and subsequently recovered. Combining the ground-based data with low and geosynchronous orbiting satellite observations on 27 February 2012, different driving mechanisms were observed for three precipitation events with clear signatures in phase space density and electron anisotropy. Comparison between flux measurements made by Polar-orbiting Operational Environmental Satellites (POES) in low Earth orbit and by the Antarctic instrumentation provides evidence of different cases of weak and strong diffusion into the bounce loss cone, helping to understand the physical mechanisms controlling the precipitation of energetic electrons into the atmosphere. Strong diffusion events occurred as the bounce loss cone. Two events had a factor of about 3 to 10 times more >30 keV flux than was reported by POES, more consistent with strong diffusion conditions.

Coarse Initial Orbit Determination for a Geostationary Satellite Using Single-Epoch GPS Measurements

Directory of Open Access Journals (Sweden)

Ghangho Kim

2015-04-01

Full Text Available A practical algorithm is proposed for determining the orbit of a geostationary orbit (GEO satellite using single-epoch measurements from a Global Positioning System (GPS receiver under the sparse visibility of the GPS satellites. The algorithm uses three components of a state vector to determine the satellite’s state, even when it is impossible to apply the classical single-point solutions (SPS. Through consideration of the characteristics of the GEO orbital elements and GPS measurements, the components of the state vector are reduced to three. However, the algorithm remains sufficiently accurate for a GEO satellite. The developed algorithm was tested on simulated measurements from two or three GPS satellites, and the calculated maximum position error was found to be less than approximately 40 km or even several kilometers within the geometric range, even when the classical SPS solution was unattainable. In addition, extended Kalman filter (EKF tests of a GEO satellite with the estimated initial state were performed to validate the algorithm. In the EKF, a reliable dynamic model was adapted to reduce the probability of divergence that can be caused by large errors in the initial state.

Coarse Initial Orbit Determination for a Geostationary Satellite Using Single-Epoch GPS Measurements

Science.gov (United States)

Kim, Ghangho; Kim, Chongwon; Kee, Changdon

2015-01-01

A practical algorithm is proposed for determining the orbit of a geostationary orbit (GEO) satellite using single-epoch measurements from a Global Positioning System (GPS) receiver under the sparse visibility of the GPS satellites. The algorithm uses three components of a state vector to determine the satellite’s state, even when it is impossible to apply the classical single-point solutions (SPS). Through consideration of the characteristics of the GEO orbital elements and GPS measurements, the components of the state vector are reduced to three. However, the algorithm remains sufficiently accurate for a GEO satellite. The developed algorithm was tested on simulated measurements from two or three GPS satellites, and the calculated maximum position error was found to be less than approximately 40 km or even several kilometers within the geometric range, even when the classical SPS solution was unattainable. In addition, extended Kalman filter (EKF) tests of a GEO satellite with the estimated initial state were performed to validate the algorithm. In the EKF, a reliable dynamic model was adapted to reduce the probability of divergence that can be caused by large errors in the initial state. PMID:25835299

Beryllium-7 and {sup 210}Pb atmospheric deposition measured in moss and dependence on cumulative precipitation

Energy Technology Data Exchange (ETDEWEB)

Krmar, M., E-mail: krmar@df.uns.ac.rs [Faculty of Science, Physics Department, Trg Dositeja Obradovića 4, Novi Sad (Serbia); Mihailović, D.T.; Arsenić, I. [Faculty of Agriculture, Trg Dositeja Obradovića 8, Novi Sad (Serbia); Radnović, D. [Faculty of Science, Biology Department, Trg Dositeja Obradovića 4, Novi Sad (Serbia); Pap, I. [Faculty of Agriculture, Trg Dositeja Obradovića 8, Novi Sad (Serbia)

2016-01-15

This paper focuses on analysis of the time series of {sup 7}Be and {sup 210}Pb activity measured in moss, and the amount, as well as duration of precipitation, to gain a better understanding of the possible relationships between airborne radionuclide deposition and precipitation. Here we consider whether the amount of these airborne radionuclides in moss samples is a cumulative measure of radionuclide deposition and decay, and a new approach for analyses of the relationships between precipitation and moss activity concentrations is suggested. Through these analyses it was shown that comparison of cumulative activity measured at one location using moss, normalized by values of cumulative amount or duration of precipitation, showed different regimes of airborne radionuclide deposition. - Graphical abstract: Correlation between cumulative activity of {sup 7}Be and {sup 210}Pb measured in moss samples normalized by the cumulative precipitation. - Highlights: • Use of mosses in measurement of airborne radionuclides deposition was investigated • Prior work indicated {sup 7}Be and {sup 210}Pb activities were not correlated with precipitation • This is unusual since radionuclides moss tissues depends on depositional fluxes. • A new method for study of {sup 7}Be and {sup 210}Pb depositional dynamics was developed • Different seasonal regimes of {sup 7}Be deposition are more noticeable in new technique.

Evaluating the performance of remotely sensed and reanalysed precipitation data over West Africa using HBV light

Science.gov (United States)

Jütten, Thomas; Jackisch, Dominik; Diekkrüger, Bernd; Kusche, Jürgen; Eicker, Annette; Springer, Anne

2016-04-01

Water is one of the most crucial natural resources in West Africa, where the livelihoods of large parts of the population rely heavily on rain-fed agriculture. Therefore, the modelling of the water balance is an important tool to aid in water resource management. Precipitation is one of most important atmospheric drivers of hydrological models. However, ground-based observation networks are sparse in Western Africa and a further decline in station numbers due to a variety of reasons such as the deterioration of stations or political unrest has been observed in recent years. In ungauged river basins, or basins with insufficiently available precipitation data, several studies have shown that remotely sensed or reanalysed precipitation data may be used to compliment or replace missing information. However, the uncertainties of these datasets over Western Africa are not well examined and a need for further studies is apparent. For validation purposes, precipitation datasets are traditionally compared to in-situ ground measurements. This is not possible in ungauged basins. A new approach to assess the quality of satellite and reanalysis data which is gaining popularity among researchers compares different precipitation datasets using hydrological models. In this so-called hydrological evaluation, ground-truth data is no longer necessary in order to validate a product. The chosen model is calibrated for different precipitation products and the simulated streamflow generated for each product is compared to the measured streamflow. Multiple state of the art satellite and reanalysis precipitation datasets with various spatial resolutions were used in this study, namely: CFSR (0.3125°), CHIRPS (0.05°), CMORPH (0.25°), PERSIANN (0.25°), RFE 2.0 (0.1°), TAMSAT (0.0375°), TRMM 3B42 v7 (0.25°) and TRMM 3B42RT (real time) (0.25°). These datasets were evaluated at the regional as well as local scale using the HBV light conceptual hydrological model for several basins

The Effects of Weather Patterns on the Spatio-Temporal Distribution of SO2 over East Asia as Seen from Satellite Measurements

Science.gov (United States)

Dunlap, L.; Li, C.; Dickerson, R. R.; Krotkov, N. A.

