WorldWideScience

Sample records for satellite precipitation retrieval

  1. Evaluating cloud precipitation efficiency with satellite retrievals of water isotopologues

    Science.gov (United States)

    Bailey, A.; Noone, D. C.; Wood, R.

    2015-12-01

    The efficiency with which clouds precipitate is believed to influence climate by modifying cloud lifetime and, ultimately, cloud amount. Aerosols can influence this linkage by reducing the effective radii of cloud droplets and suppressing precipitation. This relationship, however, is not unidirectional. Cloud precipitation efficiency can also regulate particle concentrations, since precipitation effectively scavenges aerosols from the atmosphere. One challenge in studying how aerosols, clouds, and precipitation processes interrelate is that observational constraints are difficult to attain. This work evaluates the ability of isotope ratios in water vapor to quantify cloud precipitation efficiency across the tropical and subtropical oceans. Theory suggests isotope ratios will record the precipitation efficiency of a convective plume, since heavier isotopologues precipitate preferentially; and a recent analysis of in situ measurements from the Mauna Loa Observatory (MLO, Hawaii, USA) verifies this to be the case. The challenge now lies in understanding whether satellite retrievals of isotope ratios in water vapor are sensitive enough to track precipitation efficiency globally. To answer this question, vertical profiles of the D/H ratio derived from NASA's Tropospheric Emission Spectrometer (TES) are first compared with the MLO in situ measurements. A qualitative match indicates the satellite retrievals can distinguish high from low precipitation efficiency convection. To expand the analysis geographically, TES profiles between 40°S and 40°N are compared with estimates of precipitation efficiency derived from the Tropical Rainfall Measuring Mission (TRMM) and ECMWF's ERA-Interim. Retrievals are binned by lower-tropospheric humidity and by vertical velocity in order to minimize large-scale thermodynamical influences. Co-located cloud retrievals provide the context necessary to evaluate the utility of these new estimates in elucidating cloud feedbacks on climate.

  2. Precipitation retrieval from satellite within EUMETSAT's H-SAF

    Science.gov (United States)

    Mugnai, A.; Dietrich, S.; Levizzani, V.; Casella, D.; Cattani, E.; di Paola, F.; Formenton, M.; Laviola, S.; Sanò, P.

    2010-09-01

    currently limited to Institutions that participate in product development and/or validation activities. The emphasis of precipitation product generation in H-SAF is on near-real-time applications, as requested by the European hydrological community and, specifically in Italy, by the Civil Protection Department (DPC) - i.e., the Italian Agency which is responsible for disaster management. DPC is a major sponsor of the Italian participation to H-SAF, with increasing involvement in product validation and impact assessment activities. We will present and discuss the basic algorithms for precipitation retrieval from satellite, that have been developed by CNR-ISAC. We will also discuss the activities that will be performed during CDOP in order to enhance and improve algorithms and processing schemes and extend them to satellites that will be operational in the 2010-2017 timeframe - with special emphasis on the GEO Meteosat Third Generation (MTG) satellite which is scheduled to be launched by EUMETSAT in 2017, and on the LEO Core Observatory of the Global Precipitation Measurement (GPM) mission which will launched by NASA and JAXA in 2013.

  3. Advances in Satellite Microwave Precipitation Retrieval Algorithms Over Land

    Science.gov (United States)

    Wang, N. Y.; You, Y.; Ferraro, R. R.

    2015-12-01

    Precipitation plays a key role in the earth's climate system, particularly in the aspect of its water and energy balance. Satellite microwave (MW) observations of precipitation provide a viable mean to achieve global measurement of precipitation with sufficient sampling density and accuracy. However, accurate precipitation information over land from satellite MW is a challenging problem. The Goddard Profiling Algorithm (GPROF) algorithm for the Global Precipitation Measurement (GPM) is built around the Bayesian formulation (Evans et al., 1995; Kummerow et al., 1996). GPROF uses the likelihood function and the prior probability distribution function to calculate the expected value of precipitation rate, given the observed brightness temperatures. It is particularly convenient to draw samples from a prior PDF from a predefined database of observations or models. GPROF algorithm does not search all database entries but only the subset thought to correspond to the actual observation. The GPM GPROF V1 database focuses on stratification by surface emissivity class, land surface temperature and total precipitable water. However, there is much uncertainty as to what is the optimal information needed to subset the database for different conditions. To this end, we conduct a database stratification study of using National Mosaic and Multi-Sensor Quantitative Precipitation Estimation, Special Sensor Microwave Imager/Sounder (SSMIS) and Advanced Technology Microwave Sounder (ATMS) and reanalysis data from Modern-Era Retrospective Analysis for Research and Applications (MERRA). Our database study (You et al., 2015) shows that environmental factors such as surface elevation, relative humidity, and storm vertical structure and height, and ice thickness can help in stratifying a single large database to smaller and more homogeneous subsets, in which the surface condition and precipitation vertical profiles are similar. It is found that the probability of detection (POD) increases

  4. Heavy precipitation retrieval from combined satellite observations and ground-based lightning measurements

    Science.gov (United States)

    Mugnai, A.; Dietrich, S.; Casella, D.; di Paola, F.; Formenton, M.; Sanò, P.

    2010-09-01

    We have developed a series of algorithms for the retrieval of precipitation (especially, heavy precipitation) over the Mediterranean area using satellite observations from the available microwave (MW) radiometers onboard low Earth orbit (LEO) satellites and from the visible-infrared (VIS-IR) SEVIRI radiometer onboard the European geosynchronous (GEO) satellite Meteosat Second Generation (MSG), in conjunction with lightning data from ground-based networks - such as ZEUS and LINET. These are: • A new approach for precipitation retrieval from space (which we call the Cloud Dynamics and Radiation Database approach, CDRD) that incorporates lightning and environmental/dynamical information in addition to the upwelling microwave brightness temperatures (TB’s) so as to reduce the retrieval uncertainty and improve the retrieval performance; • A new combined MW-IR technique for producing frequent precipitation retrievals from space (which we call PM-GCD technique), that uses passive-microwave (PM) retrievals in conjunction with lightning information and the Global Convection Detection (GCD) technique to discriminate deep convective clouds within the GEO observations; • A new morphing approach (which we call the Lightning-based Precipitation Evolving Technique, L-PET) that uses the available lightning measurements for propagating the rainfall estimates from satellite-borne MW radiometers to a much higher time resolution than the MW observations. We will present and discuss our combined MW/IR/lightning precipitation algorithms and analyses with special reference to some case studies over the western Mediterranean.

  5. Satellite cloud and precipitation property retrievals for climate monitoring and hydrological applications

    Science.gov (United States)

    Wolters, E. L. A.

    2012-03-01

    This thesis presents the retrieval, evaluation, and application of cloud physical property datasets (cloud phase, cloud particle effective radius, and precipitation occurrence and intensity) obtained from Spinning Enhanced Visible and Infrared Imager (SEVIRI) reflectance measurements using the Cloud Physical Properties (CPP) retrieval algorithm. In Chapter 3 it is shown that the CPP cloud-phase retrieval algorithm has sufficient accuracy (West Africa. During the afternoon, precipitation occurrence frequency over dry soils becomes significantly higher than over wet soils, whereas for precipitation intensity no significant difference is discerned. The study demonstrates that the combination of satellite-based soil moisture and precipitation observations can be helpful in improving the understanding of the land surface-precipitation interaction over tropical areas. The thesis concludes with a number of recommendations on future algorithm improvements and potential research applications. For both cloud phase and precipitation properties, extension of the algorithm to include nighttime observations would be desirable to enable detailed studies on the full diurnal cycle. Further, the SEVIRI High-Resolution Visible (HRV) channel could be incorporated to correct retrieved cloud physical properties for broken and inhomogeneous cloud cases. Finally, the accurate cloud phase and precipitation datasets combined with the high SEVIRI spatial and temporal sampling resolution enables possibilities for detailed research on climate monitoring, nowcasting applications, evaluation of cloud schemes in climate models, studies on land surface-precipitation interactions (with a special focus on the diurnal cycle), and assimilation of the datasets in weather and climate models

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

    Directory of Open Access Journals (Sweden)

    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

  7. Microwave retrievals of terrestrial precipitation over snow-covered surfaces: A lesson from the GPM satellite

    Science.gov (United States)

    Ebtehaj, A. M.; Kummerow, C. D.

    2017-06-01

    Satellites are playing an ever-increasing role in estimating precipitation over remote areas. Improving satellite retrievals of precipitation requires increased understanding of its passive microwave signatures over different land surfaces. Snow-covered surfaces are notoriously difficult to interpret because they exhibit both emission from the land below and scattering from the ice crystals. Using data from the Global Precipitation Measurement (GPM) satellite, we demonstrate that microwave brightness temperatures of rain and snowfall transition from a scattering to an emission regime from summer to winter, due to expansion of less emissive snow cover. Evidence suggests 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 results demonstrate that, using a multifrequency matching method, the probability of snowfall detection can even be higher than rainfall—chiefly because of the information content of the low-frequency channels that respond to the (near) surface temperature.

  8. PM-GCD - a combined IR-MW satellite technique for frequent retrieval of heavy precipitation

    Science.gov (United States)

    Casella, D.; Dietrich, S.; di Paola, F.; Formenton, M.; Mugnai, A.; Porcù, F.; Sanò, P.

    2012-01-01

    Precipitation retrievals based on measurements from microwave (MW) radiometers onboard low-Earth-orbit (LEO) satellites can reach high level of accuracy - especially regarding convective precipitation. At the present stage though, these observations cannot provide satisfactory coverage of the evolution of intense and rapid precipitating systems. As a result, the obtained precipitation retrievals are often of limited use for many important applications - especially in supporting authorities for flood alerts and weather warnings. To tackle this problem, over the past two decades several techniques have been developed combining accurate MW estimates with frequent infrared (IR) observations from geosynchronous (GEO) satellites, such as the European Meteosat Second Generation (MSG). In this framework, we have developed a new fast and simple precipitation retrieval technique which we call Passive Microwave - Global Convective Diagnostic, (PM-GCD). This method uses MW retrievals in conjunction with the Global Convective Diagnostic (GCD) technique which discriminates deep convective clouds based on the difference between the MSG water vapor (6.2 μm) and thermal-IR (10.8 μm) channels. Specifically, MSG observations and the GCD technique are used to identify deep convective areas. These areas are then calibrated using MW precipitation estimates based on observations from the Advanced Microwave Sounding Unit (AMSU) radiometers onboard operational NOAA and Eumetsat satellites, and then finally propagated in time with a simple tracking algorithm. In this paper, we describe the PM-GCD technique, analyzing its results for a case study that refers to a flood event that struck the island of Sicily in southern Italy on 1-2 October 2009.

  9. Object-based Evaluation of Satellite Precipitation Retrievals: A Case Study of the Summer Season over CONUS

    Science.gov (United States)

    Li, J.; Xu, P.

    2015-12-01

    Satellite precipitation retrievals that have high spatial and temporal resolutions are suitable for various applications, such as hydrologic modeling and watershed management. Many validation studies have been established to understand the strengths and limitations of these satellite precipitation retrievals. In this study, an object-based validation approach is adopted to evaluate several satellite precipitation retrievals focusing on the spatial and geometric patterns of precipitation. This object-based validation approach identifies precipitation objects using an image processing technique referred to as watershed transform. Several object attributes are diagnosed and analyzed based on the distance measurement. Three object-based verification scores are summarized to determine the overall performances of satellite precipitation retrievals. The Integrated Multi-satellitE Retrievals for GPM (IMERG) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) were evaluated using the object-based approach. The NOAA stage IV MPE multi-sensor composite rain analysis was utilized as the ground observations. The comparative assessments were conducted at 0.25° by 0.25° on a daily scale in the summer season of 2014 over the continental United States (CONUS). The results suggest that IMERG possesses the similar spatial pattern of local-scale precipitation areas against stage IV observations. In addition, IMERG depicts the sizes and locations of precipitation areas more accurately against stage IV.

  10. Early assessment of Integrated Multi-satellite Retrievals for Global Precipitation Measurement over China

    Science.gov (United States)

    Guo, Hao; Chen, Sheng; Bao, Anming; Behrangi, Ali; Hong, Yang; Ndayisaba, Felix; Hu, Junjun; Stepanian, Phillip M.

    2016-07-01

    Two post-real time precipitation products from the Integrated Multi-satellite Retrievals for Global Precipitation Measurement Mission (IMERG) are systematically evaluated over China with China daily Precipitation Analysis Product (CPAP) as reference. The IMERG products include the gauge-corrected IMERG product (IMERG_Cal) and the version of IMERG without direct gauge correction (IMERG_Uncal). The post-research TRMM Multisatellite Precipitation Analysis version 7 (TMPA-3B42V7) is also evaluated concurrently with IMERG for better perspective. In order to be consistent with CPAP, the evaluation and comparison of selected products are performed at 0.25° and daily resolutions from 12 March 2014 through 28 February 2015. The results show that: Both IMERG and 3B42V7 show similar performances. Compared to IMERG_Uncal, IMERG_Cal shows significant improvement in overall and conditional bias and in the correlation coefficient. Both IMERG_Cal and IMERG_Uncal perform relatively poor in winter and over-detect slight precipitation events in northwestern China. As an early validation of the GPM-era IMERG products that inherit the TRMM-era global satellite precipitation products, these findings will provide useful feedbacks and insights for algorithm developers and data users over China and beyond.

  11. Bayesian Estimation of Precipitation from Satellite Passive Microwave Observations Using Combined Radar-Radiometer Retrievals

    Science.gov (United States)

    Grecu, Mircea; Olson, William S.

    2006-01-01

    Precipitation estimation from satellite passive microwave radiometer observations is a problem that does not have a unique solution that is insensitive to errors in the input data. Traditionally, to make this problem well posed, a priori information derived from physical models or independent, high-quality observations is incorporated into the solution. In the present study, a database of precipitation profiles and associated brightness temperatures is constructed to serve as a priori information in a passive microwave radiometer algorithm. The precipitation profiles are derived from a Tropical Rainfall Measuring Mission (TRMM) combined radar radiometer algorithm, and the brightness temperatures are TRMM Microwave Imager (TMI) observed. Because the observed brightness temperatures are consistent with those derived from a radiative transfer model embedded in the combined algorithm, the precipitation brightness temperature database is considered to be physically consistent. The database examined here is derived from the analysis of a month-long record of TRMM data that yields more than a million profiles of precipitation and associated brightness temperatures. These profiles are clustered into a tractable number of classes based on the local sea surface temperature, a radiometer-based estimate of the echo-top height (the height beyond which the reflectivity drops below 17 dBZ), and brightness temperature principal components. For each class, the mean precipitation profile, brightness temperature principal components, and probability of occurrence are determined. The precipitation brightness temperature database supports a radiometer-only algorithm that incorporates a Bayesian estimation methodology. In the Bayesian framework, precipitation estimates are weighted averages of the mean precipitation values corresponding to the classes in the database, with the weights being determined according to the similarity between the observed brightness temperature principal

  12. Satellite cloud and precipitation property retrievals for climate monitoring and hydrological applications

    NARCIS (Netherlands)

    Wolters, E.L.A.

    2012-01-01

    This thesis presents the retrieval, evaluation, and application of cloud physical property datasets (cloud phase, cloud particle effective radius, and precipitation occurrence and intensity) obtained from Spinning Enhanced Visible and Infrared Imager (SEVIRI) reflectance measurements using the Cloud

  13. PM-GCD – a combined IR–MW satellite technique for frequent retrieval of heavy precipitation

    Directory of Open Access Journals (Sweden)

    D. Casella

    2012-01-01

    Full Text Available Precipitation retrievals based on measurements from microwave (MW radiometers onboard low-Earth-orbit (LEO satellites can reach high level of accuracy – especially regarding convective precipitation. At the present stage though, these observations cannot provide satisfactory coverage of the evolution of intense and rapid precipitating systems. As a result, the obtained precipitation retrievals are often of limited use for many important applications – especially in supporting authorities for flood alerts and weather warnings. To tackle this problem, over the past two decades several techniques have been developed combining accurate MW estimates with frequent infrared (IR observations from geosynchronous (GEO satellites, such as the European Meteosat Second Generation (MSG. In this framework, we have developed a new fast and simple precipitation retrieval technique which we call Passive Microwave – Global Convective Diagnostic, (PM-GCD. This method uses MW retrievals in conjunction with the Global Convective Diagnostic (GCD technique which discriminates deep convective clouds based on the difference between the MSG water vapor (6.2 μm and thermal-IR (10.8 μm channels. Specifically, MSG observations and the GCD technique are used to identify deep convective areas. These areas are then calibrated using MW precipitation estimates based on observations from the Advanced Microwave Sounding Unit (AMSU radiometers onboard operational NOAA and Eumetsat satellites, and then finally propagated in time with a simple tracking algorithm. In this paper, we describe the PM-GCD technique, analyzing its results for a case study that refers to a flood event that struck the island of Sicily in southern Italy on 1–2 October 2009.

  14. A novel approach to validate satellite soil moisture retrievals using precipitation data

    Science.gov (United States)

    Karthikeyan, L.; Kumar, D. Nagesh

    2016-10-01

    A novel approach is proposed that attempts to validate passive microwave soil moisture retrievals using precipitation data (applied over India). It is based on the concept that the expectation of precipitation conditioned on soil moisture follows a sigmoidal convex-concave-shaped curve, the characteristic of which was recently shown to be represented by mutual information estimated between soil moisture and precipitation. On this basis, with an emphasis over distribution-free nonparametric computations, a new measure called Copula-Kernel Density Estimator based Mutual Information (CKDEMI) is introduced. The validation approach is generic in nature and utilizes CKDEMI in tandem with a couple of proposed bootstrap strategies, to check accuracy of any two soil moisture products (here Advanced Microwave Scanning Radiometer-EOS sensor's Vrije Universiteit Amsterdam-NASA (VUAN) and University of Montana (MONT) products) using precipitation (India Meteorological Department) data. The proposed technique yields a "best choice soil moisture product" map which contains locations where any one of the two/none of the two/both the products have produced accurate retrievals. The results indicated that in general, VUA-NASA product has performed well over University of Montana's product for India. The best choice soil moisture map is then integrated with land use land cover and elevation information using a novel probability density function-based procedure to gain insight on conditions under which each of the products has performed well. Finally, the impact of using a different precipitation (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources) data set over the best choice soil moisture product map is also analyzed. The proposed methodology assists researchers and practitioners in selecting the appropriate soil moisture product for various assimilation strategies at both basin and continental scales.

  15. PM-GCD - A combined IR-MW satellite technique for frequent retrieval of heavy precipitation: Application to the EU FLASH project

    Science.gov (United States)

    Casella, Daniele; Dietrich, Stefano; di Paola, Francesco; Formenton, Marco; Mugnai, Alberto; Sanò, Paolo

    2010-05-01

    Precipitation retrievals based on measurements from microwave (MW) radiometers onboard low-Earth-orbit (LEO) satellites can reach a high level of accuracy - and especially so, for deep convective precipitating systems. However, these observations do not provide a satisfactorily coverage of the rapid evolution of intense precipitating systems. As a result, the obtained precipitation retrievals are often of limited use for many important applications -- including support to authorities in activating flood alarms. To avoid this problem, several techniques have been developed that combine accurate MW estimates with frequent infrared (IR) observations from geosynchronous (GEO) satellites, such as the European Meteosat Second Generation (MSG). Within the European Union FP6 FLASH project, we have developed a new combined MW-IR technique for producing frequent precipitation retrievals from space (which we call PM-GCD technique). This technique uses passive-microwave (PM) retrievals in conjunction with the Global Convection Detection (GCD) technique that discriminates deep convective clouds within the GEO observations, based on the difference between the water vapor (6.2 μm ) and thermal-IR (10.8 μm ) channels. In essence, within the PM-GCD technique, deep convective areas are defined from MSG observations, then calibrated using MW-AMSU precipitation retrievals and finally propagated over time with a simple tracking algorithm. In this paper, we describe the PM-GCD technique and discuss the results of its application to a flood event that occurred on September 12-15, 2006 over the north-western Mediterranean coastal areas, and that has been selected for joint research by the EU FLASH and HYDRATE projects.

  16. A feasibility study for the retrieval of the total column precipitable water vapor from satellite observations in the blue spectral range

    Directory of Open Access Journals (Sweden)

    T. Wagner

    2013-04-01

    Full Text Available We present a new algorithm for satellite retrievals of the atmospheric water vapor column in the blue spectral range. The water vapor absorption cross section in the blue spectral range is much weaker than in the red spectral range. Thus the detection limit and the uncertainty of individual observations is systematically larger than for retrievals at longer wavelengths. Nevertheless, water vapor retrievals in the blue spectral range have also several advantages: since the surface albedo in the blue spectral range is similar over land and ocean, water vapor retrievals are more consistent than for longer wavelengths. Compared to retrievals at longer wavelengths, over ocean the sensitivity for atmospheric layers close to the surface is higher due to the (typically 2 to 3 times higher ocean albedo in the blue. Water vapor retrievals in the blue spectral range are also possible for satellite sensors, which do not measure at longer wavelengths of the visible spectral range like the Ozone Monitoring instrument (OMI. We investigated details of the water vapor retrieval in the blue spectral range based on radiative transfer simulations and observations from the Global Ozone Monitoring Experiment 2 (GOME-2 and OMI. It is demonstrated that it is possible to retrieve the atmospheric water vapor column density in the blue spectral range over most parts of the globe. The findings of our study are of importance also for future satellite missions like e.g. Sentinel 4 and 5.

  17. A feasibility study for the retrieval of the total column precipitable water vapour from satellite observations in the blue spectral range

    Directory of Open Access Journals (Sweden)

    T. Wagner

    2013-10-01

    Full Text Available We present a new algorithm for satellite retrievals of the atmospheric water vapour column in the blue spectral range. The water vapour absorption cross section in the blue spectral range is much weaker than in the red spectral range. Thus the detection limit and the uncertainty of individual observations are systematically larger than for retrievals at longer wavelengths. Nevertheless, water vapour retrievals in the blue spectral range have also several advantages: since the surface albedo in the blue spectral range is similar over land and ocean, water vapour retrievals are more consistent than for longer wavelengths. Compared to retrievals at longer wavelengths, the sensitivity for atmospheric layers close to the surface is higher due to the (typically 2 to 3 times higher ocean albedo in the blue. Water vapour retrievals in the blue spectral range are also possible for satellite sensors, which do not measure at longer wavelengths of the visible spectral range like the Ozone Monitoring Instrument (OMI. We investigated details of the water vapour retrieval in the blue spectral range based on radiative transfer simulations and observations from the Global Ozone Monitoring Experiment 2 (GOME-2 and OMI. It is demonstrated that it is possible to retrieve the atmospheric water vapour column density in the blue spectral range over most parts of the globe. The findings of our study are of importance also for future satellite missions (e.g. Sentinel 4 and 5.

  18. 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

  19. Using precipitation, vertical root distribution, and satellite-retrieved vegetation information to parameterize water stress in a Penman-Monteith approach to evapotranspiration modeling under Mediterranean climate

    Science.gov (United States)

    Bai, Yun; Zhang, Jiahua; Zhang, Sha; Koju, Upama Ashish; Yao, Fengmei; Igbawua, Tertsea

    2017-03-01

    Recent studies have shown that global Penman-Monteith equation based (PM-based) models poorly simulate water stress when estimating evapotranspiration (ET) in areas having a Mediterranean climate (AMC). In this study, we propose a novel approach using precipitation, vertical root distribution (VRD), and satellite-retrieved vegetation information to simulate water stress in a PM-based model (RS-WBPM) to address this issue. A multilayer water balance module is employed to simulate the soil water stress factor (SWSF) of multiple soil layers at different depths. The water stress factor (WSF) for surface evapotranspiration is determined by VRD information and SWSF in each layer. Additionally, four older PM-based models (PMOV) are evaluated at 27 flux sites in AMC. Results show that PMOV fails to estimate the magnitude or capture the variation of ET in summer at most sites, whereas RS-WBPM is successful. The daily ET resulting from RS-WBPM incorporating recommended VI (NDVI for shrub and EVI for other biomes) agrees well with observations, with R2=0.60 (RMSE = 18.72 W m-2) for all 27 sites and R2=0.62 (RMSE = 18.21 W m-2) for 25 nonagricultural sites. However, combined results from the optimum older PM-based models at specific sites show R2 values of only 0.50 (RMSE = 20.74 W m-2) for all 27 sites. RS-WBPM is also found to outperform other ET models that also incorporate a soil water balance module. As all inputs of RS-WBPM are globally available, the results from RS-WBPM are encouraging and imply the potential of its implementation on a regional and global scale.

  20. 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

  1. On the potential of sub-mm passive MW observations from geostationary satellites to retrieve heavy precipitation over the Mediterranean Area

    Directory of Open Access Journals (Sweden)

    S. Pinori

    2006-01-01

    Full Text Available The general interest in the potential use of the mm and sub-mm frequencies up to 425 GHz resolution from geostationary orbit is increasing due to the fact that the frequent time sampling and the comparable spatial resolution relative to the "classical" (≤89 GHz microwave frequencies would allow the monitoring of precipitating intense events for the assimilation of rain in now-casting weather prediction models. In this paper, we use the simulation of a heavy precipitating event in front of the coast of Crete island (Greece performed by the University of Wisconsin - Non-hydrostatic Modeling System (UW-NMS cloud resolving model in conjunction with a 3D-adjusted plane parallel radiative transfer model to simulate the upwelling brightness temperatures (TB's at mm and sub-mm frequencies. To study the potential use of high frequencies, we first analyze the relationships of the simulated TB's with the microphysical properties of the UW-NMS simulated precipitating clouds, and then explore the capability of a Bayesian algorithm for the retrieval of surface rain rate, rain and ice water paths at such frequencies.

  2. Cross-track sensor precipitation retrievals for the Global Precipitation Measurement mission

    Science.gov (United States)

    Kidd, Chris; Randel, David; Stocker, Erich; Kummerow, Christian

    2014-05-01

    The utilization of observations from passive microwave cross-track, or sounders, for global precipitation estimation provides a number of distinct advantages including the potential to retrieve precipitation over cold surface backgrounds and improvements in temporal sampling. As part of the Global Precipitation Measurement (GPM) mission, observations from these cross-track instruments are being incorporated into the overall retrieval framework to enable better temporal and spatial sampling, particularly over regions where surface conditions provide a challenging background against which to observe precipitation. GPM is an international satellite mission and brings together a number of different component satellites and sensors, each contributing observations capable of providing information on precipitation. The joint US-Japan core observatory was launched in early 2014 and carries the GPM Microwave Imager (GMI) and the Dual-frequency Precipitation Radar (DPR). The core observatory serves as a standard against which other sensors in the constellation are calibrated, providing a consistent observational dataset to ensure the highest quality precipitation retrievals to be made. The conically-scanning GMI provides observations from 10.65 GHz through to 166 GHz with dual polarization capabilities, and two 183 GHz channels (+-1 and +-3 GHz) with vertical polarization. The highest frequencies provide resolutions in the order of 4.4x7.3 km. 885 km swath width. The DPR operates at 35.5 GHz and 13.6 GHz with swath widths 120 and 245 km respectively, and a vertical resolution of 250 m. The higher frequency radar will provide a sensitivity down to 12 dBZ, or about 0.2 mmh-1 equivalent rainrate, particularly useful for higher latitudes where light precipitation dominates. Integration of the cross-track sensors into the overall retrieval scheme of the GPM mission is achieved through the GPROF retrieval scheme, utilizing databases based upon observational and modelled data sets

  3. Developing the Integrated Multi-Satellite Retrievals for GPM (IMERG)

    Science.gov (United States)

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

    2012-04-01

    The Integrated Multi-satellitE Retrievals for GPM (IMERG) will provide the Day-1 algorithm for computing combined precipitation estimates as part of GPM. The focus is assembling the best time series of (nearly) global precipitation from the international constellation of precipitation-relevant satellites and global surface precipitation gauge analyses. It is planned that the time series will encompass both the TRMM and GPM eras, and that the coverage will be extended to fully global as algorithms are developed that provide skill in the difficult high-latitude environment. IMERG is being developed as a unified U.S. algorithm that takes advantage of strengths in the three groups that are contributing expertise: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA), which addresses inter-satellite calibration of precipitation estimates and monthly scale combination of satellite and gauge analyses; 2) the CPC Morphing algorithm with Kalman Filtering (K-CMORPH), which provides quality-weighted time interpolation of precipitation patterns following storm motion; and 3) 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. In this talk we summarize the code-level integration on which IMERG is based, including the important issues that drive the design and implementation, plans for testing and starting to run the system, and current status. One concept being pioneered by the IMERG team is that combination datasets should be computed multiple times at different latencies to serve the needs of different groups of users. Although reprocessing all of the latency "runs" complicates the reprocessing scenario, experience demonstrates that it is essential for the users. Fortunately, the IMERG team has worked with the

  4. Integrated Hydrologic Validation to Improve Physical Precipitation Retrievals for GPM

    Science.gov (United States)

    Peters-Lidard, C. D.; Harrison, K. W.; Tian, Y.; Kumar, S.

    2011-12-01

    One of the five scientific objectives for GPM is to "Improve hydrological modeling and prediction", including advancing prediction skill for high-impact hazards such as floods, droughts, landslides and landfalling hurricanes. Given the focus on land hydrology, and the range of hydrologic regimes targeted by GPM, it follows that a hydrologically-oriented ground validation program that covers these regimes from both the physical retrieval and the hydrological prediction perspectives is required for the successful application of GPM to land hydrology. In order to investigate the robustness of both hydrologic model predictions and physical precipitation retrievals, this talk will present recent evaluations of skill in land surface hydrologic models forced with TRMM-era multisensor products, with and without land data assimilation. In addition to LSM skill, we will also demonstrate how physical precipitation retrievals can be supported by land surface emissivity and temperature estimates obtained by coupling microwave emission models (e.g., the Joint Center for Satellite Data Assimilation Community Radiative Transfer Model CRTM and the European Center for Medium-Range Weather Forecasting's Community Microwave Emission Model CMEM) to the land surface models in the Land Information System (LIS; http://lis.gsfc.nasa.gov). Evaluation at multiple frequencies, with and without land data assimilation, demonstrates the critical impact of certain real-time ancillary data (e.g., snow cover) on the microwave background states required for physical retrievals.

  5. Monitoring Snow Using Geostationary Satellite Retrievals During the SAAWSO Project

    Science.gov (United States)

    Rabin, Robert M.; Gultepe, Ismail; Kuligowski, Robert J.; Heidinger, Andrew K.

    2016-09-01

    The SAAWSO (Satellite Applications for Arctic Weather and SAR (Search And Rescue) Operations) field programs were conducted by Environment Canada near St. Johns, NL and Goose Bay, NL in the winters of 2012-13 and 2013-14, respectively. The goals of these programs were to validate satellite-based nowcasting products, including snow amount, wind intensity, and cloud physical parameters (e.g., cloud cover), over northern latitudes with potential applications to Search And Rescue (SAR) operations. Ground-based in situ sensors and remote sensing platforms were used to measure microphysical properties of precipitation, clouds and fog, radiation, temperature, moisture and wind profiles. Multi-spectral infrared observations obtained from Geostationary Operational Environmental Satellite (GOES)-13 provided estimates of cloud top temperature and height, phase (water, ice), hydrometer size, extinction, optical depth, and horizontal wind patterns at 15 min intervals. In this work, a technique developed for identifying clouds capable of producing high snowfall rates and incorporating wind information from the satellite observations is described. The cloud top physical properties retrieved from operational satellite observations are validated using measurements obtained from the ground-based in situ and remote sensing platforms collected during two precipitation events: a blizzard heavy snow storm case and a moderate snow event. The retrieved snow precipitation rates are found to be comparable to those of ground-based platform measurements in the heavy snow event.

  6. Shrunken Locally Linear Embedding for Passive Microwave Retrieval of Precipitation

    CERN Document Server

    Ebtehaj, Ardeshir Mohammad; Foufoula-Georgiou, Efi

    2014-01-01

    This paper introduces a new approach to the inverse problem of passive microwave rainfall retrieval. The proposed methodology relies on modern supervised manifold learning and regularization paradigms, which makes use of two joint dictionaries of coincidental rainfall profiles and their upwelling spectral radiative fluxes. A sequential detection-estimation strategy is adopted which relies on a geometrical perception that similar rainfall intensity values and their spectral radiances lie on or live close to some sufficiently smooth manifolds with analogous geometrical structure. The detection step employs of a nearest neighborhood classification rule, while the estimation scheme is equipped with a constrained shrinkage estimator to ensure sufficiently stable retrieval and some physical consistency. The algorithm is examined using coincidental observations of the active precipitation radar (PR) and passive microwave imager (TMI) on board the Tropical Rainfall Measuring Mission (TRMM) satellite. We present impro...

  7. Regional Bias of Satellite Precipitation Estimates

    Science.gov (United States)

    Modrick, T. M.; Georgakakos, K. P.; Spencer, C. R.

    2012-12-01

    Satellite-based estimates of precipitation have improved the spatial availability of precipitation data particularly for regions with limited gauge networks due to limited accessibility or infrastructure. Understanding the quality and reliability of satellite precipitation estimates is important, especially when the estimates are utilitized for real-time hydrologic forecasting and for fast-responding phenomena. In partnership with the World Meteorological Organization (WMO), the U.S. Agency of International Development (USAID) and the National Ocean and Atmospheric Administration (NOAA), the Hydrologic Research Center has begun implementation of real-time flash flood warning systems for diverse regions around the world. As part of this effort, bias characteristics of satellite precipitation have been examined in these various regions, such includes portions of Southeastern Asia, Southeastern Europe, the Middle East, Central America, and the southern half of the African continent. The work has focused on the Global Hydro-Estimator (GHE) precipitation product from NOAA/NESDIS. These real-time systems utilize the GHE given low latency times of this product. This presentation focuses on the characterization of precipitation bias as compared to in-situ gauge records, and the regional variations or similarities. Additional analysis is currently underway considering regional bias for other satellite precipitation products (e.g., CMORPH) for comparison with the GHE results.

  8. A Method for Combined Passive-Active Microwave Retrievals of Cloud and Precipitation Profiles.

    Science.gov (United States)

    Olson, William S.; Kummerow, Christian D.; Heymsfield, Gerald M.; Giglio, Louis

    1996-10-01

    Three-dimensional tropical squall-line simulations from the Goddard cumulus ensemble (GCE) model are used as input to radiative computations of upwelling microwave brightness temperatures and radar reflectivities at selected microwave sensor frequencies. These cloud/radiative calculations form the basis of a physical cloud/precipitation profile retrieval method that yields estimates of the expected values of the hydrometeor water contents. Application of the retrieval method to simulated nadir-view observations of the aircraft-borne Advanced Microwave Precipitation Radiometer (AMPR) and NASA ER-2 Doppler radar (EDOP) produce random errors of 23%, 19%, and 53% in instantaneous estimates of integrated precipitating liquid, integrated precipitating ice, and surface rain rate, respectively.On 5 October 1993, during the Convection and Atmospheric Moisture Experiment (CAMEX), the AMPR and EDOP were used to observe convective systems in the vicinity of the Florida peninsula. Although the AMPR data alone could be used to retrieve cloud and precipitation vertical profiles over the ocean, retrievals of high-resolution vertical precipitation structure and profile information over land required the combination of AMPR and EDOP observations.No validation data are available for this study; however, the retrieved precipitation distributions from the convective systems are compatible with limited radar climatologies of such systems, as well as being radiometrically consistent with both the AMPR and EDOP observations. In the future, the retrieval method will be adapted to the passive and active microwave measurements from the Tropical Rainfall Measuring Mission (TRMM) satellite sensors.

  9. A global satellite-assisted precipitation climatology

    Science.gov (United States)

    Funk, C.; Verdin, A.; Michaelsen, J.; Peterson, P.; Pedreros, D.; Husak, G.

    2015-10-01

    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

  10. A global satellite assisted precipitation climatology

    Directory of Open Access Journals (Sweden)

    C. Funk

    2015-05-01

    Full Text Available 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

  11. A global satellite assisted precipitation climatology

    Science.gov (United States)

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

    2015-01-01

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

  12. 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.

  13. 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.

    2016-09-01

    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 ˜100 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.

  14. System refinement for content based satellite image retrieval

    Directory of Open Access Journals (Sweden)

    NourElDin Laban

    2012-06-01

    Full Text Available We are witnessing a large increase in satellite generated data especially in the form of images. Hence intelligent processing of the huge amount of data received by dozens of earth observing satellites, with specific satellite image oriented approaches, presents itself as a pressing need. Content based satellite image retrieval (CBSIR approaches have mainly been driven so far by approaches dealing with traditional images. In this paper we introduce a novel approach that refines image retrieval process using the unique properties to satellite images. Our approach uses a Query by polygon (QBP paradigm for the content of interest instead of using the more conventional rectangular query by image approach. First, we extract features from the satellite images using multiple tiling sizes. Accordingly the system uses these multilevel features within a multilevel retrieval system that refines the retrieval process. Our multilevel refinement approach has been experimentally validated against the conventional one yielding enhanced precision and recall rates.

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

    Directory of Open Access Journals (Sweden)

    Yiwen Mei

    2016-03-01

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

  16. CHINA RETRIEVES 19th RECOVERABLE SATELLITE

    Institute of Scientific and Technical Information of China (English)

    2004-01-01

    China on Sept.25 recovered its 19th recoverable sci-tech experimental satellite 27 days after the satellite orbited in space. The satellite, which was launched on Aug.29 from the Jiuquan Satellite Launch Center in Gansu Province, northwest China, touched the ground at 7:55 a.m.on Sept.25. The satellite, atop a Long March 2C carrier rocket, is mainly for

  17. Global Precipitation Measurement (GPM) Microwave Imager Falling Snow Retrieval Algorithm Performance

    Science.gov (United States)

    Skofronick Jackson, Gail; Munchak, Stephen J.; Johnson, Benjamin T.

    2015-04-01

    Retrievals of falling snow from space represent an important data set for understanding the Earth's atmospheric, hydrological, and energy cycles. 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 and uncertainties remaining. This work reports on the development and post-launch testing of retrieval algorithms for the NASA Global Precipitation Measurement (GPM) mission Core Observatory satellite launched in February 2014. In particular, we will report on GPM Microwave Imager (GMI) radiometer instrument algorithm performance with respect to falling snow detection and estimation. Since GPM's launch, the at-launch GMI precipitation algorithms, based on a Bayesian framework, have been used with the new GPM data. The at-launch database is generated using proxy satellite data merged with surface measurements (instead of models). One year after launch, the Bayesian database will begin to be replaced with the more realistic observational data from the GPM spacecraft radar retrievals and GMI data. It is expected that the observational database will be much more accurate for falling snow retrievals because that database will take full advantage of the 166 and 183 GHz snow-sensitive channels. Furthermore, much retrieval algorithm work has been done to improve GPM retrievals over land. The Bayesian framework for GMI retrievals is dependent on the a priori database used in the algorithm and how profiles are selected from that database. Thus, a land classification sorts land surfaces into ~15 different categories for surface-specific databases (radiometer brightness temperatures are quite dependent on surface characteristics). In addition, our work has shown that knowing if the land surface is snow-covered, or not, can improve the performance of the algorithm. Improvements were made to the algorithm that allow for daily inputs of ancillary snow cover

  18. Satellite derived precipitation and freshwater flux variability and its dependence on the North Atlantic Oscillation

    Science.gov (United States)

    Andersson, Axel; Bakan, Stephan; Graßl, Hartmut

    2010-08-01

    The variability of satellite retrieved precipitation and freshwater flux from the `Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data' (HOAPS) is assessed with special emphasis on the `North Atlantic Oscillation' (NAO). To cover also land areas, a novel combination of the satellite derived precipitation climatology with the rain gauge based `Full Data Reanalysis Product Version 4', of the `Global Precipitation Climatology Centre' (GPCC) is used. This yields unique high-resolution, quasi-global precipitation fields compiled from two independent data sources. Over the ocean, the response of the freshwater balance and the related parameters to the NAO is investigated for the first time by using a purely satellite based data set. A strong dependence of precipitation patterns to the state of the NAO is found. On synoptic scale this is in accordance with earlier findings by other satellite based and reanalysis products. Furthermore, the consistency of the combined HOAPS-3/GPCC data set allows also detailed regional analyses of precipitation patterns. The response of HOAPS-3 freshwater flux to the NAO is dominated by precipitation at mid and high latitudes, while for the subtropical regions the feedback of the evaporation is stronger.