2015-12-01

Weather systems, particularly mid-latitude wave cyclones, have been known to play an important role in the short-term variation of near-surface air pollution. Ground measurements and model simulations have demonstrated that stagnant air and minimal precipitation associated with high pressure systems are conducive to pollutant accumulation. With the passage of a cold front, built up pollution is transported downwind of the emission sources or washed out by precipitation. This concept is important to note when studying long-term changes in spatio-temporal pollution distribution, but has not been studied in detail from space. In this study, we focus on East Asia (especially the industrialized eastern China), where numerous large power plants and other point sources as well as area sources emit large amounts of SO2, an important gaseous pollutant and a precursor of aerosols. Using data from the Aura Ozone Monitoring Instrument (OMI) we show that such weather driven distribution can indeed be discerned from satellite data by utilizing probability distribution functions (PDFs) of SO2 column content. These PDFs are multimodal and give insight into the background pollution level at a given location and contribution from local and upwind emission sources. From these PDFs it is possible to determine the frequency for a given region to have SO2 loading that exceeds the background amount. By comparing OMI-observed long-term change in the frequency with meteorological data, we can gain insights into the effects of climate change (e.g., the weakening of Asian monsoon) on regional air quality. Such insight allows for better interpretation of satellite measurements as well as better prediction of future pollution distribution as a changing climate gives way to changing weather patterns.

Some observations on precipitation measurement on forested experimental watersheds

Science.gov (United States)

Raymond E. Leonard; Kenneth G. Reinhart

1963-01-01

Measurement of precipitation on forested experimental watersheds presents difficulties other than those associated with access to and from the gages in all kinds of weather. For instance, the tree canopy must be cleared above the gage. The accepted practice of keeping an unobstructed sky view of 45" around the gage involves considerable tree cutting. On a level...

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.

Comparison of Satellite Rainfall Estimates and Rain Gauge Measurements in Italy, and Impact on Landslide Modeling

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Mauro Rossi

2017-12-01

Full Text Available Landslides can be triggered by intense or prolonged rainfall. Rain gauge measurements are commonly used to predict landslides even if satellite rainfall estimates are available. Recent research focuses on the comparison of satellite estimates and gauge measurements. The rain gauge data from the Italian network (collected in the system database “Verifica Rischio Frana”, VRF are compared with the National Aeronautics and Space Administration (NASA Tropical Rainfall Measuring Mission (TRMM products. For the purpose, we couple point gauge and satellite rainfall estimates at individual grid cells, evaluating the correlation between gauge and satellite data in different morpho-climatological conditions. We then analyze the statistical distributions of both rainfall data types and the rainfall events derived from them. Results show that satellite data underestimates ground data, with the largest differences in mountainous areas. Power-law models, are more appropriate to correlate gauge and satellite data. The gauge and satellite-based products exhibit different statistical distributions and the rainfall events derived from them differ. In conclusion, satellite rainfall cannot be directly compared with ground data, requiring local investigation to account for specific morpho-climatological settings. Results suggest that satellite data can be used for forecasting landslides, only performing a local scaling between satellite and ground data.

The NASA CYGNSS Small Satellite Constellation

Science.gov (United States)

Ruf, C. S.; Gleason, S.; McKague, D. S.; Rose, R.; Scherrer, J.

2017-12-01

The NASA Cyclone Global Navigation Satellite System (CYGNSS) is a constellation of eight microsatellite observatories that was launched into a low (35°) inclination, low Earth orbit on 15 December 2016. Each observatory carries a 4-channel GNSS-R bistatic radar receiver. The radars are tuned to receive the L1 signals transmitted by GPS satellites, from which near-surface ocean wind speed is estimated. The mission architecture is designed to improve the temporal sampling of winds in tropical cyclones (TCs). The 32 receive channels of the complete CYGNSS constellation, combined with the 30 GPS satellite transmitters, results in a revisit time for sampling of the wind of 2.8 hours (median) and 7.2 hours (mean) at all locations between 38 deg North and 38 deg South latitude. Operation at the GPS L1 frequency of 1575 MHz allows for wind measurements in the TC inner core that are often obscured from other spaceborne remote sensing instruments by intense precipitation in the eye wall and inner rain bands. An overview of the CYGNSS mission wil be presented, followed by early on-orbit status and results.

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.

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...

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.

Rocket measurements of energetic particles in the midlatitude precipitation zone

Science.gov (United States)

Voss, H. D.; Smith, L. G.; Braswell, F. M.

1980-01-01

Measurements of energetic ion and electron properties as a function of altitude in the midlatitude zone of nighttime energetic particle precipitation are reported. The measurements of particle fluxes, energy spectra and pitch angle distributions were obtained by a Langmuir probe, six energetic particle spectrometers and an electrostatic analyzer on board a Nike Apache rocket launched near the center of the midlatitude zone during disturbed conditions. It is found that the incident flux was primarily absorbed rather than backscattered, and consists of mainly energetic hydrogen together with some helium and a small energetic electron component. Observed differential energy spectra of protons having an exponential energy spectrum, and pitch angle distributions at various altitudes indicate that the energetic particle flux decreases rapidly for pitch angles less than 70 deg. An energetic particle energy flux of 0.002 ergs/sq cm per sec is calculated which indicates the significance of energetic particles as a primary nighttime ionization source for altitudes between 120 and 200 km in the midlatitude precipitation zone.

Enhanced Research Opportunity to Study the Atmospheric Forcing by High-Energy Particle Precipitation at High Latitudes: Emerging New Satellite Data and the new Ground-Based Observations in Northern Scandinavia, including the EISCAT_3D Incoherent Scatter Facility.

Science.gov (United States)

Turunen, E. S.; Ulich, T.; Kero, A.; Tero, R.; Verronen, P. T.; Norberg, J.; Miyoshi, Y.; Oyama, S. I.; Saito, S.; Hosokawa, K.; Ogawa, Y.

2017-12-01

Recent observational and model results on the particle precipitation as source of atmospheric variability challenge us to implement better and continuously monitoring observational infrastructure for middle and upper atmospheric research. An example is the effect of high-energy electron precipitation during pulsating aurora on mesospheric ozone, the concentration of which may be reduced by several tens of percent, similarily as during some solar proton events, which are known to occur more rarely than pulsating aurora. So far the Assessment Reports by the Intergovernmental Panel on Climate Change did not include explicitely the particle forcing of middle and upper atmosphere in their climate model scenarios. This will appear for the first time in the upcoming climate simulations. We review recent results related to atmospheric forcing by particle precipitation via effects on chemical composition. We also show the research potential of new ground-based radio measurement techniques, such as spectral riometry and incoherent scatter by new phased-array radars, such as EISCAT_3D, which will be a volumetric, 3- dimensionally imaging radar, distributed in Norway, Sweden, and Finland. It is expected to be operational from 2020 onwards, surpassing all the current IS radars of the world in technology. It will be able to produce continuous information of ionospheric plasma parameters in a volume, including 3D-vector plasma velocities. For the first time we will be able to map the 3D electric currents in ionosphere, as well as we will have continuous vector wind measurements in mesosphere. The geographical area covered by the EISCAT_3D measurements can be expanded by suitably selected other continuous observations, such as optical and satellite tomography networks. A new 100 Hz all-sky camera network was recently installed in Northern Scandinavia in order to support the Japanese Arase satellite mission. In near future the ground-based measurement network will also include new

Retrieving moisture profiles from precipitable water measurements using a variational data assimilation approach

Energy Technology Data Exchange (ETDEWEB)

Guo, Y.R.; Zou, X.; Kuo, Y.H. [National Center for Atmospheric Research, Boulder, CO (United States)

1996-04-01

Atmospheric moisture distribution is directly related to the formation of clouds and precipitation and affects the atmospheric radiation and climate. Currently, several remote sensing systems can measure precipitable water (PW) with fairly high accuracy. As part of the development of an Integrated Data Assimilation and Sounding System in support of the Atmospheric Radiation Measurement Program, retrieving the 3-D water vapor fields from PW measurements is an important problem. A new four dimensional variational (4DVAR) data assimilation system based on the Penn State/National Center for Atmospheric Research (NCAR) mesoscale model (MM5) has been developed by Zou et al. (1995) with the adjoint technique. In this study, we used this 4DVAR system to retrieve the moisture profiles. Because we do not have a set of real observed PW measurements now, the special soundings collected during the Severe Environmental Storm and Mesoscale Experiment (SESAME) in 1979 were used to simulate a set of PW measurements, which were then assimilated into the 4DVAR system. The accuracy of the derived water vapor fields was assessed by direct comparison with the detailed specific humidity soundings. The impact of PW assimilation on precipitation forecast was examined by conducting a series of model forecast experiments started from the different initial conditions with or without data assimilation.

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.

Satellite passive microwave rain measurement techniques for land and ocean

Science.gov (United States)

Spencer, R. W.

1985-01-01

Multiseasonal rainfall was found to be measurable over land with satellite passive microwave data, based upon comparisons between Nimbus 7 Scanning Multichannel Microwave Radiometer (SMME) brightness temperatures (T sub B) and operational WSR-57 radar rain rates. All of the SMMR channels (bipolarized 37, 21, 18, 10.7, and 6.6. GHz T sub B) were compared to radar reflectivities for 25 SMMR passes and 234 radar scans over the U.S. during the spring, summer, and fall of 1979. It was found that the radar rain rates were closely related to the difference between 37 and 21 GHz T sub B. This result is due to the volume scattering effects of precipitation which cause emissivity decreases with frequency, as opposed to emissive surfaces (e.g., water) whose emissivities increase with frequency. Two frequencies also act to reduce the effects of thermometric temperature variations on T sub B to a miminum. During summer and fall, multiple correlation coefficients of 0.80 and 0.75 were obtained. These approach the limit of correlation that can be expected to exist between two very different data sources, especially in light of the errors attributable to manual digitization of PPI photographs of variable quality from various operational weather radar not calibrated for research purposes. During the spring, a significantly lower (0.63) correlation was found. This poorer performance was traced to cases of wet, unvegetated soil being sensed at the lower frequencies through light rain, partly negating the rain scattering signal.

Increasing importance of precipitation variability on global livestock grazing lands

Science.gov (United States)

Sloat, Lindsey L.; Gerber, James S.; Samberg, Leah H.; Smith, William K.; Herrero, Mario; Ferreira, Laerte G.; Godde, Cécile M.; West, Paul C.

2018-03-01

Pastures and rangelands underpin global meat and milk production and are a critical resource for millions of people dependent on livestock for food security1,2. Forage growth, which is highly climate dependent3,4, is potentially vulnerable to climate change, although precisely where and to what extent remains relatively unexplored. In this study, we assess climate-based threats to global pastures, with a specific focus on changes in within- and between-year precipitation variability (precipitation concentration index (PCI) and coefficient of variation of precipitation (CVP), respectively). Relating global satellite measures of vegetation greenness (such as the Normalized Difference Vegetation Index; NDVI) to key climatic factors reveals that CVP is a significant, yet often overlooked, constraint on vegetation productivity across global pastures. Using independent stocking data, we found that areas with high CVP support lower livestock densities than less-variable regions. Globally, pastures experience about a 25% greater year-to-year precipitation variation (CVP = 0.27) than the average global land surface area (0.21). Over the past century, CVP has generally increased across pasture areas, although both positive (49% of pasture area) and negative (31% of pasture area) trends exist. We identify regions in which livestock grazing is important for local food access and economies, and discuss the potential for pasture intensification in the context of long-term regional trends in precipitation variability.

Comprehensive Comparisons of Satellite Data, Signals, and Measurements between the BeiDou Navigation Satellite System and the Global Positioning System †

Science.gov (United States)

Jan, Shau-Shiun; Tao, An-Lin

2016-01-01

The Chinese BeiDou navigation satellite system (BDS) aims to provide global positioning service by 2020. The combined use of BDS and Global Positioning System (GPS) is proposed to provide navigation service with more stringent requirements. Actual satellite data, signals and measurements were collected for more than one month to analyze the positioning service qualities from both BDS and GPS. In addition to the conversions of coordinate and timing system, five data quality analysis (DQA) methods, three signal quality analysis (SQA) methods, and four measurement quality analysis (MQA) methods are proposed in this paper to improve the integrated positioning performance of BDS and GPS. As shown in the experiment results, issues related to BDS and GPS are resolved by the above proposed quality analysis methods. Thus, the anomalies in satellite data, signals and measurements can be detected by following the suggested resolutions to enhance the positioning performance of the combined use of BDS and GPS in the Asia Pacific region. PMID:27187403

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

Effects of 4D-Var Data Assimilation Using Remote Sensing Precipitation Products in a WRF Model over the Complex Terrain of an Arid Region River Basin