  19. Continued development of a global precipitation dataset from satellite and ground-based gauges

    Science.gov (United States)

    Dietzsch, Felix; Andersson, Axel; Schröder, Marc; Ziese, Markus; Becker, Andreas

    2017-04-01

    The project framework MiKlip ("Mittelfristige Klimaprognosen") is focused on the development of an operational forecast system for decadal climate predictions. The objective of the "Daily Precipitation Analysis for the validation of Global medium-range Climate predictions Operationalized" (DAPAGLOCO) project, is the development and operationalization of a global precipitation dataset for forecast validation of the MPI-ESM experiments used in MiKlip. The dataset is a combination of rain gauge measurement data over land and satellite-based precipitation retrievals over ocean. Over land, gauge data from the Global Precipitation Climatology Centre (GPCC) at Deutscher Wetterdienst (DWD) are used. Over ocean, retrievals from the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS) dataset are used as data source. The currently available dataset consists of 21 years of data (1988-2008) and is provided in different spatial resolutions of 1° and 2.5° on the global scale, and 0.5° for Europe. Rain rates over ocean are currently derived from satellite microwave imagers by using a neuronal network. For the future it is intended to switch this retrieval method to a 1D-Var method. The current state of the dataset is presented, an introduction to the future retrieval and its features is given and first results from evaluation and application are shown.

  20. Analysis of satellite precipitation over East Africa during last decades

    Science.gov (United States)

    Cattani, Elsa; Wenhaji Ndomeni, Claudine; Merino, Andrés; Levizzani, Vincenzo

    2016-04-01

    Daily accumulated precipitation time series from satellite retrieval algorithms (e.g., ARC2 and TAMSAT) are exploited to extract the spatial and temporal variability of East Africa (EA - 5°S-20°N, 28°E-52°E) precipitation during last decades (1983-2013). The Empirical Orthogonal Function (EOF) analysis is applied to precipitation time series to investigate the spatial and temporal variability in particular for October-November-December referred to as the short rain season. Moreover, the connection among EA's precipitation, sea surface temperature, and soil moisture is analyzed through the correlation with the dominant EOF modes of variability. Preliminary results concern the first two EOF's modes for the ARC2 data set. EOF1 is characterized by an inter-annual variability and a positive correlation between precipitation and El Niño, positive Indian Ocean Dipole mode, and soil moisture, while EOF2 shows a dipole structure of spatial variability associated with a longer scale temporal variability. This second dominant mode is mostly linked to sea surface temperature variations in the North Atlantic Ocean. Further analyses are carried out by computing the time series of the joint CCI/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI, http://etccdi.pacificclimate.org/index.shtml), i.e. RX1day, RX5day, CDD, CDD, CWD, SDII, PRCPTOT, R10, R20. The purpose is to identify the occurrenes of extreme events (droughts and floods) and extract precipitation temporal variation by trend analysis (Mann-Kendall technique). Results for the ARC2 data set demonstrate the existence of a dipole spatial pattern in the linear trend of the time series of PRCPTOT (annual precipitation considering days with a rain rate > 1 mm) and SDII (average precipitation on wet days over a year). A negative trend is mainly present over West Ethiopia and Sudan, whereas a positive trend is exhibited over East Ethiopia and Somalia. CDD (maximum number of consecutive dry days) and

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

    Science.gov (United States)

    Hou, Arthur Y.

    2011-01-01

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

  2. Spatial Cloud Detection and Retrieval System for Satellite Images

    Directory of Open Access Journals (Sweden)

    Ayman Nasr

    2013-01-01

    Full Text Available In last the decade we witnessed a large increase in data generated by earth observing satellites. Hence, intelligent processing of the huge amount of data received by hundreds of earth receiving stations, with specific satellite image oriented approaches, presents itself as a pressing need. One of the most important steps in earlier stages of satellite image processing is cloud detection. Satellite images having a large percentage of cloud cannot be used in further analysis. While there are many approaches that deal with different semantic meaning, there are rarely approaches that deal specifically with cloud detection and retrieval. In this paper we introduce a novel approach that spatially detect and retrieve clouds in satellite images using their unique properties .Our approach is developed as spatial cloud detection and retrieval system (SCDRS that introduce a complete framework for specific semantic retrieval system. It uses a Query by polygon (QBP paradigm for the content of interest instead of using the more conventional rectangular query by image approach. First, we extract features from the satellite images using multiple tile sizes using spatial and textural properties of cloud regions. Second, we retrieve our tiles using a parametric statistical approach within a multilevel refinement process. Our approach has been experimentally validated against the conventional ones yielding enhanced precision and recall rates in the same time it gives more precise detection of cloud coverage regions.

  3. 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.

  4. Retrieval of Precipitation from Microwave Airborne Sensors during TOGA COARE.

    Science.gov (United States)

    Viltard, Nicolas; Obligis, Estelle; Marecal, Virginie; Klapisz, Claude

    1998-07-01

    The aim of this paper is to report on the retrieval of the vertically averaged liquid cloud water content and vertically averaged precipitation rates (rain and ice) from microwave airborne radiometric observations in a two-plane parallel layer atmosphere. The approach is based on the inversion of a simple radiative transfer model in which a raindrop size distribution derived from microphysical measurements is introduced. The microwave data (18.7, 21, 37, and 92 GHz) used were acquired by the Airborne Multichannel Microwave Radiometer and Advanced Microwave Moisture Sounder on board NASA DC8 within a mesoscale convective system on 6 February 1993 during the Tropical Oceans Global Atmosphere Coupled Ocean-Atmosphere Response Experiment.Before interpreting the results, the quality of the inversion is checked. The fit between the measured and the model-retrieved brightness temperatures is good when compared to the model and measurements uncertainties. Doppler radar data from three other aircraft help the result's interpretation, providing reflectivity and wind fields. The cloud liquid content seems to be difficult to retrieve. The ice and liquid rain rates are consistent with the other data sources: order of magnitude for convective and stratiform regions, presence of ice and liquid precipitation correlated with cell structure, and presence of cloud particles in the lighter precipitating regions.A quantitative comparison is done between the radiometric rainfall rates and those derived from the Airborne Rain Mapping Radar observations (also on board NASA DC8). There is a good agreement between the two from the statistical point of view (mean and standard deviation values). Moreover, the finescale rain structures that appear in radar results are rather well reproduced in the radiometric results. The importance of the new drop size distribution introduced in the radiative transfer model is emphasized by this last comparison.

  5. Two-Channel Satellite Retrievals of Aerosol Properties: An Overview

    Science.gov (United States)

    Mishchenko, Michael I.

    1999-01-01

    In order to reduce current uncertainties in the evaluation of the direct and indirect effects of tropospheric aerosols on climate on the global scale, it has been suggested to apply multi-channel retrieval algorithms to the full period of existing satellite data. This talk will outline the methodology of interpreting two-channel satellite radiance data over the ocean and describe a detailed analysis of the sensitivity of retrieved aerosol parameters to the assumptions made in different retrieval algorithms. We will specifically address the calibration and cloud screening issues, consider the suitability of existing satellite data sets to detecting short- and long-term regional and global changes, compare preliminary results obtained by several research groups, and discuss the prospects of creating an advanced retroactive climatology of aerosol optical thickness and size over the oceans.

  6. Retrieval of Aerosol Properties from Satellite Data

    NARCIS (Netherlands)

    Kusmierczyk-Michulec, J.; Roblez Gonzalez, C.; Decae, R.; Leeuw, G. de

    2003-01-01

    Algorithms for the retrieval of aerosol properties over land and over sea have been developed by the TNO Physics and Electronics Laboratory (TNO-FEL) for several instruments, such as AVHRR (Veefkind et al., 1998a), GOME, ATSR-2 (Veelkind et al. 1998a, b; 1999) and OMI (Torres et al. 2002). OMI will

  7. 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.

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

    Science.gov (United States)

    Verdin, Andrew; Rajagopalan, Balaji; Kleiber, William; Funk, Chris

    2015-02-01

    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

  9. Retrievals of Falling Snow from Satellite-borne Active and Passive Sensors

    Science.gov (United States)

    Jackson, Gail; Munchak, S. Joseph; Johnson, Benjamin

    2014-05-01

    Precipitation, including rain and snow, is a critical part of the Earth's energy and hydrology cycles. Precipitation impacts latent heating profiles locally while global circulation patterns distribute precipitation and energy from the equator to the poles. For the hydrological cycle, falling snow is a primary contributor in northern latitudes during the winter seasons. Falling snow is the source of snow pack accumulations that provide fresh water resources for many communities in the world. Furthermore, falling snow impacts society by causing transportation disruptions during severe snow events. In order to collect information on the complete global precipitation cycle, both liquid and frozen precipitation must be collected. The Global Precipitation Measurement (GPM) mission's Core satellite, scheduled for launch in February 2014, is well designed to detect and estimate falling snow. The GPM core carries a passive radiometer with frequencies (10-183 GHz) and an active radar with Ku- and Ka-band frequencies. Combined with the 65o inclination of the GPM Core satellite, these instruments allow for the GPM Core to sense and retrieve information about falling snow and light rain in regions of the earth where snow is common. The GPM Core's comprehensive active and passive channel set will also allow it to serve as a unifying reference for GPM constellation radiometer satellites. Since falling snow from space is the next precipitation measurement challenge from space, information is needed to guide retrieval algorithm development for these current and future missions. This information includes thresholds of detection for various sensor channel configurations, sensitivity to macroscale snow event system characteristics, and sensitivity to microscale snowflake particle characteristics. While the work in this area will continue for many years to come, our group has made substantial progress in this area by identifying minimum detectable melted rates of ~0.5 mm hr-1. Results

  10. Day 1 and Beyond for Multi-satellite Retrievals in GPM (Invited)

    Science.gov (United States)

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

    2013-12-01

    Merged multi-satellite estimates of precipitation constitute one of the key goals of the Global Precipitation Measurement (GPM) mission. These allow users access to quasi-global precipitation estimates at relatively fine time/space scales without detailed knowledge of satellites, sensors, or algorithms. The Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm will provide the at-launch combined-satellite precipitation dataset being produced by the U.S. GPM Science Team. This talk will review IMERG's development as a unified U.S. algorithm that takes advantage of strengths in three current U.S. algorithms, namely the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), CPC Morphing algorithm with Kalman Filtering (KF-CMORPH), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS). 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 as feasible. The record will begin January 1998 corresponding with the start of the 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). We plan to compute multiple runs at different latencies (most likely around 4 hours, 12 hours, and 2 months after observation time) to address the needs of different groups of users. We will describe the current focus of bringing up the Day-1 IMERG in the Precipitation Processing System using TRMM-based calibration until the GPM sensor algorithms finish check-out in 2014, and then transition to GPM-based calibration after that. However, at the same time we are looking ahead to the next challenges for Day 2 and beyond. This talk will briefly

  11. Software for validating parameters retrieved from satellite

    Digital Repository Service at National Institute of Oceanography (India)

    Muraleedharan, P.M.; Sathe, P.V.; Pankajakshan, T.

    surface layer (skin temperature) whereas the conventional sea truth platforms (MB) measure temperature represented by the upper 2-3 m layer (Wick et al., 1992). During the day, the air temperature instantly modifies the skin temperature of the sea... between satellite measured skin and multi-channel SST. J. Geophys. Res., 97: 5569-5595. Now the weighted average of SST is obtained from the following relation ...

  12. Satellite rainfall retrieval by logistic regression

    Science.gov (United States)

    Chiu, Long S.

    1986-01-01

    The potential use of logistic regression in rainfall estimation from satellite measurements is investigated. Satellite measurements provide covariate information in terms of radiances from different remote sensors.The logistic regression technique can effectively accommodate many covariates and test their significance in the estimation. The outcome from the logistical model is the probability that the rainrate of a satellite pixel is above a certain threshold. By varying the thresholds, a rainrate histogram can be obtained, from which the mean and the variant can be estimated. A logistical model is developed and applied to rainfall data collected during GATE, using as covariates the fractional rain area and a radiance measurement which is deduced from a microwave temperature-rainrate relation. It is demonstrated that the fractional rain area is an important covariate in the model, consistent with the use of the so-called Area Time Integral in estimating total rain volume in other studies. To calibrate the logistical model, simulated rain fields generated by rainfield models with prescribed parameters are needed. A stringent test of the logistical model is its ability to recover the prescribed parameters of simulated rain fields. A rain field simulation model which preserves the fractional rain area and lognormality of rainrates as found in GATE is developed. A stochastic regression model of branching and immigration whose solutions are lognormally distributed in some asymptotic limits has also been developed.

  13. Making Satellite Precipitation Data Work for the Developing World

    Science.gov (United States)

    Gebregiorgis, A. S.; Hossain, F.

    2013-12-01

    The traditional approach to measuring precipitation by placing a probe on the ground will likely never be adequate or affordable in most parts of the world. Fortunately, satellites today provide a continuous global bird's-eye view (above ground) at any given location.However, the usefulness of such precipitation products for hydrological applications depends on their error characteristics and how intelligently we can harness the implications of uncertainty for surface hydrology. Satellite precipitation data is most useful where there exists little to none conventional measurements. As a result, the conventional method of comparing satellite estimate against in-situ records to 'harness' the uncertainty is unrealistic and impractical. As a community tasked with the job of making satellite precipitation 'work' for applications in most parts of the world, there is now a need think outside the box. The manuscript aims to describe a method that will 'truly' work in the developing world. The proposed manuscript aims to provide a broad view summary of our work on making hydrologically merged precipitation data work in the Middle East, Europe, Asia and Mediterranean regions. The aim will be to appeal to a broad range of water managers, climate decision makers and policy and planners in the developing world. The merged precipitation data has already been created for 2002-2010 and will be made freely available to BAMS readers through our ftp site. Globally selected study regions for developing and validating error variance regression model and satellite rainfall products merging scheme

  14. The potential of clear-sky carbon dioxide satellite retrievals

    Directory of Open Access Journals (Sweden)

    R. R. Nelson

    2015-12-01

    Full Text Available Since the launch of the Greenhouse Gases Observing Satellite (GOSAT in 2009, retrieval algorithms designed to infer the column-averaged dry-air mole fraction of carbon dioxide (XCO2 from hyperspectral near-infrared observations of reflected sunlight have been greatly improved. They now generally include the scattering effects of clouds and aerosols, as early work found that absorption-only retrievals, which neglected these effects, often incurred unacceptably large errors, even for scenes with optically thin cloud or aerosol layers. However, these "full-physics" retrievals tend to be computationally expensive and may incur biases from trying to deduce the properties of clouds and aerosols when there are none present. Additionally, algorithms are now available that can quickly and effectively identify and remove most scenes in which cloud or aerosol scattering plays a significant role. In this work, we test the hypothesis that non-scattering, or "clear-sky", retrievals may perform as well as full-physics retrievals for sufficiently clear scenes. Clear-sky retrievals could potentially avoid errors and biases brought about by trying to infer properties of clouds and aerosols when none are present. Clear-sky retrievals are also desirable because they are orders of magnitude faster than full-physics retrievals. Here we use a simplified version of the Atmospheric Carbon Observations from Space (ACOS XCO2 retrieval algorithm that does not include the scattering and absorption effects of clouds or aerosols. It was found that for simulated Orbiting Carbon Observatory-2 (OCO-2 measurements, the clear-sky retrieval had errors comparable to those of the full-physics retrieval. For real GOSAT data, the clear-sky retrieval had nearly indistinguishable error characteristics over land, but roughly 30–60 % larger errors over ocean, depending on filtration level, compared to the full-physics retrieval. In general, the clear-sky retrieval had XCO2 root

  15. Snowline retrievals using operational satellite data

    Science.gov (United States)

    Becker, R.

    2010-09-01

    Making use of atmosphere and surface parameters derived from satellite remote sensing is of increasing importance to describe appropriately status and changes of weather and climate. Even in regions with poor coverage concerning ground based measurements and/or heterogenous terrain satellite products contribute to fill temporal and spatial gaps. Imaging radiometers provide information on surface snow and ice based on multispectral algorithms with a spatial resolution from 250 m to about 3000 m. Observations by passive imaging spectro-/radiometers like SEVIRI onboard Meteosat second generation, Noaa/MetOp AVHRR and Terra/Aqua MODIS have the potential to provide snow products on a daily basis with spatial resolution comparable or better than grid increment of the hydrological models. For the evaluation of MODIS imagery a dedicated algorithm was set up utilising multispectral thresholding of calibrated radiances to separate clear land and sea from cloudy and snow-covered scenes. The scheme works independently of a-priori atmospheric data like numerical model forecasts. It outputs a combined snow/cloudmask that is finally convoluted with background topography information (GIS), allowing for the calculation of snowlines. The core snow and ice detection is based on a NDSI module (normalised difference snow index, Hall et.al. 2001). A well established algorithm developed within the framework of the Satellite Application Facility for Nowcasting (NWCSAF, Dybbroe et.al. 2005), is used to detect snowy pixels in the AVHRR imagery. MODIS and AVHRR results were compared to each other. It shows a good agreement by means of correlation (.94) but systematic deviations are considered. A verification study was carried out by taking into account all European synoptical and climatological snow measurements with snow depths of at least 1 cm. The scores show a clear seasonal cycle with PODs of .2 in summer (both) and .86 (AVHRR) and .82 (MODIS) in winter months. The evaluation data

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

    Directory of Open Access Journals (Sweden)

    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%.

  17. Estimating the Retrievability of Temperature Profiles from Satellite Infrared Measurements

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A method is developed to assess retrievability, namely the retrieval potential for atmospheric temperature profiles, from satellite infrared measurements in clear-sky conditions. This technique is based upon generalized linear inverse theory and empirical orthogonal function analysis. Utilizing the NCEP global temperature reanalysis data in January and July from 1999 to 2003, the retrievabilities obtained with the Atmospheric Infrared Sounder (AIRS) and the High Resolution Infrared Radiation Sounder/3 (HIRS/3)sounding channel data are derived respectively for each standard pressure level on a global scale. As an incidental result of this study, the optimum truncation number in the method of generalized linear inverse is deduced too. The results show that the retrievabilities of temperature obtained with the two datasets are similar in spatial distribution and seasonal change characteristics. As for the vertical distribution, the retrievabilities are low in the upper and lower atmosphere, and high between 400 hPa and 850 hPa. For the geographical distribution, the retrievabilities are low in the low-latitude oceanic regions and in some regions in Antarctica, and relatively high in mid-high latitudes and continental regions. Compared with the HIRS/3 data, the retrievability obtained with the AIRS data can be improved by an amount between 0.15 and 0.40.

  18. Investigating Satellite Microwave observations of Precipitation in Different Climate Regimes

    Science.gov (United States)

    Wang, N.; Ferraro, R. R.

    2013-12-01

    Microwave satellite remote sensing of precipitation over land is a challenging problem due to the highly variable land surface emissivity, which, if not properly accounted for, can be much greater than the precipitation signal itself, especially in light rain/snow conditions. Additionally, surfaces such as arid land, deserts and snow cover have brightness temperature characteristics similar to precipitation Ongoing work by GPM microwave radiometer team is constructing databases through a variety of means, however, there is much uncertainty as to what is the optimal information needed for the wide array of sensors in the GPM constellation, including examination of regional conditions. The original data sets will focus on stratification by emissivity class, surface temperature and total perceptible water. We'll perform sensitivity studies to determine the potential role of ancillary data (e.g., land surface temperature, snow cover/water equivalent, etc.) to improve precipitation estimation over land in different climate regimes, including rain and snow. In other words, what information outside of the radiances can help describe the background and subsequent departures from it that are active precipitating regions? It is likely that this information will be a function of the various precipitation regimes. Statistical methods such as Principal Component Analysis (PCA) will be utilized in this task. Databases from a variety of sources are being constructed. They include existing satellite microwave measurements of precipitating and non-precipitating conditions, ground radar precipitation rate estimates, surface emissivity climatology from satellites, surface temperature and TPW from NWP reanalysis. Results from the analysis of these databases with respect to the microwave precipitation sensitivity to the variety of environmental conditions in different climate regimes will be discussed.

  19. Heading Toward Launch with the Integrated Multi-Satellite Retrievals for GPM (IMERG)

    Science.gov (United States)

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

    2012-01-01

    The Day-l algorithm for computing combined precipitation estimates in GPM is the Integrated Multi-satellitE Retrievals for GPM (IMERG). We plan for the period of record to encompass both the TRMM and GPM eras, and the coverage to extend to fully global as experience is gained in the difficult high-latitude environment. IMERG is being developed as a unified U.S. algorithm that takes advantage of strengths in the three groups that are contributing expertise: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA), which addresses inter-satellite calibration of precipitation estimates and monthly scale combination of satellite and gauge analyses; 2) the CPC Morphing algorithm with Kalman Filtering (KF-CMORPH), which provides quality-weighted time interpolation of precipitation patterns following cloud motion; and 3) 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. In this talk we summarize the major building blocks and important design issues driven by user needs and practical data issues. One concept being pioneered by the IMERG team is that the code system should produce estimates for the same time period but at different latencies to support the requirements of different groups of users. Another user requirement is that all these runs must be reprocessed as new IMERG versions are introduced. IMERG's status at meeting time will be summarized, and the processing scenario in the transition from TRMM to GPM will be laid out. Initially, IMERG will be run with TRMM-based calibration, and then a conversion to a GPM-based calibration will be employed after the GPM sensor products are validated. A complete reprocessing will be computed, which will complete the transition from TMPA.

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

    Science.gov (United States)

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

    2016-04-01

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

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

    Science.gov (United States)

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

    2010-05-01

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

  2. A hybrid framework for verification of satellite precipitation products

    Science.gov (United States)

    Li, J.; Hsu, K.; AghaKouchak, A.; Sorooshian, S.

    2011-12-01

    Advances in satellite technology have led to the development of many remote-sensing algorithms to estimate precipitation at quasi-global scales. A number of satellite precipitation products are provided at high spatial and temporal resolutions that are suitable for short-term hydrologic applications. Several coordinated validation activities have been established to evaluate the accuracy of satellite precipitation. Traditional verification measures summarize pixel-to-pixel differences between observation and estimates. Object-based verification methods, however, extend pixel based validation to address errors related to spatial patterns and storm structure, such as the shape, volume, and distribution of precipitation rain-objects. In this investigation, a 2D watershed segmentation technique is used to identify rain storm objects and is further adopted in a hybrid verification framework to diagnose the storm-scale rainfall objects from both satellite-based precipitation estimates and ground observations (radar estimates). Five key scores are identified in the objective-based verification framework, including false alarm ratio, missing ratio, maximum of total interest, equal weight and weighted summation of total interest. These scores indicate the performance of satellite estimates with features extracted from the segmented storm objects. The proposed object-based verification framework was used to evaluate PERSIANN, PERSIANN-CCS, CMORPH, 3B42RT against NOAA stage IV MPE multi-sensor composite rain analysis. All estimates are evaluated at 0.25°x0.25° daily-scale in summer 2008 over the continental United States (CONUS). The five final scores for each precipitation product are compared with the median of maximum interest (MMI) of the Method for Object-Based Diagnostic Evaluation (MODE). The results show PERSIANN and CMORPH outperform 3B42RT and PERSIANN-CCS. Different satellite products presented distinct features of precipitation. For example, the sizes of

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

    Science.gov (United States)

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

    2009-04-01

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

  4. Assessing the performance of satellite-based precipitation products over the Mediterranean region

    Science.gov (United States)

    Xaver, Angelika; Dorigo, Wouter; Brocca, Luca; Ciabatta, Luca

    2017-04-01

    Detailed knowledge about the spatial and temporal patterns and quantities of precipitation is of high importance. This applies especially in the Mediterranean region, where water demand for agricultural, industrial and touristic needs is growing and climate projections foresee a decrease of precipitation amounts and an increase in variability. In this region, ground-based rain gauges are available only limited in number, particularly in northern Africa and the Middle East and lack to capture the high spatio-temporal character of precipitation over large areas. This has motivated the development of a large number of remote sensing products for monitoring rainfall. Satellite-based precipitation products are based on various observation principles and retrieval approaches, i.e. from thermal infra-red and microwaves. Although, many individual validation studies on the performance of these precipitation datasets exist, they mostly examine only one or a few of these rainfall products at the same time and are not targeted at the Mediterranean basin as a whole. Here, we present an extensive comparative study of seven different satellite-based precipitation products, namely CMORPH 30-minutes, CMORPH 3-hourly, GPCP, PERSIANN, SM2Rain CCI, TRMM TMPA 3B42, and TRMM TMPA 3B42RT, focusing on the whole Mediterranean region and on individual Mediterranean catchments. The time frame of investigation is restricted by the common availability of all precipitation products and covers the period 2000-2013. We assess the skill of the satellite products against gridded gauge-based data provided by GPCC and E-OBS. Apart from common characteristics like biases and temporal correlations we evaluate several sophisticated dataset properties that are of particular interest for Mediterranean hydrology, including the capability of the remotely sensed products to capture extreme events and trends. A clear seasonal dependency of the correlation results can be observed for the whole Mediterranean

  5. Diagnosing Aircraft Icing Potential from Satellite Cloud Retrievals

    Science.gov (United States)

    Smith, William L., Jr.; Minnis, Patrick; Fleeger, Cecilia; Spangenberg, Douglas

    2013-01-01

    The threat for aircraft icing in clouds is a significant hazard that routinely impacts aviation operations. Accurate diagnoses and forecasts of aircraft icing conditions requires identifying the location and vertical distribution of clouds with super-cooled liquid water (SLW) droplets, as well as the characteristics of the droplet size distribution. Traditional forecasting methods rely on guidance from numerical models and conventional observations, neither of which currently resolve cloud properties adequately on the optimal scales needed for aviation. Satellite imagers provide measurements over large areas with high spatial resolution that can be interpreted to identify the locations and characteristics of clouds, including features associated with adverse weather and storms. This paper describes new techniques for interpreting cloud products derived from satellite data to infer the flight icing threat to aircraft. For unobscured low clouds, the icing threat is determined using empirical relationships developed from correlations between satellite imager retrievals of liquid water path and droplet size with icing conditions reported by pilots (PIREPS). For deep ice over water cloud systems, ice and liquid water content (IWC and LWC) profiles are derived by using the imager cloud properties to constrain climatological information on cloud vertical structure and water phase obtained apriori from radar and lidar observations, and from cloud model analyses. Retrievals of the SLW content embedded within overlapping clouds are mapped to the icing threat using guidance from an airfoil modeling study. Compared to PIREPS and ground-based icing remote sensing datasets, the satellite icing detection and intensity accuracies are approximately 90% and 70%, respectively, and found to be similar for both low level and deep ice over water cloud systems. The satellite-derived icing boundaries capture the reported altitudes over 90% of the time. Satellite analyses corresponding to

  6. Global Land Surface Emissivity Retrieved From Satellite Ultraspectral IR Measurements

    Science.gov (United States)

    Zhou, D. K.; Larar, A. M.; Liu, Xu; Smith, W. L.; Strow, L. L.; Yang, Ping; Schlussel, P.; Calbet, X.

    2011-01-01

    Ultraspectral resolution infrared (IR) radiances obtained from nadir observations provide information about the atmosphere, surface, aerosols, and clouds. Surface spectral emissivity (SSE) and surface skin temperature from current and future operational satellites can and will reveal critical information about the Earth s ecosystem and land-surface-type properties, which might be utilized as a means of long-term monitoring of the Earth s environment and global climate change. In this study, fast radiative transfer models applied to the atmosphere under all weather conditions are used for atmospheric profile and surface or cloud parameter retrieval from ultraspectral and/or hyperspectral spaceborne IR soundings. An inversion scheme, dealing with cloudy as well as cloud-free radiances observed with ultraspectral IR sounders, has been developed to simultaneously retrieve atmospheric thermodynamic and surface or cloud microphysical parameters. This inversion scheme has been applied to the Infrared Atmospheric Sounding Interferometer (IASI). Rapidly produced SSE is initially evaluated through quality control checks on the retrievals of other impacted surface and atmospheric parameters. Initial validation of retrieved emissivity spectra is conducted with Namib and Kalahari desert laboratory measurements. Seasonal products of global land SSE and surface skin temperature retrieved with IASI are presented to demonstrate seasonal variation of SSE.

  7. Total ozone retrieval from satellite multichannel filter radiometer measurements

    Energy Technology Data Exchange (ETDEWEB)

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

    1978-05-25

    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 (preliminary data--299 m.atm.cm).

  8. The Passive Microwave Neural Network Precipitation Retrieval (PNPR) for AMSU/MHS and ATMS cross-track scanning radiometers

    Science.gov (United States)

    Sano', Paolo; Casella, Daniele; Panegrossi, Giulia; Cinzia Marra, Anna; Dietrich, Stefano

    2016-04-01

    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

  9. Retrieving co-occurring cloud and precipitation properties of warm marine boundary layer clouds with A-Train data

    Science.gov (United States)

    Mace, Gerald G.; Avey, Stephanie; Cooper, Steven; Lebsock, Matthew; Tanelli, Simone; Dobrowalski, Greg

    2016-04-01

    In marine boundary layer (MBL) clouds the formation of precipitation from the cloud droplet distribution in the presence of variable aerosol plays a fundamental role in determining the coupling of these clouds to their environment and ultimately to the climate system. Here the degree to which A-Train satellite measurements can diagnose simultaneously occurring cloud and precipitation properties in MBL clouds is examined. Beginning with the measurements provided by CloudSat and Moderate Resolution Imaging Spectroradiometer (including a newly available microwave brightness temperature from CloudSat), and a climatology of MBL cloud properties from past field campaigns, an assumption is made that any hydrometeor volume could contain both cloud droplet and precipitation droplet modes. Bayesian optimal estimation is then used to derive atmospheric states by inverting a measurement vector carefully accounting for uncertainties due to instrument noise, forward model error, and assumptions. It is found that in many cases where significant precipitation coexists with cloud, due to forward model error driven by uncertainties in assumptions, the uncertainty in retrieved cloud properties is greater than the variance in the prior climatology. It is often necessary to average several thousand (hundred) precipitating (weakly precipitating) profiles to obtain meaningful information regarding the properties important to microphysical processes. Regardless, if such process level information is deemed necessary for better constraining predictive models of the climate system, measurement systems specifically designed to accomplish such retrievals must be considered for the future.

  10. Using ARM Data to Evaluate Satellite Surface Solar Flux Retrievals

    Energy Technology Data Exchange (ETDEWEB)

    Hinkelman, L.M.; Stackhouse, P.W.; Young, D.F.; Long, C.N.; Rutan, D.

    2005-03-18

    The accurate, long-term radiometric data collected by Atmospheric Radiation Measurement (ARM) has become essential to the evaluation of surface radiation budget data from satellites. Since the spatial and temporal characteristics of data from these two sources are very different, the comparisons are typically made for long-term average values. While such studies provide a general indication of the quality of satellite flux products, more detailed analysis is required to understand specific retrieval algorithm weaknesses. Here we show how data from the ARM shortwave flux analysis (SFA) value added product (VAP) are being used to assess solar fluxes in the Global Energy and Water Cycle Experiment (GEWEX) Surface Radiation Budget (SRB), release 2.5.

  11. Study on the Algorithm to Retrieve Precipitation with X-Band Synthetic Aperture Radar

    Institute of Scientific and Technical Information of China (English)

    XIE Yanan; HUAN Jianping; TAO Yang

    2010-01-01

    In order to obtain the global precipitation distribution data,this paper investigates the precipitation distribution model,the normalized radar cross-section model,and the retrieval algorithm with X-band synthetic aperture radar(X-SAR).A new retrieval algorithm based on the surface-scattering reference attenuation is developed to retrieve the rain rate above the ground surface.This new algorithm needs no statistical work load and has more extensive applications.Calculations using the new algorithm for three cases verify that the rainfall is retrieved with high precision,which proves the capability of the algorithm.

  12. Efficient Methods to Assimilate Satellite Retrievals Based on Information Content. Part 2; Suboptimal Retrieval Assimilation

    Science.gov (United States)

    Joiner, J.; Dee, D. P.

    1998-01-01

    One of the outstanding problems in data assimilation has been and continues to be how best to utilize satellite data while balancing the tradeoff between accuracy and computational cost. A number of weather prediction centers have recently achieved remarkable success in improving their forecast skill by changing the method by which satellite data are assimilated into the forecast model from the traditional approach of assimilating retrievals to the direct assimilation of radiances in a variational framework. The operational implementation of such a substantial change in methodology involves a great number of technical details, e.g., pertaining to quality control procedures, systematic error correction techniques, and tuning of the statistical parameters in the analysis algorithm. Although there are clear theoretical advantages to the direct radiance assimilation approach, it is not obvious at all to what extent the improvements that have been obtained so far can be attributed to the change in methodology, or to various technical aspects of the implementation. The issue is of interest because retrieval assimilation retains many practical and logistical advantages which may become even more significant in the near future when increasingly high-volume data sources become available. The central question we address here is: how much improvement can we expect from assimilating radiances rather than retrievals, all other things being equal? We compare the two approaches in a simplified one-dimensional theoretical framework, in which problems related to quality control and systematic error correction are conveniently absent. By assuming a perfect radiative transfer model and perfect knowledge of radiance and background error covariances, we are able to formulate a nonlinear local error analysis for each assimilation method. Direct radiance assimilation is optimal in this idealized context, while the traditional method of assimilating retrievals is suboptimal because it

  13. NESDIS Microwave Integrated Retrieval System (MIRS) ATMS Precipitation and Surface Products

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains two-dimensional precipitation and surface products from the NESDIS Microwave Integrated Retrieval System (MIRS) using sensor data from the...

  14. Using radiance of cloud shadow for retrieve Investigation of AOD retrieval with Himawari-8 satellite data

    Science.gov (United States)

    Sun, Ta-Min; Chang, Yuan-Hsiang; Chang, Kuo-En; Lin, Tang-Huang

    2016-04-01

    As we know, the emission of pollutants, such as dust storm, biomass burning and anthropogenic pollution are serious issues related to the environmental change and human health topics in Asia. With the high temporal observation over a broad area, the new generated geostationary satellite, Himawari-8 (H-8) seems to be a good choice for atmospheric pollution monitor. It can provide the observation over Asia with 16 bands in visible and thermal infrared spectral every 10 minutes. For the atmospheric pollutant monitor by means of remote sensing, the retrieval of aerosol optical depth (AOD) is the most important index. In this study, the long method is employed for AOD retrieval which depends on the path radiance significantly. Apparent radiance of the suitable cloud shadow is selected as the path radiance. In order to let the atmospheric pollution monitor is used efficiently, so the distribution of the path radiance is using the objective analysis to expand it. The results of AOD retrieval from H-8 visible data are well consistent with MODIS (Moderate Resolution Imaging Spectroradiometer) AOD products and ground measurements AERONET (Aerosol Robotic Networks), indicating the practical of proposed approach for the AOD retrieval with H-8 data.

  15. Spatio-temporal multi-modality ontology for indexing and retrieving satellite images

    OpenAIRE

    MESSOUDI, Wassim; FARAH, Imed Riadh; SAHEB ETTABAA, Karim; Ben Ghezala, Henda; SOLAIMAN, Basel

    2009-01-01

    International audience; This paper presents spatio-temporal multi-modality ontology for indexing and retrieving satellite images in the high level to improve the quality of the system retrieval and to perform semantic in the retrieval process.Our approach is based on three modules: (1) regions and features extraction, (2) ontological indexing and (3) semantic image retrieval. The first module allows extracting regions from the satellite image using the fuzzy c-means FCM) segmentation algorith...

  16. Fast Simulators for Satellite Cloud Optical Centroid Pressure Retrievals, 1. Evaluation of OMI Cloud Retrievals

    Science.gov (United States)

    Joiner, J.; Vasilkov, A.; Gupta, P.; Bhartia, P. K.; Veefkind, P.; Sneep, M.; de Haan, J.; Polonsky, I.; Spurr, R.

    2012-01-01

    The cloud Optical Centroid Pressure (OCP), also known as the effective cloud pressure, is a satellite-derived parameter that is commonly used in trace-gas retrievals to account for the effects of clouds on near-infrared through ultraviolet radiance measurements. Fast simulators are desirable to further expand the use of cloud OCP retrievals into the operational and climate communities for applications such as data assimilation and evaluation of cloud vertical structure in general circulation models. In this paper, we develop and validate fast simulators that provide estimates of the cloud OCP given a vertical profile of optical extinction. We use a pressure-weighting scheme where the weights depend upon optical parameters of clouds and/or aerosol. A cloud weighting function is easily extracted using this formulation. We then use fast simulators to compare two different satellite cloud OCP retrievals from the Ozone Monitoring Instrument (OMI) with estimates based on collocated cloud extinction profiles from a combination of CloudS at radar and MODIS visible radiance data. These comparisons are made over a wide range of conditions to provide a comprehensive validation of the OMI cloud OCP retrievals. We find generally good agreement between OMI cloud OCPs and those predicted by CloudSat. However, the OMI cloud OCPs from the two independent algorithms agree better with each other than either does with the estimates from CloudSat/MODIS. Differences between OMI cloud OCPs and those based on CloudSat/MODIS may result from undetected snow/ice at the surface, cloud 3-D effects, low altitude clouds missed by CloudSat, and the fact that CloudSat only observes a relatively small fraction of an OMI field-of-view.

  17. Fast simulators for satellite cloud optical centroid pressure retrievals; evaluation of OMI cloud retrievals

    Directory of Open Access Journals (Sweden)

    J. Joiner

    2012-03-01

    Full Text Available The cloud Optical Centroid Pressure (OCP is a satellite-derived parameter that is commonly used in trace-gas retrievals to account for the effects of clouds on near-infrared through ultraviolet radiance measurements. Fast simulators are desirable to further expand the use of cloud OCP retrievals into the operational and climate communities for applications such as data assimilation and evaluation of cloud vertical structure in general circulation models. In this paper, we develop and validate fast simulators that provide estimates of the cloud OCP given a vertical profile of optical extinction. We use a pressure-weighting scheme where the weights depend upon optical parameters of clouds and/or aerosols. A cloud weighting function is easily extracted using this formulation. We then use fast simulators to compare two different satellite cloud OCP retrievals, from the Ozone Monitoring Instrument (OMI, with estimates based on collocated cloud extinction profiles from a combination of CloudSat radar and MODIS visible radiance data. These comparisons are made over a wide range of conditions to provide a comprehensive validation of the OMI cloud OCP retrievals. We find generally good agreement between OMI cloud OCPs and those predicted by CloudSat. However, the OMI cloud OCPs from the two independent algorithms agree better with each other than either does with the estimates from CloudSat/MODIS. Differences between OMI cloud OCPs and those based on CloudSat/MODIS may result from undetected snow/ice at the surface, cloud 3-D effects, cases of low clouds obscurred by ground-clutter in CloudSat observations and by opaque high clouds in CALIPSO lidar observations, and the fact that CloudSat/CALIPSO only observes a relatively small fraction of an OMI field-of-view.

  18. Using Satellite Aerosol Retrievals to Monitor Surface Particulate Air Quality

    Science.gov (United States)

    Levy, Robert C.; Remer, Lorraine A.; Kahn, Ralph A.; Chu, D. Allen; Mattoo, Shana; Holben, Brent N.; Schafer, Joel S.

    2011-01-01

    The MODIS and MISR aerosol products were designed nearly two decades ago for the purpose of climate applications. Since launch of Terra in 1999, these two sensors have provided global, quantitative information about column-integrated aerosol properties, including aerosol optical depth (AOD) and relative aerosol type parameters (such as Angstrom exponent). Although primarily designed for climate, the air quality (AQ) community quickly recognized that passive satellite products could be used for particulate air quality monitoring and forecasting. However, AOD and particulate matter (PM) concentrations have different units, and represent aerosol conditions in different layers of the atmosphere. Also, due to low visible contrast over brighter surface conditions, satellite-derived aerosol retrievals tend to have larger uncertainty in urban or populated regions. Nonetheless, the AQ community has made significant progress in relating column-integrated AOD at ambient relative humidity (RH) to surface PM concentrations at dried RH. Knowledge of aerosol optical and microphysical properties, ambient meteorological conditions, and especially vertical profile, are critical for physically relating AOD and PM. To make urban-scale maps of PM, we also must account for spatial variability. Since surface PM may vary on a finer spatial scale than the resolution of standard MODIS (10 km) and MISR (17km) products, we test higher-resolution versions of MODIS (3km) and MISR (1km research mode) retrievals. The recent (July 2011) DISCOVER-AQ campaign in the mid-Atlantic offers a comprehensive network of sun photometers (DRAGON) and other data that we use for validating the higher resolution satellite data. In the future, we expect that the wealth of aircraft and ground-based measurements, collected during DISCOVER-AQ, will help us quantitatively link remote sensed and ground-based measurements in the urban region.

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

    Directory of Open Access Journals (Sweden)

    Ruifang Guo

    2016-07-01

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

  20. Hydrologic evaluation of a Generalized Statistical Uncertainty Model for Satellite Precipitation Products

    Science.gov (United States)

    Sarachi, S.; Hsu, K. L.; Sorooshian, S.

    2014-12-01

    Development of satellite based precipitation retrieval algorithms and using them in hydroclimatic studies have been of great interest to hydrologists. It is important to understand the uncertainty associated with precipitation products and how they further contribute to the variability in stream flow simulation. In this study a mixture model of Generalized Normal Distribution and Gamma distribution (GND-G) is used to model the joint probability distribution of satellite-based (PERSIANN) and stage IV radar rainfall. The study area for constructing the uncertainty model covers a 15°×15°box of 0.25°×0.25° cells over the eastern United States for summer 2004 to 2009. Cells are aggregated in space and time to obtain data with different resolutions for the construction of the model's parameter space. This uncertainty model is evaluated using data from National Weather Service (NWS) Distributed Hydrologic Model Intercomparison Project - Phase 2 (DMIP 2) basin over Illinois River basin south of Siloam, OK. This data covers the time period of 2006 to 2008.The uncertainty range of precipitation is estimated. The impact of precipitation uncertainty to the stream flow estimation is demonstrated by Monte Carlo simulation of precipitation forcing in the Sacramento Soil Moisture Accounting (SAC-SMA) model. The results show that using precipitation along with its uncertainty distribution as forcing to SAC-SMA make it possible to have an estimation of the uncertainty associated with the stream flow simulation ( in this case study %90 confidence interval is used). The mean of this stream flow confidence interval is compared to the reference stream flow for evaluation of the model and the results show that this method helps to better estimate the variability of the stream flow simulation along with its statistics e.g. percent bias and root mean squared error.

  1. Utilizing Satellite-derived Precipitation Products in Hydrometeorological Applications

    Science.gov (United States)

    Liu, Z.; Ostrenga, D.; Teng, W. L.; Kempler, S. J.; Huffman, G. J.

    2012-12-01

    Each year droughts and floods happen around the world and can cause severe property damages and human casualties. Accurate measurement and forecast are important for preparedness and mitigation efforts. Through multi-satellite blended techniques, significant progress has been made over the past decade in satellite-based precipitation product development, such as, products' spatial and temporal resolutions as well as timely availability. These new products are widely used in various research and applications. In particular, the TRMM Multi-satellite Precipitation Analysis (TMPA) products archived and distributed by the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) provide 3-hourly, daily and monthly near-global (50° N - 50° S) precipitation datasets for research and applications. Two versions of TMPA products are available, research (3B42, 3B43, rain gauge adjusted) and near-real-time (3B42RT). At GES DISC, we have developed precipitation data services to support hydrometeorological applications in order to maximize the TRMM mission's societal benefits. In this presentation, we will present examples of utilizing TMPA precipitation products in hydrometeorological applications including: 1) monitoring global floods and droughts; 2) providing data services to support the USDA Crop Explorer; 3) support hurricane monitoring activities and research; and 4) retrospective analog year analyses to improve USDA's world agricultural supply and demand estimates. We will also present precipitation data services that can be used to support hydrometeorological applications including: 1) User friendly TRMM Online Visualization and Analysis System (TOVAS; URL: http://disc2.nascom.nasa.gov/Giovanni/tovas/); 2) Mirador (http://mirador.gsfc.nasa.gov/), a simplified interface for searching, browsing, and ordering Earth science data at GES DISC; 3) Simple Subset Wizard (http://disc.sci.gsfc.nasa.gov/SSW/ ) for data subsetting and format conversion; 4) Data

  2. Performance of the Dual-frequency Precipitation Radar on the GPM core satellite

    Science.gov (United States)

    Iguchi, Toshio; Seto, Shinta; Awaka, Jun; Meneghini, Robert; Kubota, Takuji; Oki, Riko; Chandra, Venkatchalam; Kawamoto, Nozomi

    2016-04-01

    The GPM core satellite was launched on February 28, 2014. This paper describes some of the results of precipitation measurements with the Dual-Frequency Precipitation Radar (DPR) on the GPM core satellite. The DPR, which was developed by Japan Aerospace Exploration Agency (JAXA) and National Institute of Information and Communications Technology (NICT), consists of two radars: Ku-band precipitation radar (KuPR) and Ka-band radar (KaPR). The performance of the DPR is evaluated by comparing the level 2 products with the corresponding TRMM/PR data and surface rain measurements. The scanning geometry and footprint size of KuPR and those of PR are nearly identical. The major differences between them are the sensitivity, visiting frequency, and the rain retrieval algorithm. KuPR's sensitivity is twice as good as PR. The increase of sensitivity reduces the cases of missing light rain. Since relatively light rain prevails in Japan, the difference in sensitivity may cause a few percentage points in the bias. Comparisons of the rain estimates by GPM/DPR with AMeDAS rain gauge data over Japan show that annual KuPR's estimates over Japan agree quite well with the rain gauge estimates although the monthly or local statistics of these two kinds of data scatter substantially. KuPR's esimates are closer to the gauge estimates than the TRMM/PR. Possible sources of the differences that include sampling errors, sensitivity, and the algorithm are examined.

  3. A Generalized Statistical Uncertainty Model for Satellite Precipitation Products

    Science.gov (United States)

    Sarachi, S.

    2013-12-01

    A mixture model of Generalized Normal Distribution and Gamma distribution (GND-G) is used to model the joint probability distribution of satellite-based and stage IV radar rainfall under a given spatial and temporal resolution (e.g. 1°x1° and daily rainfall). The distribution parameters of GND-G are extended across various rainfall rates and spatial and temporal resolutions. In the study, GND-G is used to describe the uncertainty of the estimates from Precipitation Estimation from Remote Sensing Information using Artificial Neural Network algorithm (PERSIANN). The stage IV-based multi-sensor precipitation estimates (MPE) are used as reference measurements .The study area for constructing the uncertainty model covers a 15°×15°box of 0.25°×0.25° cells over the eastern United States for summer 2004 to 2009. Cells are aggregated in space and time to obtain data with different resolutions for the construction of the model's parameter space. Result shows that comparing to the other statistical uncertainty models, GND-G fits better than the other models, such as Gaussian and Gamma distributions, to the reference precipitation data. The impact of precipitation uncertainty to the stream flow is further demonstrated by Monte Carlo simulation of precipitation forcing in the hydrologic model. The NWS DMIP2 basins over Illinois River basin south of Siloam is selected in this case study. The data covers the time period of 2006 to 2008.The uncertainty range of stream flow from precipitation of GND-G distributions calculated and will be discussed.

  4. An improved Glyoxal retrieval from OMI satellite data

    Science.gov (United States)

    Alvarado, Leonardo; Richter, Andreas; Vrekoussis, Mihalis; Wittrock, Folkard; Burrows, John

    2013-04-01

    Glyoxal (CHOCHO) originates from natural and anthropogenic activities similar to formaldehyde (HCHO). It is the smallest of the alpha-dicarbonyls and the most predominant in the atmosphere. It is an intermediate product in the oxidation of most VOCs and an indicator of secondary aerosol formation in the atmosphere. Among others, CHOCHO is a product of the oxidation of isoprene, alkyne, and aromatic hydrocarbons. CHOCHO is not influenced directly by vehicle emissions, because direct CHOCHO emissions are believed to be small. CHOCHO has a short lifetime (few hours) in the presence of sunlight, because it is removed from the atmosphere by photolysis and reaction with OH. Also, CHOCHO is removed by dry and wet deposition. For atmospheric observations, CHOCHO is of interest as it has slightly different sources than HCHO, and can be used as indicator of the rate of photochemical VOCs processing, because in contrast to HCHO it is not produced in the oxidation of methane. Atmospheric CHOCHO columns can be determined by remote sensing using the Differential Optical Absorption Spectroscopy (DOAS) method. This sensitive technique has been used both from the ground applying active and passive DOAS and from satellite. Global fields of HCHO and CHOCHO have been retrieved from GOME, SCIAMACHY, GOME-2 and OMI measurements. Some aspects of CHOCHO retrievals still have to be improved, including possible spectral interferences over water and better correction of cloud and aerosol effects, in particular in cases of biomass burning when atmospheric aerosol levels are high. This study is focused on a new CHOCHO OMI product, including preliminary test of spectral interference with liquid water over ocean regions and comparison with CHOCHO retrievals using GOME-2 measurements over oceans and continental regions.

  5. Retrieving pace in vegetation growth using precipitation and soil moisture

    Science.gov (United States)

    Sohoulande Djebou, D. C.; Singh, V. P.

    2013-12-01

    The complexity of interactions between the biophysical components of the watershed increases the challenge of understanding water budget. Hence, the perspicacity of the continuum soil-vegetation-atmosphere's functionality still remains crucial for science. This study targeted the Texas Gulf watershed and evaluated the behavior of vegetation covers by coupling precipitation and soil moisture patterns. Growing season's Normalized Differential Vegetation Index NDVI for deciduous forest and grassland were used over a 23 year period as well as precipitation and soil moisture data. The role of time scales on vegetation dynamics analysis was appraised using both entropy rescaling and correlation analysis. This resulted in that soil moisture at 5 cm and 25cm are potentially more efficient to use for vegetation dynamics monitoring at finer time scale compared to precipitation. Albeit soil moisture at 5 cm and 25 cm series are highly correlated (R2>0.64), it appeared that 5 cm soil moisture series can better explain the variability of vegetation growth. A logarithmic transformation of soil moisture and precipitation data increased correlation with NDVI for the different time scales considered. Based on a monthly time scale we came out with a relationship between vegetation index and the couple soil moisture and precipitation [NDVI=a*Log(% soil moisture)+b*Log(Precipitation)+c] with R2>0.25 for each vegetation type. Further, we proposed to assess vegetation green-up using logistic regression model and transinformation entropy using the couple soil moisture and precipitation as independent variables and vegetation growth metrics (NDVI, NDVI ratio, NDVI slope) as the dependent variable. The study is still ongoing and the results will surely contribute to the knowledge in large scale vegetation monitoring. Keywords: Precipitation, soil moisture, vegetation growth, entropy Time scale, Logarithmic transformation and correlation between soil moisture and NDVI, precipitation and

  6. Utilization of Precipitation and Moisture Products Derived from Satellites to Support NOAA Operational Precipitation Forecasts

    Science.gov (United States)

    Ferraro, R.; Zhao, L.; Kuligowski, R. J.; Kusselson, S.; Ma, L.; Kidder, S. Q.; Forsythe, J. M.; Jones, A. S.; Ebert, E. E.; Valenti, E.

    2012-12-01

    NOAA/NESDIS operates a constellation of polar and geostationary orbiting satellites to support weather forecasts and to monitor the climate. Additionally, NOAA utilizes satellite assets from other U.S. agencies like NASA and the Department of Defense, as well as those from other nations with similar weather and climate responsibilities (i.e., EUMETSAT and JMA). Over the past two decades, through joint efforts between U.S. and international government researchers, academic partners, and private sector corporations, a series of "value added" products have been developed to better serve the needs of weather forecasters and to exploit the full potential of precipitation and moisture products generated from these satellites. In this presentation, we will focus on two of these products - Ensemble Tropical Rainfall Potential (eTRaP) and Blended Total Precipitable Water (bTPW) - and provide examples on how they contribute to hydrometeorological forecasts. In terms of passive microwave satellite products, TPW perhaps is most widely used to support real-time forecasting applications, as it accurately depicts tropospheric water vapor and its movement. In particular, it has proven to be extremely useful in determining the location, timing, and duration of "atmospheric rivers" which contribute to and sustain flooding events. A multi-sensor approach has been developed and implemented at NESDIS in which passive microwave estimates from multiple satellites and sensors are merged to create a seamless, bTPW product that is more efficient for forecasters to use. Additionally, this product is being enhanced for utilization for television weather forecasters. Examples will be shown to illustrate the roll of atmospheric rivers and contribution to flooding events, and how the bTPW product was used to improve the forecast of these events. Heavy rains associated with land falling tropical cyclones (TC) frequently trigger floods that cause millions of dollars of damage and tremendous loss

  7. PoPSat: The Polar Precipitation Satellite Mission

    Science.gov (United States)

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

    2017-04-01

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

  8. How Well Can We Estimate Error Variance of Satellite Precipitation Data Around the World?

    Science.gov (United States)

    Gebregiorgis, A. S.; Hossain, F.

    2014-12-01

    The traditional approach to measuring precipitation by placing a probe on the ground will likely never be adequate or affordable in most parts of the world. Fortunately, satellites today provide a continuous global bird's-eye view (above ground) at any given location. However, the usefulness of such precipitation products for hydrological applications depends on their error characteristics. Thus, providing error information associated with existing satellite precipitation estimates is crucial to advancing applications in hydrologic modeling. In this study, we present a method of estimating satellite precipitation error variance using regression model for three satellite precipitation products (3B42RT, CMORPH, and PERSIANN-CCS) using easily available geophysical features and satellite precipitation rate. The goal of this work is to explore how well the method works around the world in diverse geophysical settings. Topography, climate, and seasons are considered as the governing factors to segregate the satellite precipitation uncertainty and fit a nonlinear regression equation as function of satellite precipitation rate. The error variance models were tested on USA, Asia, Middle East, and Mediterranean region. Rain-gauge based precipitation product was used to validate the errors variance of satellite precipitation products. Our study attests that transferability of model estimators (which help to estimate the error variance) from one region to another is practically possible by leveraging the similarity in geophysical features. Therefore, the quantitative picture of satellite precipitation error over ungauged regions can be discerned even in the absence of ground truth data.

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

    Science.gov (United States)

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

    2016-12-01

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

  10. Ozone Profile Retrieval Algorithm (OPERA) for nadir-looking satellite instruments in the UV-VIS

    NARCIS (Netherlands)

    Van Peet, J.C.A.; Van der A, R.J.; Tuinder, O.N.E.; Wolfram, E.; Salvador, J.; Levelt, P.F.; Kelder, H.M.

    2014-01-01

    For the retrieval of the vertical distribution of ozone in the atmosphere the Ozone ProfilE Retrieval Algorithm (OPERA) has been further developed. The new version (1.26) of OPERA is capable of retrieving ozone profiles from UV–VIS observations of most nadir-looking satellite instruments like GOME,

  11. Online Assessment of Satellite-Derived Global Precipitation Products

    Science.gov (United States)

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

    2012-01-01

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

  12. Retrieval of vegetation hydrodynamic parameters from satellite multispectral data

    Science.gov (United States)

    Forzieri, Giovanni; Degetto, Massimo; Righetti, Maurizio; Castelli, Fabio; Preti, Federico

    2013-04-01

    Riparian vegetation plays a crucial role on affecting the floodplain hydraulic roughness, which in turn significantly influences the dynamics of flood waves. This work explores the potential accuracies of retrieving vegetation hydrodynamic parameters through satellite multispectral data. The method is focused on estimation of vegetation height and flexural rigidity for herbaceous patterns and of plant density, tree height, stem diameter, crown base height and crown diameter of high-forest and coppice consociations for arboreal and shrub patterns. The retrieval algorithm performs: (1) classification procedure of riparian corridor; (2) land cover-based Principal Component Analysis of spectral channels; (3) explorative analysis of correlation structure between principal components and biomechanical properties and (4) model identification/estimation/validation for floodplain roughness parameterization. To capture the impacts of stiff/flexible vegetation, a GIS hydrodynamic model has been coupled with a flow resistance external routine that estimates the hydraulic roughness by using simulated water stages and the remote sensing-derived vegetation parameters. The procedure is tested along a 3-km reach of the Avisio river (Trentino Alto Adige, Italy) by comparing extended field surveys and a synchronous SPOT-5 multispectral image acquired on 28/08/2004. Results showed significant correlation values between spectral-derived information and hydrodynamic parameters. Predictive models provided high coefficients of determination, especially for mixed arboreal and shrub land covers. The generated structural parameter maps represent spatially explicit data layers that can be used as inputs to hydrodynamic models to analyze flow resistance effects in different submergence conditions of vegetation. The hydraulic modelling results showed that the new method is able to provide accurate hydraulic output data and to enhance the roughness estimation up to 73% with respect to a

  13. Improved global high resolution precipitation estimation using multi-satellite multi-spectral information

    Science.gov (United States)

    Behrangi, Ali

    In respond to the community demands, combining microwave (MW) and infrared (IR) estimates of precipitation has been an active area of research since past two decades. The anticipated launching of NASA's Global Precipitation Measurement (GPM) mission and the increasing number of spectral bands in recently launched geostationary platforms will provide greater opportunities for investigating new approaches to combine multi-source information towards improved global high resolution precipitation retrievals. After years of the communities' efforts the limitations of the existing techniques are: (1) Drawbacks of IR-only techniques to capture warm rainfall and screen out no-rain thin cirrus clouds; (2) Grid-box- only dependency of many algorithms with not much effort to capture the cloud textures whether in local or cloud patch scale; (3) Assumption of indirect relationship between rain rate and cloud-top temperature that force high intensity precipitation to any cold cloud; (4) Neglecting the dynamics and evolution of cloud in time; (5) Inconsistent combination of MW and IR-based precipitation estimations due to the combination strategies and as a result of above described shortcomings. This PhD dissertation attempts to improve the combination of data from Geostationary Earth Orbit (GEO) and Low-Earth Orbit (LEO) satellites in manners that will allow consistent high resolution integration of the more accurate precipitation estimates, directly observed through LEO's PMW sensors, into the short-term cloud evolution process, which can be inferred from GEO images. A set of novel approaches are introduced to cope with the listed limitations and is consist of the following four consecutive components: (1) starting with the GEO part and by using an artificial-neural network based method it is demonstrated that inclusion of multi-spectral data can ameliorate existing problems associated with IR-only precipitating retrievals; (2) through development of Precipitation Estimation

  14. View of a pallet configured to support 51-A satellite-retrieval mission

    Science.gov (United States)

    1984-01-01

    A high angle view of a Spacelab type pallet configured to support NASA's 51-A satellite-retrieval mission. At left are two capture devices called 'stingers' used to enter the communications satellites at the nozzle of the spent engine. Center are circular areas for clamping down and securing the satellites for the remainder of the trip.

  15. An Evaluation of Satellite Retrievals of Snowfall in Regions of Complex Terrain

    Science.gov (United States)

    Reed, K. A.; Nesbitt, S. W.; Kulie, M.; L'Ecuyer, T. S.; Wood, N.

    2013-12-01

    Snowfall in regions of complex terrain plays an important role in the global hydrologic cycle, and can have major physical and social implications ranging from water resource management, to flash flooding, to climate change impacts. Due to the diversity of impacts that can result from snowfall, the ability to directly observe and measure snowfall in real-time is of great importance. However, the physical limitations of ground-based radars particularly in complex terrain and the lack of spatially complete measurement networks in mountainous regions make high-resolution ground-based snowfall observations a challenging task. Spaceborne satellite retrievals of snowfall such as those that will be made possible by the Global Precipitation Measurement (GPM) mission offer the ability to make high spatial and temporal resolution measurements that are otherwise not possible using traditional ground-based methods. This study seeks to investigate the skill level of current spaceborne snowfall products over the complex terrain of the Rocky Mountains in the western United States. Satellite derived snowfall products from measurements obtained via instruments including the CloudSat Cloud Profiling Radar (CPR), EOS Aqua Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and GCOM-W1 Advanced Microwave Scanning Radiometer 2 (AMSR2) are evaluated using ground-based observations such as the Natural Resources Conservation Service Snow Telemetry (SNOTEL) data and the NCEP Stage IV data. Satellite derived snowfall variables including snowfall rate and snow water equivalent are compared to ground-based observations to determine the overall accuracy and skill level of current satellite derived snowfall products in the region of interest. An analysis is also done to determine how the accuracy and skill level change based on varying snowfall regimes such as light, moderate, and heavy snowfall events. The knowledge gained will be used to determine how satellite derived snowfall

  16. 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.

  17. Analysis of long-term precipitation pattern over Antarctica derived from satellite-borne radar

    Science.gov (United States)

    Milani, L.; Porcù, F.; Casella, D.; Dietrich, S.; Panegrossi, G.; Petracca, M.; Sanò, P.

    2015-01-01

    Mass accumulation is a key geophysical parameter in understanding the Antarctic climate and its role in the global system. The local mass variation is driven by a number of different mechanisms: the deposition of snow and ice crystals on the surface from the atmosphere is generally modified by strong surface winds and variations in temperature and humidity at the ground, making it difficult to measure directly the accumulation by a sparse network of ground based instruments. Moreover, the low cloud total water/ice content and the varying radiative properties of the ground pose problems in the retrieval of precipitation from passive space-borne sensors at all frequencies. Finally, numerical models, despite their high spatial and temporal resolution, show discordant results and are difficult to be validated using ground-based measurements. A significant improvement in the knowledge of the atmospheric contribution to the mass balance over Antarctica is possible by using active space-borne instruments, such as the Cloud Profiling Radar (CPR) on board the low earth orbit CloudSat satellite, launched in 2006 and still operating. The radar measures the vertical profile of reflectivity at 94 GHz (sensitive to small ice particles) providing narrow vertical cross-sections of clouds along the satellite track. The aim of this work is to show that, after accounting for the characteristics of precipitation and the effect of surface on reflectivity in Antarctica, the CPR can retrieve snowfall rates on a single event temporal scale. Furthermore, the CPR, despite its limited temporal and spatial sampling capabilities, also effectively observes the annual snowfall cycle in this region. Two years of CloudSat data over Antarctica are analyzed and converted in water equivalent snowfall rate. Two different approaches for precipitation estimates are considered in this work. The results are analyzed in terms of annual and monthly averages, as well as in terms of instantaneous values. The

  18. Analysis of long-term precipitation pattern over Antarctica derived from satellite-borne radar

    Directory of Open Access Journals (Sweden)

    L. Milani

    2015-01-01

    Full Text Available Mass accumulation is a key geophysical parameter in understanding the Antarctic climate and its role in the global system. The local mass variation is driven by a number of different mechanisms: the deposition of snow and ice crystals on the surface from the atmosphere is generally modified by strong surface winds and variations in temperature and humidity at the ground, making it difficult to measure directly the accumulation by a sparse network of ground based instruments. Moreover, the low cloud total water/ice content and the varying radiative properties of the ground pose problems in the retrieval of precipitation from passive space-borne sensors at all frequencies. Finally, numerical models, despite their high spatial and temporal resolution, show discordant results and are difficult to be validated using ground-based measurements. A significant improvement in the knowledge of the atmospheric contribution to the mass balance over Antarctica is possible by using active space-borne instruments, such as the Cloud Profiling Radar (CPR on board the low earth orbit CloudSat satellite, launched in 2006 and still operating. The radar measures the vertical profile of reflectivity at 94 GHz (sensitive to small ice particles providing narrow vertical cross-sections of clouds along the satellite track. The aim of this work is to show that, after accounting for the characteristics of precipitation and the effect of surface on reflectivity in Antarctica, the CPR can retrieve snowfall rates on a single event temporal scale. Furthermore, the CPR, despite its limited temporal and spatial sampling capabilities, also effectively observes the annual snowfall cycle in this region. Two years of CloudSat data over Antarctica are analyzed and converted in water equivalent snowfall rate. Two different approaches for precipitation estimates are considered in this work. The results are analyzed in terms of annual and monthly averages, as well as in terms of

  19. Retrieval of frontal cloudiness microstructure characteristics from satellite radiometeric data

    Science.gov (United States)

    Bakhanov, V.; Dorman, B.; Kryvobok, A.

    This paper presents results of consecutive numerical simulation of the NOAA satellite signal reflectance of frontal mixed stratiform clouds for channels of AVHRR in visible and near infrared regions of spectrum The simulation is based on the next models a The time-dependent numerical microphysical model of stratiform frontal clouds with 3 forms of ice crystals needles plates columnes b Models of computations of scattering characteristics of drop and crystal systems Simulations of scattering characteristics of liquid drops are based on the Mie theory Simulations of scattering properties of randomly oriented ice crystals are based on the geometric optics and far-field diffraction approximation Computations were realized in visible and near-infrared part of spectrum lambda 1 0 55 mu m lambda 2 1 6 mu m lambda quad 3 quad quad 3 6 quad mu m c The Discrete Ordinate Method DOM for simulation of solar radiation transfer in not uniform clouds Simulations of CR cloud reflrctance show that CR lambda 1 and CR lambda 2 change synchronously with the cloud intrgral optical thickness IOT which is detrmined basically with liquid water content LWC The channel lambda quad 3 3 6 mu m is less sensible to the optical thickness CR lambda 2 and CR lambda 3 are very different in a great LWC region but become close in a region of significant crystallization and precipitation The comparison CR lambda 1 CR lambda quad 2 CR lambda 3 gives

  20. The Passive microwave Neural network Precipitation Retrieval (PNPR algorithm for AMSU/MHS observations: description and application to European case studies

    Directory of Open Access Journals (Sweden)

    P. Sanò

    2014-09-01

    Full Text Available The purpose of this study is to describe a new algorithm based on a Neural Network approach (Passive microwave Neural network Precipitation Retrieval – PNPR for precipitation rate estimation from AMSU/MHS observations, and to provide examples of its performance for specific case studies over the European/Mediterranean area. The algorithm optimally exploits the different characteristics of AMSU-A and MHS channels, and their combinations, including the TB differences of the 183.31 channels, with the goal of having a single neural network for different types of background surfaces (vegetated land, snow covered surface, coast and ocean. The training of the neural network is based on the use of a cloud-radiation database, built from cloud-resolving model simulations coupled to a radiative transfer model, representative of the European and Mediterranean basin precipitation climatology. The algorithm provides also the phase of the precipitation and a pixel-based confidence index for the evaluation of the reliability of the retrieval. Applied to different weather conditions in Europe, the algorithm shows good performance both in the identification of precipitation areas and in the retrieval of precipitation, particularly valuable over the extremely variable environmental and meteorological conditions of the region. In particular, the PNPR is particularly efficient in: (1 screening and retrieval of precipitation over different background surfaces, (2 identification and retrieval of heavy rain for convective events, (3 identification of precipitation over cold/iced background, with some uncertainties affecting light precipitation. In this paper, examples of good agreement of precipitation pattern and intensity with ground-based data (radar and rain gauges are provided for four different case studies. The algorithm has been developed in order to be easily tailored to new radiometers as they become available (such as the cross-track scanning Suomi NPP

  1. On the balance of precipitation and evaporation over global oceans in satellite based and reanalysis data sets

    Science.gov (United States)

    Bakan, S.; Andersson, A.; Fennig, K.; Klepp, C.; Klocke, D.; Schulz, J.

    2009-04-01

    Over the global oceans, precipitation should be smaller than evaporation and the balance should be compensated by the global runoff from land surfaces. But to which extent do satellite climatologies and reanalysis products reproduce this basic feature of the global water cycle? The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data set, HOAPS-3 (www.hoaps.org), contains fields of precipitation and evaporation over the global ocean and all basic state variables needed for the derivation of the fluxes. Except for the NOAA Pathfinder SST data set, all variables are derived from SSM/I satellite data over the ice free global ocean between 1987 and 2005. Special emphasis has been put into quality control and inter-satellite calibration in order to derive the data fields as homogeneous as possible. One of the major design goals of HOAPS was to provide a data set that is based exclusively on retrieval procedures which avoid any additional model or reanalysis input. On a global scale, the average evaporation since 1987 exceeds precipitation rate over the oceans in HOAPS-3 systematically, with almost negligible yearly cycle and small monthly variations. While the globally averaged precipitation time series does not exhibit any significant trend over the study period, evaporation shows a continuous increase during this time. Regionally, this increase concentrates in the subtropics and is, together with some reduction in precipitation, consistent with a strengthening of the Hadley circulation during the observation period. These results are compared with similar data fields of the same period from various satellite climatologies to insure the consistency of our results and to the NCEP and ERA40 as well as ERAInterim reanalysis products. Remarkable similarities and differences between the different information sources have been found and will be discussed in the presentation.

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

    Science.gov (United States)

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

    2016-12-01

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

  3. Assimilation of radar precipitation and satellite data into a NWP model using a physical initialisation scheme

    Science.gov (United States)

    Milan, M.; Schüttemeyer, D.; Venema, V.; Simmer, C.

    2009-04-01

    We implemented a PI (Physical Initialization) method in the non hydrostatic limited-area model COSMO (version 4.2) of the DWD (German Meteorological Service). The goal is the improvement of quantitative rain nowcasting with a high resolution NWP model. Input radar data is a DWD product: the national radar composite for 16 radars with a spatial resolution of one kilometer and a time resolution of 5 minutes. The conversion from reflectivity to rain rate is already made by DWD. This data is interpolated on the LM grid ( 2.8 × 2.8 km resolution) in order to calculate the analysed precipitation rate which depends on the observed precipitation and the model precipitation. The PIB (Physical Initialization Bonn) takes as input the radar based precipitation product and a cloud top height field retrieved from satellite observations, in our case we are using the SAFNWC products generated from Meteosat Second Generation data by DWD. During the assimilation window PIB adjusts the vertical wind, humidity, cloud water and cloud ice in order to force the model state towards the measurements. The most distinctive feature of the algorithm is the adjustment of the vertical wind profile in the framework of a simple precipitation scheme. The PIB assumes that the rain rate is proportional to the vertical humidity flux at cloud base and the vertical wind is adapted according to the conversion efficiency of saturated water vapor into rain water at the cloud base. This parameter is dynamically adjusted by the comparison between the model precipitation and the radar precipitation. The model is tested in convective cases over Germany, an identical twin experiment is used in order to demonstrate the consistency of PIB with the physics of the NWP model. In the tests which we have already performed this method has improved the forecast of the precipitation patterns, as well as the dynamics of the events. These improvements are found both during the assimilation window and for the first hours

  4. Orbiting Retrievable Far and Extreme Ultraviolet Spectrometer - Shuttle Pallet Satellite (ORFEUS-SPAS)

    Science.gov (United States)

    1993-01-01

    The objective of the ORFEUS mission is to launch a deployable/retrievable astronomical platform and obtain ultraviolet spectra for both astrophysically interesting sources and the intervening interstellar medium. Also, the IMAX cameras will obtain footage of both the Shuttle and the ORFEUS-SPAS satellite during the deployment/retrieval operations phase of the ORFEUS-SPAS mission.

  5. Retrieval of aerosol optical depth for Chongqing using the HJ-1 satellite data

    Science.gov (United States)

    Wang, Zengwu; Yang, Shiqi; Zeng, Qiaolin; Wang, Yongqian

    2017-06-01

    Aerosol optical depth (AOD) is a common indicator applied in monitoring aerosols in the atmosphere. The hilly landscape and rapid economic growth of the megacity Chongqing have facilitated increased aerosol concentration, and it is meaningful to accurately retrieve AOD over Chongqing. The HJ-1A/B satellite of China carries a sensor/camera called the Charge Coupled Device (CCD), the spatial resolution of which meets the requirement for retrieving high resolution AOD. In this paper, analysis of the AOD retrievals from different methods using the HJ-1 satellite data revealed the most suitable algorithm. Through comparison with the AOD product of Moderate Resolution Imaging Spectroradiometer (MODIS), the AOD retrieval results using enhanced vegetation index (EVI) to estimate dark pixels showed the highest correlation. The continental aerosol model was used to build a lookup table that was able to facilitate a good AOD retrieval for both city and rural areas. Finally, the algorithm that combined dark pixels, buffer areas, and the deep blue algorithm was found to be most suitable for AOD retrieval. The AOD retrieval results based on the HJ-1 data were consistent with MODIS products, and our algorithm yields reasonable results in most cases. The results were also compared with ground-based PM10 measurements synchronized with the overpass time of the HJ-1 satellite, and high correlation was found. The findings are relevant to other Chinese satellite data used for retrieving AOD on the same channels.

  6. Developments and applications of the Global Satellite Mapping of Precipitation (GSMaP) for the Global Precipitation Measurement (GPM)

    Science.gov (United States)

    Kachi, Misako; Aonashi, Kazumasa; Kubota, Takuji; Shige, Shoichi; Ushio, Tomoo; Mega, Tomoaki; Yamamoto, Munehisa; Hamada, Atsushi; Seto, Shinta; Takayabu, Yukari N.; Oki, Riko

    2016-04-01

    The Global Satellite Mapping of Precipitation (GSMaP) is a global rainfall map based on a blended Microwave-Infrared product and has been developed in Japan for the Global Precipitation Measurement (GPM) mission. To fulfill gaps of passive microwave observations, we developed a method to interpolate observations between each microwave imager by utilizing information from the Infrared imagers on board the geostationary satellites, and achieved production of an hourly global rainfall map in 0.1-degree latitude/longitude grid. The latest GSMaP version 6 product was released in September 2014 to the public as one of Japanese GPM products after the launch of the GPM Core Observatory, which is Japan and U.S. joint mission and carrying both the Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI), in February 2014. In the next version (version 7), which is scheduled to be released in the summer 2016, we plan to apply databases produced from DPR instead of those from PR, and to introduce snow retrieval algorithm for the passive microwave instruments that have higher frequency channels. The GSMaP near-real-time version (GSMaP_NRT) product is available 4-hour after observation through the "JAXA Global Rainfall Watch" web site (http://sharaku.eorc.jaxa.jp/GSMaP) since 2008. To assure near-real-time data availability, the GSMaP_NRT system simplified part of the algorithm and its processing procedure. Therefore, the GSMaP_NRT product gives higher priority to data latency than accuracy. Since its data release, GSMaP_NRT data has been used by various users for various purposes, such as rainfall monitoring, flood alert and warning, drought monitoring, crop yield forecast, and agricultural insurance. There are, however, several requirements from users for GSMaP improvements not only for accuracy but also specification. Among those requests for data specification, the most popular ones are shortening of data latency time and higher horizontal resolution. To reduce

  7. Correcting satellite-based precipitation products from SMOS soil moisture data assimilation using two models of different complexity

    Science.gov (United States)

    Román-Cascón, Carlos; Pellarin, Thierry; Gibon, François

    2017-04-01

    Real-time precipitation information at the global scale is quite useful information for many applications. However, satellite-based precipitation products in real time are known to be biased from real values observed in situ. On the other hand, the information about precipitation contained in soil moisture data can be very useful to improve precipitation estimation, since the evolution of this variable is highly influenced by the amount of rainfall at a certain area after a rain event. In this context, the soil moisture data from the Soil Moisture Ocean Salinity (SMOS) satellite is used to correct the precipitation provided by real-time satellite-based products such as CMORPH, TRMM-3B42RT or PERSIANN. In this work, we test an assimilation algorithm based on the data assimilation of SMOS measurements in two models of different complexity: a simple hydrological model (Antecedent Precipitation Index (API)) and a state-of-the-art complex land-surface model (Surface Externalisée (SURFEX)). We show how the assimilation technique, based on a particle filter method, leads to the improvement of correlation and root mean squared error (RMSE) of precipitation estimates, with slightly better results for the simpler (and less expensive computationally) API model. This methodology has been evaluated for six years in ten sites around the world with different features, showing the limitations of the methodology in regions affected by mountainous terrain or by high radio-frequency interferences (RFI), which notably affect the quality of the soil moisture retrievals from brightness temperatures by SMOS. The presented results are promising for a potential near-real time application at the global scale.

  8. Retrieval of Precipitation Profiles from Multiresolution, Multifrequency, Active and Passive Microwave Observations

    Science.gov (United States)

    Grecu, Mircea; Olson, William S.; Anagnostou, Emmanouil N.