Directory of Open Access Journals (Sweden)

Xiaoduo Pan

2017-09-01

Full Text Available Individually, ground-based, in situ observations, remote sensing, and regional climate modeling cannot provide the high-quality precipitation data required for hydrological prediction, especially over complex terrains. Data assimilation techniques can be used to bridge the gap between observations and models by assimilating ground observations and remote sensing products into models to improve precipitation simulation and forecasting. However, only a small portion of satellite-retrieved precipitation products assimilation research has been implemented over complex terrains in an arid region. Here, we used the weather research and forecasting (WRF model to assimilate two satellite precipitation products (The Tropical Rainfall Measuring Mission: TRMM 3B42 and Fengyun-2D: FY-2D using the 4D-Var data assimilation method for a typical inland river basin in northwest China’s arid region, the Heihe River Basin, where terrains are very complex. The results show that the assimilation of remote sensing precipitation products can improve the initial WRF fields of humidity and temperature, thereby improving precipitation forecasting and decreasing the spin-up time. Hence, assimilating TRMM and FY-2D remote sensing precipitation products using WRF 4D-Var can be viewed as a positive step toward improving the accuracy and lead time of numerical weather prediction models, particularly over regions with complex terrains.

Spin motion determination of the Envisat satellite through laser ranging measurements from a single pass measured by a single station

Science.gov (United States)

Pittet, Jean-Noël; Šilha, Jiří; Schildknecht, Thomas

2018-02-01

The Satellite Laser Ranging (SLR) technology is used to accurately determine the position of space objects equipped with so-called retro-reflectors or retro-reflector arrays (RRA). This type of measurement allows to measure the range to the spacecraft with high precision, which leads to determination of very accurate orbits for these targets. Non-active spacecraft, which are not attitude controlled any longer, tend to start to spin or tumble under influence of the external and internal torques and forces. If the return signal is measured for a non-spherical non-active rotating object, the signal in the range residuals with respect to the reference orbit is more complex. For rotating objects the return signal shows an oscillating pattern or patterns caused by the RRA moving around the satellite's centre of mass. This behaviour is projected onto the radial component measured by the SLR. In our work, we demonstrate how the SLR ranging technique from one sensor to a satellite equipped with a RRA can be used to precisely determine its spin motion during one passage. Multiple SLR measurements of one target over time allow to accurately monitor spin motion changes which can be further used for attitude predictions. We show our solutions of the spin motion determined for the non-active ESA satellite Envisat obtained from measurements acquired during years 2013-2015 by the Zimmerwald SLR station, Switzerland. All the necessary parameters are defined for our own so-called point-like model which describes the motion of a point in space around the satellite centre of mass.

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...

Contribution of BeiDou satellite system for long baseline GNSS measurement in Indonesia

Science.gov (United States)

Gumilar, I.; Bramanto, B.; Kuntjoro, W.; Abidin, H. Z.; Trihantoro, N. F.

2018-05-01

The demand for more precise positioning method using GNSS (Global Navigation Satellite System) in Indonesia continue to rise. The accuracy of GNSS positioning depends on the length of baseline and the distribution of observed satellites. BeiDou Navigation Satellite System (BDS) is a positioning system owned by China that operating in Asia-Pacific region, including Indonesia. This research aims to find out the contribution of BDS in increasing the accuracy of long baseline static positioning in Indonesia. The contributions are assessed by comparing the accuracy of measurement using only GPS (Global Positioning System) and measurement using the combination of GPS and BDS. The data used is 5 days of GPS and BDS measurement data for baseline with 120 km in length. The software used is open-source RTKLIB and commercial software Compass Solution. This research will explain in detail the contribution of BDS to the accuracy of position in long baseline static GNSS measurement.

Quantifying the Precipitation Loss of Radiation Belt Electrons during a Rapid Dropout Event

Science.gov (United States)

Pham, K. H.; Tu, W.; Xiang, Z.

2017-12-01

Relativistic electron flux in the radiation belt can drop by orders of magnitude within the timespan of hours. In this study, we used the drift-diffusion model that includes azimuthal drift and pitch angle diffusion of electrons to simulate low-altitude electron distribution observed by POES/MetOp satellites for rapid radiation belt electron dropout event occurring on May 1, 2013. The event shows fast dropout of MeV energy electrons at L>4 over a few hours, observed by the Van Allen Probes mission. By simulating the electron distributions observed by multiple POES satellites, we resolve the precipitation loss with both high spatial and temporal resolution and a range of energies. We estimate the pitch angle diffusion coefficients as a function of energy, pitch angle, and L-shell, and calculate corresponding electron lifetimes during the event. The simulation results show fast electron precipitation loss at L>4 during the electron dropout, with estimated electron lifetimes on the order of half an hour for MeV energies. The electron loss rate show strong energy dependence with faster loss at higher energies, which suggest that this dropout event is dominated by quick and localized scattering process that prefers higher energy electrons. The estimated pitch angle diffusion rates from the model are then compared with in situ wave measurements from Van Allen Probes to uncover the underlying wave-particle-interaction mechanisms that are responsible for the fast electron precipitation. Comparing the resolved precipitation loss with the observed electron dropouts at high altitudes, our results will suggest the relative role of electron precipitation loss and outward radial diffusion to the radiation belt dropouts during storm and non-storm times, in addition to its energy and L dependence.

Measurement of the Lense-Thirring drag on high-altitude, laser-ranged artificial satellites

International Nuclear Information System (INIS)

Ciufolini, I.

1986-01-01

We describe a new method of measuring the Lense-Thirring relativistic nodal drag using LAGEOS together with another high-altitude, laser-ranged, similar satellite with appropriately chosen orbital parameters. We propose, for this purpose, that a future satellite such as LAGEOS II have an inclination supplementary to that of LAGEOS. The experiment proposed here would provide a method for experimental verification of the general relativistic formulation of Mach's principle and measurement of the gravitomagnetic field

Comparison of Ground- and Space-based Radar Observations with Disdrometer Measurements During the PECAN Field Campaign

Science.gov (United States)

Torres, A. D.; Rasmussen, K. L.; Bodine, D. J.; Dougherty, E.

2015-12-01

Plains Elevated Convection At Night (PECAN) was a large field campaign that studied nocturnal mesoscale convective systems (MCSs), convective initiation, bores, and low-level jets across the central plains in the United States. MCSs are responsible for over half of the warm-season precipitation across the central U.S. plains. The rainfall from deep convection of these systems over land have been observed to be underestimated by satellite radar rainfall-retrieval algorithms by as much as 40 percent. These algorithms have a strong dependence on the generally unmeasured rain drop-size distribution (DSD). During the campaign, our group measured rainfall DSDs, precipitation fall velocities, and total precipitation in the convective and stratiform regions of MCSs using Ott Parsivel optical laser disdrometers. The disdrometers were co-located with mobile pod units that measured temperature, wind, and relative humidity for quality control purposes. Data from the operational NEXRAD radar in LaCrosse, Wisconsin and space-based radar measurements from a Global Precipitation Measurement satellite overpass on July 13, 2015 were used for the analysis. The focus of this study is to compare DSD measurements from the disdrometers to radars in an effort to reduce errors in existing rainfall-retrieval algorithms. The error analysis consists of substituting measured DSDs into existing quantitative precipitation estimation techniques (e.g. Z-R relationships and dual-polarization rain estimates) and comparing these estimates to ground measurements of total precipitation. The results from this study will improve climatological estimates of total precipitation in continental convection that are used in hydrological studies, climate models, and other applications.

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.

Monsoon Convective During the South China Sea Monsoon Experiment: Observations from Ground-Based Radar and the TRMM Satellite

Science.gov (United States)

Cifelli, Rob; Rickenbach, Tom; Halverson, Jeff; Keenan, Tom; Kucera, Paul; Atkinson, Lester; Fisher, Brad; Gerlach, John; Harris, Kathy; Kaufman, Cristina

1999-01-01

A main goal of the recent South China Sea Monsoon Experiment (SCSMEX) was to study convective processes associated with the onset of the Southeast Asian summer monsoon. The NASA TOGA C-band scanning radar was deployed on the Chinese research vessel Shi Yan #3 for two 20 day cruises, collecting dual-Doppler measurements in conjunction with the BMRC C-Pol dual-polarimetric radar on Dongsha Island. Soundings and surface meteorological data were also collected with an NCAR Integrated Sounding System (ISS). This experiment was the first major tropical field campaign following the launch of the Tropical Rainfall Measuring Mission (TRMM) satellite. These observations of tropical oceanic convection provided an opportunity to make comparisons between surface radar measurements and the Precipitation Radar (PR) aboard the TRMM satellite in an oceanic environment. Nearly continuous radar operations were conducted during two Intensive Observing Periods (IOPS) straddling the onset of the monsoon (5-25 May 1998 and 5-25 June 1998). Mesoscale lines of convection with widespread regions of both trailing and forward stratiform precipitation were observed following the onset of the active monsoon in the northern South China Sea region. The vertical structure of the convection during periods of strong westerly flow and relatively moist environmental conditions in the lower to mid-troposphere contrasted sharply with convection observed during periods of low level easterlies, weak shear, and relatively dry conditions in the mid to upper troposphere. Several examples of mesoscale convection will be shown from the ground (ship)-based and spaceborne radar data during times of TRMM satellite overpasses. Examples of pre-monsoon convection, characterized by isolated cumulonimbus and shallow, precipitating congestus clouds, will also be discussed.

Transportable IOT measurement station for direct-broadcast satellites

Science.gov (United States)

Ulbricht, Michael

A transportable 11.7-12.5-GHz flux-density measurement facility for use in the in-orbit testing (IOT) of the FRG TV-Sat direct-broadcast satellites is described. Major components include a 1.2-m-diameter antenna, the fluxmeter, a radiometer to determine atmospheric attenuation, a weather station, and a control and data-processing computer; all of the components are mounted on a 5.10 x 2.35 x 2.70-m trailer. IOT performance parameters include gain/temperature ratio 15.9 dB/K, measurement range -97 to -117 dBW/sq m, measurement accuracy less than 0.5 dB rms, and measurement rate 250-650 msec. Photographs and a block diagram are provided.

Using satellite data on meteorological and vegetation characteristics and soil surface humidity in the Land Surface Model for the vast territory of agricultural destination

Science.gov (United States)

Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Vasilenko, Eugene; Volkova, Elena; Kukharsky, Alexander

2017-04-01

The model of water and heat exchange between vegetation covered territory and atmosphere (LSM, Land Surface Model) for vegetation season has been developed to calculate soil water content, evapotranspiration, infiltration of water into the soil, vertical latent and sensible heat fluxes and other water and heat balances components as well as soil surface and vegetation cover temperatures and depth distributions of moisture and temperature. The LSM is suited for utilizing satellite-derived estimates of precipitation, land surface temperature and vegetation characteristics and soil surface humidity for each pixel. Vegetation and meteorological characteristics being the model parameters and input variables, correspondingly, have been estimated by ground observations and thematic processing measurement data of scanning radiometers AVHRR/NOAA, SEVIRI/Meteosat-9, -10 (MSG-2, -3) and MSU-MR/Meteor-M № 2. Values of soil surface humidity has been calculated from remote sensing data of scatterometers ASCAT/MetOp-A, -B. The case study has been carried out for the territory of part of the agricultural Central Black Earth Region of European Russia with area of 227300 km2 located in the forest-steppe zone for years 2012-2015 vegetation seasons. The main objectives of the study have been: - to built estimates of precipitation, land surface temperatures (LST) and vegetation characteristics from MSU-MR measurement data using the refined technologies (including algorithms and programs) of thematic processing satellite information matured on AVHRR and SEVIRI data. All technologies have been adapted to the area of interest; - to investigate the possibility of utilizing satellite-derived estimates of values above in the LSM including verification of obtained estimates and development of procedure of their inputting into the model. From the AVHRR data there have been built the estimates of precipitation, three types of LST: land skin temperature Tsg, air temperature at a level of

Challenges in complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate – lessons from temperate wetland-upland landscapes

Science.gov (United States)

Gallant, Alisa L.; Sadinski, Walter J.; Brown, Jesslyn F.; Senay, Gabriel B.; Roth, Mark F.

2018-01-01

Assessing climate-related ecological changes across spatiotemporal scales meaningful to resource managers is challenging because no one method reliably produces essential data at both fine and broad scales. We recently confronted such challenges while integrating data from ground- and satellite-based sensors for an assessment of four wetland-rich study areas in the U.S. Midwest. We examined relations between temperature and precipitation and a set of variables measured on the ground at individual wetlands and another set measured via satellite sensors within surrounding 4 km2 landscape blocks. At the block scale, we used evapotranspiration and vegetation greenness as remotely sensed proxies for water availability and to estimate seasonal photosynthetic activity. We used sensors on the ground to coincidentally measure surface-water availability and amphibian calling activity at individual wetlands within blocks. Responses of landscape blocks generally paralleled changes in conditions measured on the ground, but the latter were more dynamic, and changes in ecological conditions on the ground that were critical for biota were not always apparent in measurements of related parameters in blocks. Here, we evaluate the effectiveness of decisions and assumptions we made in applying the remotely sensed data for the assessment and the value of integrating observations across scales, sensors, and disciplines.