    2003-01-01

    In this study, a technique for estimating vertical profiles of precipitation from multifrequency, multiresolution active and passive microwave observations is investigated. The technique is applicable to the Tropical Rainfall Measuring Mission (TRMM) observations and it is based on models that simulate high-resolution brightness temperatures as functions of observed reflectivity profiles and a parameter related to the rain drop-size-distribution. The modeled high-resolution brightness temperatures are used to determine normalized brightness temperature polarizations at the microwave radiometer resolution. An optimal estimation procedure is employed to minimize the differences between the simulated and observed normalized polarizations by adjusting the drop-size-distribution parameter. The impact of other unknowns that are not independent variables in the optimal estimation but affect the retrievals is minimized through statistical parameterizations derived from cloud model simulations. The retrieval technique is investigated using TRMM observations collected during the Kwajalein Experiment (KWAJEX). These observations cover an area extending from 5 deg to deg N latitude and 166 deg to 172 deg E longitude from July to September 1999, and are coincident with various ground-based observations, facilitating a detailed analysis of the retrieved precipitation. Using the method developed in this study, precipitation estimates consistent with both the passive and active TRMM observations are obtained. Various parameters characterizing these estimates, i.e. the rain rate, the precipitation water content, the drop-size-distribution intercept, and the mass weighted mean drop diameter, are in good qualitative agreement with independent experimental and theoretical estimates. Combined rain estimates are in general higher than the official TRMM Precipitation Radar (PR) only estimates for the area and the period considered in the study. Ground-based precipitation estimates

  9. Meteorological considerations and satellite retrievals in supporting to the assessment of local hydrologic homogeneity over Italy

    Science.gov (United States)

    Gabriele, Salvatore; Laviola, Sante; Chiaravalloti, Francesco

    2014-05-01

    Regional frequency analysis is a useful tool for estimating precipitation quantiles more accurately than at-site frequency analysis, especially in the case of regions with a brief history of short-time rainfall records. Since the rainfalls with short duration are mainly due to convective phenomena, usually affecting areas of few square kilometers, the description of these events with traditional tools such as in-situ rain gauges is often incomplete and not exhaustive. Thus, the application of these datasets to the regional analysis typically provides unrealistic description of the event and large miscalculations of the return time, usually higher than observation. Therefore, in order to evaluate the possible regional homogeneity and improve the performance of hydrologic models the inference analysis of the regional climatic regimes is revealed a useful tool. Starting from the intense rainfall of 19 November 2013 over Southern Italy, we demonstrate that the synoptic meteorological situation well-matched with results of Gabriele & Chiaravalloti (2013a, 2013b) where the regional homogeneity has been calculated on the basis of different climate indexes such as Convective Available Potential Energy (CAPE) and the Q-vector Divergence (QD). In support to that analysis two different methodologies based on satellite microwave information have been applied: the Water vapor Strong Lines at 183 GHz (183-WSL) (Laviola and Levizzani, 2011) algorithm provides to define the precipitation patterns while the MicroWave Cloud Classification (MWCC) (Miglietta et al., 2013) characterizes the cloud type in terms of stratiform and convective. Although, this study is still in progress the current results clearly demonstrate that the Mediterranean storms move on a sort of 'preferential trajectories' especially during the months September-November where the most intense convections have been found. Laviola, S., and V. Levizzani, 2011: The 183-WSL fast rainrate retrieval algorithm. Part I

  10. Satellite Retrieval of Precipitation: An Overview%卫星遥感反演降水研究综述

    Institute of Scientific and Technical Information of China (English)

    刘元波; 傅巧妮; 宋平; 赵晓松; 豆翠翠

    2011-01-01

    Precipitation is a fundamental component of the global water cycle. It is a key hydrologic variable of the water cycle in meteorology, climatology and hydrology. Accurate observation of precipitation and its regional, global distributions has long been a challenging scientific goal. With five-decade development of space-borne sen- sors, the approaches to retrieving precipitation appear mature. This paper briefly describes the principles and the main types of retrieval algorithms of precipitation using visible/infrared (VIS/IR), passive-microwave (PMW), precipitation radar (PR) data, or their combinations. The VIS/IR algorithms generally had relatively low retrieval accuracy, but it could provide better long-term retrieval due to better temporal sampling of geostationary data. The PMW algorithms were more accurate but more complicated than the VIS/IR algorithms in retrieval of instantaneous precipitation, and the PMW data had low spatial and temporal resolution. Among all the PMW algorithms, the God- dard Profiling Algorithm (GPROF) is the most widely applied one. The PR algorithm enabled capture of three-di- mensional precipitation structure over the ocean and land. While the PR retrievals had accuracy on the order of ground-radar data, it had limited coverage of the Earth' s surface. The deficiencies of a single sensor algorithm were alleviated with the combination use of multi-sensors. A number of algorithms have been proposed with a parti- cular combination of VIS/IR, PMW, and/or PR data. The commonly used algorithms include the Climate Predic- tion Center Morphing (CMORPH) algorithm, the Tropical Rainfall Measuring Mission (TRMM) Muhisatellite Pre- cipitation Analysis (TMPA) algorithm and the Global Satellite Mapping of Precipitation (GSMaP) algorithm. Cur- rently, scientific efforts have been made to compare and evaluate the existing algorithms, for example, the Programto Evaluate High-Resolution Precipitation Products

  11. Evaluation of GPM-based Multi-satellite IMERG Precipitation Products Over the Lower Colorado River Basin, Texas

    Science.gov (United States)

    Omranian, S. E.; Sharif, H. O.

    2016-12-01

    This study evaluates the Global Precipitation Measurement (GPM) satellite products by analyzing extreme rainfall events over the Lower Colorado River Basin, Texas that resulted in unprecedented flash floods in May 2015. Records of a dense rain gauge network (241 stations) are compared with Integrated Multi-satellite Retrievals for GPM (IMERG) products. The spatial resolution of the GPM satellite product is 0.1º x 0.1º and the temporal resolution is 30 minutes. Reference gauge-based observations are distributed through the basin with total area of over 5,000 square kilometers at 15-minute time intervals. A preliminary assessment of GPM-based IMERG precipitation products shows reasonable correlation, especially when for periods of high amounts of rainfall. the results indicate that GPM satellite products can potentially be employed in hydrologic modeling, especially for large events. Moreover, since the IMERG products have semi-global coverage, it can be extremely useful in hydrological modeling and analysis studies over ungauged or poorly gauged regions.

  12. 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.

  13. A microwave satellite water vapour column retrieval for polar winter conditions

    Science.gov (United States)

    Perro, Christopher; Lesins, Glen; Duck, Thomas J.; Cadeddu, Maria

    2016-05-01

    A new microwave satellite water vapour retrieval for the polar winter atmosphere is presented. The retrieval builds on the work of Miao et al. (2001) and Melsheimer and Heygster (2008), employing auxiliary information for atmospheric conditions and numerical optimization. It was tested using simulated and actual measurements from the Microwave Humidity Sounder (MHS) satellite instruments. Ground truth was provided by the G-band vapour radiometer (GVR) at Barrow, Alaska. For water vapour columns less than 6 kg m-2, comparisons between the retrieval and GVR result in a root mean square (RMS) deviation of 0.39 kg m-2 and a systematic bias of 0.08 kg m-2. These results are compared with RMS deviations and biases at Barrow for the retrieval of Melsheimer and Heygster (2008), the AIRS and MIRS satellite data products, and the ERA-Interim, NCEP, JRA-55, and ASR reanalyses. When applied to MHS measurements, the new retrieval produces a smaller RMS deviation and bias than for the earlier retrieval and satellite data products. The RMS deviations for the new retrieval were comparable to those for the ERA-Interim, JRA-55, and ASR reanalyses; however, the MHS retrievals have much finer horizontal resolution (15 km at nadir) and reveal more structure. The new retrieval can be used to obtain pan-Arctic maps of water vapour columns of unprecedented quality. It may also be applied to measurements from the Special Sensor Microwave/Temperature 2 (SSM/T2), Advanced Microwave Sounding Unit B (AMSU-B), Special Sensor Microwave Imager/Sounder (SSMIS), Advanced Technology Microwave Sounder (ATMS), and Chinese MicroWave Humidity Sounder (MWHS) instruments.

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

    Directory of Open Access Journals (Sweden)

    Yu Liu

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

  15. 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.

  16. Testing the MODIS Satellite Retrieval of Aerosol Fine-Mode Fraction

    Science.gov (United States)

    Anderson, Theodore L.; Wu, Yonghua; Chu, D. Allen; Schmid, Beat; Redemann, Jens; Dubovik, Oleg

    2005-01-01

    Satellite retrievals of the fine-mode fraction (FMF) of midvisible aerosol optical depth, tau, are potentially valuable for constraining chemical transport models and for assessing the global distribution of anthropogenic aerosols. Here we compare satellite retrievals of FMF from the Moderate Resolution Imaging Spectroradiometer (MODIS) to suborbital data on the submicrometer fraction (SMF) of tau. SMF is a closely related parameter that is directly measurable by in situ techniques. The primary suborbital method uses in situ profiling of SMF combined with airborne Sun photometry both to validate the in situ estimate of ambient extinction and to take into account the aerosol above the highest flight level. This method is independent of the satellite retrieval and has well-known accuracy but entails considerable logistical and technical difficulties. An alternate method uses Sun photometer measurements near the surface and an empirical relation between SMF and the Angstrom exponent, A, a measure of the wavelength dependence of optical depth or extinction. Eleven primary and fifteen alternate comparisons are examined involving varying mixtures of dust, sea salt, and pollution in the vicinity of Korea and Japan. MODIS ocean retrievals of FMF are shown to be systematically higher than suborbital estimates of SMF by about 0.2. The most significant cause of this discrepancy involves the relationship between 5 and fine-mode partitioning; in situ measurements indicate a systematically different relationship from what is assumed in the satellite retrievals. Based on these findings, we recommend: (1) satellite programs should concentrate on retrieving and validating since an excellent validation program is in place for doing this, and (2) suborbital measurements should be used to derive relationships between A and fine-mode partitioning to allow interpretation of the satellite data in terms of fine-mode aerosol optical depth.

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

    Directory of Open Access Journals (Sweden)

    Tarendra Lakhankar

    2013-08-01

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

  18. Satellite-retrieval and modeling of glacier mass balance

    NARCIS (Netherlands)

    Ruyter de Wildt, Martijn Sybren de

    2002-01-01

    In this research project we use satellite measurements to infer the mean specific mass balance (Bm) of glaciers. Vatnajökull, the largest ice cap in Europe, is being used as a test-case because this ice cap has often been studied. Only one aspect of Vatnajökull has not been investigated so far, and

  19. 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.

  20. An algorithm for retrieval of precipitation using microwave humidity sounder channels around 183 GHz

    Science.gov (United States)

    Varma, A. K.; Piyush, D. N.

    2016-05-01

    An algorithm is developed to identify precipitation affected pixels and quantitatively measure the precipitation using Megha-Tropiques humidity sounder (SAPHIR) channels around water vapor absorption line at 183 GHz. Based on observed brightness temperatures at all the six channels of the SAPHIR, a probabilistic rain identification algorithm is proposed. The rain thus identified is subjected to intensive testing using SAPHIR and PR collocated dataset, that showed that false alarm and missing rain is below 0.9 mm/h. Further a radiative transfer simulations supported rain retrieval algorithm is developed that explained a correlation of 0.7 and rmse of 0.81 mm/h. When both precipitation detection and retrieval algorithms are applied the correlation marginally deteriorates but rmse reduces to 0.55 mm/h. Further comparisons are made of monthly, daily and instantaneous rain over different geographical regions from SAPHIR with corresponding rain values from GSMap, TRMM-3B42 V7 and TRMM-TMI/PR, etc. The paper provides details of algorithm development and validation results.

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

    Science.gov (United States)

    Wolff, David B.; Fisher, Brad L.

    2011-01-01

    Space-borne microwave sensors provide critical rain information used in several global multi-satellite rain products, which in turn are used for a variety of important studies, including landslide forecasting, flash flood warning, data assimilation, climate studies, and validation of model forecasts of precipitation. This study employs four years (2003-2006) of satellite data to assess the relative performance and skill of SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), AMSR-E (Aqua) and the TRMM Microwave Imager (TMI) in estimating surface rainfall based on direct instantaneous comparisons with ground-based rain estimates from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The relative performance of each of these satellite estimates is examined via comparisons with space- and time-coincident GV radar-based rain rate estimates. Because underlying surface terrain is known to affect the relative performance of the satellite algorithms, the data for MELB was further stratified into ocean, land and coast categories using a 0.25deg terrain mask. Of all the satellite estimates compared in this study, TMI and AMSR-E exhibited considerably higher correlations and skills in estimating/observing surface precipitation. While SSM/I and AMSU-B exhibited lower correlations and skills for each of the different terrain categories, the SSM/I absolute biases trended slightly lower than AMSR-E over ocean, where the observations from both emission and scattering channels were used in the retrievals. AMSU-B exhibited the least skill relative to GV in all of the relevant statistical categories, and an anomalous spike was observed in the probability distribution functions near 1.0 mm/hr. This statistical artifact appears to be related to attempts by algorithm developers to include some lighter rain rates, not easily detectable by its scatter-only frequencies. AMSU

  2. Retrieval of Atmospheric Horizontal Visibility by Statistical Regression from NOAA/AVHRR Satellite Data

    Institute of Scientific and Technical Information of China (English)

    HUANG Fei; WANG Hong; QIAN Junping; WANG Guofu

    2006-01-01

    Based on the atmospheric horizontal visibility data from forty-seven observational stations along the eastern coast of China near the Taiwan Strait and simultaneous NOAA/AVHRR multichannel satellite data during January 2001 to December 2002, the spectral characters associated with visibility were investigated.Successful retrieval of visibility from multichannel NOAA/AVHRR data was performed using the principal component regression (PCR) method.A sample of retrieved visibility distribution was discussed with a sea fog process.The correlation coefficient between the observed and retrieved visibility was about 0.82, which is far higher than the 99.9% confidence level by statistical test.The rate of successful retrieval is 94.98% of the 458 cases during 2001- 2002.The error distribution showed that high visibilities were usually under-estimated and low visibilities were over-estimated and the relative error between the observed and retrieved visibilities was about 21.4%.

  3. Spatial Distribution of Accuracy of Aerosol Retrievals from Multiple Satellite Sensors

    Science.gov (United States)

    Petrenko, Maksym; Ichoku, Charles

    2012-01-01

    Remote sensing of aerosols from space has been a subject of extensive research, with multiple sensors retrieving aerosol properties globally on a daily or weekly basis. The diverse algorithms used for these retrievals operate on different types of reflected signals based on different assumptions about the underlying physical phenomena. Depending on the actual retrieval conditions and especially on the geographical location of the sensed aerosol parcels, the combination of these factors might be advantageous for one or more of the sensors and unfavorable for others, resulting in disagreements between similar aerosol parameters retrieved from different sensors. In this presentation, we will demonstrate the use of the Multi-sensor Aerosol Products Sampling System (MAPSS) to analyze and intercompare aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS. Based on this intercomparison, we are determining geographical locations where these products provide the greatest accuracy of the retrievals and identifying the products that are the most suitable for retrieval at these locations. The analyses are performed by comparing quality-screened satellite aerosol products to available collocated ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations, during the period of 2006-2010 when all the satellite sensors were operating concurrently. Furthermore, we will discuss results of a statistical approach that is applied to the collocated data to detect and remove potential data outliers that can bias the results of the analysis.

  4. Depiction of global drought by reanalysis and real-time satellite precipitation products

    Science.gov (United States)

    Wood, Eric; Zhan, Wang

    2017-04-01

    Reanalysis precipitation is routinely used as a surrogate of observations due to its high spatial and temporal resolution and global coverage, and thus widely used in hydrologic and agricultural applications. The resultant product is largely dependent on the accuracy of reanalysis precipitation datasets. With advances in satellite remote sensing technology, the latest generation of reanalysis systems starts to include real time satellite precipitation estimates as inputs to their assimilation system. In this presentation, reanalysis precipitations datasets and real-time satellite rainfall products are used for the depiction of global drought events by comparing them against an observational reference dataset, namely the Princeton Global Forcing (PGF) dataset, during the period of March 2000 to December 2012. The selected reanalyses are the Climate Forecast System Reanalysis (CFSR), ERA-Interim, and the Modern-Era Retrospective Analysis for Research and Applications, version 1 (MERRA) and 2 (MERRA-2). Three real-time satellite precipitation estimates; namely the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) 3B42RT, the Climate Prediction Center (CPC) morphing algorithm (CMORPH) and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) are included in the study. Our results show that all datasets depict Sub-Saharan African drought events with limited skill, as opposed to mid latitude regions. Reanalyses and satellite real-time precipitation datasets have comparative skill in the low latitudes. Specific drought events are analyzed that demonstrate the drought depiction from the various datasets. In North America, Asia and Europe, drought events are better replicated and inter-dataset variability is significantly smaller. Overall, temporal characteristics of identified drought events are better estimated than their spatial extent.

  5. Atmospheric correction for sea surface temperature retrieval from single thermal channel radiometer data onboard Kalpana satellite

    Science.gov (United States)

    Shahi, Naveen R.; Agarwal, Neeraj; Mathur, Aloke K.; Sarkar, Abhijit

    2011-06-01

    An atmospheric correction method has been applied on sea surface temperature (SST) retrieval algorithm using Very High Resolution Radiometer (VHRR) single window channel radiance data onboard Kalpana satellite (K-SAT). The technique makes use of concurrent water vapour fields available from Microwave Imager onboard Tropical Rainfall Measuring Mission (TRMM/TMI) satellite. Total water vapour content and satellite zenith angle dependent SST retrieval algorithm has been developed using Radiative Transfer Model [MODTRAN ver3.0] simulations for Kalpana 10.5-12.5 μm thermal window channel. Retrieval of Kalpana SST (K-SST) has been carried out for every half-hourly acquisition of Kalpana data for the year 2008 to cover whole annual cycle of SST over Indian Ocean (IO). Validation of the retrieved corrected SST has been carried out using near-simultaneous observations of ship and buoys datasets covering Arabian Sea, Bay of Bengal and IO regions. A significant improvement in Root Mean Square Deviation (RMSD) of K-SST with respect to buoy (1.50-1.02 K) and to ship datasets (1.41-1.19 K) is seen with the use of near real-time water vapour fields of TMI. Furthermore, comparison of the retrieved SST has also been carried out using near simultaneous observations of TRMM/TMI SST over IO regions. The analysis shows that K-SST has overall cold bias of 1.17 K and an RMSD of 1.09 K after bias correction.

  6. Simulation of land surface temperatures: comparison of two climate models and satellite retrievals

    Directory of Open Access Journals (Sweden)

    J. M. Edwards

    2009-03-01

    Full Text Available Recently there has been significant progress in the retrieval of land surface temperature from satellite observations. Satellite retrievals of surface temperature offer several advantages, including broad spatial coverage, and such data are potentially of great value in assessing general circulation models of the atmosphere. Here, retrievals of the land surface temperature over the contiguous United States are compared with simulations from two climate models. The models generally simulate the diurnal range realistically, but show significant warm biases during the summer. The models' diurnal cycle of surface temperature is related to their surface flux budgets. Differences in the diurnal cycle of the surface flux budget between the models are found to be more pronounced than those in the diurnal cycle of surface temperature.

  7. Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers

    Science.gov (United States)

    Rosenfeld, Daniel; Zheng, Youtong; Hashimshoni, Eyal; Pöhlker, Mira L.; Jefferson, Anne; Pöhlker, Christopher; Yu, Xing; Zhu, Yannian; Liu, Guihua; Yue, Zhiguo; Fischman, Baruch; Li, Zhanqing; Giguzin, David; Goren, Tom; Artaxo, Paulo; Pöschl, Ulrich

    2016-01-01

    Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by Wb and the satellite-retrieved cloud base drop concentrations (Ndb), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25° restricts the satellite coverage to ∼25% of the world area in a single day. PMID:26944081

  8. The Multi-Sensor Aerosol Products Sampling System (MAPSS) for Integrated Analysis of Satellite Retrieval Uncertainties

    Science.gov (United States)

    Ichoku, Charles; Petrenko, Maksym; Leptoukh, Gregory

    2010-01-01

    Among the known atmospheric constituents, aerosols represent the greatest uncertainty in climate research. Although satellite-based aerosol retrieval has practically become routine, especially during the last decade, there is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. As long as there is no consensus and the inconsistencies are not well characterized and understood ', there will be no way of developing reliable climate data records from satellite aerosol measurements. Fortunately, the most globally representative well-calibrated ground-based aerosol measurements corresponding to the satellite-retrieved products are available from the Aerosol Robotic Network (AERONET). To adequately utilize the advantages offered by this vital resource,., an online Multi-sensor Aerosol Products Sampling System (MAPSS) was recently developed. The aim of MAPSS is to facilitate detailed comparative analysis of satellite aerosol measurements from different sensors (Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and Calipso-CALIOP) based on the collocation of these data products over AERONET stations. In this presentation, we will describe the strategy of the MAPSS system, its potential advantages for the aerosol community, and the preliminary results of an integrated comparative uncertainty analysis of aerosol products from multiple satellite sensors.

  9. Evaluation of Satellite and Ground Based Precipitation Products for Flood Forecasting

    Science.gov (United States)

    Chintalapudi, S.; Sharif, H.; Yeggina, S.

    2012-04-01

    The development in satellite-derived rainfall estimates encouraged the hydrological modeling in sparse gauged basins or ungauged basins. Especially, physically-based distributed hydrological models can benefit from the good spatial and temporal coverage of satellite precipitation products. In this study, three satellite derived precipitation datasets (TRMM, CMORPH, and PERSIANN), NEXRAD, and rain gauge precipitation datasets were used to drive the hydrological model. The physically-based, distributed hydrological model Gridded Surface Subsurface Hydrological Analysis (GSSHA) was used in this study. Focus will be on the results from the Guadalupe River Basin above Canyon Lake and below Comfort, Texas. The Guadalupe River Basin above Canyon Lake and below Comfort Texas drains an area of 1232 km2. Different storm events will be used in these simulations. August 2007 event was used as calibration and June 2007 event was used as validation. Results are discussed interms of accuracy of satellite precipitation estimates with the ground based precipitation estimates, predicting peak discharges, runoff volumes, time lag, and spatial distribution. The initial results showed that, model was able to predict the peak discharges and runoff volumes when using NEXRAD MPE data, and TRMM 3B42 precipitation product. The results also showed that there was time lag in hydrographs driven by both PERSIANN and CMORPH data sets.

  10. Influence of 3D Radiative Effects on Satellite Retrievals of Cloud Properties

    Science.gov (United States)

    Varnai, Tamas; Marshak, Alexander; Einaudi, Franco (Technical Monitor)

    2001-01-01

    When cloud properties are retrieved from satellite observations, the calculations apply 1D theory to the 3D world: they only consider vertical structures and ignore horizontal cloud variability. This presentation discusses how big the resulting errors can be in the operational retrievals of cloud optical thickness. A new technique was developed to estimate the magnitude of potential errors by analyzing the spatial patterns of visible and infrared images. The proposed technique was used to set error bars for optical depths retrieved from new MODIS measurements. Initial results indicate that the 1 km resolution retrievals are subject to abundant uncertainties. Averaging over 50 by 50 km areas reduces the errors, but does not remove them completely; even in the relatively simple case of high sun (30 degree zenith angle), about a fifth of the examined areas had biases larger than ten percent. As expected, errors increase substantially for more oblique illumination.

  11. Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

    Directory of Open Access Journals (Sweden)

    Y. Y. Liu

    2010-09-01

    Full Text Available Combining information derived from satellite-based passive and active microwave sensors has the potential to offer improved retrievals of surface soil moisture variations at global scales. Here we propose a technique to take advantage of retrieval characteristics of passive (AMSR-E and active (ASCAT microwave satellite estimates over sparse-to-moderately vegetated areas to obtain an improved soil moisture product. To do this, absolute soil moisture values from AMSR-E and relative soil moisture derived from ASCAT are rescaled against a reference land surface model date set using a cumulative distribution function (CDF matching approach. While this technique imposes the bias of the reference to the rescaled satellite products, it adjusts both satellite products to the same range and almost preserves the correlation between satellite products and in situ measurements. Comparisons with in situ data demonstrated that over the regions where the correlation coefficient between rescaled AMSR-E and ASCAT is above 0.65 (hereafter referred to as transitional regions, merging the different satellite products together increases the number of observations while minimally changing the accuracy of soil moisture retrievals. These transitional regions also delineate the boundary between sparsely and moderately vegetated regions where rescaled AMSR-E and ASCAT are respectively used in the merged product. Thus the merged product carries the advantages of better spatial coverage overall and increased number of observations particularly for the transitional regions. The combination approach developed in this study has the potential to be applied to existing microwave satellites as well as to new microwave missions. Accordingly, a long-term global soil moisture dataset can be developed and extended, enhancing basic understanding of the role of soil moisture in the water, energy and carbon cycles.

  12. Towards a surface radiation climatology: Retrieval of downward irradiances from satellites

    Science.gov (United States)

    Schmetz, Johannes

    Methods are reviewed for retrieving the downward shortwave (0.3-4 μm) and longwave (4-100 μm) irradiances at the earth's surface from satellites. Emphasis is placed on elucidating the physical aspects relevant to the satellite retrieval. For the shortwave irradiance an example of a retrieval is presented. The shortwave retrieval is facilitated by a close linear coupling between the reflected radiance field at the top of the atmosphere and the surface irradiance. A linear relationship between planetary albedo and surface irradiance does also account properly for cloud absorption, since cloud absorption and albedo are linearly related. In the longwave the retrieval is more difficult since only atmospheric window radiances at the top of the atmosphere can bear information on the near-surface radiation field. For the remainder of the longwave spectrum the radiation regimes at the top of the atmosphere and at the surface are decoupled. More than 80% of the clear-sky longwave flux reaching the surface is emitted within the lowest 500 m of the atmosphere. In cloudy conditions the radiation fields at the surface and at the top of the atmosphere are entirely decoupled. Cloud contributions to the surface irradiance are important within the atmospheric window (8-13 μm) and the relative contribution increases in drier climates. Summaries are presented of various techniques devised for both the solar and longwave surface irradiances. A compilation of reported standard errors of shortwave techniques in comparison with ground measurements yields median values of about 5% and 10% for monthly and daily mean values, respectively. Standard errors for the longwave are of the order of 10-25 W m -2. Reported biases are typically of the order of 5 W m -2. For the shortwave retrieval there are fairly good prospects to obtain monthly mean estimates with the requested accuracy of about 10 W m -2 over regional scale areas. The inherent problems of the longwave still entails improvements

  13. A Retrieval of Tropical Latent Heating Using the 3D Structure of Precipitation Features

    Energy Technology Data Exchange (ETDEWEB)

    Ahmed, Fiaz; Schumacher, Courtney; Feng, Zhe; Hagos, Samson

    2016-09-01

    Traditionally, radar-based latent heating retrievals use rainfall to estimate the total column-integrated latent heating and then distribute that heating in the vertical using a model-based look-up table (LUT). In this study, we develop a new method that uses size characteristics of radar-observed precipitating echo (i.e., area and mean echo-top height) to estimate the vertical structure of latent heating. This technique (named the Convective-Stratiform Area [CSA] algorithm) builds on the fact that the shape and magnitude of latent heating profiles are dependent on the organization of convective systems and aims to avoid some of the pitfalls involved in retrieving accurate rainfall amounts and microphysical information from radars and models. The CSA LUTs are based on a high-resolution Weather Research and Forecasting model (WRF) simulation whose domain spans much of the near-equatorial Indian Ocean. When applied to S-PolKa radar observations collected during the DYNAMO/CINDY2011/AMIE field campaign, the CSA retrieval compares well to heating profiles from a sounding-based budget analysis and improves upon a simple rain-based latent heating retrieval. The CSA LUTs also highlight the fact that convective latent heating increases in magnitude and height as cluster area and echo-top heights grow, with a notable congestus signature of cooling at mid levels. Stratiform latent heating is less dependent on echo-top height, but is strongly linked to area. Unrealistic latent heating profiles in the stratiform LUT, viz., a low-level heating spike, an elevated melting layer, and net column cooling were identified and corrected for. These issues highlight the need for improvement in model parameterizations, particularly in linking microphysical phase changes to larger mesoscale processes.

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

    Science.gov (United States)

    Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye

    2016-10-01

    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 (+30 years), 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 evaluate their applicability for agricultural drought evaluation 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-based precipitation estimates. 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-based estimates. Nine statistics were used to evaluate the performance of satellite products to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to

  15. Retrieving leaf area index from SPOT4 satellite data

    Directory of Open Access Journals (Sweden)

    M. Aboelghar

    2010-12-01

    Full Text Available A research project was conducted as collaboration between the National Authority for Remote Sensing and Space Sciences (NARSS in Egypt and the Institute of Remote Sensing Applications (IRSA, Chinese Academy of Sciences. The objective of this study is to generate normalized difference vegetation index (NDVI–leaf area index (LAI statistical inversion models for three rice varieties planted in Egypt (Giza-178, Sakha-102, and Sakha-104 using the data of two rice growing seasons. Field observations were carried out to collect LAI field measurements during 2008 and 2009 rice seasons. The SPOT4 satellite data acquired in rice season of 2008 and 2009 conjunction with field observations dates were used to calculate the vegetation indices values. Statistical analyses were performed to confirm the assumptions of inversion modeling for plant variables and to get reliable models that fit the inversion relationship between LAI and NDVI. The inversion process resulted in three NDVI–LAI models adequate to predict LAI with 95% confidence for the three different rice varieties. The accuracy of the generated models ranged between 50% in the case of Sakha-104 and 82% in the case of Giza-178. LAI maps were produced from NDVI imageries based on the generated models.

  16. Retrieval of fire radiative power and biomass combustion using the Korean geostationary meteorological satellite

    Science.gov (United States)

    Kim, D. S.; Lee, Y. W.

    2013-10-01

    Global warming induced by greenhouse gases is increasing wildfire frequencies and scale. Since wildfire again releases greenhouse gases(GHGs) into the air, the vicious cycle is repeated. Satellite remote sensing is a useful tool for detecting wildfire. However, estimating the GHGs emission from wildfire has not been challenged yet. Wildfires are estimated to be responsible for, on average, around 30% of global total CO emissions, 10% of methane emissions, 38% of tropospheric ozone, and over 86% of black carbon. So we need to quantify the emitted gases by biomass combustions, which can be measured by the FRP (fire radiative power) derived from the spectral characteristics of satellite sensors. This paper described the algorithm for retrieval of FRP using COMS(Communication, Ocean and Meteorological Satellite), the Korean geostationary meteorological satellite. The FRP of wildfire is retrieved by single waveband methods suitable to COMS channels. The retrieval of FRP is dependent on the emissivity of each bandwidth. So, we used MODIS NDVI through a spatio-temporal calibration for the emissivity calculations. We made sure that the FRP in wildfire pixel is much higher than its spatially and temporally neighboring pixels. For future work, we should quantify the relationships between FRP and the biomass combustion according to fuel types.

  17. Surface Emissivity Retrieved with Satellite Ultraspectral IR Measurements for Monitoring Global Change

    Science.gov (United States)

    Zhou, Daniel K.; Larar, Allen M.; Liu, Xu; Smith, William L.; Schluessel, Peter

    2009-01-01

    Surface and atmospheric thermodynamic parameters retrieved with advanced ultraspectral remote sensors aboard Earth observing satellites are critical to general atmospheric and Earth science research, climate monitoring, and weather prediction. Ultraspectral resolution infrared radiance obtained from nadir observations provide atmospheric, surface, and cloud information. Presented here is the global surface IR emissivity retrieved from Infrared Atmospheric Sounding Interferometer (IASI) measurements under "clear-sky" conditions. Fast radiative transfer models, applied to the cloud-free (or clouded) atmosphere, are used for atmospheric profile and surface parameter (or cloud parameter) retrieval. The inversion scheme, dealing with cloudy as well as cloud-free radiances observed with ultraspectral infrared sounders, has been developed to simultaneously retrieve atmospheric thermodynamic and surface (or cloud microphysical) parameters. Rapidly produced surface emissivity is initially evaluated through quality control checks on the retrievals of other impacted atmospheric and surface parameters. Surface emissivity and surface skin temperature from the current and future operational satellites can and will reveal critical information on the Earth s ecosystem and land surface type properties, which can be utilized as part of long-term monitoring for the Earth s environment and global climate change.

  18. Deriving atmospheric visibility from satellite retrieved aerosol optical depth

    Science.gov (United States)

    Riffler, M.; Schneider, Ch.; Popp, Ch.; Wunderle, S.

    2009-04-01

    Atmospheric visibility is a measure that reflects different physical and chemical properties of the atmosphere. In general, poor visibility conditions come along with risks for transportation (e.g. road traffic, aviation) and can negatively impact human health since visibility impairment often implies the presence of atmospheric pollution. Ambient pollutants, particulate matter, and few gaseous species decrease the perceptibility of distant objects. Common estimations of this parameter are usually based on human observations or devices that measure the transmittance of light from an artificial light source over a short distance. Such measurements are mainly performed at airports and some meteorological stations. A major disadvantage of these observations is the gap between the measurements, leaving large areas without any information. As aerosols are one of the most important factors influencing atmospheric visibility in the visible range, the knowledge of their spatial distribution can be used to infer visibility with the so called Koschmieder equation, which relates visibility and atmospheric extinction. In this study, we evaluate the applicability of satellite aerosol optical depth (AOD) products from the Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) to infer atmospheric visibility on large spatial scale. First results applying AOD values scaled with the planetary boundary layer height are promising. For the comparison we use a full automated and objective procedure for the estimation of atmospheric visibility with the help of a digital panorama camera serving as ground truth. To further investigate the relation between the vertical measure of AOD and the horizontal visibility data from the Aerosol Robotic Network (AERONET) site Laegeren (Switzerland), where the digital camera is mounted, are included as well. Finally, the derived visibility maps are compared with synoptical observations in central

  19. Transfer and distortion of atmospheric information in the satellite temperature retrieval problem

    Science.gov (United States)

    Thompson, O. E.

    1981-01-01

    A systematic approach to investigating the transfer of basic ambient temperature information and its distortion by satellite systems and subsequent analysis algorithms is discussed. The retrieval analysis cycle is derived, the variance spectrum of information is examined as it takes different forms in that process, and the quality and quantity of information existing at each stop is compared with the initial ambient temperature information. Temperature retrieval algorithms can smooth, add, or further distort information, depending on how stable the algorithm is, and how heavily influenced by a priori data.

  20. Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR

    Directory of Open Access Journals (Sweden)

    C. A. Poulsen

    2011-04-01

    Full Text Available Clouds play an important role in balancing the Earth's radiation budget. Clouds reflect sunlight which cools the Earth, and also trap infrared radiation in the same manner as greenhouse gases. Changes in cloud cover and cloud properties over time can have important consequences for climate. The Intergovernmental Panel for Climate Change (IPCC has identified current gaps in the understanding of clouds and related climate feedback processes as a leading cause of uncertainty in forecasting climate change. In this paper we present an algorithm that uses optimal estimation to retrieve cloud parameters from satellite multi-spectral imager data, in particular the Along-Track Scanning Radiometers ATSR-2 and AATSR. The cloud parameters retrieved are the cloud top pressure, cloud optical depth, cloud effective radius, cloud fraction and cloud phase. Importantly, the technique also provides estimated errors along with the retrieved values and quantifies the consistency between retrieval representation of cloud and satellite radiances. This should enable the effective use of the products for comparison with climate models or for exploitation via data assimilation. The technique is evaluated by performing retrieval simulations for a variety of simulated single layer and multi-layer conditions. Examples of applying the algorithm to ATSR-2 flight data are presented and the sensitivity of the retrievals assessed. This algorithm has been applied to both ATSR-2 and AATSR visible and infrared measurements in the context of the GRAPE (Global Retrieval and cloud Product Evaluation project to produce a 14 year consistent record for climate research (Sayer et al., 2010.

  1. Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR

    Directory of Open Access Journals (Sweden)

    C. A. Poulsen

    2012-08-01

    Full Text Available Clouds play an important role in balancing the Earth's radiation budget. Hence, it is vital that cloud climatologies are produced that quantify cloud macro and micro physical parameters and the associated uncertainty. In this paper, we present an algorithm ORAC (Oxford-RAL retrieval of Aerosol and Cloud which is based on fitting a physically consistent cloud model to satellite observations simultaneously from the visible to the mid-infrared, thereby ensuring that the resulting cloud properties provide both a good representation of the short-wave and long-wave radiative effects of the observed cloud. The advantages of the optimal estimation method are that it enables rigorous error propagation and the inclusion of all measurements and any a priori information and associated errors in a rigorous mathematical framework. The algorithm provides a measure of the consistency between retrieval representation of cloud and satellite radiances. The cloud parameters retrieved are the cloud top pressure, cloud optical depth, cloud effective radius, cloud fraction and cloud phase.

    The algorithm can be applied to most visible/infrared satellite instruments. In this paper, we demonstrate the applicability to the Along-Track Scanning Radiometers ATSR-2 and AATSR. Examples of applying the algorithm to ATSR-2 flight data are presented and the sensitivity of the retrievals assessed, in particular the algorithm is evaluated for a number of simulated single-layer and multi-layer conditions. The algorithm was found to perform well for single-layer cloud except when the cloud was very thin; i.e., less than 1 optical depths. For the multi-layer cloud, the algorithm was robust except when the upper ice cloud layer is less than five optical depths. In these cases the retrieved cloud top pressure and cloud effective radius become a weighted average of the 2 layers. The sum of optical depth of multi-layer cloud is retrieved well until the cloud becomes thick

  2. Ozone Profile Retrieval from Satellite Observation Using High Spectral Resolution Infrared Sounding Instrument

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper presents a preliminary result on the retrieval of atmospheric ozone profiles using an im proved regression technique and utilizing the data from the Atmospheric InfraRed Sounder (AIRS), a hyper-spectral instrument expected to be flown on the EOS-AQUA platform in 2002. Simulated AIRS spectra were used to study the sensitivity of AIRS radiance on the tropospheric and stratospheric ozone changes, and to study the impact of various channel combinations on the ozone profile retrieval. Sensitivity study results indicate that the AIRS high resolution spectral channels between the wavenumber 650- 800 cm-1 provide very useful information to accurately retrieve tropospheric and stratospheric ozone pro files. Eigenvector decomposition of AIRS spectra indicate that no more than 100 eigenvectors are needed to retrieve very accurate ozone profiles. The accuracy of the retrieved atmospheric ozone profile from the pres ent technique and utilizing the AIRS data was compared with the accuracy obtained from current Advanced TIROS Operational Vertical Sounder (ATOVS) data aboard National Oceanic and Atmospheric Admini stration (NOAA) satellites. As expected, a comparison of retrieval results confirms that the ozone profile re trieved with the AIRS data is superior to that of ATOVS.

  3. Bias adjustment of satellite-based precipitation estimation using gauge observations: A case study in Chile

    Science.gov (United States)

    Yang, Zhongwen; Hsu, Kuolin; Sorooshian, Soroosh; Xu, Xinyi; Braithwaite, Dan; Verbist, Koen M. J.

    2016-04-01

    Satellite-based precipitation estimates (SPEs) are promising alternative precipitation data for climatic and hydrological applications, especially for regions where ground-based observations are limited. However, existing satellite-based rainfall estimations are subject to systematic biases. This study aims to adjust the biases in the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) rainfall data over Chile, using gauge observations as reference. A novel bias adjustment framework, termed QM-GW, is proposed based on the nonparametric quantile mapping approach and a Gaussian weighting interpolation scheme. The PERSIANN-CCS precipitation estimates (daily, 0.04°×0.04°) over Chile are adjusted for the period of 2009-2014. The historical data (satellite and gauge) for 2009-2013 are used to calibrate the methodology; nonparametric cumulative distribution functions of satellite and gauge observations are estimated at every 1°×1° box region. One year (2014) of gauge data was used for validation. The results show that the biases of the PERSIANN-CCS precipitation data are effectively reduced. The spatial patterns of adjusted satellite rainfall show high consistency to the gauge observations, with reduced root-mean-square errors and mean biases. The systematic biases of the PERSIANN-CCS precipitation time series, at both monthly and daily scales, are removed. The extended validation also verifies that the proposed approach can be applied to adjust SPEs into the future, without further need for ground-based measurements. This study serves as a valuable reference for the bias adjustment of existing SPEs using gauge observations worldwide.

  4. Atmospheric correction for sea surface temperature retrieval from single thermal channel radiometer data onboard Kalpana satellite

    Indian Academy of Sciences (India)

    Naveen R Shahi; Neeraj Agarwal; Aloke K Mathur; Abhijit Sarkar

    2011-06-01

    An atmospheric correction method has been applied on sea surface temperature (SST) retrieval algorithm using Very High Resolution Radiometer (VHRR) single window channel radiance data onboard Kalpana satellite (K-SAT). The technique makes use of concurrent water vapour fields available from Microwave Imager onboard Tropical Rainfall Measuring Mission (TRMM/TMI) satellite. Total water vapour content and satellite zenith angle dependent SST retrieval algorithm has been developed using Radiative Transfer Model [MODTRAN ver3.0] simulations for Kalpana 10.5–12.5 m thermal window channel. Retrieval of Kalpana SST (K-SST) has been carried out for every half-hourly acquisition of Kalpana data for the year 2008 to cover whole annual cycle of SST over Indian Ocean (IO). Validation of the retrieved corrected SST has been carried out using near-simultaneous observations of ship and buoys datasets covering Arabian Sea, Bay of Bengal and IO regions. A significant improvement in Root Mean Square Deviation (RMSD) of K-SST with respect to buoy (1.50–1.02 K) and to ship datasets (1.41–1.19 K) is seen with the use of near real-time water vapour fields of TMI. Furthermore, comparison of the retrieved SST has also been carried out using near simultaneous observations of TRMM/TMI SST over IO regions. The analysis shows that K-SST has overall cold bias of 1.17 K and an RMSD of 1.09 K after bias correction.