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.

Exploring Database Improvements for GPM Constellation Precipitation Retrievals

Science.gov (United States)

Ringerud, S.; Kidd, C.; Skofronick Jackson, G.

2017-12-01

The Global Precipitation Measurement Mission (GPM) offers an unprecedented opportunity for understanding and mapping of liquid and frozen precipitation on a global scale. GPM mission development of physically based retrieval algorithms, for application consistently across the constellation radiometers, relies on combined active-passive retrievals from the GPM core satellite as a transfer standard. Radiative transfer modeling is then utilized to compute a priori databases at the frequency and footprint geometry of each individual radiometer. The Goddard Profiling Algorithm (GPROF) performs constellation retrievals across the GPM databases in a Bayesian framework, constraining searches using model data on a pixel-by-pixel basis. This work explores how the retrieval might be enhanced with additional information available within the brightness temperature observations themselves. In order to better exploit available information content, model water vapor is replaced with retrieved water vapor. Rather than treating each footprint as a 1D profile alone in space, information regarding Tb variability in the horizontal is added as well as variability in the time dimension. This additional information is tested and evaluated for retrieval improvement in the context of the Bayesian retrieval scheme. Retrieval differences are presented as a function of precipitation and surface type for evaluation of where the added information proves most effective.

Inter-satellite calibration of FengYun 3 medium energy electron fluxes with POES electron measurements

Science.gov (United States)

Zhang, Yang; Ni, Binbin; Xiang, Zheng; Zhang, Xianguo; Zhang, Xiaoxin; Gu, Xudong; Fu, Song; Cao, Xing; Zou, Zhengyang

2018-05-01

We perform an L-shell dependent inter-satellite calibration of FengYun 3 medium energy electron measurements with POES measurements based on rough orbital conjunctions within 5 min × 0.1 L × 0.5 MLT. By comparing electron flux data between the U.S. Polar Orbiting Environmental Satellites (POES) and Chinese sun-synchronous satellites including FY-3B and FY-3C for a whole year of 2014, we attempt to remove less reliable data and evaluate systematic uncertainties associated with the FY-3B and FY-3C datasets, expecting to quantify the inter-satellite calibration factors for the 150-350 keV energy channel at L = 2-7. Compared to the POES data, the FY-3B and FY-3C data generally exhibit a similar trend of electron flux variations but more or less underestimate them within a factor of 5 for the medium electron energy 150-350 keV channel. Good consistency in the flux conjunctions after the inter-calibration procedures gives us certain confidence to generalize our method to calibrate electron flux measurements from various satellite instruments.

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.

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...

Global Drought Monitoring and Forecasting based on Satellite Data and Land Surface Modeling

Science.gov (United States)

Sheffield, J.; Lobell, D. B.; Wood, E. F.

2010-12-01

Monitoring drought globally is challenging because of the lack of dense in-situ hydrologic data in many regions. In particular, soil moisture measurements are absent in many regions and in real time. This is especially problematic for developing regions such as Africa where water information is arguably most needed, but virtually non-existent on the ground. With the emergence of remote sensing estimates of all components of the water cycle there is now the potential to monitor the full terrestrial water cycle from space to give global coverage and provide the basis for drought monitoring. These estimates include microwave-infrared merged precipitation retrievals, evapotranspiration based on satellite radiation, temperature and vegetation data, gravity recovery measurements of changes in water storage, microwave based retrievals of soil moisture and altimetry based estimates of lake levels and river flows. However, many challenges remain in using these data, especially due to biases in individual satellite retrieved components, their incomplete sampling in time and space, and their failure to provide budget closure in concert. A potential way forward is to use modeling to provide a framework to merge these disparate sources of information to give physically consistent and spatially and temporally continuous estimates of the water cycle and drought. Here we present results from our experimental global water cycle monitor and its African drought monitor counterpart (http://hydrology.princeton.edu/monitor). The system relies heavily on satellite data to drive the Variable Infiltration Capacity (VIC) land surface model to provide near real-time estimates of precipitation, evapotranspiraiton, soil moisture, snow pack and streamflow. Drought is defined in terms of anomalies of soil moisture and other hydrologic variables relative to a long-term (1950-2000) climatology. We present some examples of recent droughts and how they are identified by the system, including

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.)

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

Correlation between auroral kilometric radiation and inverted v electron precipitation

International Nuclear Information System (INIS)

Green, J.L.; Gurnfti, D.A.; Hoffmans, R.A.

1979-01-01

Simultaneous observations of energetic electron precipitations and auroral kilometric radiation (AKR) were obtained from the polar orbiting satellites AE-D and Hawkeye. The Hawkeye observations were restricted to periods when the satellite was in the AKR emission cone in the northern hemisphere an at radial distances > or approx. =7 R/sub E/ to avoid local propagation cutoff effects. In addition, the AE-D measurements were restricted to complete passes across the auroral oval in the evening to midnight local time sector (from 20 to 01 hours magnetic local time). This is the local time region where the most intense bursts of AKR are believed to originate. A qualitative survey of AKR and electron precipitation than with plasma sheet precipitation. Quantitatively, a good correlation is found between the AKR intensity and the peak energy of inverted V events. In addition, in the tail of the most field-aligned portion (approx.O 0 pitch angle) of the distribution functions of the inverted V events,systematic changes are indicated as the associated AKR intensity increases. When the AKR power flux is weak ( -17 W/(m 2 Hz)). From a determination of the simultaneous power in the inverted V events and the AKR bursts, the efficiency of converting the charge particle energy into EM radiation increases to a maximum of about 1% for the most intense AKR bursts. However, conversion efficiencies as low as 10 -5 % are also found. There is some evidence which suggests that the tail temperature, T in F (V) of the inverted V events, may play an important role in the efficient generation or amplification of auroral kilometric radiation

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.

Real-Time Rain Rate Evaluation via Satellite Downlink Signal Attenuation Measurement.