  5. Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers

    OpenAIRE

    2016-01-01

    Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting wea...

  6. Evaluation of satellite-based precipitation estimates in winter season using an object-based approach

    Science.gov (United States)

    Li, J.; Hsu, K.; AghaKouchak, A.; Sorooshian, S.

    2012-12-01

    Verification has become an integral component of satellite precipitation algorithms and products. A number of object-based verification methods have been proposed to provide diagnostic information regarding the precipitation products' ability to capture the spatial pattern, intensity, and placement of precipitation. However, most object-based methods are not capable of investigating precipitation objects at the storm-scale. In this study, an image processing approach known as watershed segmentation was adopted to detect the storm-scale rainfall objects. Then, a fuzzy logic-based technique was utilized to diagnose and analyze storm-scale object attributes, including centroid distance, area ratio, intersection area ratio and orientation angle difference. Three verification metrics (i.e., false alarm ratio, missing ratio and overall membership score) were generated for validation and verification. Three satellite-based precipitation products, including PERSIANN, CMORPH, 3B42RT, were evaluated against NOAA stage IV MPE multi-sensor composite rain analysis at 0.25° by 0.25° on a daily scale in the winter season of 2010 over the contiguous United States. Winter season is dominated by frontal systems which usually have larger area coverage. All three products and the stage IV observation tend to find large size storm objects. With respect to the evaluation attributes, PERSIANN tends to obtain larger area ratio and consequently has larger centroid distance to the stage IV observations, while 3B42RT are found to be closer to the stage IV for the object size. All evaluation products give small orientation angle differences but vary significantly for the missing ratio and false alarm ratio. This implies that satellite estimates can fail to detect storms in winter. The overall membership scores are close for all three different products which indicate that all three satellite-based precipitation products perform well for capturing the spatial and geometric characteristics of

  7. Retrieving latent heating vertical structure from cloud and precipitation Profiles—Part I: Warm rain processes

    Science.gov (United States)

    Min, Qilong; Li, Rui; Wu, Xiaoqing; Fu, Yunfei

    2013-06-01

    An exploratory study on physical based latent heat (LH) retrieval algorithm is conducted by parameterizing the physical linkages of hydrometeor profiles of cloud and precipitation to the major processes related to the phase change of atmospheric water. Specifically, rain events are segregated into three rain types: warm, convective, and stratiform, based on their dynamical and thermodynamical characteristics. As the first of the series, only the warm rain LH algorithm is presented and evaluated here. The major microphysical processes of condensation and evaporation for warm rain are parameterized through traditional rain growth theory, with the aid of Cloud Resolving Model (CRM) simulations. The evaluation or the self-consistency tests indicate that the physical based retrievals capture the fundamental LH processes associated with the warm rain life cycle. There is no significant systematic bias in terms of convection strength, illustrated by the month-long CRM simulation as the mesoscale convective systems (MCSs) experience from initial, mature, to decay stages. The overall monthly-mean LH comparison showed that the total LH, as well as condensation heating and evaporation cooling components, agree with the CRM simulation.

  8. Evaluation of Land Surface Temperature Operationally Retrieved from Korean Geostationary Satellite (COMS Data

    Directory of Open Access Journals (Sweden)

    A-Ra Cho

    2013-08-01

    Full Text Available We evaluated the precision of land surface temperature (LST operationally retrieved from the Korean multipurpose geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS. The split-window (SW-type retrieval algorithm was developed through radiative transfer model simulations under various atmospheric profiles, satellite zenith angles, surface emissivity values and surface lapse rate conditions using Moderate Resolution Atmospheric Transmission version 4 (MODTRAN4. The estimation capabilities of the COMS SW (CSW LST algorithm were evaluated for various impacting factors, and the retrieval accuracy of COMS LST data was evaluated with collocated Moderate Resolution Imaging Spectroradiometer (MODIS LST data. The surface emissivity values for two SW channels were generated using a vegetation cover method. The CSW algorithm estimated the LST distribution reasonably well (averaged bias = 0.00 K, Root Mean Square Error (RMSE = 1.41 K, correlation coefficient = 0.99; however, the estimation capabilities of the CSW algorithm were significantly impacted by large brightness temperature differences and surface lapse rates. The CSW algorithm reproduced spatiotemporal variations of LST comparing well to MODIS LST data, irrespective of what month or time of day the data were collected from. The one-year evaluation results with MODIS LST data showed that the annual mean bias, RMSE and correlation coefficient for the CSW algorithm were −1.009 K, 2.613 K and 0.988, respectively.

  9. Applying satellite retrievals to identify urban emissions of GHG's over East Asia

    Science.gov (United States)

    Shim, C.; Henze, D. K.

    2016-12-01

    Here we have used satellite retrievals to identify GHG's emissions over East Asia. With multi-year GOSAT CO2/CH4 products (2009 - 2014) and recent OCO-2 retrievals (2014 - 2015), better availability of the data enabled to show the regional/local scale (less than 1° x 1° spatial resolution) urban GHG's emissions. We identified the urban emissions from the enhanced values of xCO2/xCH4 and estimated the correlation of those signals with available GHG's emissions inventory over East Asia. Also, some of those retrievals were compared with ground/aircraft measurements to verify those remotely sensed data. Those efforts are useful to identify regional/local anthropogenic GHG's emissions over East Asia where the GHG's emissions inventories are still uncertain, which can support government policy to mitigate air pollution. In addition, we introduce our efforts to constrain the emissions of CO2 from GOSAT/OCO-2 data using 4-Dvar inverse modeling framework and we show some preliminary results. This study represents the current progress to understand sub-continental scale atmospheric CO2 variabilities and its emissions with recent satellite retrievals and advanced modeling.

  10. A New Algorithm for the Satellite-Based Retrieval of Solar Surface Irradiance in Spectral Bands

    Directory of Open Access Journals (Sweden)

    Annette Hammer

    2012-03-01

    Full Text Available Accurate solar surface irradiance data is a prerequisite for an efficient planning and operation of solar energy systems. Further, it is essential for climate monitoring and analysis. Recently, the demand on information about spectrally resolved solar surface irradiance has grown. As surface measurements are rare, satellite derived information with high accuracy might fill this gap. This paper describes a new approach for the retrieval of spectrally resolved solar surface irradiance from satellite data. The method combines a eigenvector-hybrid look-up table approach for the clear sky case with satellite derived cloud transmission (Heliosat method. The eigenvector LUT approach is already used to retrieve the broadband solar surface irradiance of data sets provided by the Climate Monitoring Satellite Application Facility (CM-SAF. This paper describes the extension of this approach to wavelength bands and the combination with spectrally resolved cloud transmission values derived with radiative transfer corrections of the broadband cloud transmission. Thus, the new approach is based on radiative transfer modeling and enables the use of extended information about the atmospheric state, among others, to resolve the effect of water vapor and ozone absorption bands. The method is validated with spectrally resolved measurements from two sites in Europe and by comparison with radiative transfer calculations. The validation results demonstrate the ability of the method to retrieve accurate spectrally resolved irradiance from satellites. The accuracy is in the range of the uncertainty of surface measurements, with exception of the UV and NIR ( ≥ 1200 nm part of the spectrum, where higher deviations occur.

  11. Global Precipitation: Means, Variations and Trends During the Satellite Era (1979-2014)

    Science.gov (United States)

    Adler, Robert F.; Gu, Guojun; Sapiano, Matthew; Wang, Jian-Jian; Huffman, George J.

    2017-07-01

    Global precipitation variations over the satellite era are reviewed using the Global Precipitation Climatology Project (GPCP) monthly, globally complete analyses, which integrate satellite and surface gauge information. Mean planetary values are examined and compared, over ocean, with information from recent satellite programs and related estimates, with generally positive agreements, but with some indication of small underestimates for GPCP over the global ocean. Variations during the satellite era in global precipitation are tied to ENSO events, with small increases during El Ninos, and very noticeable decreases after major volcanic eruptions. No overall significant trend is noted in the global precipitation mean value, unlike that for surface temperature and atmospheric water vapor. However, there is a pattern of positive and negative trends across the planet with increases over tropical oceans and decreases over some middle latitude regions. These observed patterns are a result of a combination of inter-decadal variations and the effect of the global warming during the period. The results reviewed here indicate the value of such analyses as GPCP and the possible improvement in the information as the record lengthens and as new, more sophisticated and more accurate observations are included.

  12. High-resolution satellite-gauge merged precipitation climatologies of the Tropical Andes

    Science.gov (United States)

    Manz, Bastian; Buytaert, Wouter; Zulkafli, Zed; Lavado, Waldo; Willems, Bram; Robles, Luis Alberto; Rodríguez-Sánchez, Juan-Pablo

    2016-02-01

    Satellite precipitation products are becoming increasingly useful to complement rain gauge networks in regions where these are too sparse to capture spatial precipitation patterns, such as in the Tropical Andes. The Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (TPR) was active for 17 years (1998-2014) and has generated one of the longest single-sensor, high-resolution, and high-accuracy rainfall records. In this study, high-resolution (5 km) gridded mean monthly climatological precipitation is derived from the raw orbital TPR data (TRMM 2A25) and merged with 723 rain gauges using multiple satellite-gauge (S-G) merging approaches. The resulting precipitation products are evaluated by cross validation and catchment water balances (runoff ratios) for 50 catchments across the Tropical Andes. Results show that the TPR captures major synoptic and seasonal precipitation patterns and also accurately defines orographic gradients but underestimates absolute monthly rainfall rates. The S-G merged products presented in this study constitute an improved source of climatological rainfall data, outperforming the gridded TPR product as well as a rain gauge-only product based on ordinary Kriging. Among the S-G merging methods, performance of inverse distance interpolation of satellite-gauge residuals was similar to that of geostatistical methods, which were more sensitive to gauge network density. High uncertainty and low performance of the merged precipitation products predominantly affected regions with low and intermittent precipitation regimes (e.g., Peruvian Pacific coast) and is likely linked to the low TPR sampling frequency. All S-G merged products presented in this study are available in the public domain.

  13. 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

  14. Real-time retrieval of precipitable water vapor from GPS precise point positioning

    Science.gov (United States)

    Yuan, Yubin; Zhang, Kefei; Rohm, Witold; Choy, Suelynn; Norman, Robert; Wang, Chuan-Sheng

    2014-08-01

    Sensing of precipitable water vapor (PWV) using the Global Positioning System (GPS) has been intensively investigated in the past 2 decades. However, it still remains a challenging task at a high temporal resolution and in the real-time mode. In this study the accuracy of real-time zenith total delay (ZTD) and PWV using the GPS precise point positioning (PPP) technique is investigated. GPS observations in a 1 month period from 20 globally distributed stations are selected for testing. The derived real-time ZTDs at most stations agree well with the tropospheric products from the International Global Navigation Satellite Systems Service, and the root-mean-square errors (RMSEs) are conditions. This implies that the real-time GPS PPP technique can be complementary to current atmospheric sounding systems, especially for nowcasting of extreme weather due to its real-time, all-day, and all-weather capabilities and high temporal resolutions.

  15. Clouds-Aerosols-Precipitation Satellite Analysis Tool (CAPSAT

    Directory of Open Access Journals (Sweden)

    I. M. Lensky

    2008-03-01

    Full Text Available A methodology for representing much of the physical information content of the METEOSAT Second Generation (MSG geostationary satellite using red-green-blue (RGB composites of the computed physical values of the picture elements is presented. The physical values are the solar reflectance in the solar channels and brightness temperature in the thermal channels. The main RGB compositions are (1 "Day Natural Colors", presenting vegetation in green, bare surface in brown, sea surface in black, water clouds as white, ice as magenta; (2 "Day Microphysical", presenting cloud microstructure using the solar reflectance component of the 3.9 μm, visible and thermal IR channels; (3 "Night Microphysical", also presenting clouds microstructure using the brightness temperature differences between 10.8 and 3.9 μm; (4 "Day and Night", using only thermal channels for presenting surface and cloud properties, desert dust and volcanic emissions; (5 "Air Mass", presenting mid and upper tropospheric features using thermal water vapor and ozone channels. The scientific basis for these rendering schemes is provided, with examples for the applications. The expanding use of these rendering schemes requires their proper documentation and setting as standards, which is the main objective of this publication.

  16. Soil Moisture Retrieval Using Reflected Signals of BeiDou GEO Satellites

    Directory of Open Access Journals (Sweden)

    ZOU Wenbo

    2016-02-01

    Full Text Available This paper proposes a method of continuous long-term soil moisture measurement using signals from BeiDou GEO satellites. It also presents the soil moisture inversion model as well as the relevant signal processing steps. Moreover, a land-based experiment is carried out to verify its validity. This method adopts the dual-antenna Global Navigation Satellite System Reflection (GNSS-R mode to receive and process direct signal from BeiDou GEO satellites and reflected signal from soil. Based on signal synchronization, the reflectivity of soil can be calculated according to the extracted signal power values. And then, the soil moisture can be obtained in light of the inversion model. By taking singals from BeiDou GEO satellites, not only the positioning calculation step of general GNSS-R data processing can be ignored, but also a continuous long-term observation of soil moisture for fixed area can be realized. Experiment results based on the method above show a good continuity in both time and magnitude. They are also highly consistent with reference values and the root mean square error equals to 0.049. Compared with BeiDou IGSO and GPS MEO satellites, BeiDou GEO satellites can present a better performance in soil moisture retrieval.

  17. Observations of Three-Dimensional Radiative Effects that Influence Satellite Retrievals of Cloud Properties

    Science.gov (United States)

    Varnai, Tamas; Marshak, Alexander; Lau, William K. M. (Technical Monitor)

    2001-01-01

    This paper examines three-dimensional (3D) radiative effects, which arise from horizontal radiative interactions between areas that have different cloud properties. Earlier studies have argued that these effects can cause significant uncertainties in current satellite retrievals of cloud properties, because the retrievals rely on one-dimensional (1D) theory and do not consider the effects of horizontal changes in cloud properties. This study addresses two questions: which retrieved cloud properties are influenced by 3D radiative effects, and where 3D effects tend to occur? The influence of 3D effects is detected from the wayside illumination and shadowing make clouds appear asymmetric: Areas appear brighter if the cloud top surface is tilted toward, rather than away from, the Sun. The analysis of 30 images by the Moderate Resolution Imaging Spectroradiometer (MODIS) reveals that retrievals of cloud optical thickness and cloud water content are most influenced by 3D effects, whereas retrievals of cloud particle size are much less affected. The results also indicate that while 3D effects are strongest at cloud edges, cloud top variability in cloud interiors, even in overcast regions, also produces considerable 3D effects. Finally, significant 3D effects are found in a wide variety of situations, ranging from thin clouds to thick ones and from low clouds to high ones.

  18. A method for retrieving clouds with satellite infrared radiances using the particle filter

    Science.gov (United States)

    Xu, Dongmei; Auligné, Thomas; Descombes, Gaël; Snyder, Chris

    2016-11-01

    Ensemble-based techniques have been widely utilized in estimating uncertainties in various problems of interest in geophysical applications. A new cloud retrieval method is proposed based on the particle filter (PF) by using ensembles of cloud information in the framework of Gridpoint Statistical Interpolation (GSI) system. The PF cloud retrieval method is compared with the Multivariate Minimum Residual (MMR) method that was previously established and verified. Cloud retrieval experiments involving a variety of cloudy types are conducted with the PF and MMR methods with measurements of infrared radiances on multi-sensors onboard both geostationary and polar satellites, respectively. It is found that the retrieved cloud masks with both methods are consistent with other independent cloud products. MMR is prone to producing ambiguous small-fraction clouds, while PF detects clearer cloud signals, yielding closer heights of cloud top and cloud base to other references. More collections of small-fraction particles are able to effectively estimate the semi-transparent high clouds. It is found that radiances with high spectral resolutions contribute to quantitative cloud top and cloud base retrievals. In addition, a different way of resolving the filtering problem over each model grid is tested to better aggregate the weights with all available sensors considered, which is proven to be less constrained by the ordering of sensors. Compared to the MMR method, the PF method is overall more computationally efficient, and the cost of the model grid-based PF method scales more directly with the number of computing nodes.

  19. Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

    Directory of Open Access Journals (Sweden)

    Y. Y. Liu

    2011-02-01

    Full Text Available Combining information derived from satellite-based passive and active microwave sensors has the potential to offer improved estimates of surface soil moisture at global scale. We develop and evaluate a methodology that takes advantage of the retrieval characteristics of passive (AMSR-E and active (ASCAT microwave satellite estimates to produce an improved soil moisture product. First, volumetric soil water content (m3 m−3 from AMSR-E and degree of saturation (% from ASCAT are rescaled against a reference land surface model data set using a cumulative distribution function matching approach. While this imposes any bias of the reference on the rescaled satellite products, it adjusts them to the same range and preserves the dynamics of original satellite-based products. Comparison with in situ measurements demonstrates that where the correlation coefficient between rescaled AMSR-E and ASCAT is greater than 0.65 ("transitional regions", merging the different satellite products increases the number of observations while minimally changing the accuracy of soil moisture retrievals. These transitional regions also delineate the boundary between sparsely and moderately vegetated regions where rescaled AMSR-E and ASCAT, respectively, are used for the merged product. Therefore the merged product carries the advantages of better spatial coverage overall and increased number of observations, particularly for the transitional regions. The combination method developed has the potential to be applied to existing microwave satellites as well as to new missions. Accordingly, a long-term global soil moisture dataset can be developed and extended, enhancing basic understanding of the role of soil moisture in the water, energy and carbon cycles.

  20. Impact of sea surface temperature on satellite retrieval of sea surface salinity

    Science.gov (United States)

    Jin, Xuchen; Zhu, Qiankun; He, Xianqiang; Chen, Peng; Wang, Difeng; Hao, Zengzhou; Huang, Haiqing

    2016-10-01

    Currently, global sea surface salinity (SSS) can be retrieved by the satellite microwave radiometer onboard the satellite, such as the Soil Moisture and Ocean Salinity(SMOS) and the Aqurius. SMOS is an Earth Explorer Opportunity Mission from the European Space Agency(ESA). It was launched at a sun-synchronous orbit in 2009 and one of the payloads is called MIRAS(Microwave Imaging Radiometer using Aperture Synthesis), which is the first interferometric microwave radiometer designed for observing SSS at L-band(1.41 GHz).The foundation of the salinity retrieval by microwave radiometer is that the sea surface radiance at L-band has the most suitable sensitivity with the variation of the salinity. It is well known that the sensitivity of brightness temperatures(TB) to SSS depends on the sea surface temperature (SST), but the quantitative impact of the SST on the satellite retrieval of the SSS is still poorly known. In this study, we investigate the impact of the SST on the accuracy of salinity retrieval from the SMOS. First of all, The dielectric constant model proposed by Klein and Swift has been used to estimate the vertically and horizontally polarized brightness temperatures(TV and TH) of a smooth sea water surface at L-band and derive the derivatives of TV and TH as a function of SSS to show the relative sensitivity at 45° incident angle. Then, we use the GAM(generalized additive model) method to evaluate the association between the satellite-measured brightness temperature and in-situ SSS at different SST. Moreover, the satellite-derived SSS from the SMOS is validated using the ARGO data to assess the RMSE(root mean squared error). We compare the SMOS SSS and ARGO SSS over two regions of Pacific ocean far from land and ice under different SST. The RMSE of retrieved SSS at different SST have been estimated. Our results showed that SST is one of the most significant factors affecting the accuracy of SSS retrieval. The satellite-measured brightness temperature has a

  1. Assessment of North Atlantic Precipitation and Freshwater Flux from the HOAPS-3 satellite climatology

    Science.gov (United States)

    Andersson, A.; Klepp, C.; Bakan, S.; Schulz, J.

    2009-04-01

    To attain a better understanding and modeling of climate processes attaining a proper knowledge of global water cycle components is essential. For the assessment of the freshwater flux at the ocean surface on global scale, exchange processes at the air-sea interface play a key-role. With the ability to derive ocean latent heat flux and precipitation from satellite data with acceptable accuracy, and frequent global coverage, a climatological assessment of the crucial processes has become possible. The HOAPS-3 climatology (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data) contains fields of precipitation, surface fluxes and atmospheric parameters over the global ice-free ocean between 1987 and 2005. Except for the NOAA Pathfinder SST, all basic state variables needed for the derivation of the fluxes are calculated from SSM/I passive microwave radiometer measurements. Multi-satellite averages, inter-sensor calibration, and an efficient sea ice detection procedure make HOAPS a suitable data set for climatological applications as well as for case studies. Gridded 0.5 degree monthly, pentad and twice daily data products are freely available from www.hoaps.org. For the precipitation parameter, quasi-global coverage is achieved by complementing HOAPS-3 over land areas using the rain gauge based "Full Data Reanalysis Product Version 4", which is provided by the Global Precipitation Climatology Centre (GPCC). North Atlantic intra-decadal precipitation variability is investigated using this combined data set. The mutual response of the two independent precipitation data sources to the North Atlantic Oscillation (NAO) reveals coherent patterns and a detailed view on the structural changes in precipitation during the high and low states of the NAO. A second focus will be put on the evaluation of HOAPS-3 ocean surface freshwater fluxes and their interaction with the NAO.

  2. Interannual Variability of Tropical Precipitation: How Well Do Climate Models Agree With Current Satellite Estimates?

    Science.gov (United States)

    Robertson, Franklin R.; Marshall, Susan; Roads, John; Oglesby, Robert J.; Fitzjarrald, Dan; Goodman, H. Michael (Technical Monitor)

    2001-01-01

    Since the beginning of the World Climate Research Program's Global Precipitation Climatology Project (GPCP) satellite remote sensing of precipitation has made dramatic improvements, particularly for tropical regions. Data from microwave and infrared sensors now form the most critical input to precipitation data sets and can be calibrated with surface gauges to so that the strengths of each data source can be maximized in some statistically optimal sense. Recent availability of the TRMM (Tropical Rainfall Measuring Mission) has further aided in narrowing uncertainties in rainfall over die tropics and subtropics. Although climate modeling efforts have long relied on space-based precipitation estimates for validation, we now are in a position to make more quantitative assessments of model performance, particularly in tropical regions. An integration of the CCM3 using observed SSTs as a lower boundary condition is used to examine how well this model responds to ENSO forcing in terms of anomalous precipitation. An integration of the NCEP spectral model used for the Reanalysis-H effort is also examined. This integration is run with specified SSTs, but with no data assimilation. Our analysis focuses on two aspects of inter-annual variability. First are the spatial anomalies that are indicative of dislocations in Hadley and Walker circulations. Second, we consider the ability of models to replicate observed increases in oceanic precipitation that are noted in satellite observations for large ENSO events. Finally, we consider a slab ocean version of the CCM3 model with prescribed ocean beat transports that mimic upwelling anomalies, but which still allows the surface energy balance to be predicted. This less restrictive experiment is used to understand why model experiments with specified SSTs seem to have noticeably less interannual variability in precipitation than do the satellite observations.

  3. Structural uncertainty in air mass factor calculation for NO2 and HCHO satellite retrievals

    Science.gov (United States)

    Lorente, Alba; Folkert Boersma, K.; Yu, Huan; Dörner, Steffen; Hilboll, Andreas; Richter, Andreas; Liu, Mengyao; Lamsal, Lok N.; Barkley, Michael; De Smedt, Isabelle; Van Roozendael, Michel; Wang, Yang; Wagner, Thomas; Beirle, Steffen; Lin, Jin-Tai; Krotkov, Nickolay; Stammes, Piet; Wang, Ping; Eskes, Henk J.; Krol, Maarten

    2017-03-01

    Air mass factor (AMF) calculation is the largest source of uncertainty in NO2 and HCHO satellite retrievals in situations with enhanced trace gas concentrations in the lower troposphere. Structural uncertainty arises when different retrieval methodologies are applied within the scientific community to the same satellite observations. Here, we address the issue of AMF structural uncertainty via a detailed comparison of AMF calculation methods that are structurally different between seven retrieval groups for measurements from the Ozone Monitoring Instrument (OMI). We estimate the escalation of structural uncertainty in every sub-step of the AMF calculation process. This goes beyond the algorithm uncertainty estimates provided in state-of-the-art retrievals, which address the theoretical propagation of uncertainties for one particular retrieval algorithm only. We find that top-of-atmosphere reflectances simulated by four radiative transfer models (RTMs) (DAK, McArtim, SCIATRAN and VLIDORT) agree within 1.5 %. We find that different retrieval groups agree well in the calculations of altitude resolved AMFs from different RTMs (to within 3 %), and in the tropospheric AMFs (to within 6 %) as long as identical ancillary data (surface albedo, terrain height, cloud parameters and trace gas profile) and cloud and aerosol correction procedures are being used. Structural uncertainty increases sharply when retrieval groups use their preference for ancillary data, cloud and aerosol correction. On average, we estimate the AMF structural uncertainty to be 42 % over polluted regions and 31 % over unpolluted regions, mostly driven by substantial differences in the a priori trace gas profiles, surface albedo and cloud parameters. Sensitivity studies for one particular algorithm indicate that different cloud correction approaches result in substantial AMF differences in polluted conditions (5 to 40 % depending on cloud fraction and cloud pressure, and 11 % on average) even for low

  4. Satellite observation of atmospheric methane: intercomparison between AIRS and GOSAT TANSO-FTS retrievals

    Science.gov (United States)

    Zou, Mingmin; Xiong, Xiaozhen; Saitoh, Naoko; Warner, Juying; Zhang, Ying; Chen, Liangfu; Weng, Fuzhong; Fan, Meng

    2016-08-01

    Space-borne observations of atmospheric methane (CH4) have been made using the Atmospheric Infrared Sounder (AIRS) on the EOS/Aqua satellite since August 2002 and the Thermal and Near-infrared Sensor for Carbon Observation Fourier Transform Spectrometer (TANSO-FTS) on the Greenhouse Gases Observing Satellite (GOSAT) since April 2009. This study compared the GOSAT TANSO-FTS thermal infrared (TIR) version 1.0 CH4 product with the collocated AIRS version 6 CH4 product using data from 1 August 2010 to 30 June 2012, including the CH4 mixing ratios and the total column amounts. The results show that at 300-600 hPa, where both AIRS and GOSAT-TIR CH4 have peak sensitivities, they agree very well, but GOSAT-TIR retrievals tend to be higher than AIRS in layer 200-300 hPa. At 300 hPa the CH4 mixing ratio from GOSAT-TIR is, on average, 10.3 ± 31.8 ppbv higher than that from AIRS, and at 600 hPa GOSAT-TIR retrieved CH4 is -16.2 ± 25.7 ppbv lower than AIRS CH4. Comparison of the total column amount of CH4 shows that GOSAT-TIR agrees with AIRS to within 1 % in the mid-latitude regions of the Southern Hemisphere and in the tropics. In the mid to high latitudes in the Northern Hemisphere, comparison shows that GOSAT-TIR is ˜ 1-2 % lower than AIRS, and in the high-latitude regions of the Southern Hemisphere the difference of GOSAT from AIRS varies from -3 % in October to +2 % in July. The difference between AIRS and GOSAT TANSO-FTS retrievals is mainly due to the difference in retrieval algorithms and instruments themselves, and the larger difference in the high-latitude regions is associated with the low information content and small degrees of freedom of the retrieval. The degrees of freedom of GOSAT-TIR retrievals are lower than that of AIRS, which also indicates that the constraint in GOSAT-TIR retrievals may be too strong. From the good correlation between AIRS and GOSAT-TIR retrievals and the seasonal variation they observed, we are confident that the thermal infrared

  5. An improved NO2 retrieval for the GOME-2 satellite instrument

    Directory of Open Access Journals (Sweden)

    J. P. Burrows

    2011-01-01

    Full Text Available Satellite observations of nitrogen dioxide (NO2 provide valuable information on both stratospheric and tropospheric composition. Nadir measurements from GOME, SCIAMACHY, OMI, and GOME-2 have been used in many studies on tropospheric NO2 burdens, the importance of different NOx emissions sources and their change over time. The observations made by the three GOME-2 instruments will extend the existing data set by more than a decade, and a high quality of the data as well as their good consistency with existing time series is of high importance. In this paper, an improved GOME-2 NO2 retrieval is described which reduces the scatter of the individual NO2 columns globally but in particular in the region of the Southern Atlantic Anomaly. This is achieved by using a larger fitting window including more spectral points, and by applying a two step spike removal algorithm in the fit. The new GOME-2 data set is shown to have good consistency with SCIAMACHY NO2 columns. Remaining small differences are shown to be linked to changes in the daily solar irradiance measurements used in both GOME-2 and SCIAMACHY retrievals. In the large retrieval window, a not previously identified spectral signature was found which is linked to deserts and other regions with bare soil. Inclusion of this empirically derived pseudo cross-section significantly improves the retrievals and potentially provides information on surface properties and desert aerosols. Using the new GOME-2 NO2 data set, a long-term average of tropospheric columns was computed and high-pass filtered. The resulting map shows evidence for pollution from several additional shipping lanes, not previously identified in satellite observations. This illustrates the excellent signal to noise ratio achievable with the improved GOME-2 retrievals.

  6. A Three-Dimensional Satellite Retrieval Method for Atmospheric Temperature and Moisture Profiles

    Institute of Scientific and Technical Information of China (English)

    ZHANG Lei; QIU Chongjian; HUANG Jianping

    2008-01-01

    A three-dimensional variational method iS proposed to simultaneously retrieve the 3-D atmospheric temperature and moisture profiles from satellite radiance measurements.To include both vertical structure and the horizontal patterns of the atmospheric temperature and moisture.an EOF technique iS used to decompose the temperature and moisture field in a 3-D space.A number of numerical simulations are conducted and they demonstrate that the 3-D method iS less sensitive to the observation errors compared to the 1-D method.When the observation error iS more than 2.0 K.to get the best results.the truncation number for the EOF'S expansion have to be restricted to 2 in the 1-D method.while it can be set as large as 40 in a 3-D method.This results in the truncation error being reduced and the retrieval accuracy being improved in the 3-D method.Compared to the 1-D method.the rlTLS errors of the 3-D method are reduced by 48%and 36%for the temperature and moisture retrievals,respectively.Using the real satellite measured brightness temperatures at 0557 UTC 31 July 2002,the temperature and moisture profiles are retrieved over a region(20°-45°N,100°-125°E)and compared with 37 collocated radiosonde observations.The results show that the retrieval accuracy with a 3-D method iS significantly higher than those with the 1-D method.

  7. Numerical Research on Effects Upon Precipitation Forecast of Doppler-Radar Estimated Precipitation and Retrieved Wind Field Under Different Model Initial Schemes

    Institute of Scientific and Technical Information of China (English)

    WANG Yehong; ZHAO Yuchun; CUI Chunguang

    2007-01-01

    On the basis of the joint estimated 1-h precipitation from Changde, Jingzhou, and Yichang Doppler radars as well as Wuhan digital radar, and the retrieved wind fields from Yichang and Jingzhou Doppler radars, a series of numerical experiments with an advanced regional η-coordinate model (AREM) under different model initial schemes, i.e., Grapes-3DVAR, Barnes objective analysis, and Barnes-3DVAR, are carried out for a torrential rain process occurring along the Yangtze River in the 24-h period from 2000 BT 22 July 2002 to investigate the effects of the Doppler-radar estimated rainfall and retrieved winds on the rainfall forecast. The main results are as follows: (1) The simulations are obviously different under three initial schemes with the same data source (the radiosounding and T213L31 analysis). On the whole,Barnes-3DVAR, which combines the advantages of the Barnes objective analysis and the Grapes-3DVAR method, gives the best simulations: well-simulated rain band and clear mesoscale structures, as well as their location and intensity close to observations. (2) Both Barnes-3DVAR and Grapes-3DVAR schemes are able to assimilate the Doppler-radar estimated rainfall and retrieved winds, but differences in simulation results are very large, with Barnes-3DVAR's simulation much better than Grapes-3DVAR's. (3) Under Grapes3DVAR scheme, the simulation of 24-h rainfall is improved obviously when assimilating the Doppler-radar estimated precipitation into the model in compared with the control experiment; but it becomes a little worse when assimilating the Doppler-radar retrieved winds into the model, and it becomes worse obviously when assimilating the Doppler-radar estimated precipitation as well as retrieved winds into the model. However,the simulation is different under Barnes-3DVAR scheme. The simulation is improved to a certain degree no matter assimilating the estimated precipitation or retrieved winds, or both of them. The result is the best when assimilating both

  8. 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.

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

    Science.gov (United States)

    Zubieta, Ricardo; Getirana, Augusto; Carlo Espinoza, Jhan; Lavado-Casimiro, Waldo; Aragon, Luis

    2017-07-01

    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.

  10. Influence of low spatial resolution a priori data on tropospheric NO2 satellite retrievals

    Directory of Open Access Journals (Sweden)

    J. P. Burrows

    2011-09-01

    Full Text Available The retrieval of tropospheric columns of NO2 and other trace gases from satellite observations of backscattered solar radiation relies on the use of accurate a priori information. The spatial resolution of current space sensors is often significantly higher than that of the a priori datasets used, introducing uncertainties from spatial misrepresentation. In this study, the effect of spatial under-sampling of a priori data on the retrieval of NO2 columns was studied for a typical coastal area (around San Francisco. High-resolution (15 × 15 km2 NO2 a priori data from the WRF-Chem model in combination with high-resolution MODIS surface reflectance and aerosol data were used to investigate the uncertainty introduced by applying a priori data at typical global chemical transport model resolution. The results show that the relative uncertainties can be large (more than a factor of 2 if all a priori data used is at the coarsest resolution for individual measurements, mainly due to spatial variations in NO2 profile and surface albedo, with smaller contributions from aerosols and surface height changes. Similar sensitivities are expected for other coastal regions and localised sources such as power plants, highlighting the need for high-resolution a priori data in quantitative analysis of the spatial patterns retrieved from satellite observations of tropospheric pollution.

  11. Influence of under-sampled a priori data on tropospheric NO2 satellite retrievals

    Directory of Open Access Journals (Sweden)

    M. Trainer

    2011-03-01

    Full Text Available The retrieval of tropospheric columns of NO2 and other trace gases from satellite observations of backscattered solar radiation relies on the use of accurate a priori information. The spatial resolution of current space sensors is often significantly higher than that of the a priori datasets used, introducing uncertainties from spatial misrepresentation. In this study, the effect of spatial under-sampling of a priori data on the retrieval of NO2 columns was studied for a typical coastal area (around San Francisco. High-resolution (15 × 15 km2 NO2 a priori data from the WRF-Chem model in combination with high-resolution MODIS surface reflectance and aerosol data were used to investigate the uncertainty introduced by applying a priori data at typical global chemical transport model resolution. The results show that the relative uncertainties can be large (more than a factor of 2 for individual measurements, mainly due to spatial variations in NO2 profile and surface albedo, with smaller contributions from aerosols and surface height changes. Similar sensitivities are expected for other coastal regions and localised sources such as power plants, highlighting the need for high-resolution a priori data in quantitative analysis of the spatial patterns retrieved from satellite observations of tropospheric pollution.

  12. Identification and recovery of discontinuous synoptic features in satellite-retrieved brightness temperatures using a radiative transfer model

    Science.gov (United States)

    White, G. A., III; Mcguirk, J. P.; Thompson, A. H.

    1988-01-01

    An attempt is made to recover and identify discontinuous synoptic features from satellite-retrieved brightness temperatures, with attention to near-discontinuities in temperature and moisture that are typically found in fronts and inversions. Efforts are made to ascertain whether the vectors of satellite channel brightness temperatures can be classified according to synoptic source, and whether those sources are amenable to quantification.

  13. Retrieving Precipitable Water Vapor Data Using GPS Zenith Delays and Global Reanalysis Data in China

    Directory of Open Access Journals (Sweden)

    Peng Jiang

    2016-05-01

    Full Text Available GPS has become a very effective tool to remotely sense precipitable water vapor (PWV information, which is important for weather forecasting and nowcasting. The number of geodetic GNSS stations set up in China has substantially increased over the last few decades. However, GPS PWV derivation requires surface pressure to calculate the precise zenith hydrostatic delay and weighted mean temperature to map the zenith wet delay to precipitable water vapor. GPS stations without collocated meteorological sensors can retrieve water vapor using standard atmosphere parameters, which lead to a decrease in accuracy. In this paper, a method of interpolating NWP reanalysis data to site locations for generating corresponding meteorological elements is explored over China. The NCEP FNL dataset provided by the NCEP (National Centers for Environmental Prediction and over 600 observed stations from different sources was selected to assess the quality of the results. A one-year experiment was performed in our study. The types of stations selected include meteorological sites, GPS stations, radio sounding stations, and a sun photometer station. Compared with real surface measurements, the accuracy of the interpolated surface pressure and air temperature both meet the requirements of GPS PWV derivation in most areas; however, the interpolated surface air temperature exhibits lower precision than the interpolated surface pressure. At more than 96% of selected stations, PWV differences caused by the differences between the interpolation results and real measurements were less than 1.0 mm. Our study also indicates that relief amplitude exerts great influence on the accuracy of the interpolation approach. Unsatisfactory interpolation results always occurred in areas of strong relief. GPS PWV data generated from interpolated meteorological parameters are consistent with other PWV products (radio soundings, the NWP reanalysis dataset, and sun photometer PWV data. The

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

    Directory of Open Access Journals (Sweden)

    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.

  15. 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.

  16. The Evolution of El Nino-Precipitation Relationships from Satellites and Gauges

    Science.gov (United States)

    Curtis, Scott; Adler, Robert F.; Starr, David OC (Technical Monitor)

    2002-01-01

    This study uses a twenty-three year (1979-2001) satellite-gauge merged community data set to further describe the relationship between El Nino Southern Oscillation (ENSO) and precipitation. The globally complete precipitation fields reveal coherent bands of anomalies that extend from the tropics to the polar regions. Also, ENSO-precipitation relationships were analyzed during the six strongest El Ninos from 1979 to 2001. Seasons of evolution, Pre-onset, Onset, Peak, Decay, and Post-decay, were identified based on the strength of the El Nino. Then two simple and independent models, first order harmonic and linear, were fit to the monthly time series of normalized precipitation anomalies for each grid block. The sinusoidal model represents a three-phase evolution of precipitation, either dry-wet-dry or wet-dry-wet. This model is also highly correlated with the evolution of sea surface temperatures in the equatorial Pacific. The linear model represents a two-phase evolution of precipitation, either dry-wet or wet-dry. These models combine to account for over 50% of the precipitation variability for over half the globe during El Nino. Most regions, especially away from the Equator, favor the linear model. Areas that show the largest trend from dry to wet are southeastern Australia, eastern Indian Ocean, southern Japan, and off the coast of Peru. The northern tropical Pacific and Southeast Asia show the opposite trend.