Science.gov (United States)

Giannetti, Filippo; Reggiannini, Ruggero; Moretti, Marco; Adirosi, Elisa; Baldini, Luca; Facheris, Luca; Antonini, Andrea; Melani, Samantha; Bacci, Giacomo; Petrolino, Antonio; Vaccaro, Attilio

2017-08-12

We present the NEFOCAST project (named by the contraction of "Nefele", which is the Italian spelling for the mythological cloud nymph Nephele, and "forecast"), funded by the Tuscany Region, about the feasibility of a system for the detection and monitoring of precipitation fields over the regional territory based on the use of a widespread network of new-generation Eutelsat "SmartLNB" (smart low-noise block converter) domestic terminals. Though primarily intended for interactive satellite services, these devices can also be used as weather sensors, as they have the capability of measuring the rain-induced attenuation incurred by the downlink signal and relaying it on an auxiliary return channel. We illustrate the NEFOCAST system architecture, consisting of the network of ground sensor terminals, the space segment, and the service center, which has the task of processing the information relayed by the terminals for generating rain field maps. We discuss a few methods that allow the conversion of a rain attenuation measurement into an instantaneous rainfall rate. Specifically, we discuss an exponential model relating the specific rain attenuation to the rainfall rate, whose coefficients were obtained from extensive experimental data. The above model permits the inferring of the rainfall rate from the total signal attenuation provided by the SmartLNB and from the link geometry knowledge. Some preliminary results obtained from a SmartLNB installed in Pisa are presented and compared with the output of a conventional tipping bucket rain gauge. It is shown that the NEFOCAST sensor is able to track the fast-varying rainfall rate accurately with no delay, as opposed to a conventional gauge.

Cloud and Thermodynamic Parameters Retrieved from Satellite Ultraspectral Infrared Measurements

Science.gov (United States)

Zhou, Daniel K.; Smith, William L.; Larar, Allen M.; Liu, Xu; Taylor, Jonathan P.; Schluessel, Peter; Strow, L. Larrabee; Mango, Stephen A.

2008-01-01

Atmospheric-thermodynamic parameters and surface properties are basic meteorological parameters for weather forecasting. A physical geophysical parameter retrieval scheme dealing with cloudy and cloud-free radiance observed with satellite ultraspectral infrared sounders has been developed and applied to the Infrared Atmospheric Sounding Interferometer (IASI) and the Atmospheric InfraRed Sounder (AIRS). The retrieved parameters presented herein are from radiance data gathered during the Joint Airborne IASI Validation Experiment (JAIVEx). JAIVEx provided intensive aircraft observations obtained from airborne Fourier Transform Spectrometer (FTS) systems, in-situ measurements, and dedicated dropsonde and radiosonde measurements for the validation of the IASI products. Here, IASI atmospheric profile retrievals are compared with those obtained from dedicated dropsondes, radiosondes, and the airborne FTS system. The IASI examples presented here demonstrate the ability to retrieve fine-scale horizontal features with high vertical resolution from satellite ultraspectral sounder radiance spectra.

Arsenic speciation in water by precipitation with APDC and EDXRF measurements

International Nuclear Information System (INIS)

Valcarcel, L.; Estevez, J.; Montero, A.; Pupo, I.

2006-01-01

A method for the determination of As (III) by precipitation with APDC and EDXRF measurements was developed. A reduction step with sodium thiosulphate is necessary in order to determine the As(V) concentration. Recoveries of As(III) and As(V) were approximately 95-96%

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.

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.

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

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

History of satellite missions and measurements of the Earth Radiation Budget (1957-1984)

Science.gov (United States)

House, F. B.; Gruber, A.; Hunt, G. E.; Mecherikunnel, A. T.

1986-01-01

The history of satellite missions and their measurements of the earth radiation budget from the beginning of the space age until the present time are reviewed. The survey emphasizes the early struggle to develop instrument systems to monitor reflected shortwave and emitted long-wave exitances from the earth, and the problems associated with the interpretation of these observations from space. In some instances, valuable data sets were developed from satellite measurements whose instruments were not specifically designed for earth radiation budget observations.

Evaluation of precipitation extremes over the Asian domain: observation and modelling studies

Science.gov (United States)

Kim, In-Won; Oh, Jaiho; Woo, Sumin; Kripalani, R. H.

2018-04-01

In this study, a comparison in the precipitation extremes as exhibited by the seven reference datasets is made to ascertain whether the inferences based on these datasets agree or they differ. These seven datasets, roughly grouped in three categories i.e. rain-gauge based (APHRODITE, CPC-UNI), satellite-based (TRMM, GPCP1DD) and reanalysis based (ERA-Interim, MERRA, and JRA55), having a common data period 1998-2007 are considered. Focus is to examine precipitation extremes in the summer monsoon rainfall over South Asia, East Asia and Southeast Asia. Measures of extreme precipitation include the percentile thresholds, frequency of extreme precipitation events and other quantities. Results reveal that the differences in displaying extremes among the datasets are small over South Asia and East Asia but large differences among the datasets are displayed over the Southeast Asian region including the maritime continent. Furthermore, precipitation data appear to be more consistent over East Asia among the seven datasets. Decadal trends in extreme precipitation are consistent with known results over South and East Asia. No trends in extreme precipitation events are exhibited over Southeast Asia. Outputs of the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulation data are categorized as high, medium and low-resolution models. The regions displaying maximum intensity of extreme precipitation appear to be dependent on model resolution. High-resolution models simulate maximum intensity of extreme precipitation over the Indian sub-continent, medium-resolution models over northeast India and South China and the low-resolution models over Bangladesh, Myanmar and Thailand. In summary, there are differences in displaying extreme precipitation statistics among the seven datasets considered here and among the 29 CMIP5 model data outputs.

Thermal Conductivity Measurements on Icy Satellite Analogs

Science.gov (United States)

Javeed, Aurya; Barmatz, Martin; Zhong, Fang; Choukroun, Mathieu

2012-01-01

With regard to planetary science, NASA aspires to: "Advance scientific knowledge of the origin and history of the solar system, the potential for life elsewhere, and the hazards and resources present as humans explore space". In pursuit of such an end, the Galileo and Cassini missions garnered spectral data of icy satellite surfaces implicative of the satellites' structure and material composition. The potential for geophysical modeling afforded by this information, coupled with the plausibility of life on icy satellites, has pushed Jupiter's Europa along with Saturn's Enceladus and Titan toward the fore of NASA's planetary focus. Understanding the evolution of, and the present processes at work on, the aforementioned satellites falls squarely in-line with NASA's cited goal.

Satellite data sets for the atmospheric radiation measurement (ARM) program

Energy Technology Data Exchange (ETDEWEB)

Shi, L.; Bernstein, R.L. [SeaSpace Corp., San Diego, CA (United States)

1996-04-01

This abstract describes the type of data obtained from satellite measurements in the Atmospheric Radiation Measurement (ARM) program. The data sets have been widely used by the ARM team to derive cloud-top altitude, cloud cover, snow and ice cover, surface temperature, water vapor, and wind, vertical profiles of temperature, and continuoous observations of weather needed to track and predict severe weather.