  17. Exploiting the sensitivity of two satellite cloud height retrievals to cloud vertical distribution

    Directory of Open Access Journals (Sweden)

    C. K. Carbajal Henken

    2015-03-01

    Full Text Available This work presents a study on the sensitivity of two satellite cloud height retrievals to cloud vertical distribution. The difference in sensitivity is exploited by relating the difference in the retrieved cloud heights to cloud vertical extent. The two cloud height retrievals, performed within the Freie Universität Berlin AATSR MERIS Cloud (FAME-C algorithm, are based on independent measurements and different retrieval techniques. First, cloud top temperature (CTT is retrieved from Advanced Along Track Scanning Radiometer (AATSR measurements in the thermal infrared. Second, cloud top pressure (CTP is retrieved from Medium Resolution Imaging Spectrometer (MERIS measurements in the oxygen-A absorption band. Both CTT and CTP are converted to cloud top height (CTH using atmospheric profiles from a numerical weather prediction model. A sensitivity study using radiative transfer simulations in the near-infrared and thermal infrared were performed to demonstrate the larger impact of the assumed cloud vertical extinction profile on MERIS than on AATSR top-of-atmosphere measurements. The difference in retrieved CTH (ΔCTH from AATSR and MERIS are related to cloud vertical extent (CVE as observed by ground-based lidar and radar at three ARM sites. To increase the impact of the cloud vertical extinction profile on the MERIS-CTP retrievals, single-layer and geometrically thin clouds are assumed in the forward model. The results of the comparison to the ground-based observations were separated into single-layer and multi-layer cloud cases. Analogous to previous findings, the MERIS-CTP retrievals appear to be close to pressure levels in the middle of the cloud. Assuming a linear relationship, the ΔCTH multiplied by 2.5 gives an estimate on the CVE for single-layer clouds. The relationship is weaker for multi-layer clouds. Due to large variations of cloud vertical extinction profiles occurring in nature, a quantitative estimate of the cloud vertical extent

  18. Validating Microwave-Based Satellite Rain Rate Retrievals Over TRMM Ground Validation Sites

    Science.gov (United States)

    Fisher, B. L.; Wolff, D. B.

    2008-12-01

    Multi-channel, passive microwave instruments are commonly used today to probe the structure of rain systems and to estimate surface rainfall from space. Until the advent of meteorological satellites and the development of remote sensing techniques for measuring precipitation from space, there was no observational system capable of providing accurate estimates of surface precipitation on global scales. Since the early 1970s, microwave measurements from satellites have provided quantitative estimates of surface rainfall by observing the emission and scattering processes due to the existence of clouds and precipitation in the atmosphere. This study assesses the relative performance of microwave precipitation estimates from seven polar-orbiting satellites and the TRMM TMI using four years (2003-2006) of instantaneous radar rain estimates obtained from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The seven polar orbiters include three different sensor types: SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), and AMSR-E. The TMI aboard the TRMM satellite flies in a sun asynchronous orbit between 35 S and 35 N latitudes. The rain information from these satellites are combined and used to generate several multi-satellite rain products, namely the Goddard TRMM Multi-satellite Precipitation Analysis (TMPA), NOAA's CPC Morphing Technique (CMORPH) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). Instantaneous rain rates derived from each sensor were matched to the GV estimates in time and space at a resolution of 0.25 degrees. The study evaluates the measurement and error characteristics of the various satellite estimates through inter-comparisons with GV radar estimates. The GV rain observations provided an empirical ground-based reference for assessing the relative performance of each sensor and sensor

  19. Evaluating the Impact of Smoke Particle Absorption on Passive Satellite Cloud Optical Depth Retrievals

    Science.gov (United States)

    Alfaro-Contreras, R.; Zhang, J.; Reid, J. S.; Campbell, J. R.

    2013-12-01

    Absorbing aerosol particles, when lifted above clouds, can perturb top-of-atmosphere radiation radiances measured by passive satellite sensors through the absorption of reflected solar energy. This scenario, if not properly screened, impacts cloud physical retrievals, like cloud optical depth (COD), conducted using radiances/channels in the visible spectrum. We describe observations of smoke particle presence above cloud off the southwest coast of Africa, using spatially and temporally collocated Aqua Moderate Resolution Imaging Spectroradiometer (AQUA MODIS), Ozone Monitoring Instrument (OMI) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements. Results from this study indicate that above cloud aerosol episodes happen rather frequent in the smoke outflow region during the Northern Hemisphere summer where above cloud aerosol plumes introduce a significant bias to MODIS COD retrievals in the visible spectrum. This suggests that individual COD retrievals as well as COD climatology from MODIS can be affected over the smoke outflow region by above cloud aerosol contamination and thus showing the need to account for the presence of above cloud absorbing aerosols in the MODIS visible COD retrievals.

  20. A Non-MLE Approach for Satellite Scatterometer Wind Vector Retrievals in Tropical Cyclones

    Directory of Open Access Journals (Sweden)

    Suleiman Alsweiss

    2014-05-01

    Full Text Available Satellite microwave scatterometers are the principal source of global synoptic-scale ocean vector wind (OVW measurements for a number of scientific and operational oceanic wind applications. However, for extreme wind events such as tropical cyclones, their performance is significantly degraded. This paper presents a novel OVW retrieval algorithm for tropical cyclones which improves the accuracy of scatterometer based ocean surface winds when compared to low-flying aircraft with in-situ and remotely sensed observations. Unlike the traditional maximum likelihood estimation (MLE wind vector retrieval technique, this new approach sequentially estimates scalar wind directions and wind speeds. A detailed description of the algorithm is provided along with results for ten QuikSCAT hurricane overpasses (from 2003–2008 to evaluate the performance of the new algorithm. Results are compared with independent surface wind analyses from the National Oceanic and Atmospheric Administration (NOAA Hurricane Research Division’s H*Wind surface analyses and with the corresponding SeaWinds Project’s L2B-12.5 km OVW products. They demonstrate that the proposed algorithm extends the SeaWinds capability to retrieve wind speeds beyond the current range of approximately 35 m/s (minimal hurricane category-1 with improved wind direction accuracy, making this new approach a potential candidate for current and future conically scanning scatterometer wind retrieval algorithms.

  1. Development and Comparison of Ground and Satellite-based Retrievals of Cirrus Cloud Physical Properties

    Energy Technology Data Exchange (ETDEWEB)

    Mitchell, David L

    2009-10-14

    This report is the final update on ARM research conducted at DRI through May of 2006. A relatively minor amount of work was done after May, and last month (November), two journal papers partially funded by this project were published. The other investigator on this project, Dr. Bob d'Entremont, will be submitting his report in February 2007 when his no-cost extension expires. The main developments for this period, which concludes most of the DRI research on this project, are as follows: (1) Further development of a retrieval method for cirrus cloud ice particle effective diameter (De) and ice water path (IWP) using terrestrial radiances measured from satellites; (2) Revision and publication of the journal article 'Testing and Comparing the Modified Anomalous Diffraction Approximation'; and (3) Revision and publication of our radar retrieval method for IWC and snowfall rate.

  2. South African Weather Service operational satellite based precipitation estimation technique: applications and improvements

    Directory of Open Access Journals (Sweden)

    E. de Coning

    2010-11-01

    Full Text Available Extreme weather related to heavy or more frequent precipitation events seem to be a likely possibility for the future of our planet. While precipitation measurements can be done by means of rain gauges, the obvious disadvantages of point measurements are driving meteorologists towards remotely sensed precipitation methods. In South Africa more sophisticated and expensive nowcasting technology such as radar and lightning networks are available, supported by a fairly dense rain gauge network of about 1500 gauges. In the rest of southern Africa rainfall measurements are more difficult to obtain. The availability of the local version of the Unified Model and the Meteosat Second Generation satellite data make these products ideal components of precipitation measurement in data sparse regions such as Africa. In this article the local version of the Hydroestimator (originally from NOAA/NESDIS is discussed as well as its applications for precipitation measurement in this region. Hourly accumulations of the Hydroestimator are currently used as a satellite based precipitation estimator for the South African Flash Flood Guidance system. However, the Hydroestimator is by no means a perfect representation of the real rainfall. In this study the Hydroestimator and the stratiform rainfall field from the Unified Model are both bias corrected and then combined into a new precipitation field which can feed into the South African Flash Flood Guidance system. This new product should provide a more accurate and comprehensive input to the Flash Flood Guidance systems in South Africa as well as southern Africa. In this way the southern African region where data is sparse and very few radars are available can have access to more accurate flash flood guidance.

  3. 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.

    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... observations for getting the estimates of heat flux across the air-sea boundary (Miller, 1981; Liu, 1988). Bulk method has widely been used for this purpose and the parameters required are: sea surface temperature, and wind speed, air-temperature and specific...

  4. The influence of aerosols and land-use type on NO2 satellite retrieval over China

    Science.gov (United States)

    Liu, Mengyao; Lin, Jintai; Boersma, Folkert; Eskes, Henk; Chimot, Julien

    2017-04-01

    Both aerosols and surface reflectance have a strong influence on the retrieval of NO2 tropospheric vertical column densities (VCDs), especially over China with its heavy aerosol loading and rapid changes in land-use type. However, satellite retrievals of NO2 VCDs usually do not explicitly account for aerosol optical effects and surface reflectance anisotropy (BRDF) that varies in space and time. We develop an improved algorithm to derive tropospheric AMFs and VCDs over China from the OMI instrument - POMINO and DOMINO. This method can also be applied to TropOMI NO2 retrievals in the future. With small pixels of TropOMI and higher probability of encountering clear-sky scenes, the influence of BRDF and aerosol interference becomes more important than for OMI. Daily aerosol information is taken from the GEOS-Chem chemistry transport model and the aerosol optical depth (AOD) is adjusted via MODIS AOD climatology. We take the MODIS MCD43C2 C5 product to account for BRDF effects. The relative altitude of NO2 and aerosols is critical factor influencing the NO2 retrieval. In order to evaluate the aerosol extinction profiles (AEP) of GEOS-Chem improve our algorithm, we compare the GEOS-Chem simulation with CALIOP and develop a CALIOP AEP climatology to regulate the model's AEP. This provides a new way to include aerosol information into the tracer gas retrieval for OMI and TropOMI. Preliminary results indicate that the model performs reasonably well in reproducing the AEP shape. However, it seems to overestimate aerosols under 2km and underestimate above. We find that relative humidity (RH) is an important factor influencing the AEP shape when comparing the model with observations. If we adjust the GEOS-Chem RH to CALIOP's RH, the correlations of their AEPs also improve. Besides, take advantage of our retrieval method, we executed sensitivity tests to analyze their influences on NO2 trend and spatiotemporal variations in retrieval. It' the first time to investigate

  5. Bias reduction for Satellite Based Precipitation Estimates using statistical transformations in Guiana Shield

    Science.gov (United States)

    Ringard, Justine; Becker, Melanie; Seyler, Frederique; Linguet, Laurent

    2016-04-01

    Currently satellite-based precipitation estimates exhibit considerable biases, and there have been many efforts to reduce these biases by merging surface gauge measurements with satellite-based estimates. In Guiana Shield all products exhibited better performances during the dry season (August- December). All products greatly overestimate very low intensities (50 mm). Moreover the responses of each product are different according to hydro climatic regimes. The aim of this study is to correct spatially the bias of precipitation, and compare various correction methods to define the best methods depending on the rainfall characteristic correcting (intensity, frequency). Four satellites products are used: Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) research product (3B42V7) and real time product (3B42RT), the Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Network (PERSIANN) and the NOAA Climate Prediction Center (CPC) Morphing technique (CMORPH), for six hydro climatic regimes between 2001 and 2012. Several statistical transformations are used to correct the bias. Statistical transformations attempt to find a function h that maps a simulated variable Ps such that its new distribution equals the distribution of the observed variable Po. The first is the use of a distribution derived transformations which is a mixture of the Bernoulli and the Gamma distribution, where the Bernoulli distribution is used to model the probability of precipitation occurrence and the Gamma distribution used to model precipitation intensities. The second a quantile-quantile relation using parametric transformation, and the last one is a common approach using the empirical CDF of observed and modelled values instead of assuming parametric distributions. For each correction 30% of both, simulated and observed data sets, are used to calibrate and the other part used to validate. The validation are test with statistical

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. Application of Multi-Satellite Precipitation Analysis to Floods and Landslides

    Science.gov (United States)

    Adler, Robert; Hong, Yang; Huffman, George

    2007-01-01

    Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers. In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described

  11. Effects of Slope and Aspect Variations on Satellite Surface Temperature Retrievals and Mesoscale Analysis in Mountainous Terrain.

    Science.gov (United States)

    Lipton, Alan E.

    1992-03-01

    Surface temperature retrieval in mountainous areas is complicated by the high variability of temperatures that can occur within a single satellite field of view. Temperatures depend in part on slope orientation relative to the sun, which can vary radically over very short distances. The surface temperature detected by a satellite is biased toward the temperatures of the sub-field-of-view terrain elements that most directly face the satellite. Numerical simulations were conducted to estimate the effects of satellite viewing geometry on surface temperature retrievals for a section of central Colorado. Surface temperatures were computed using a mesoscale model with a parameterization of subgrid variations in slope and aspect angles.The simulations indicate that the slope-aspect effect can lead to local surface temperature variations up to 30°C for autumn conditions in the Colorado mountains. For realistic satellite viewing conditions, these variations can give rise to biases in retrieved surface temperatures of about 3°C. Relative biases between retrievals from two satellites with different viewing angles can be over 6°C, which could lead to confusion when merging datasets. The bias computations were limited by the resolution of the available terrain height data (90 m). The results suggest that the biases would be significantly larger if the data resolution was fine enough to represent every detail of the real Colorado terrain or if retrievals were made in mountain areas that have a larger proportion of steep slopes than the Colorado Rockies. The computed bias gradients across the Colorado domain were not large enough to significantly alter the forcing of the diurnal upslope-downslope circulations, according to simulations in which surface temperature retrievals with view-dependent biases were assimilated into time-continuous analyses. View-dependent retrieval biases may be relevant to climatological analysts that rely on remotely sensed data, given that bias

  12. 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

  13. Simulation of Ship-Track versus Satellite-Sensor Differences in Oceanic Precipitation Using an Island-Based Radar

    Directory of Open Access Journals (Sweden)

    Jörg Burdanowitz

    2017-06-01

    Full Text Available The point-to-area problem strongly complicates the validation of satellite-based precipitation estimates, using surface-based point measurements. We simulate the limited spatial representation of light-to-moderate oceanic precipitation rates along ship tracks with respect to areal passive microwave satellite estimates using data from a subtropical island-based radar. The radar data serves to estimate the discrepancy between point-like and areal precipitation measurements. From the spatial discrepancy, two statistical adjustments are derived so that along-track precipitation ship data better represent areal precipitation estimates from satellite sensors. The first statistical adjustment uses the average duration of a precipitation event as seen along a ship track, and the second adjustment uses the median-normalized along-track precipitation rate. Both statistical adjustments combined reduce the root mean squared error by 0.24 mm h − 1 (55% compared to the unadjusted average track of 60 radar pixels in length corresponding to a typical ship speed of 24–34 km h − 1 depending on track orientation. Beyond along-track averaging, the statistical adjustments represent an important step towards a more accurate validation of precipitation derived from passive microwave satellite sensors using point-like along-track surface precipitation reference data.

  14. Limiting Factors for Satellite-Based Retrievals of Surface-Level Carbon Monoxide

    Science.gov (United States)

    Martinez-Alonso, S.; Deeter, M. N.; Worden, H. M.; Barré, J.

    2015-12-01

    CO is mostly produced in the lower troposphere by incomplete combustion of biomass and fuels. CO oxidation consumes ~75% of the tropospheric OH, which then is not available to remove CH4 and other greenhouse gases. CO oxidation also leads to the production of tropospheric O3. These critical impacts of CO on air quality and climate require accurate determination of the abundance and evolution of CO near the surface.Satellite retrievals would be well-suited to monitor surface CO globally. However, how do they compare to actual surface abundances? Some aspects to be considered include: the vertical sensitivity of retrievals (given by the averaging kernels), or how thick are the atmospheric layers that can be resolved; the vertical correlation length of CO with respect to the thickness of those layers; and the horizontal variability of CO with respect to the instrument's footprint.To investigate these questions we analyze MOPITT retrievals, DISCOVER-AQ and NOAA profiles, as well as WDCGG surface measurements. MOPITT, on board NASA's Terra satellite, has been measuring tropospheric CO since 2000, providing the longest global CO record to date. Its unique multispectral CO product offers enhanced sensitivity to CO near the surface. Vertical profiles of the lower troposphere were acquired during the DISCOVER-AQ airborne campaigns over selected regions of the USA. NOAA's airborne flask sampling program results in a multi-year, multi-seasonal record of vertical profiles from near the surface up to the mid troposphere, acquired over a number of stations, mostly in North America. Long-term, cross-calibrated surface CO data from ground stations worldwide are available through the WDCGG.Statistical analyses of the DISCOVER-AQ and NOAA profiles indicate that surface vertical correlation length varies greatly depending on geographic location. This may explain contrasting results obtained for different ground stations when comparing MOPITT and WDCGG co-located data and timeseries.

  15. Direct Radiative Forcing from Saharan Mineral Dust Layers from In-situ Measurements and Satellite Retrievals

    Science.gov (United States)

    Sauer, D. N.; Vázquez-Navarro, M.; Gasteiger, J.; Chouza, F.; Weinzierl, B.

    2016-12-01

    Mineral dust is the major species of airborne particulate matter by mass in the atmosphere. Each year an estimated 200-3000 Tg of dust are emitted from the North African desert and arid regions alone. A large fraction of the dust is lifted into the free troposphere and gets transported in extended dust layers westward over the Atlantic Ocean into the Caribbean Sea. Especially over the dark surface of the ocean, those dust layers exert a significant effect on the atmospheric radiative balance though aerosol-radiation interactions. During the Saharan Aerosol Long-range Transport and Aerosol-Cloud-Interaction Experiment (SALTRACE) in summer 2013 airborne in-situ aerosol measurements on both sides of the Atlantic Ocean, near the African coast and the Caribbean were performed. In this study we use data about aerosol microphysical properties acquired between Cabo Verde and Senegal to derive the aerosol optical properties and the resulting radiative forcing using the radiative transfer package libRadtran. We compare the results to values retrieved from MSG/SEVIRI data using the RRUMS algorithm. The RRUMS algorithm can derive shortwave and longwave top-of-atmosphere outgoing fluxes using only information issued from the narrow-band MSG/SEVIRI channels. A specific calibration based on collocated Terra/CERES measurements ensures a correct retrieval of the upwelling flux from the dust covered pixels. The comparison of radiative forcings based on in-situ data to satellite-retrieved values enables us to extend the radiative forcing estimates from small-scale in-situ measurements to large scale satellite coverage over the Atlantic Ocean.

  16. Improvement of Cold Season Land Precipitation Retrievals Through The Use Of WRF Simulations and High Frequency Microwave Radiative Transfer Model

    Science.gov (United States)

    Wang, N.; Ferraro, R. R.; Gopalan, K.; Tao, W.; Shi, J. J.

    2009-12-01

    As we move from the TRMM to GPM era, more emphasis will be placed on a larger regime of precipitation in mid- and high-latitudes, including light rain, mixed-phase precipitation and snowfall. In these areas, a large and highly variable portion of the total annual precipitation is snow. There is a wealth of observational evidence of brightness temperature depression from frozen hydrometeor scattering at the high frequency from aircraft and spacecraft microwave instruments. Research on the development of snowfall retrieval over land has become increasing important in the last few years (Chen and Staelin, 2003; Kongoli et al., 2004; Skofronick-Jackson et al., 2004, Noh et al., 2006; Aonashi et al., 2007; Liu, 2008; Grecu and Olson, 2008; Kim et al., 2008). However, there is still a considerable amount of work that needs to be done to develop global snowfall detection and retrieval algorithms. This paper describes the development and testing of snowfall models and retrieval algorithms using WRF snowfall simulations and high frequency radiative transfer models for snowfall events took place in January 2007 over Ontario, Canada.

  17. Retrieval of precipitable water vapor using MFRSR and comparison with other multisensors over the semi-arid area of northwest China

    Science.gov (United States)

    Li, Xia; Zhang, Lei; Cao, Xianjie; Quan, Jiannong; Wang, Tianhe; Liang, Jiening; Shi, Jinsen

    2016-05-01

    Precipitable water vapor (PWV) was retrieved using direct solar irradiance at 938 nm measured by a multifilter rotating shadowband radiometer (MFRSR) at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) located in the semi-arid area of northwest China from August 2007 to June 2010. Measurement also occurred at Zhangye, China, at the Atmosphere Radiation Measurements (ARM) Program's Ancillary Facility during the dust period from April to June 2008. The line-by-line radiative transfer model (LBLRTM) code combined with the HITRAN 2004 spectral database is used to model the water vapor spectral transmittance throughout the 938-nm spectral response of MFRSR in the retrieval algorithm. Gaussian fitting is proposed to determine the daily calibration constant at the top of atmosphere for a long-term series under an obvious annual change in solar radiation. PWV retrieved by MFRSR over SACOL shows that 90% of PWV values are smaller than 1.52 cm, and PWV distribution has a seasonal variation, with maximum in summer and minimum in winter. The comparisons between MFRSR and other measurements show a better agreement between MFRSR and sunphotometer (AERONET's Cimel) PWV retrievals with relative bias of 2.9% and RMS difference of 9.1% than between MFRSR and microwave radiometer (MWR) with relative bias of 10% and RMS difference of 23% over SACOL, and an excellent agreement between MFRSR and sunphotometer with relative bias of 0.56% and RMS difference of 6.1% over Zhangye. To verify satellite PWV products over the semi-arid area of northwest China, the comparisons of PWV from MODIS and AIRS with MFRSR suggest that the agreement between satellite and MFRSR PWV retrievals is not as good as that between MFRSR and other ground-based instruments. MODIS appears to slightly underestimate PWV in a dry atmosphere but overestimate PWV in a moist atmosphere against MFRSR. A method is proposed to correct MODIS PWV products. AIRS PWV products relative to MFRSR show

  18. Exploiting the sensitivity of two satellite cloud height retrievals to cloud vertical distribution

    Science.gov (United States)

    Carbajal Henken, C. K.; Doppler, L.; Lindstrot, R.; Preusker, R.; Fischer, J.

    2015-08-01

    This work presents a study on the sensitivity of two satellite cloud height retrievals to cloud vertical distribution. The difference in sensitivity is exploited by relating the difference in the retrieved cloud heights to cloud vertical extent. The two cloud height retrievals, performed within the Freie Universität Berlin AATSR MERIS Cloud (FAME-C) algorithm, are based on independent measurements and different retrieval techniques. First, cloud-top temperature (CTT) is retrieved from Advanced Along Track Scanning Radiometer (AATSR) measurements in the thermal infrared. Second, cloud-top pressure (CTP) is retrieved from Medium Resolution Imaging Spectrometer (MERIS) measurements in the oxygen-A absorption band and a nearby window channel. Both CTT and CTP are converted to cloud-top height (CTH) using atmospheric profiles from a numerical weather prediction model. First, a sensitivity study using radiative transfer simulations in the near-infrared and thermal infrared was performed to demonstrate, in a quantitative manner, the larger impact of the assumed cloud vertical extinction profile, described in terms of shape and vertical extent, on MERIS than on AATSR top-of-atmosphere measurements. Consequently, cloud vertical extinction profiles will have a larger influence on the MERIS than on the AATSR cloud height retrievals for most cloud types. Second, the difference in retrieved CTH (ΔCTH) from AATSR and MERIS are related to cloud vertical extent (CVE), as observed by ground-based lidar and radar at three ARM sites. To increase the impact of the cloud vertical extinction profile on the MERIS-CTP retrievals, single-layer and geometrically thin clouds are assumed in the forward model. Similarly to previous findings, the MERIS-CTP retrievals appear to be close to pressure levels in the middle of the cloud. Assuming a linear relationship, the ΔCTH multiplied by 2.5 gives an estimate on the CVE for single-layer clouds. The relationship is stronger for single

  19. Real-Time Application of Multi-Satellite Precipitation Analysis for Floods and Landslides

    Science.gov (United States)

    Adler, Robert; Hong, Yang; Huffman, George

    2007-01-01

    Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets-- both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers, In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described

  20. Utilizing Satellite Precipitation Products to Understand the Link Between Climate Variability and Malaria

    Science.gov (United States)

    Maggioni, V.; Mousam, A.; Delamater, P. L.; Cash, B. A.; Quispe, A.

    2015-12-01

    Malaria is a public health threat to people globally leading to 198 million cases and 584,000 deaths annually. Outbreaks of vector borne diseases such as malaria can be significantly impacted by climate variables such as precipitation. For example, an increase in rainfall has the potential to create pools of water that can serve as breeding locations for mosquitos. Peru is a country that is currently controlling malaria, but has not been able to completely eliminate the disease. Despite the various initiatives in order to control malaria - including regional efforts to improve surveillance, early detection, prompt treatment, and vector management - malaria cases in Peru have risen between 2011 and 2014. The purpose of this study is to test the hypothesis that climate variability plays a fundamental role in malaria occurrence over a 12-year period (2003-2014) in Peru. When analyzing climate variability, it is important to obtain high-quality, high-resolution data for a time series long enough to draw conclusion about how climate variables have been and are changing. Remote sensing is a powerful tool for measuring and monitoring climate variables continuously in time and space. A widely used satellite-based precipitation product, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), available globally since 1998, was used to obtain 3-hourly data with a spatial resolution of 0.25° x 0.25°. The precipitation data was linked to weekly (2003-2014) malaria cases collected by health centers and available at a district level all over Peru to investigate the relationship between precipitation and the seasonal and annual variations in malaria incidence. Further studies will incorporate additional climate variables such as temperature, humidity, soil moisture, and surface pressure from remote sensing data products and climate models. Ultimately, this research will help us to understand if climate variability impacts malaria incidence

  1. Retrieving Clear-Sky Surface Skin Temperature for Numerical Weather Prediction Applications from Geostationary Satellite Data

    Directory of Open Access Journals (Sweden)

    Baojuan Shan

    2013-01-01

    Full Text Available Atmospheric models rely on high-accuracy, high-resolution initial radiometric and surface conditions for better short-term meteorological forecasts, as well as improved evaluation of global climate models. Remote sensing of the Earth’s energy budget, particularly with instruments flown on geostationary satellites, allows for near-real-time evaluation of cloud and surface radiation properties. The persistence and coverage of geostationary remote sensing instruments grant the frequent retrieval of near-instantaneous quasi-global skin temperature. Among other cloud and clear-sky retrieval parameters, NASA Langley provides a non-polar, high-resolution land and ocean skin temperature dataset for atmospheric modelers by applying an inverted correlated k-distribution method to clear-pixel values of top-of-atmosphere infrared temperature. The present paper shows that this method yields clear-sky skin temperature values that are, for the most part, within 2 K of measurements from ground-site instruments, like the Southern Great Plains Atmospheric Radiation Measurement (ARM Infrared Thermometer and the National Climatic Data Center Apogee Precision Infrared Thermocouple Sensor. The level of accuracy relative to the ARM site is comparable to that of the Moderate-resolution Imaging Spectroradiometer (MODIS with the benefit of an increased number of daily measurements without added bias or increased error. Additionally, matched comparisons of the high-resolution skin temperature product with MODIS land surface temperature reveal a level of accuracy well within 1 K for both day and night. This confidence will help in characterizing the diurnal and seasonal biases and root-mean-square differences between the retrievals and modeled values from the NASA Goddard Earth Observing System Version 5 (GEOS-5 in preparation for assimilation of the retrievals into GEOS-5. Modelers should find the immediate availability and broad coverage of these skin temperature

  2. Snow thickness retrieval over thick Arctic sea ice using SMOS satellite data

    Directory of Open Access Journals (Sweden)

    N. Maaß

    2013-12-01

    Full Text Available The microwave interferometric radiometer of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS mission measures at a frequency of 1.4 GHz in the L-band. In contrast to other microwave satellites, low frequency measurements in L-band have a large penetration depth in sea ice and thus contain information on the ice thickness. Previous ice thickness retrievals have neglected a snow layer on top of the ice. Here, we implement a snow layer in our emission model and investigate how snow influences L-band brightness temperatures and whether it is possible to retrieve snow thickness over thick Arctic sea ice from SMOS data. We find that the brightness temperatures above snow-covered sea ice are higher than above bare sea ice and that horizontal polarisation is more affected by the snow layer than vertical polarisation. In accordance with our theoretical investigations, the root mean square deviation between simulated and observed horizontally polarised brightness temperatures decreases from 20.9 K to 4.7 K, when we include the snow layer in the simulations. Although dry snow is almost transparent in L-band, we find brightness temperatures to increase with increasing snow thickness under cold Arctic conditions. The brightness temperatures' dependence on snow thickness can be explained by the thermal insulation of snow and its dependence on the snow layer thickness. This temperature effect allows us to retrieve snow thickness over thick sea ice. For the best simulation scenario and snow thicknesses up to 35 cm, the average snow thickness retrieved from horizontally polarised SMOS brightness temperatures agrees within 0.1 cm with the average snow thickness measured during the IceBridge flight campaign in the Arctic in spring 2012. The corresponding root mean square deviation is 5.5 cm, and the coefficient of determination is r2 = 0.58.

  3. Snow thickness retrieval over thick Arctic sea ice using SMOS satellite data

    Directory of Open Access Journals (Sweden)

    N. Maaß

    2013-07-01

    Full Text Available The microwave interferometric radiometer of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS mission measures at a frequency of 1.4 GHz in the L-band. In contrast to other microwave satellites, low frequency measurements in L-band have a large penetration depth in sea ice and thus contain information on the ice thickness. Previous ice thickness retrievals have neglected a snow layer on top of the ice. Here, we implement a snow layer in our emission model and investigate how snow influences L-band brightness temperatures and whether it is possible to retrieve snow thickness over thick Arctic sea ice from SMOS data. We find that the brightness temperatures above snow-covered sea ice are higher than above bare sea ice and that horizontal polarisation is more affected by the snow layer than vertical polarisation. In accordance with our theoretical investigations, the root mean square deviation between simulated and observed horizontally polarised brightness temperatures decreases from 20.0 K to 4.4 K, when we include the snow layer in the simulations. Under cold Arctic conditions we find brightness temperatures to increase with increasing snow thickness. Because dry snow is almost transparent in L-band, this brightness temperature's dependence on snow thickness origins from the thermal insulation of snow and its dependence on the snow layer thickness. This temperature effect allows us to retrieve snow thickness over thick sea ice. For the best simulation scenario and snow thicknesses up to 35 cm, the average snow thickness retrieved from horizontally polarised SMOS brightness temperatures agrees within 0.7 cm with the average snow thickness measured during the IceBridge flight campaign in the Arctic in spring 2012. The corresponding root mean square deviation is 6.3 cm, and the correlation coefficient is r2 = 0.55.

  4. Retrieval Using Texture Features in High Resolution Multi-spectral Satellite Imagery

    Energy Technology Data Exchange (ETDEWEB)

    Newsam, S D; Kamath, C

    2004-01-22

    Texture features have long been used in remote sensing applications to represent and retrieve image regions similar to a query region. Various representations of texture have been proposed based on the Fourier power spectrum, spatial co-occurrence, wavelets, Gabor filters, etc. These representations vary in their computational complexity and their suitability for representing different region types. Much of the work done thus far has focused on panchromatic imagery at low to moderate spatial resolutions, such as images from Landsat 1-7 which have a resolution of 15-30 m/pixel, and from SPOT 1-5 which have a resolution of 2.5-20 m/pixel. However, it is not clear which texture representation works best for the new classes of high resolution panchromatic (60-100 cm/pixel) and multi-spectral (4 bands for red, green, blue, and near infra-red at 2.4-4 m/pixel) imagery. It is also not clear how the different spectral bands should be combined. In this paper, we investigate the retrieval performance of several different texture representations using multi-spectral satellite images from IKONOS. A query-by-example framework, along with a manually chosen ground truth dataset, allows different combinations of texture representations and spectral bands to be compared. We focus on the specific problem of retrieving inhabited regions from images of urban and rural scenes. Preliminary results show that (1) the use of all spectral bands improves the retrieval performance, and (2) co-occurrence, wavelet and Gabor texture features perform comparably.

  5. Snow thickness retrieval using SMOS satellite data: Comparison with airborne IceBridge and buoy measurements

    Science.gov (United States)

    Maaß, N.; Kaleschke, L.; Tian-Kunze, X.

    2015-12-01

    The passive microwave mission SMOS (Soil Moisture and Ocean Salinity) provides daily coverage of the polar regions and its data have been used to retrieve thin sea ice thickness up to about one meter. In addition, there has been an attempt to retrieve snow thickness over thick Arctic multi-year ice, which is a crucial parameter for the freeboard-based estimation of (thick) sea ice thickness from lidar and radar altimetry. SMOS provides measurements at a frequency of 1.4 GHz (L-band) at horizontal and vertical polarization for a range of incidence angles (0 to 60°). The retrieval of ice or snow parameters from SMOS measurements is based on an emission model that describes the 1.4 GHz brightness temperature of (snow-covered) sea ice as a function of the ice and snow thicknesses and the permittivities of these media, which are mainly determined by ice temperature and salinity and snow density, respectively. In the first attempts to retrieve snow thickness from SMOS data, these parameters were assumed to be constant in the emission model, and the resulting maps were compared with airborne ice and snow thickness measurements taken during NASA's Operation IceBridge mission in spring 2012. The present approach to produce SMOS snow thickness maps is more elaborate. For example, available information on the ice surface temperature from MODIS (MODerate resolution Imaging Spectroradiometer) satellite images or from the IceBridge campaign itself are used, and the ice in the retrieval model is described by temperature and salinity profiles instead of using bulk values. As a first step we have produced (winter/spring) snow thickness maps of the Arctic, from 3-day-averages up to monthly means, using the available SMOS data from 2010 on. Here, we show how our spatial snow thickness distributions compare with IceBridge campaign data in the western Arctic from spring 2011 to 2015. In addition, we show how the temporal evolution of SMOS-retrieved snow thickness compares with snow

  6. Accounting for surface reflectance anisotropy in satellite retrievals of tropospheric NO2

    Directory of Open Access Journals (Sweden)

    B. Buchmann

    2010-05-01

    Full Text Available Surface reflectance is a key parameter in satellite trace gas retrievals in the UV/visible range and in particular for the retrieval of nitrogen dioxide (NO2 vertical tropospheric columns (VTCs. Current operational retrievals rely on coarse-resolution reflectance data and do not account for the generally anisotropic properties of surface reflectance. Here we present a NO2 VTC retrieval that uses MODIS bi-directional reflectance distribution function (BRDF data at high temporal (8 days and spatial (1 km×1 km resolution in combination with the LIDORT radiative transfer model to account for the dependence of surface reflectance on viewing and illumination geometry. The method was applied to two years of NO2 observations from the Ozone Monitoring Instrument (OMI over Europe. Due to its wide swath, OMI is particularly sensitive to BRDF effects. Using representative BRDF parameters for various land surfaces, we found that in July (low solar zenith angles and November (high solar zenith angles and for typical viewing geometries of OMI, differences between MODIS black-sky albedos and surface bi-directional reflectances are of the order of 0–10% and 0–40%, respectively, depending on the position of the OMI pixel within the swath. In the retrieval, black-sky albedo was treated as a Lambertian (isotropic reflectance, while for BRDF effects we used the kernel-based approach in the MODIS BRDF product. Air Mass Factors were computed using the LIDORT radiative transfer model based on these surface reflectance conditions. Differences in NO2 VTCs based on the Lambertian and BRDF approaches were found to be of the order of 0–3% in July and 0–20% in November with the extreme values found at large viewing angles. The much larger differences in November are partly due to higher solar zenith angles and partly to the choice of a priori NO2 profiles – the latter typically have more pronounced maxima in the boundary layer during the cold season. However, BRDF

  7. Correlating Global Precipitation Measurement satellite data with karst spring hydrographs for rapid catchment delineation

    Science.gov (United States)

    Longenecker, Jake; Bechtel, Timothy; Chen, Zhao; Goldscheider, Nico; Liesch, Tanja; Walter, Robert

    2017-05-01

    To protect karst spring water resources, catchments must be known. We have developed a method for correlating spring hydrographs with newly available, high-resolution, satellite-based Global Precipitation Measurement data to rapidly and remotely locate recharge areas. We verify the method using a synthetic comparison of ground-based rain gage data with the satellite precipitation data set. Application to karst springs is proven by correlating satellite data with hydrographs from well-known springs with published catchments in Europe and North America. Application to an unknown-catchment spring in Pennsylvania suggests distant recharge, requiring a flow path that crosses topographic divides, as well as multiple lithologies, physiographic provinces, and tectonic boundaries. Although surprising, this latter result is consistent with published geologic/geophysical, monitoring well, and stream gage data. We conclude that the method has considerable potential to improve the speed and accuracy of catchment identification and hydrodynamic characterization, with applications to water resource protection and groundwater exploration, among others.

  8. Evaluation of Six High-Resolution Satellite and Ground-Based Precipitation Products over Malaysia

    Directory of Open Access Journals (Sweden)

    Mou Leong Tan

    2015-01-01

    Full Text Available Satellite precipitation products (SPPs potentially constitute an alternative to sparse rain gauge networks for assessing the spatial distribution of precipitation. However, applications of these products are still limited due to the lack of robust quality assessment. This study compares daily, monthly, seasonal, and annual rainfall amount at 342 rain gauges over Malaysia to estimations using five SPPs (3B42RT, 3B42V7, GPCP-1DD, PERSIANN-CDR, and CMORPH and a ground-based precipitation product (APHRODITE. The performance of the precipitation products was evaluated from 2003 to 2007 using continuous (RMSE, R2, ME, MAE, and RB and categorical (ACC, POD, FAR, CSI, and HSS statistical approaches. Overall, 3B42V7 and APHRODITE performed the best, while the worst performance was shown by GPCP-1DD. 3B42RT, 3B42V7, and PERSIANN-CDR slightly overestimated observed precipitation by 2%, 4.7%, and 2.1%, respectively. By contrast, APHRODITE and CMORPH significantly underestimated precipitations by 19.7% and 13.2%, respectively, whereas GPCP-1DD only slightly underestimated by 2.8%. All six precipitation products performed better in the northeast monsoon than in the southwest monsoon. The better performances occurred in eastern and southern Peninsular Malaysia and in the north of East Malaysia, which receives higher rainfall during the northeast monsoon, whereas poor performances occurred in the western and dryer Peninsular Malaysia. All precipitation products underestimated the no/tiny (<1 mm/day and extreme (≥20 mm/day rainfall events, while they overestimated low (1–20 mm/day rainfall events. 3B42RT and 3B42V7 showed the best ability to detect precipitation amounts with the highest HSS value (0.36. Precipitations during flood events such as those which occurred in late 2006 and early 2007 were estimated the best by 3B42RT and 3B42V7, as shown by an R2 value ranging from 0.49 to 0.88 and 0.52 to 0.86, respectively. These results on SPPs’ uncertainties

  9. Employing satellite retrieved soil moisture for parameter estimation of the hydrologic model mHM

    Science.gov (United States)

    Zink, Matthias; Mai, Juliane; Rakovec, Oldrich; Schrön, Martin; Kumar, Rohini; Schäfer, David; Samaniego, Luis

    2016-04-01

    Hydrological models are usually calibrated against observed streamflow at the catchment outlet and thus they are conditioned by an integral catchment signal. Rakovec et al. 2016 (JHM) recently demonstrated that constraining model parameters against river discharge is a necessary, but not a sufficient condition. Such a procedure ensures the fulfillment of the catchment's water balance but can lead to high predictive uncertainties of model internal states, like soil moisture, or a lack in spatial representativeness of the model. However, some hydrologic applications, as e.g. soil drought monitoring and prediction, rely on this information. Within this study we propose a framework in which the mesoscale Hydrologic Model (mHM) is calibrated with soil moisture retrievals from various sources. The aim is to condition the model on soil moisture (SM), while preserving good performance in streamflow estimation. We identify the most appropriate objective functions by conducting synthetic experiments. The best objective function is determined based on: 1) deviation between synthetic and simulated soil moisture, 2) nonparametric comparison of SM fields (e.g. copulas), and 3) by euclidian distance of model parameters, which is zero if the parameters of the synthetic data are recovered. Those objective functions performing best are used to calibrate mHM against different satellite soil moisture products, e.g. ESA-CCI, H-SAF, and in situ observations. This procedure is tested in three distinct European basins (upper Sava, Neckar, and upper Guadalquivir basin) ranging from snow domination to semi arid climatic conditions. Results obtained with the synthetic experiment indicate that objective functions focusing on the temporal dynamics of SM are preferable to objective functions aiming at spatial patterns or catchment averages. Since the deviation of soil moisture fields (1) and their copulas (2) don't lead to conclusive results, the decision of the best performing objective

  10. Improving Quantitative Precipitation Estimation via Data Fusion of High-Resolution Ground-based Radar Network and CMORPH Satellite-based Product

    Science.gov (United States)

    Cifelli, R.; Chen, H.; Chandrasekar, V.; Xie, P.

    2015-12-01

    A large number of precipitation products at multi-scales have been developed based upon satellite, radar, and/or rain gauge observations. However, how to produce optimal rainfall estimation for a given region is still challenging due to the spatial and temporal sampling difference of different sensors. In this study, we develop a data fusion mechanism to improve regional quantitative precipitation estimation (QPE) by utilizing satellite-based CMORPH product, ground radar measurements, as well as numerical model simulations. The CMORPH global precipitation product is essentially derived based on retrievals from passive microwave measurements and infrared observations onboard satellites (Joyce et al. 2004). The fine spatial-temporal resolution of 0.05o Lat/Lon and 30-min is appropriate for regional hydrologic and climate studies. However, it is inadequate for localized hydrometeorological applications such as urban flash flood forecasting. Via fusion of the Regional CMORPH product and local precipitation sensors, the high-resolution QPE performance can be improved. The area of interest is the Dallas-Fort Worth (DFW) Metroplex, which is the largest land-locked metropolitan area in the U.S. In addition to an NWS dual-polarization S-band WSR-88DP radar (i.e., KFWS radar), DFW hosts the high-resolution dual-polarization X-band radar network developed by the center for Collaborative Adaptive Sensing of the Atmosphere (CASA). This talk will present a general framework of precipitation data fusion based on satellite and ground observations. The detailed prototype architecture of using regional rainfall instruments to improve regional CMORPH precipitation product via multi-scale fusion techniques will also be discussed. Particularly, the temporal and spatial fusion algorithms developed for the DFW Metroplex will be described, which utilizes CMORPH product, S-band WSR-88DP, and X-band CASA radar measurements. In order to investigate the uncertainties associated with each

  11. Evaluation of clouds and precipitation in the ECHAM5 general circulation model using CALIPSO and CloudSat satellite data

    OpenAIRE

    Nam, Christine C. W.; Quaas, Johannes

    2015-01-01

    Observations from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat satellites are used to evaluate clouds and precipitation in the ECHAM5 general circulation model. Active lidar and radar instruments on board CALIPSO and CloudSat allow the vertical distribution of clouds and their optical properties to be studied on a global scale. To evaluate the clouds modeled by ECHAM5 with CALIPSO and CloudSat, the lidar and radar satellite simulators of the Cloud ...

  12. Improving volcanic ash predictions with the HYSPLIT dispersion model by assimilating MODIS satellite retrievals

    Science.gov (United States)

    Chai, Tianfeng; Crawford, Alice; Stunder, Barbara; Pavolonis, Michael J.; Draxler, Roland; Stein, Ariel

    2017-02-01

    Currently, the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) runs the HYSPLIT dispersion model with a unit mass release rate to predict the transport and dispersion of volcanic ash. The model predictions provide information for the Volcanic Ash Advisory Centers (VAAC) to issue advisories to meteorological watch offices, area control centers, flight information centers, and others. This research aims to provide quantitative forecasts of ash distributions generated by objectively and optimally estimating the volcanic ash source strengths, vertical distribution, and temporal variations using an observation-modeling inversion technique. In this top-down approach, a cost functional is defined to quantify the differences between the model predictions and the satellite measurements of column-integrated ash concentrations weighted by the model and observation uncertainties. Minimizing this cost functional by adjusting the sources provides the volcanic ash emission estimates. As an example, MODIS (Moderate Resolution Imaging Spectroradiometer) satellite retrievals of the 2008 Kasatochi volcanic ash clouds are used to test the HYSPLIT volcanic ash inverse system. Because the satellite retrievals include the ash cloud top height but not the bottom height, there are different model diagnostic choices for comparing the model results with the observed mass loadings. Three options are presented and tested. Although the emission estimates vary significantly with different options, the subsequent model predictions with the different release estimates all show decent skill when evaluated against the unassimilated satellite observations at later times. Among the three options, integrating over three model layers yields slightly better results than integrating from the surface up to the observed volcanic ash cloud top or using a single model layer. Inverse tests also show that including the ash-free region to constrain the model is not

  13. Investigation of S3-2 satellite data for local time variation of energetic electron precipitation

    Science.gov (United States)

    Robbe, S.; Sheldon, W. R.; Benbrook, J. R.; Bering, E. A.; Vampola, A. L.

    1994-01-01

    Data on precipitating electrons from the S3-2 satellite were investigated for local time variation at four L = 4 stations in the southern hemisphere. The equatorial pitch angles of electrons mirroring at 100 km, assumed to be the edge of the bounce loss cone, are calculated for L = 4 using the International Geomagnetic Reference Field for the epoch of the S3-2 data, along with the variation in mirror altitude per degree of equatorial pitch angle. The largest obstacle to the investigation was uneven sampling in terms of local time for all of the stations. However, this situation was improved upon by the use of S3-2 measurements at the conjugate locations of the four stations which provided additional data on electrons in the southern hemisphere bounce loss cone. Evidence for an effect of the dawn-to-dusk geoelectric field was found at two of the stations, Halley Bay and Siple, in the form of a minimum in electron precipitation at dusk. However, the present study does not completely resolve the question of local time modulation of electron precipitation at L = 4 in the southern hemisphere. Furthermore, while the average precipitation was lowest at the Kerguelen site, as would be expected on the basis of drift loss cone (DLC) theories, the intensity at that site exceeds the level that is expected on the basis of these DLC theories.

  14. Satellite-based retrieval of particulate matter concentrations over the United Arab Emirates (UAE)

    Science.gov (United States)

    Zhao, Jun; Temimi, Marouane; Hareb, Fahad; Eibedingil, Iyasu

    2016-04-01

    In this study, an empirical algorithm was established to retrieve particulate matter (PM) concentrations (PM2.5 and PM10) using satellite-derived aerosol optical depth (AOD) over the United Arab Emirates (UAE). Validation of the proposed algorithm using ground truth data demonstrates its good accuracy. Time series of in situ measured PM concentrations between 2014 and 2015 showed high values in summer and low values in winter. Estimated and in situ measured PM concentrations were higher in 2015 than 2014. Remote sensing is an essential tool to reveal and back track the seasonality and inter-annual variations of PM concentrations and provide valuable information on the protection of human health and the response of air quality to anthropogenic activities and climate change.

  15. Satellite radiometric remote sensing of rainfall fields: multi-sensor retrieval techniques at geostationary scale

    Directory of Open Access Journals (Sweden)

    F. S. Marzano

    2005-01-01

    Full Text Available The Microwave Infrared Combined Rainfall Algorithm (MICRA consists in a statistical integration method using the satellite microwave-based rain-rate estimates, assumed to be accurate enough, to calibrate spaceborne infrared measurements on limited sub-regions and time windows. Rainfall retrieval is pursued at the space-time scale of typical geostationary observations, that is at a spatial resolution of few kilometers and a repetition period of few tens of minutes. The actual implementation is explained, although the basic concepts of MICRA are very general and the method is easy to be extended for considering innovative statistical techniques or measurements from additional space-borne platforms. In order to demonstrate the potentiality of MICRA, case studies over central Italy are also discussed. Finally, preliminary results of MICRA validation by ground based remote and in situ measurements are shown and a comparison with a Neural Network (NN based technique is briefly illustrated.

  16. Retrieving the Height of Smoke and Dust Aerosols by Synergistic Use of Multiple Satellite Sensors

    Science.gov (United States)

    Lee, Jaehwa; Hsu, N. Christina; Bettenhausen, Corey; Sayer, Andrew M.; Seftor, Colin J.; Jeong, Myeong-Jae

    2016-01-01

    The Aerosol Single scattering albedo and Height Estimation (ASHE) algorithm was first introduced in Jeong and Hsu (2008) to provide aerosol layer height and single scattering albedo (SSA) for biomass burning smoke aerosols. By using multiple satellite sensors synergistically, ASHE can provide the height information over much broader areas than lidar observations alone. The complete ASHE algorithm uses aerosol data from MODIS or VIIRS, OMI or OMPS, and CALIOP. A simplified algorithm also exists that does not require CALIOP data as long as the SSA of the aerosol layer is provided by another source. Several updates have recently been made: inclusion of dust layers in the retrieval process, better determination of the input aerosol layer height from CALIOP, improvement in aerosol optical depth (AOD) for nonspherical dust, development of quality assurance (QA) procedure, etc.

  17. 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.

  18. Constraints on a priori assumptions and microphysical properties in precipitation from in situ measurements in GPM-GV field campaigns: regime dependence and impact on retrievals

    Science.gov (United States)

    Nesbitt, S. W.; Harnos, D. S.; Harnos, K.; Reed, K. A.; Duffy, G.; McFarquhar, G. M.; Tanelli, S.; Williams, C. R.; Johnson, B. T.; Petersen, W. A.; Tokay, A.; Barros, A. P.; Wilson, A. M.

    2014-12-01

    Active and passive physical precipitation retrieval algorithms are tasked to retrieve precipitation across a wide variety of precipitation types and environments, however, there is presently little knowledge as to how characteristics of precipitation, some of which are retrieved and some assumed a priori, vary across the diverse precipitation profiles on earth, particular in the vertical. GPM-Ground Validation (GV) has collected a broad range of microphysical observations both on the ground and through airborne campaigns. For retrieval algorithm a priori assumptions, which must reliably represent the natural variability of cloud properties, statistical characterization of in situ measurements of parameters that algorithms retrieve or assume are known to vary in meteorological regimes and must be characterized as well as their uncertainties reported in order to aid in algorithm accuracy and uncertainty characterization. In this study, we will use data collected from in situ aircraft and ground based sensors, as well as remote sensing retrievals from GPM field campaigns across meteorological regimes to characterize the statistical relationships among a priori assumptions as a function of height as well as meteorological regime. Parameters that will be investigated include the variability of parameters such as cloud liquid water, effective mass-diameter relationships, as well as parameterized hydrometeor size distribution characteristics. Joint probability distributions of these parameters will be examined across campaigns as a function of height to understand the variability in these parameters for constraining algorithm assumptions. Variations in these parameters will be propagated through a dual-wavelength precipitation retrieval algorithm to assess their impacts on retrievals in warm and cold season precipitation. Results will consider how these parameters to what degree these parameters should be allowed to vary in global retrieval algorithms.

  19. Transitioning from CRD to CDRD in Bayesian retrieval of rainfall from satellite passive microwave measurements: Part 3 - Identification of optimal meteorological tags

    Science.gov (United States)

    Smith, E. A.; Leung, H. W.-Y.; Elsner, J. B.; Mehta, A. V.; Tripoli, G. J.; Casella, D.; Dietrich, S.; Mugnai, A.; Panegrossi, G.; Sanò, P.

    2013-05-01

    In the first two parts of this study we have presented a performance analysis of our new Cloud Dynamics and Radiation Database (CDRD) satellite precipitation retrieval algorithm on various convective and stratiform rainfall case studies verified with precision radar ground truth data, and an exposition of the algorithm's detailed design in conjunction with a proof-of-concept analysis vis-à-vis its theoretical underpinnings. In this third part of the study, we present the underlying analysis used to identify what we refer to as the optimal metrological and geophysical tags, which are the optimally effective atmospheric and geographic parameters that are used to refine the selection of candidate microphysical profiles used for the Bayesian retrieval. These tags enable extending beyond the conventional Cloud Radiation Database (CRD) algorithm by invoking meteorological-geophysical guidance, drawn from a simulated database, which affect and are in congruence with the observed precipitation states. This is guidance beyond the restrictive control provided by only simulated radiative transfer equation (RTE) model-derived database brightness temperature (TB) vector proximity information in seeking to relate physically consistent precipitation profile solutions to individual satellite-observed TB vectors. The first two parts of the study have rigorously demonstrated that the optimal tags effectively mitigate against solution ambiguity, where use of only a CRD framework (TB guidance only) leads to pervasive non-uniqueness problems in finding rainfall solutions. Alternatively, a CDRD framework (TB + tag guidance) mitigates against non-uniqueness problems through improved constraints. It remains to show how these optimal tags are identified. By use of three statistical analysis procedures applied to a database from 120 North American atmospheric simulations of precipitating storms (independent of the 60 simulations for the European-Mediterranean basin region used in the Parts

  20. Real-time, Quasi-Global, Multi-Satellite Precipitation Analysis Using TRMM and other Satellite Observations

    Science.gov (United States)

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

    2003-01-01

    A TRMM-based 3-hr analyses that use TRMM observations to calibrate polar-orbit microwave observations from SSM/I (and other satellites) and geosynchronous IR observations and merges the various calibrated observations into a final, 3-hr resolution map is described. This TRMM standard product will be available for the entire TRMM period (January 1998-present) in 2003 as part of Version 6 of the TRMM products. A real-time version of this merged product is being produced and is available at 0.25" latitude-longitude resolution over the latitude range from 50 N-500S. Examples will be shown, including its use in monitoring flood conditions and in relating weather-scale patterns to climate-scale patterns. Plans to incorporate the TRMM data and 3-hourly analysis into the Global Precipitation Climatology Project (GPCP) products are outlined. The outcome in the near future should be an improved global analysis and climatology on monthly scales for the 23 year period and finer time scale analyses for more recent periods, including 3-hourly analyses over the globe. These technique developments are potential prototypes for analyses with the Global Precipitation Measurement (GPM) mission.

  1. The validation service of the hydrological SAF geostationary and polar satellite precipitation products

    Science.gov (United States)

    Puca, S.; Porcu, F.; Rinollo, A.; Vulpiani, G.; Baguis, P.; Balabanova, S.; Campione, E.; Ertürk, A.; Gabellani, S.; Iwanski, R.; Jurašek, M.; Kaňák, J.; Kerényi, J.; Koshinchanov, G.; Kozinarova, G.; Krahe, P.; Lapeta, B.; Lábó, E.; Milani, L.; Okon, L'.; Öztopal, A.; Pagliara, P.; Pignone, F.; Rachimow, C.; Rebora, N.; Roulin, E.; Sönmez, I.; Toniazzo, A.; Biron, D.; Casella, D.; Cattani, E.; Dietrich, S.; Di Paola, F.; Laviola, S.; Levizzani, V.; Melfi, D.; Mugnai, A.; Panegrossi, G.; Petracca, M.; Sanò, P.; Zauli, F.; Rosci, P.; De Leonibus, L.; Agosta, E.; Gattari, F.

    2014-04-01

    The development phase (DP) of the EUMETSAT Satellite Application Facility for Support to Operational Hydrology and Water Management (H-SAF) led to the design and implementation of several precipitation products, after 5 yr (2005-2010) of activity. Presently, five precipitation estimation algorithms based on data from passive microwave and infrared sensors, on board geostationary and sun-synchronous platforms, function in operational mode at the H-SAF hosting institute to provide near real-time precipitation products at different spatial and temporal resolutions. In order to evaluate the precipitation product accuracy, a validation activity has been established since the beginning of the project. A Precipitation Product Validation Group (PPVG) works in parallel with the development of the estimation algorithms with two aims: to provide the algorithm developers with indications to refine algorithms and products, and to evaluate the error structure to be associated with the operational products. In this paper, the framework of the PPVG is presented: (a) the characteristics of the ground reference data available to H-SAF (i.e. radar and rain gauge networks), (b) the agreed upon validation strategy settled among the eight European countries participating in the PPVG, and (c) the steps of the validation procedures. The quality of the reference data is discussed, and the efforts for its improvement are outlined, with special emphasis on the definition of a ground radar quality map and on the implementation of a suitable rain gauge interpolation algorithm. The work done during the H-SAF development phase has led the PPVG to converge into a common validation procedure among the members, taking advantage of the experience acquired by each one of them in the validation of H-SAF products. The methodology is presented here, indicating the main steps of the validation procedure (ground data quality control, spatial interpolation, up-scaling of radar data vs. satellite grid

  2. Evaluation of Satellite Precipitation and Hydrological Model Predictions for Flood Events Over The Guadalupe River Basin, Texas

    Science.gov (United States)

    Sharif, H. O.; Furl, C.

    2016-12-01

    In this study, we evaluate the quality of several satellite precipitation products in comparison to gauge corrected ground based radar estimaties for moderate to high magnitude events across the Guadalupe River system in south Texas. The analysis is conducted across four partially nested watersheds (200-10,000 km2) such that scale effects can also be examined. Additionally, the precipitation data sets are used as input to the fully-distributed, physics-based Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model to examine rainfall error propagation through the hydrologic model predictions. Both gauge corrected and uncorrected satellite products are used encompassing a variety of latent delivery times, spatial resolutions, and temporal resolutions. Satellite precipitation datasets used in the study include various products from GPM, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) system, the NOAA CPC Morphing Technique (CMORPH), and the Tropical Rainfall Measuring Mission (TRMM).

  3. Evaluation of Satellite Retrievals of Ocean Chlorophyll-a in the California Current

    Directory of Open Access Journals (Sweden)

    Mati Kahru

    2014-09-01

    Full Text Available Retrievals of ocean surface chlorophyll-a concentration (Chla by multiple ocean color satellite sensors (SeaWiFS, MODIS-Terra, MODIS-Aqua, MERIS, VIIRS using standard algorithms were evaluated in the California Current using a large archive of in situ measurements. Over the full range of in situ Chla, all sensors produced a coefficient of determination (R2 between 0.79 and 0.88 and a median absolute percent error (MdAPE between 21% and 27%. However, at in situ Chla > 1 mg m−3, only products from MERIS (both the ESA produced algal_1 and NASA produced chlor_a maintained reasonable accuracy (R2 from 0.74 to 0.52 and MdAPE from 23% to 31%, respectively, while the other sensors had R2 below 0.5 and MdAPE higher than 36%. We show that the low accuracy at medium and high Chla is caused by the poor retrieval of remote sensing reflectance.

  4. A new method to retrieve salinity profiles from sea surface salinity observed by SMOS satellite

    Institute of Scientific and Technical Information of China (English)

    YANG Tingting; CHEN Zhongbiao; HE Yijun

    2015-01-01

    This paper proposes a new method to retrieve salinity profiles from the sea surface salinity (SSS) observed by the Soil Moisture and Ocean Salinity (SMOS) satellite. The main vertical patterns of the salinity profiles are firstly extracted from the salinity profiles measured by Argo using the empirical orthogonal function. To determine the time coefficients for each vertical pattern, two statistical models are developed. In the linear model, a transfer function is proposed to relate the SSS observed by SMOS (SMOS_SSS) with that measured by Argo, and then a linear relationship between the SMOS_SSS and the time coefficient is established. In the nonlinear model, the neural network is utilized to estimate the time coefficients from SMOS_SSS, months and positions of the salinity profiles. The two models are validated by comparing the salinity profiles retrieved from SMOS with those measured by Argo and the climatological salinities. The root-mean-square error (RMSE) of the linear and nonlinear model are 0.08–0.16 and 0.08–0.14 for the upper 400 m, which are 0.01–0.07 and 0.01–0.09 smaller than the RMSE of climatology. The error sources of the method are also discussed.

  5. Fuzzy Classification of Ocean Color Satellite Data for Bio-optical Algorithm Constituent Retrievals

    Science.gov (United States)

    Campbell, Janet W.

    1998-01-01

    The ocean has been traditionally viewed as a 2 class system. Morel and Prieur (1977) classified ocean water according to the dominant absorbent particle suspended in the water column. Case 1 is described as having a high concentration of phytoplankton (and detritus) relative to other particles. Conversely, case 2 is described as having inorganic particles such as suspended sediments in high concentrations. Little work has gone into the problem of mixing bio-optical models for these different water types. An approach is put forth here to blend bio-optical algorithms based on a fuzzy classification scheme. This scheme involves two procedures. First, a clustering procedure identifies classes and builds class statistics from in-situ optical measurements. Next, a classification procedure assigns satellite pixels partial memberships to these classes based on their ocean color reflectance signature. These membership assignments can be used as the basis for a weighting retrievals from class-specific bio-optical algorithms. This technique is demonstrated with in-situ optical measurements and an image from the SeaWiFS ocean color satellite.

  6. Improved modeling of cloudy-sky actinic flux using satellite cloud retrievals

    Science.gov (United States)

    Ryu, Young-Hee; Hodzic, Alma; Descombes, Gael; Hall, Samuel; Minnis, Patrick; Spangenberg, Douglas; Ullmann, Kirk; Madronich, Sasha

    2017-02-01

    Clouds play a critical role in modulating tropospheric radiation and thus photochemistry. We develop a methodology for calculating the vertical distribution of tropospheric ultraviolet (300-420 nm) actinic fluxes using satellite cloud retrievals and a radiative transfer model. We demonstrate that our approach can accurately reproduce airborne-measured actinic fluxes from the 2013 Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign as a case study. The results show that the actinic flux is reduced below moderately thick clouds with increasing cloud optical depth and can be enhanced by a factor of 2 above clouds. Inside clouds, the actinic flux can be enhanced by up to 2.4 times in the upper part of clouds or reduced up to 10 times in the lower parts of clouds. Our study suggests that the use of satellite-derived actinic fluxes as input to chemistry-transport models can improve the accuracy of photochemistry calculations.

  7. Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations

    Science.gov (United States)

    Dubovik, O.; Herman, M.; Holdak, A.; Lapyonok, T.; Tanré, D.; Deuzé, J. L.; Ducos, F.; Sinyuk, A.; Lopatin, A.

    2011-05-01

    The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL micro-satellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation. The algorithm is designed to retrieve complete aerosol properties globally. Over land, the algorithm retrieves the parameters of underlying surface simultaneously with aerosol. In all situations, the approach is anticipated to achieve a robust retrieval of complete aerosol properties including information about aerosol particle sizes, shape, absorption and composition (refractive index). In order to achieve reliable retrieval from PARASOL observations even over very reflective

  8. Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations

    Directory of Open Access Journals (Sweden)

    O. Dubovik

    2011-05-01

    Full Text Available The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns that is not common in satellite observations. The POLDER imager on board the PARASOL micro-satellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.

    The algorithm is designed to retrieve complete aerosol properties globally. Over land, the algorithm retrieves the parameters of underlying surface simultaneously with aerosol. In all situations, the approach is anticipated to achieve a robust retrieval of complete aerosol properties including information about aerosol particle sizes, shape, absorption and composition (refractive index. In order to achieve reliable retrieval from PARASOL observations

  9. Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations

    Directory of Open Access Journals (Sweden)

    O. Dubovik

    2010-11-01

    Full Text Available The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns that is not common in satellite observations. The POLDER imager on board of the PARASOL micro-satellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of the all available angular observations of total and polarized radiances obtained by POLDER sensor in the window spectral channels where absorption by gaseous is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed on retrieval of extended set of parameters affecting measured radiation.

    The algorithm is designed to retrieve complete aerosol properties globally. Over land, the algorithm retrieves the parameters of underlying surface simultaneously with aerosol. In all situations, the approach is anticipated to achieve a robust retrieval of complete aerosol properties including information about aerosol particle sizes, shape, absorption and composition (refractive index. In order to achieve

  10. Representativeness errors in comparing chemistry transport and chemistry climate models with satellite UV-Vis tropospheric column retrievals

    NARCIS (Netherlands)

    Boersma, K.F.; Vinken, G.C.M.; Eskes, H.J.

    2016-01-01

    Ultraviolet-visible (UV-Vis) satellite retrievals of trace gas columns of nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO) are useful to test and improve models of atmospheric composition, for data assimilation, air quality hindcasting and forecasting, a

  11. Precipitating Snow Retrievals from Combined Airborne Cloud Radar and Millimeter-Wave Radiometer Observations

    Science.gov (United States)

    Grecu, Mircea; Olson, William S.

    2008-01-01

    An algorithm for retrieving snow over oceans from combined cloud radar and millimeter-wave radiometer observations is developed. The algorithm involves the use of physical models to simulate cloud radar and millimeter-wave radiometer observations from basic atmospheric variables such as hydrometeor content, temperature, and relative humidity profiles and is based on an optimal estimation technique to retrieve these variables from actual observations. A high-resolution simulation of a lake-effect snowstorm by a cloud-resolving model is used to test the algorithm. That is, synthetic observations are generated from the output of the cloud numerical model, and the retrieval algorithm is applied to the synthetic data. The algorithm performance is assessed by comparing the retrievals with the reference variables used in synthesizing the observations. The synthetic observation experiment indicates good performance of the retrieval algorithm. The algorithm is also applied to real observations from the Wakasa Bay field experiment that took place over the Sea of Japan in January and February 2003. The application of the retrieval algorithm to data from the field experiment yields snow estimates that are consistent with both the cloud radar and radiometer observations.

  12. Assessment of Satellite-based Precipitation Products (TRMM) in Hydrologic Modeling: Case Studies from Northern Morocco

    Science.gov (United States)

    EL kadiri, R.; Milewski, A.; Durham, M.

    2012-12-01

    Precipitation is the most important forcing parameter in hydrological modeling, yet it is largely unknown in the arid Middle East. We assessed the magnitude, probability of detection, and false alarm rates of various rainfall satellite products (e.g., TRMM, RFE2.0) compared to in situ gauge data (~79 stations) across the Our Er Rbia, Sebou, and Melouya Watersheds in Northern Morocco. Precipitation over the area is relatively high with an average of ~400mm/year according to TRMM (1998-2008). The existing gauges indicate that the average annual precipitation across the Tadla and Coastal Plains region is 260mm/year and 390mm/year across the Atlas Mountains. Following the assessment of satellite products against in situ gauge data, we evaluated the effects (e.g., runoff and recharge amounts) of using satellite driven hydrologic models using SWAT. Specifically, we performed a four-fold exercise: (1) The first stage focused on the analysis of the rainfall products; (2) the second stage involved the construction of a rainfall-runoff model using gauge data; (3) the third stage entailed the calibration of the model against flow gauges and/or dams storage variability, and (4) model simulation using satellite based rainfall products using the calibrated parameters from the initial simulation. Results suggest the TRMM V7 has a much better correlation with the field data over the Oum Er Rbia watershed. The Correlation E (Nash-Suncliffe coefficient) has a positive value of 0.5, while the correlation coefficient of TRMM V6 vs. gauges data is a negative value of -0.25. This first order evaluation of the TRMM V7 shows the new algorithm has partially overcame the underestimation effect in the semi-arid environments. However, more research needs to be done to increase the usability of TRMM V7 in hydrologic models. Low correlations are most likely a result of the following: (1) snow at the high elevations in the Oum Er Rbia watershed, (2) the ocean effect on TRMM measurements along

  13. Comparison between volcanic ash satellite retrievals and FALL3D transport model

    Science.gov (United States)

    Corradini, Stefano; Merucci, Luca; Folch, Arnau

    2010-05-01

    Volcanic eruptions represent one of the most important sources of natural pollution because of the large emission of gas and solid particles into the atmosphere. Volcanic clouds can contain different gas species (mainly H2O, CO2, SO2 and HCl) and a mix of silicate-bearing ash particles in the size range from 0.1 μm to few mm. Determining the properties, movement and extent of volcanic ash clouds is an important scientific, economic, and public safety issue because of the harmful effects on environment, public health and aviation. In particular, real-time tracking and forecasting of volcanic clouds is key for aviation safety. Several encounters of en-route aircrafts with volcanic ash clouds have demonstrated the harming effects of fine ash particles on modern aircrafts. Alongside these considerations, the economical consequences caused by disruption of airports must be also taken into account. Both security and economical issues require robust and affordable ash cloud detection and trajectory forecasting, ideally combining remote sensing and modeling. We perform a quantitative comparison between Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of volcanic ash cloud mass and Aerosol Optical Depth (AOD) with the FALL3D ash dispersal model. MODIS, aboard the NASA-Terra and NASA-Aqua polar satellites, is a multispectral instrument with 36 spectral bands from Visible (VIS) to Thermal InfraRed (TIR) and spatial resolution varying between 250 and 1000 m at nadir. The MODIS channels centered around 11 and 12 mm have been used for the ash retrievals through the Brightness Temperature Difference algorithm and MODTRAN simulations. FALL3D is a 3-D time-dependent Eulerian model for the transport and deposition of volcanic particles that outputs, among other variables, cloud column mass and AOD. We consider the Mt. Etna volcano 2002 eruptive event as a test case. Results show a good agreement between the mean AOT retrieved and the spatial ash dispersion in the

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

    Directory of Open Access Journals (Sweden)

    Andrea Lammert

    2015-08-01

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

  15. Forecasting Lake-Effect Precipitation in the Great Lakes Region Using NASA Enhanced-Satellite Data

    Science.gov (United States)

    Cipullo, Michelle; Molthan, Andrew; Shafer, Jackie; Case, Jonathan; Jedlovec, Gary

    2011-01-01

    Lake-effect precipitation is common in the Great Lakes region, particularly during the late fall and winter. The synoptic processes of lake-effect precipitation are well understood by operational forecasters, but individual forecast events still present a challenge. Locally run, high resolution models can assist the forecaster in identifying the onset and duration of precipitation, but model results are sensitive to initial conditions, particularly the assumed surface temperature of the Great Lakes. The NASA Short-term Prediction Research and Transition (SPoRT) Center has created a Great Lakes Surface Temperature (GLST) composite, which uses infrared estimates of water temperatures obtained from the MODIS instrument aboard the Aqua and Terra satellites, other coarser resolution infrared data when MODIS is not available, and ice cover maps produced by the NOAA Great Lakes Environmental Research Lab (GLERL). This product has been implemented into the Weather Research and Forecast (WRF) model Environmental Modeling System (WRF-EMS), used within forecast offices to run local, high resolution forecasts. The sensitivity of the model forecast to the GLST product was analyzed with a case study of the Lake Effect Storm Echinacea, which produced 10 to 12 inches of snowfall downwind of Lake Erie, and 8 to 18 inches downwind of Lake Ontario from 27-29 January 2010. This research compares a forecast using the default Great Lakes surface temperatures from the Real Time Global sea surface temperature (RTG SST), in the WRF-EMS model to the enhanced NASA SPoRT GLST product to study forecast impacts. Results from this case study show that the SPoRT GLST contained less ice cover over Lake Erie and generally cooler water temperatures over Lakes Erie and Ontario. Latent and sensible heat fluxes over Lake Ontario were decreased in the GLST product. The GLST product decreased the quantitative precipitation forecast (QPF), which can be correlated to the decrease in temperatures and heat

  16. Optical and Microphysical Retrievals of Marine Stratocumulus Clouds off the Coast of Namibia from Satellite and Aircraft

    Science.gov (United States)

    Platnick, Steven E.

    2010-01-01

    these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, and fundamental atmospheric research. The archived MODIS Collection 5 cloud products processing stream will be used to analyze low water cloud scenes off the Namibian and Angolan coasts during SAFARI 2000 time period, as well as other years. Pixel-level Terra and Aqua MODIS retrievals (l. km spatial resolution at nadir) and gridded (1' uniform grid) statistics of cloud optical thickness and effective particle radius will be presented, including joint probability distributions between the two quantities. In addition, perspectives from the MODIS Airborne Simulator, which flew on the ER-2 during SAFARI 2000 providing high spatial resolution retrievals (50 m at nadir), will be presented as appropriate. The H-SAF Program requires an experimental operational European-centric Satellite Precipitation Algorithm System (E-SPAS) that produces medium spatial resolution and high temporal resolution surface rainfall and snowfall estimates over the Greater European Region including the Greater Mediterranean Basin. Currently, there are various types of experimental operational algorithm methods of differing spatiotemporal resolutions that generate global precipitation estimates. This address will first assess the current status of these methods and then recommend a methodology for the H-SAF Program that deviates somewhat from the current approach under development but one that takes advantage of existing techniques and existing software developed for the TRMM Project and available through the public domain.

  17. Source mass eruption rate retrieved from satellite-based data using statistical modelling

    Science.gov (United States)

    Gouhier, Mathieu; Guillin, Arnaud; Azzaoui, Nourddine; Eychenne, Julia; Valade, Sébastien

    2015-04-01

    Ash clouds emitted during volcanic eruptions have long been recognized as a major hazard likely to have dramatic consequences on aircrafts, environment and people. Thus, the International Civil Aviation Organization (ICAO) established nine Volcanic Ash Advisory Centers (VAACs) around the world, whose mission is to forecast the location and concentration of ash clouds over hours to days, using volcanic ash transport and dispersion models (VATDs). Those models use input parameters such as plume height (PH), particle size distribution (PSD), and mass eruption rate (MER), the latter being a key parameter as it directly controls the amount of ash injected into the atmosphere. The MER can be obtained rather accurately from detailed ground deposit studies, but this method does not match the operational requirements in case of a volcanic crisis. Thus, VAACs use empirical laws to determine the MER from the estimation of the plume height. In some cases, this method can be difficult to apply, either because plume height data are not available or because uncertainties related to this method are too large. We propose here an alternative method based on the utilization of satellite data to assess the MER at the source, during explosive eruptions. Satellite-based techniques allow fine ash cloud loading to be quantitatively retrieved far from the source vent. Those measurements can be carried out in a systematic and real-time fashion using geostationary satellite, in particular. We tested here the relationship likely to exist between the amount of fine ash dispersed in the atmosphere and of coarser tephra deposited on the ground. The sum of both contributions yielding an estimate of the MER. For this purpose we examined 19 eruptions (of known duration) in detail for which both (i) the amount of fine ash dispersed in the atmosphere, and (ii) the mass of tephra deposited on the ground have been estimated and published. We combined these data with contextual information that may

  18. A Wide-band, Ka-band Amplifier and Radar System for Precipitation Retrievals Project

    Data.gov (United States)

    National Aeronautics and Space Administration — NASA is committed to measuring precipitation on a global scale. In 1997, NASA launched the Tropical Rain Measuring Mission which carried the first spaceborne...

  19. An inversion method for retrieving soil moisture information from satellite altimetry observations

    Science.gov (United States)

    Uebbing, Bernd; Forootan, Ehsan; Kusche, Jürgen; Braakmann-Folgmann, Anne

    2016-04-01

    Soil moisture represents an important component of the terrestrial water cycle that controls., evapotranspiration and vegetation growth. Consequently, knowledge on soil moisture variability is essential to understand the interactions between land and atmosphere. Yet, terrestrial measurements are sparse and their information content is limited due to the large spatial variability of soil moisture. Therefore, over the last two decades, several active and passive radar and satellite missions such as ERS/SCAT, AMSR, SMOS or SMAP have been providing backscatter information that can be used to estimate surface conditions including soil moisture which is proportional to the dielectric constant of the upper (few cm) soil layers . Another source of soil moisture information are satellite radar altimeters, originally designed to measure sea surface height over the oceans. Measurements of Jason-1/2 (Ku- and C-Band) or Envisat (Ku- and S-Band) nadir radar backscatter provide high-resolution along-track information (~ 300m along-track resolution) on backscatter every ~10 days (Jason-1/2) or ~35 days (Envisat). Recent studies found good correlation between backscatter and soil moisture in upper layers, especially in arid and semi-arid regions, indicating the potential of satellite altimetry both to reconstruct and to monitor soil moisture variability. However, measuring soil moisture using altimetry has some drawbacks that include: (1) the noisy behavior of the altimetry-derived backscatter (due to e.g., existence of surface water in the radar foot-print), (2) the strong assumptions for converting altimetry backscatters to the soil moisture storage changes, and (3) the need for interpolating between the tracks. In this study, we suggest a new inversion framework that allows to retrieve soil moisture information from along-track Jason-2 and Envisat satellite altimetry data, and we test this scheme over the Australian arid and semi-arid regions. Our method consists of: (i

  20. An overview of neural network applications for soil moisture retrieval from radar satellite sensors

    Science.gov (United States)

    Santi, E.; Paloscia, S.; Pettinato, S.

    2014-10-01

    Frequent and spatially distributed measurements of soil moisture (SMC), at different spatial scales, are advisable for all applications related to the environmental disciplines, such as climatology, meteorology, hydrology and agriculture. Satellite sensors operating in the low part of microwave spectrum are very suitable for this purpose, and their signals can be directly related to the moisture content of the observed surfaces, provided that all the contributions from soil and vegetation to the measured signal are properly accounted for. Among the algorithms used for the retrieval of SMC from both active (i.e. Synthetic Aperture Radar, SAR or real aperture radars) and passive (radiometers) microwave sensors, the artificial neural networks (ANN) represent the best compromise between accuracy and computation speed. ANN based algorithms have been developed at IFAC, and adapted to several radar and radiometric satellite sensors, in order to generate SMC products at different spatial resolutions, varying from hundreds of meters to tens of kilometers. These algorithms, which use the ANN techniques for inverting theoretical and semi-empirical models, such as Advanced Integral Equation (AIEM), Oh models, and Radiative transfer Theory (RTT), have been adapted to the C-band acquisitions from SAR (Envisat/ASAR) and real aperture radar (ASCAT) and to the X-band SAR acquisitions of Cosmo-SkyMed and TerraSAR-X. Moreover, a specific ANN algorithm has also been implemented for the L-band active and passive acquisitions of the incoming SMAP mission. The latter satellite will carry onboard simultaneously one radar and one radiometer operating at the same frequency, but with different spatial resolutions (3 and 40 km, respectively). Large datasets of co-located satellite acquisitions and direct SMC measurements on several test sites located worldwide have been used along with simulations derived from forward electromagnetic models for setting up, training and validating these

  1. Flood forecasting in Niger-Benue basin using satellite and quantitative precipitation forecast data

    Science.gov (United States)

    Haile, Alemseged Tamiru; Tefera, Fekadu Teshome; Rientjes, Tom

    2016-10-01

    Availability of reliable, timely and accurate rainfall data is constraining the establishment of flood forecasting and early warning systems in many parts of Africa. We evaluated the potential of satellite and weather forecast data as input to a parsimonious flood forecasting model to provide information for flood early warning in the central part of Nigeria. We calibrated the HEC-HMS rainfall-runoff model using rainfall data from post real time Tropical Rainfall Measuring Mission (TRMM) Multi satellite Precipitation Analysis product (TMPA). Real time TMPA satellite rainfall estimates and European Centre for Medium-Range Weather Forecasts (ECMWF) rainfall products were tested for flood forecasting. The implication of removing the systematic errors of the satellite rainfall estimates (SREs) was explored. Performance of the rainfall-runoff model was assessed using visual inspection of simulated and observed hydrographs and a set of performance indicators. The forecast skill was assessed for 1-6 days lead time using categorical verification statistics such as Probability Of Detection (POD), Frequency Of Hit (FOH) and Frequency Of Miss (FOM). The model performance satisfactorily reproduced the pattern and volume of the observed stream flow hydrograph of Benue River. Overall, our results show that SREs and rainfall forecasts from weather models have great potential to serve as model inputs for real-time flood forecasting in data scarce areas. For these data to receive application in African transboundary basins, we suggest (i) removing their systematic error to further improve flood forecast skill; (ii) improving rainfall forecasts; and (iii) improving data sharing between riparian countries.