Use of GOES, SSM/I, TRMM Satellite Measurements Estimating Water Budget Variations in Gulf of Mexico - Caribbean Sea Basins

Science.gov (United States)

Smith, Eric A.

2004-01-01

This study presents results from a multi-satellite/multi-sensor retrieval system designed to obtain the atmospheric water budget over the open ocean. A combination of 3ourly-sampled monthly datasets derived from the GOES-8 5-channel Imager, the TRMM TMI radiometer, and the DMSP 7-channel passive microwave radiometers (SSM/I) have been acquired for the combined Gulf of Mexico-Caribbean Sea basin. Whereas the methodology has been tested over this basin, the retrieval system is designed for portability to any open-ocean region. Algorithm modules using the different datasets to retrieve individual geophysical parameters needed in the water budget equation are designed in a manner that takes advantage of the high temporal resolution of the GOES-8 measurements, as well as the physical relationships inherent to the TRMM and SSM/I passive microwave measurements in conjunction with water vapor, cloud liquid water, and rainfall. The methodology consists of retrieving the precipitation, surface evaporation, and vapor-cloud water storage terms in the atmospheric water balance equation from satellite techniques, with the water vapor advection term being obtained as the residue needed for balance. Thus, the intent is to develop a purely satellite-based method for obtaining the full set of terms in the atmospheric water budget equation without requiring in situ sounding information on the wind profile. The algorithm is validated by cross-checking all the algorithm components through multiple- algorithm retrieval intercomparisons. A further check on the validation is obtained by directly comparing water vapor transports into the targeted basin diagnosed from the satellite algorithms to those obtained observationally from a network of land-based upper air stations that nearly uniformly surround the basin, although it is fair to say that these checks are more effective m identifying problems in estimating vapor transports from a leaky operational radiosonde network than in verifying

Improving snow water equivalent simulations in an alpine basin using blended gage precipitation and snow pillow measurements

Science.gov (United States)

Sohrabi, M.; Safeeq, M.; Conklin, M. H.

2017-12-01

Snowpack is a critical freshwater reservoir that sustains ecosystem, natural habitat, hydropower, agriculture, and urban water supply in many areas around the world. Accurate estimation of basin scale snow water equivalent (SWE), through both measurement and modeling, has been significantly recognized to improve regional water resource management. Recent advances in remote data acquisition techniques have improved snow measurements but our ability to model snowpack evolution is largely hampered by poor knowledge of inherently variable high-elevation precipitation patterns. For a variety of reasons, majority of the precipitation gages are located in low and mid-elevation range and function as drivers for basin scale hydrologic modeling. Here, we blend observed gage precipitation from low and mid-elevation with point observations of SWE from high-elevation snow pillow into a physically based snow evolution model (SnowModel) to better represent the basin-scale precipitation field and improve snow simulations. To do this, we constructed two scenarios that differed in only precipitation. In WTH scenario, we forced the SnowModel using spatially distributed gage precipitation data. In WTH+SP scenario, the model was forced with spatially distributed precipitation data derived from gage precipitation along with observed precipitation from snow pillows. Since snow pillows do not directly measure precipitation, we uses positive change in SWE as a proxy for precipitation. The SnowModel was implemented at daily time step and 100 m resolution for the Kings River Basin, USA over 2000-2014. Our results show an improvement in snow simulation under WTH+SP as compared to WTH scenario, which can be attributed to better representation in high-elevation precipitation patterns under WTH+SP. The average Nash Sutcliffe efficiency over all snow pillow and course sites was substantially higher for WTH+SP (0.77) than for WTH scenario (0.47). The maximum difference in observed and simulated

California Wintertime Precipitation in Regional and Global Climate Models

Energy Technology Data Exchange (ETDEWEB)

Caldwell, P M

2009-04-27

In this paper, wintertime precipitation from a variety of observational datasets, regional climate models (RCMs), and general circulation models (GCMs) is averaged over the state of California (CA) and compared. Several averaging methodologies are considered and all are found to give similar values when model grid spacing is less than 3{sup o}. This suggests that CA is a reasonable size for regional intercomparisons using modern GCMs. Results show that reanalysis-forced RCMs tend to significantly overpredict CA precipitation. This appears to be due mainly to overprediction of extreme events; RCM precipitation frequency is generally underpredicted. Overprediction is also reflected in wintertime precipitation variability, which tends to be too high for RCMs on both daily and interannual scales. Wintertime precipitation in most (but not all) GCMs is underestimated. This is in contrast to previous studies based on global blended gauge/satellite observations which are shown here to underestimate precipitation relative to higher-resolution gauge-only datasets. Several GCMs provide reasonable daily precipitation distributions, a trait which doesn't seem tied to model resolution. GCM daily and interannual variability is generally underpredicted.

GPM GROUND VALIDATION SATELLITE SIMULATED ORBITS TWP-ICE 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...

Getting water right: A case study in water yield modelling based on precipitation data.

Science.gov (United States)

Pessacg, Natalia; Flaherty, Silvia; Brandizi, Laura; Solman, Silvina; Pascual, Miguel

2015-12-15

Water yield is a key ecosystem service in river basins and especially in dry regions around the World. In this study we carry out a modelling analysis of water yields in the Chubut River basin, located in one of the driest districts of Patagonia, Argentina. We focus on the uncertainty around precipitation data, a driver of paramount importance for water yield. The objectives of this study are to: i) explore the spatial and numeric differences among six widely used global precipitation datasets for this region, ii) test them against data from independent ground stations, and iii) explore the effects of precipitation data uncertainty on simulations of water yield. The simulations were performed using the ecosystem services model InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) with each of the six different precipitation datasets as input. Our results show marked differences among datasets for the Chubut watershed region, both in the magnitude of precipitations and their spatial arrangement. Five of the precipitation databases overestimate the precipitation over the basin by 50% or more, particularly over the more humid western range. Meanwhile, the remaining dataset (Tropical Rainfall Measuring Mission - TRMM), based on satellite measurements, adjusts well to the observed rainfall in different stations throughout the watershed and provides a better representation of the precipitation gradient characteristic of the rain shadow of the Andes. The observed differences among datasets in the representation of the rainfall gradient translate into large differences in water yield simulations. Errors in precipitation of +30% (-30%) amplify to water yield errors ranging from 50 to 150% (-45 to -60%) in some sub-basins. These results highlight the importance of assessing uncertainties in main input data when quantifying and mapping ecosystem services with biophysical models and cautions about the undisputed use of global environmental datasets. Copyright �

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.

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.

Determination of atmospheric aerosol properties over land using satellite measurements