  2. A Comparison of Different Regression Algorithms for Downscaling Monthly Satellite-Based Precipitation over North China

    Directory of Open Access Journals (Sweden)

    Wenlong Jing

    2016-10-01

    Full Text Available Environmental monitoring of Earth from space has provided invaluable information for understanding land–atmosphere water and energy exchanges. However, the use of satellite-based precipitation observations in hydrologic and environmental applications is often limited by their coarse spatial resolutions. In this study, we propose a downscaling approach based on precipitation–land surface characteristics. Daytime land surface temperature, nighttime land surface temperature, and day–night land surface temperature differences were introduced as variables in addition to the Normalized Difference Vegetation Index (NDVI, the Digital Elevation Model (DEM, and geolocation (longitude, latitude. Four machine learning regression algorithms, the classification and regression tree (CART, the k-nearest neighbors (k-NN, the support vector machine (SVM, and random forests (RF, were implemented to downscale monthly TRMM 3B43 V7 precipitation data from 25 km to 1 km over North China for the purpose of comparison of algorithm performance. The downscaled results were validated based on observations from meteorological stations and were also compared to a previous downscaling algorithm. According to the validation results, the RF-based model produced the results with the highest accuracy. It was followed by SVM, CART, and k-NN, but the accuracy of the downscaled results using SVM relied greatly on residual correction. The downscaled results were well correlated with the observations during the year, but the accuracies were relatively lower in July to September. Downscaling errors increase as monthly total precipitation increases, but the RF model was less affected by this proportional effect between errors and observation compared with the other algorithms. The variable importances of the land surface temperature (LST feature variables were higher than those of NDVI, which indicates the significance of considering the precipitation–land surface temperature

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

    National Research Council Canada - National Science Library

    Fei Yuan; Limin Zhang; Khin Wah Wah Win; Liliang Ren; Chongxu Zhao; Yonghua Zhu; Shanhu Jiang; Yi Liu

    2017-01-01

    ...) 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...

  4. Simulation of the satellite radar altimeter sea ice thickness retrieval uncertainty

    Directory of Open Access Journals (Sweden)

    R. T. Tonboe

    2009-07-01

    Full Text Available Although it is well known that radar waves penetrate into snow and sea ice, the exact mechanisms for radar-altimeter scattering and its link to the depth of the effective scattering surface from sea ice are still unknown. Previously proposed mechanisms linked the snow ice interface, i.e. the dominating scattering horizon, directly with the depth of the effective scattering surface. However, simulations using a multilayer radar scattering model show that the effective scattering surface is affected by snow-cover and ice properties. With the coming Cryosat-2 (planned launch 2009 satellite radar altimeter it is proposed that sea ice thickness can be derived by measuring its freeboard. In this study we evaluate the radar altimeter sea ice thickness retrieval uncertainty in terms of floe buoyancy, radar penetration and ice type distribution using both a scattering model and ''Archimedes' principle''. The effect of the snow cover on the floe buoyancy and the radar penetration and on the ice cover spatial and temporal variability is assessed from field campaign measurements in the Arctic and Antarctic. In addition to these well known uncertainties we use high resolution RADARSAT SAR data to simulate errors due to the variability of the effective scattering surface as a result of the sub-footprint spatial backscatter and elevation distribution sometimes called preferential sampling. In particular in areas where ridges represent a significant part of the ice volume (e.g. the Lincoln Sea the simulated altimeter thickness estimate is lower than the real average footprint thickness. This means that the errors are large, yet manageable if the relevant quantities are known a priori. A discussion of the radar altimeter ice thickness retrieval uncertainties concludes the paper.

  5. Simulation of the satellite radar altimeter sea ice thickness retrieval uncertainty

    Science.gov (United States)

    Tonboe, R. T.; Pedersen, L. T.; Haas, C.

    2009-07-01

    Although it is well known that radar waves penetrate into snow and sea ice, the exact mechanisms for radar-altimeter scattering and its link to the depth of the effective scattering surface from sea ice are still unknown. Previously proposed mechanisms linked the snow ice interface, i.e. the dominating scattering horizon, directly with the depth of the effective scattering surface. However, simulations using a multilayer radar scattering model show that the effective scattering surface is affected by snow-cover and ice properties. With the coming Cryosat-2 (planned launch 2009) satellite radar altimeter it is proposed that sea ice thickness can be derived by measuring its freeboard. In this study we evaluate the radar altimeter sea ice thickness retrieval uncertainty in terms of floe buoyancy, radar penetration and ice type distribution using both a scattering model and ''Archimedes' principle''. The effect of the snow cover on the floe buoyancy and the radar penetration and on the ice cover spatial and temporal variability is assessed from field campaign measurements in the Arctic and Antarctic. In addition to these well known uncertainties we use high resolution RADARSAT SAR data to simulate errors due to the variability of the effective scattering surface as a result of the sub-footprint spatial backscatter and elevation distribution sometimes called preferential sampling. In particular in areas where ridges represent a significant part of the ice volume (e.g. the Lincoln Sea) the simulated altimeter thickness estimate is lower than the real average footprint thickness. This means that the errors are large, yet manageable if the relevant quantities are known a priori. A discussion of the radar altimeter ice thickness retrieval uncertainties concludes the paper.

  6. Near-Real Time Satellite-Retrieved Cloud and Surface Properties for Weather and Aviation Safety Applications

    Science.gov (United States)

    Minnis, Patrick; Smith, William L., Jr.; Bedka, Kristopher M.; Nguyen, Louis; Palikonda, Rabindra; Hong, Gang; Trepte, Qing Z.; Chee, Thad; Scarino, Benjamin; Spangenberg, Douglas A.; Sun-Mack, Szedung; Fleeger, Cecilia; Ayers, J. Kirk; Chang, Fu-Lung; Heck, Patrick M.

    2014-01-01

    Cloud properties determined from satellite imager radiances provide a valuable source of information for nowcasting and weather forecasting. In recent years, it has been shown that assimilation of cloud top temperature, optical depth, and total water path can increase the accuracies of weather analyses and forecasts. Aircraft icing conditions can be accurately diagnosed in near-­-real time (NRT) retrievals of cloud effective particle size, phase, and water path, providing valuable data for pilots. NRT retrievals of surface skin temperature can also be assimilated in numerical weather prediction models to provide more accurate representations of solar heating and longwave cooling at the surface, where convective initiation. These and other applications are being exploited more frequently as the value of NRT cloud data become recognized. At NASA Langley, cloud properties and surface skin temperature are being retrieved in near-­-real time globally from both geostationary (GEO) and low-­-earth orbiting (LEO) satellite imagers for weather model assimilation and nowcasting for hazards such as aircraft icing. Cloud data from GEO satellites over North America are disseminated through NCEP, while those data and global LEO and GEO retrievals are disseminated from a Langley website. This paper presents an overview of the various available datasets, provides examples of their application, and discusses the use of the various datasets downstream. Future challenges and areas of improvement are also presented.

  7. Diagnosis of an intense atmospheric river impacting the pacific northwest: Storm summary and offshore vertical structure observed with COSMIC satellite retrievals

    Science.gov (United States)

    Neiman, P.J.; Ralph, F.M.; Wick, G.A.; Kuo, Y.-H.; Wee, T.-K.; Ma, Z.; Taylor, G.H.; Dettinger, M.D.

    2008-01-01

    This study uses the new satellite-based Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission to retrieve tropospheric profiles of temperature and moisture over the data-sparse eastern Pacific Ocean. The COSMIC retrievals, which employ a global positioning system radio occultation technique combined with "first-guess" information from numerical weather prediction model analyses, are evaluated through the diagnosis of an intense atmospheric river (AR; i.e., a narrow plume of strong water vapor flux) that devastated the Pacific Northwest with flooding rains in early November 2006. A detailed analysis of this AR is presented first using conventional datasets and highlights the fact that ARs are critical contributors to West Coast extreme precipitation and flooding events. Then, the COSMIC evaluation is provided. Offshore composite COSMIC soundings north of, within, and south of this AR exhibited vertical structures that are meteorologically consistent with satellite imagery and global reanalysis fields of this case and with earlier composite dropsonde results from other landfalling ARs. Also, a curtain of 12 offshore COSMIC soundings through the AR yielded cross-sectional thermodynamic and moisture structures that were similarly consistent, including details comparable to earlier aircraft-based dropsonde analyses. The results show that the new COSMIC retrievals, which are global (currently yielding ???2000 soundings per day), provide high-resolution vertical-profile information beyond that found in the numerical model first-guess fields and can help monitor key lower-tropospheric mesoscale phenomena in data-sparse regions. Hence, COSMIC will likely support a wide array of applications, from physical process studies to data assimilation, numerical weather prediction, and climate research. ?? 2008 American Meteorological Society.

  8. Low-cost Citizen Science Balloon Platform for Measuring Air Pollutants to Improve Satellite Retrieval Algorithms

    Science.gov (United States)

    Potosnak, M. J.; Beck-Winchatz, B.; Ritter, P.

    2016-12-01

    High-altitude balloons (HABs) are an engaging platform for citizen science and formal and informal STEM education. However, the logistics of launching, chasing and recovering a payload on a 1200 g or 1500 g balloon can be daunting for many novice school groups and citizen scientists, and the cost can be prohibitive. In addition, there are many interesting scientific applications that do not require reaching the stratosphere, including measuring atmospheric pollutants in the planetary boundary layer. With a large number of citizen scientist flights, these data can be used to constrain satellite retrieval algorithms. In this poster presentation, we discuss a novel approach based on small (30 g) balloons that are cheap and easy to handle, and low-cost tracking devices (SPOT trackers for hikers) that do not require a radio license. Our scientific goal is to measure air quality in the lower troposphere. For example, particulate matter (PM) is an air pollutant that varies on small spatial scales and has sources in rural areas like biomass burning and farming practices such as tilling. Our HAB platform test flight incorporates an optical PM sensor, an integrated single board computer that records the PM sensor signal in addition to flight parameters (pressure, location and altitude), and a low-cost tracking system. Our goal is for the entire platform to cost less than $500. While the datasets generated by these flights are typically small, integrating a network of flight data from citizen scientists into a form usable for comparison to satellite data will require big data techniques.

  9. High resolution modeling of CO2 over Europe: implications for representation errors of satellite retrievals

    Directory of Open Access Journals (Sweden)

    T. Koch

    2010-01-01

    Full Text Available Satellite retrievals for column CO2 with better spatial and temporal sampling are expected to improve the current surface flux estimates of CO2 via inverse techniques. However, the spatial scale mismatch between remotely sensed CO2 and current generation inverse models can induce representation errors, which can cause systematic biases in flux estimates. This study is focused on estimating these representation errors associated with utilization of satellite measurements in global models with a horizontal resolution of about 1 degree or less. For this we used simulated CO2 from the high resolution modeling framework WRF-VPRM, which links CO2 fluxes from a diagnostic biosphere model to a weather forecasting model at 10×10 km2 horizontal resolution. Sub-grid variability of column averaged CO2, i.e. the variability not resolved by global models, reached up to 1.2 ppm with a median value of 0.4 ppm. Statistical analysis of the simulation results indicate that orography plays an important role. Using sub-grid variability of orography and CO2 fluxes as well as resolved mixing ratio of CO2, a linear model can be formulated that could explain about 50% of the spatial patterns in the systematic (bias or correlated error component of representation error in column and near-surface CO2 during day- and night-times. These findings give hints for a parameterization of representation error which would allow for the representation error to taken into account in inverse models or data assimilation systems.

  10. Retrieval of vertical wind profiles during monsoon from satellite observed winds over the Indian Ocean using complex EOF analysis

    Indian Academy of Sciences (India)

    C M Kishtawal; Sujit Basu; S Karthikeyan

    2001-03-01

    The aim of this paper is to study the feasibility of deriving vertical wind profiles from current satellite observations. With this aim, we carried out complex empirical orthogonal function (CEOF) analysis of a large number of radiosonde observations of wind profiles over the Indian Ocean during the monsoon months. It has been found that the first two CEOFs explain 67% of the total variance in wind fields. While the first principal component is well correlated with the winds at 850 mb ( = 0.80), the second one is highly correlated with winds at 200 mb ( = 0.89). This analysis formed the basis of a retrieval algorithm which ensures the retrieval of vertical profiles of winds using satellite tracked cloud motion vector winds. Under the assumption that accurate measurements of wind are available at the above mentioned levels, the r.m.s. error of retrieval of each component of wind is estimated to range between 2ms-1 and 6ms-1 at different levels, which is much less than the natural variance of winds at these levels. For a better visualization of retrieval, we have provided retrieved and true wind profiles side by side for four typical synoptic conditions during the monsoon season.

  11. The Contribution Of Sampling Errors In Satellite Precipitation Estimates To High Flood Uncertainty In Subtropical South America

    Science.gov (United States)

    Demaria, E. M.; Valdes, J. B.; Nijssen, B.; Rodriguez, D.; Su, F.

    2009-12-01

    Satellite precipitation estimates are becoming increasingly available at temporal and spatial scales of interest for hydrological applications. Unfortunately precipitation estimated from global satellites is prone to errors hailing from different sources. The impact of sampling errors on the hydrological cycle of a large-size basin was assessed with a macroscale hydrological model. Synthetic precipitation fields were generated in a Monte Carlo fashion by perturbing observed precipitation fields with sampling errors. Three sampling intervals were chosen to generate the precipitation fields: one-hour, three-hours which is the canonical Global Precipitation Mission (GPM) sampling interval, and six-hours. The Variable Infiltration Capacity (VIC) model was used to assess the impact of sampling errors on hydrological fluxes and states in the Iguazu basin in South America for the period 1982-2005. The propagation of sampling errors through the hydrological cycle was evaluated for high flow events that have the 2% chance of being exceeded in any given time. Results show that observed event volumes are underestimated for small volumes for the three and six-hours sampling intervals but for the one-hour sampling interval the difference is almost negligible.The timing of the hydrograph is not affected by uncertainty existent in satellite-derived precipitation when it propagates through the hydrological cycle. Results of two non-parametric tests: the Kruskal-Wallis test on the mean ranks of the population and the Ansari-Bradley test on the equality of the variances indicate that sampling errors do no affect the occurrence of high flows since their probability distribution is not affected. The applicability of these results is limited to a humid climate. However the Iguazu basin is representative of several basins located in subtropical regions around the world, many of which are under-instrumented catchments, where satellite precipitation might be one of the few available data

  12. Hail detection algorithm for the Global Precipitation Measuring mission core satellite sensors

    Science.gov (United States)

    Mroz, Kamil; Battaglia, Alessandro; Lang, Timothy J.; Tanelli, Simone; Cecil, Daniel J.; Tridon, Frederic

    2017-04-01

    By exploiting an abundant number of extreme storms observed simultaneously by the Global Precipitation Measurement (GPM) mission core satellite's suite of sensors and by the ground-based S-band Next-Generation Radar (NEXRAD) network over continental US, proxies for the identification of hail are developed based on the GPM core satellite observables. The full capabilities of the GPM observatory are tested by analyzing more than twenty observables and adopting the hydrometeor classification based on ground-based polarimetric measurements as truth. The proxies have been tested using the Critical Success Index (CSI) as a verification measure. The hail detection algorithm based on the mean Ku reflectivity in the mixed-phase layer performs the best, out of all considered proxies (CSI of 45%). Outside the Dual frequency Precipitation Radar (DPR) swath, the Polarization Corrected Temperature at 18.7 GHz shows the greatest potential for hail detection among all GMI channels (CSI of 26% at a threshold value of 261 K). When dual variable proxies are considered, the combination involving the mixed-phase reflectivity values at both Ku and Ka-bands outperforms all the other proxies, with a CSI of 49%. The best-performing radar-radiometer algorithm is based on the mixed-phase reflectivity at Ku-band and on the brightness temperature (TB) at 10.7 GHz (CSI of 46%). When only radiometric data are available, the algorithm based on the TBs at 36.6 and 166 GHz is the most efficient, with a CSI of 27.5%.

  13. Satellite retrievals of leaf chlorophyll and photosynthetic capacity for improved modeling of GPP

    KAUST Repository

    Houborg, Rasmus

    2013-08-01

    This study investigates the utility of in situ and satellite-based leaf chlorophyll (Chl) estimates for quantifying leaf photosynthetic capacity and for constraining model simulations of Gross Primary Productivity (GPP) over a corn field in Maryland, U.S.A. The maximum rate of carboxylation (V-max) represents a key control on leaf photosynthesis within the widely employed C-3 and C-4 photosynthesis models proposed by Farquhar et al. (1980) and Collatz et al. (1992), respectively. A semi-mechanistic relationship between V-max(5) (V-max normalized to 25 degrees C) and Chl is derived based on interlinkages between V-max(25), Rubisco enzyme kinetics, leaf nitrogen, and Chl reported in the experimental literature. The resulting linear V-max(25) - Chl relationship is embedded within the photosynthesis scheme of the Community Land Model (CLM), thereby bypassing the use of fixed plant functional type (PFT) specific V-max(25) values. The effect of the updated parameterization on simulated carbon fluxes is tested over a corn field growing season using: (1) a detailed Chl time-series established on the basis of intensive field measurements and (2) Chl estimates derived from Landsat imagery using the REGularized canopy reFLECtance (REGFLEC) tool. Validations against flux tower observations demonstrate benefit of using Chl to parameterize V-max(25) to account for variations in nitrogen availability imposed by severe environmental conditions. The use of V-max(25) that varied seasonally as a function of satellite-based Chl, rather than a fixed PFT-specific value, significantly improved the agreement with observed tower fluxes with Pearson\\'s correlation coefficient (r) increasing from 0.88 to 0.93 and the root-mean-square-deviation decreasing from 4.77 to 3.48 mu mol m(-2) s(-1). The results support the use of Chl as a proxy for photosynthetic capacity using generalized relationships between V-max(25) and Chl, and advocate the potential of satellite retrieved Chl for

  14. Retrieval of humidity and temperature profiles over the oceans from INSAT 3D satellite radiances

    Indian Academy of Sciences (India)

    C Krishnamoorthy; Deo Kumar; C Balaji

    2016-03-01

    In this study, retrieval of temperature and humidity profiles of atmosphere from INSAT 3D-observed radiances has been accomplished. As the first step, a fast forward radiative transfer model using an Artificial neural network has been developed and it was proven to be highly effective, giving a correlationcoefficient of 0.97. In order to develop this, a diverse set of physics-based clear sky profiles of pressure (P), temperature (T) and specific humidity (q) has been developed. The developed database was further used for geophysical retrieval experiments in two different frameworks, namely, an ANN and Bayesianestimation. The neural network retrievals were performed for three different cases, viz., temperature only retrieval, humidity only retrieval and combined retrieval. The temperature/humidity only ANN retrievals were found superior to combined retrieval using an ANN. Furthermore, Bayesian estimation showed superior results when compared with the combined ANN retrievals.

  15. Retrieving Marine Inherent Optical Properties from Satellites Using Temperature and Salinity-dependent Backscattering by Seawater

    Science.gov (United States)

    Werdell, Paul J.; Franz, Bryan Alden; Lefler, Jason Travis; Robinson, Wayne D.; Boss, Emmanuel

    2013-01-01

    Time-series of marine inherent optical properties (IOPs) from ocean color satellite instruments provide valuable data records for studying long-term time changes in ocean ecosystems. Semi-analytical algorithms (SAAs) provide a common method for estimating IOPs from radiometric measurements of the marine light field. Most SAAs assign constant spectral values for seawater absorption and backscattering, assume spectral shape functions of the remaining constituent absorption and scattering components (e.g., phytoplankton, non-algal particles, and colored dissolved organic matter), and retrieve the magnitudes of each remaining constituent required to match the spectral distribution of measured radiances. Here, we explore the use of temperature- and salinity-dependent values for seawater backscattering in lieu of the constant spectrum currently employed by most SAAs. Our results suggest that use of temperature- and salinity-dependent seawater spectra elevate the SAA-derived particle backscattering, reduce the non-algal particles plus colored dissolved organic matter absorption, and leave the derived absorption by phytoplankton unchanged.

  16. Monitoring and tracking the trans-Pacific transport of aerosols using multi-satellite aerosol optical depth retrievals

    Directory of Open Access Journals (Sweden)

    A. R. Naeger

    2015-10-01

    Full Text Available The primary goal of this study was to generate a near-real time (NRT aerosol optical depth (AOD product capable of providing a comprehensive understanding of the aerosol spatial distribution over the Pacific Ocean in order to better monitor and track the trans-Pacific transport of aerosols. Therefore, we developed a NRT product that takes advantage of observations from both low-earth orbiting and geostationary satellites. In particular, we utilize AOD products from the Moderate Resolution Imaging Spectroradiometer (MODIS and Suomi National Polar-orbiting Partnership (NPP Visible Infrared Imaging Radiometer Suite (VIIRS satellites. Then, we combine these AOD products with our own retrieval algorithms developed for the NOAA Geostationary Operational Environmental Satellite (GOES-15 and Japan Meteorological Agency (JMA Multi-functional Transport Satellite (MTSAT-2 to generate a NRT daily AOD composite product. We present examples of the daily AOD composite product for a case study of trans-Pacific transport of Asian pollution and dust aerosols in mid-March 2014. Overall, the new product successfully tracks this aerosol plume during its trans-Pacific transport to the west coast of North America. However, we identify several areas across the domain of interest from Asia to North America where the new product can encounter significant uncertainties due to the inclusion of the geostationary AOD retrievals. The uncertainties associated with geostationary AOD retrievals are expected to be minimized after the successful launch of the next-generation advanced NOAA GOES-R and recently launched JMA Himawari satellites. Observations from these advanced satellites will ultimately provide an enhanced understanding of the spatial and temporal distribution of aerosols over the Pacific.

  17. Multi-Grid-Cell Validation of Satellite Aerosol Property Retrievals in INTEX/ITCT/ICARTT 2004

    Science.gov (United States)

    Russell, P. B.; Livingston, J. M.; Redemann, J.; Schmid, B.; Ramirez, S. A.; Eilers, J.; Kahn, R.; Chu, D. A.; Remer, L.; Quinn, P. K.; Rood, M. J.; Wang, W.

    2007-01-01

    Aerosol transport off the US Northeast coast during the Summer 2004 International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) Intercontinental Chemical Transport Experiment (INTEX) and Intercontinental Transport and Chemical Transformation (ITCT) experiments produced a wide range of aerosol types and aerosol optical depth (AOD) values, often with strong horizontal AOD gradients. In these conditions we flew the 14-channel NASA Ames Airborne Tracking Sun photometer (AATS) on a Jetstream 31 (J31) aircraft. Legs flown at low altitude (usually less than 100 m ASL) provided comparisons of AATS AOD spectra to retrievals for 90 grid cells of the satellite radiometers MODIS-Terra, MODIS-Aqua, and MISR, all over the ocean. Characterization of the retrieval environment was aided by using vertical profiles by the J31 (showing aerosol vertical structure) and, on occasion, shipboard measurements of light scattering and absorption. AATS provides AOD at 13 wavelengths lambda from 354 to 2138 nm, spanning the range of aerosol retrieval wavelengths for MODIS over ocean (466-2119 nm) and MISR (446-866 nm). Midvisible AOD on low-altitude J31 legs in satellite grid cells ranged from 0.05 to 0.9, with horizontal gradients often in the range 0.05 to 0.13 per 10 km. When possible, we used ship measurements of humidified aerosol scattering and absorption to estimate AOD below the J31. In these cases, which had J31 altitudes 60-110 m ASL (typical of J31 low-altitude transects), estimated midvisible AOD below the J31 ranged from 0.003 to 0.013, with mean 0.009 and standard deviation 0.003. These values averaged 6 percent of AOD above the 53 1. MISR-AATS comparisons on 29 July 2004 in 8 grid cells (each -17.6 km x 17.6 km) show that MISR versions 15 and 16 captured the AATS-measured AOD gradient (correlation coefficient R2 = 0.87 to 0.92), but the MISR gradient was somewhat weaker than the AATS gradient. The large AOD (midvisible values up to -0.9) and

  18. Integrating satellite retrieved leaf chlorophyll into land surface models for constraining simulations of water and carbon fluxes

    KAUST Repository

    Houborg, Rasmus

    2013-07-01

    In terrestrial biosphere models, key biochemical controls on carbon uptake by vegetation canopies are typically assigned fixed literature-based values for broad categories of vegetation types although in reality significant spatial and temporal variability exists. Satellite remote sensing can support modeling efforts by offering distributed information on important land surface characteristics, which would be very difficult to obtain otherwise. This study investigates the utility of satellite based retrievals of leaf chlorophyll for estimating leaf photosynthetic capacity and for constraining model simulations of water and carbon fluxes. © 2013 IEEE.

  19. Evaluation of the latest satellite-gauge precipitation products and their hydrologic applications over the Huaihe River basin

    Science.gov (United States)

    Sun, Ruochen; Yuan, Huiling; Liu, Xiaoli; Jiang, Xiaoman

    2016-05-01

    Satellite-gauge quantitative precipitation estimate (QPE) products may reduce the errors in near real-time satellite precipitation estimates by combining rain gauge data, which provides great potential to hydrometeorological applications. This study aims to comprehensively evaluate four of the latest satellite-gauge QPEs, including NASA's Tropical Rainfall Measuring Mission (TRMM) 3B42V7 product, NOAA's Climate Prediction Center (CPC) MORPHing technique (CMORPH) bias-corrected product (CMORPH CRT), CMORPH satellite-gauge merged product (CMORPH BLD) and CMORPH satellite-gauge merged product developed at the National Meteorological Information Center (NMIC) of the China Meteorological Administration (CMA) (CMORPH CMA). These four satellite-gauge QPEs are statistically evaluated over the Huaihe River basin during 2003-2012 and applied into the distributed Variable Infiltration Capacity (VIC) model to assess hydrologic utilities. Compared to the China Gauge-based Daily Precipitation Analysis (CGDPA) newly developed at CMA/NMIC, the four satellite-gauge QPEs generally depict the spatial distribution well, with the underestimation in the southern mountains and overestimation in the northern plain of the Huaihe River basin. Specifically, both TRMM and CMORPH CRT adopt simple gauge adjustment algorithms and exhibit relatively poor performance, with evidently deteriorated quality in winter. In contrast, the probability density function-optimal interpolation (PDF-OI) gauge adjustment procedure has been applied in CMORPH BLD and CMORPH CMA, resulting in higher quality and more stable performance. CMORPH CMA further benefits from a merged dense gauge observation network and outperforms the other QPEs with significant improvements in rainfall amount and spatial/temporal distributions. Due to the insufficient gauge observations in the merging process, CMORPH BLD features the similar error characteristics of CMORPH CRT with a positive bias of light precipitation and a negative

  20. Comparison and evaluation of satellite- and reanalysis-based precipitation products for water resources management in the Brahmaputra River basin

    Science.gov (United States)

    Saleh Khan, Abu; Sohel Masud, Md.; Abdulla Hel Kafi, Md.; Sultana, Tashrifa; Lopez Lopez, Patricia

    2017-04-01

    The Brahmaputra River, with a transboundary basin area of approx. 554,500 km2, has its origin on the northern slope of the Himalayas in China, from where it flows through India, Bhutan and finally Bangladesh. Brahmaputra basin's climatology is heavily conditioned by precipitation during the monsoon months, concentrating about the 85 % of the rainfall in this period and originating severe and frequent floods that impact specially the Bangladeshi population in the delta region. Recent campaigns to increase the quality and to share ground-based hydro-meteorological data, in particular precipitation, within the basin have provided limited results. Global rainfall data from satellite and reanalysis may improve the temporal and spatial availability of in-situ observations for advanced water resources management. This study aims to evaluate the applicability of several global precipitation products from satellite and reanalysis in comparison with in-situ data to quantify their added value for hydrological modeling at a basin and sub-basin scale for the Brahmaputra River. Precipitation products from CMORPH, TRMM-3B42, GsMAP, WFDEI, MSWEP and various combinations with ground-based data were evaluated at basin and sub-basin level at a daily and monthly temporal resolution. The Brahmaputra was delineated into 54 sub-basins for a more detailed evaluation of the precipitation products. The data were analysed and inter-compared for the time period from 2002 to 2010. Precipitation performance assessment was conducted including several indicators, such as probability of detection (POD), false alarm ratio (FAR), Pearson's correlation coefficient (r), bias and root mean square error (RMSE). Preliminary results indicate high correlation and low bias and RMSE values between WFDEI, TRMM-3B42 and CMORPH precipitation and in-situ observations at a monthly time scale. Lower correlations and higher bias and RMSE values were found between GsMAP and MSWEP and ground-observed precipitation

  1. 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.

  2. 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.

  3. Dust aerosol impact on the retrieval of cloud top height from satellite observations of CALIPSO, CloudSat and MODIS

    Science.gov (United States)

    Wang, Wencai; Sheng, Lifang; Dong, Xu; Qu, Wenjun; Sun, Jilin; Jin, Hongchun; Logan, Timothy

    2017-02-01

    Dust aerosol effect on the retrievals of dusty cloud top height (DCTH) are analyzed over Northwest China using cloud products from MODerate Resolution Imaging Spectroradiometer (MODIS) on Aqua, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat for the Spring season of March-May over the years 2007-2011. An excellent agreement is found between CloudSat and CALIPSO derived DCTHs for all cloud types, suggesting that the effect of dust aerosols plays a small role in DCTHs determination for lidar and radar measurements. However, the presence of dust aerosols greatly affects the retrievals of DCTHs for MODIS compared with pure clouds and the active sensors derived results. The differences of DCTHs retrieving from CloudSat and MODIS range from -2.30 to 6.8 km. Likewise, the differences of DCTHs retrieving from CALIPSO and MODIS range from -2.66 to 6.78 km. In addition, the results show that the differences in DCTHs for active and passive sensors are dependent on cloud type. On the whole, dust aerosols have the largest effect on cloud top heights (CTH) retrieved of nimbostratus (Ns), followed by altocumulus (Ac) and altostratus (As), the last is cirrus (Ci) over Northwest China. Our results also indicate that the accuracy of MODIS-derived retrievals reduces accompanied with a decrease of height.

  4. Precipitation measurements with GNSS polarimetric Radio Occultations: Status of the ROHP-PAZ mission and anticipated retrievals

    Science.gov (United States)

    Padullés, Ramon; Cardellach, Estel; de la Torre Juárez, Manuel; Tomás, Sergio; Turk, F. Joseph; Ao, Chi O.; Rius, Toni; Oliveras, Santi

    2016-04-01

    The upcoming ROHP-PAZ (Radio Occultations and Heavy Precipitation experiment aboard the spanish PAZ satellite) mission aims to detect, for the first time, precipitation using Global Navigation Satellite System Radio Occultations (GNSS-RO). The electromagnetic signals coming from the GNSS satellites travel tangentially through the atmosphere and will be collected in the PAZ Low Earth Orbiter at two polarizations (vertical and horizontal). This sounding-like technique of the atmosphere will measure all the atmospheric phenomena that are inducing depolarization effects, in addition to all the thermodynamic profiles that standard RO are nowadays providing. The main contributors to depolarization in the troposphere are known to be the hydrometeors, both rain drops from heavy precipitation events and horizontally oriented ice particles in the top of clouds. Their effects on the GNSS signals were predicted in Cardellach et. al. 2015 (IEEE Trans. Geosci. Remote Sens.), and measured in the ROHP-PAZ field campaign Padullés et. al. 2016 (Atmos. Chem. Phys.). Prior to the launch, a complete characterization of all the possible effects, including hydrometeors but also taking into account other elements was needed. To do so, actual data from the COSMIC - FORMOSAT 3 mission (Radio Occultation events) have been collocated with the TRMM, GPM and CloudSat missions (precipitation and clouds missions). Thousands of events have been analyzed, in terms of SNR and phase delays. For the same events, the effect of hydrometeors has been simulated as well as the most known ionospheric effects, such as Faraday Rotation and Cotton-Mouton effects. And finally, the predicted noise, actual measurements of the antenna pattern and some tolerance in the purity of the emitted signal have been included. This has resulted in an extensive data base that is key in the understanding of the upcoming actual data, as well as for the characterization of all the unpredicted effects. We will discuss here the

  5. Time variable gravity retrieval and treatment of temporal aliasing using optical two-way links between GALILEO and LEO satellites

    Science.gov (United States)

    Hauk, Markus; Pail, Roland; Murböck, Michael; Schlicht, Anja

    2016-04-01

    For the determination of temporal gravity fields satellite missions such as GRACE (Gravity Recovery and Climate Experiment) or CHAMP (Challenging Minisatellite Payload) were used in the last decade. These missions improved the knowledge of atmospheric, oceanic and tidal mass variations. The most limiting factor of temporal gravity retrieval quality is temporal aliasing due to the undersampling of high frequency signals, especially in the atmosphere and oceans. This kind of error causes the typical stripes in spatial representations of global gravity fields such as from GRACE. As part of the GETRIS (Geodesy and Time Reference in Space) mission, that aims to establish a geodetic reference station and precise time- and frequency reference in space by using optical two-way communication links between geostationary (GEO) and low Earth orbiting (LEO) satellites, a possible future gravity field mission can be set up. By expanding the GETRIS space segment to the global satellite navigation systems (GNSS) the optical two-way links also connect the GALILEO satellites among themselves and to LEO satellites. From these links between GALILEO and LEO satellites gravitational information can be extracted. In our simulations inter-satellite links between GALILEO and LEO satellites are used to determine temporal changes in the Earth's gravitational field. One of the main goals of this work is to find a suitable constellation together with the best analysis method to reduce temporal aliasing errors. Concerning non-tidal aliasing, it could be shown that the co-estimation of short-period long-wavelength gravity field signals, the so-called Wiese approach, is a powerful method for aliasing reduction (Wiese et al. 2013). By means of a closed loop mission simulator using inter-satellite observations as acceleration differences along the line-of-sight, different mission scenarios for GALILEO-LEO inter-satellite links and different functional models like the Wiese approach are analysed.

  6. Tropospheric BrO column densities in the Arctic derived from satellite: retrieval and comparison to ground-based measurements

    OpenAIRE

    H Sihler; Platt, U.; Beirle, S.; Marbach, T.; S. Kühl; S. Dörner; Verschaeve, J.; Frieß, U.; Pöhler, D.; Vogel, L.; Sander, R.; T. Wagner

    2012-01-01

    During polar spring, halogen radicals like bromine monoxide (BrO) play an important role in the chemistry of tropospheric ozone destruction. Satellite measurements of the BrO distribution have become a particularly useful tool to investigate this probably natural phenomenon, but the separation of stratospheric and tropospheric partial columns of BrO is challenging. In this study, an algorithm was developed to retrieve tropospheric vertical...

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

    Science.gov (United States)

    Zörner, Jan; Penning de Vries, Marloes; Beirle, Steffen; Sihler, Holger; Veres, Patrick R.; Williams, Jonathan; Wagner, Thomas

    2016-07-01

    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 s-1. The pulsed emissions contribute about 21-44 % to total

  8. 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.

  9. Effects of Per-Pixel Variability on Uncertainties in Bathymetric Retrievals from High-Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Elizabeth J. Botha

    2016-05-01

    Full Text Available Increased sophistication of high spatial resolution multispectral satellite sensors provides enhanced bathymetric mapping capability. However, the enhancements are counter-acted by per-pixel variability in sunglint, atmospheric path length and directional effects. This case-study highlights retrieval errors from images acquired at non-optimal geometrical combinations. The effects of variations in the environmental noise on water surface reflectance and the accuracy of environmental variable retrievals were quantified. Two WorldView-2 satellite images were acquired, within one minute of each other, with Image 1 placed in a near-optimal sun-sensor geometric configuration and Image 2 placed close to the specular point of the Bidirectional Reflectance Distribution Function (BRDF. Image 2 had higher total environmental noise due to increased surface glint and higher atmospheric path-scattering. Generally, depths were under-estimated from Image 2, compared to Image 1. A partial improvement in retrieval error after glint correction of Image 2 resulted in an increase of the maximum depth to which accurate depth estimations were returned. This case-study indicates that critical analysis of individual images, accounting for the entire sun elevation and azimuth and satellite sensor pointing and geometry as well as anticipated wave height and direction, is required to ensure an image is fit for purpose for aquatic data analysis.

  10. Arctic clouds and surface radiation – a critical comparison of satellite retrievals and the ERA-interim reanalysis

    Directory of Open Access Journals (Sweden)

    M. Zygmuntowska

    2011-12-01

    Full Text Available Clouds regulate Earth's radiation budget, both by reflecting part of the incoming sunlight leading to cooling and by absorbing and emitting infrared radiation which tends to have a warming effect. Globally averaged, at the top of the atmosphere the cloud radiative effect is to cool the climate, while at the Arctic surface, clouds are thought to be warming. Ground-based observations of central Arctic Ocean cloudiness are limited to sporadic field campaigns. Therefore many studies rely on satellite- or reanalysis data. Here we compare a passive instrument, the AVHRR-based retrieval from CM-SAF, with recently launched active instruments onboard CloudSat and CALIPSO and the widely used ERA-Interim reanalysis. We find that the three data sets differ significantly. In summer, the two satellite products agree having monthly means of 70–80 percent, but the reanalysis are approximately ten percent higher. In winter passive satellite instruments have serious difficulties, detecting only half the cloudiness of the reanalysis, active instruments being in between. The monthly mean long- and shortwave components of the surface cloud radiative effect obtained from the ERA-Interim reanalysis are about twice that calculated on the basis of CloudSat retrievals. We discuss these discrepancies in terms of instrument-, retrieval- and reanalysis characteristics.

  11. A strategy for merging objective estimates of global daily precipitation from gauge observations, satellite estimates, and numerical predictions

    Science.gov (United States)

    Nie, Suping; Wu, Tongwen; Luo, Yong; Deng, Xueliang; Shi, Xueli; Wang, Zaizhi; Liu, Xiangwen; Huang, Jianbin

    2016-07-01

    This paper describes a strategy for merging daily precipitation information from gauge observations, satellite estimates (SEs), and numerical predictions at the global scale. The strategy is designed to remove systemic bias and random error from each individual daily precipitation source to produce a better gridded global daily precipitation product through three steps. First, a cumulative distribution function matching procedure is performed to remove systemic bias over gauge-located land areas. Then, the overall biases in SEs and model predictions (MPs) over ocean areas are corrected using a rescaled strategy based on monthly precipitation. Third, an optimal interpolation (OI)-based merging scheme (referred as the HL-OI scheme) is used to combine unbiased gauge observations, SEs, and MPs to reduce random error from each source and to produce a gauge—satellite-model merged daily precipitation analysis, called BMEP-d (Beijing Climate Center Merged Estimation of Precipitation with daily resolution), with complete global coverage. The BMEP-d data from a four-year period (2011-14) demonstrate the ability of the merging strategy to provide global daily precipitation of substantially improved quality. Benefiting from the advantages of the HL-OI scheme for quantitative error estimates, the better source data can obtain more weights during the merging processes. The BMEP-d data exhibit higher consistency with satellite and gauge source data at middle and low latitudes, and with model source data at high latitudes. Overall, independent validations against GPCP-1DD (GPCP one-degree daily) show that the consistencies between BMEP-d and GPCP-1DD are higher than those of each source dataset in terms of spatial pattern, temporal variability, probability distribution, and statistical precipitation events.

  12. Satellite retrieval of the liquid water fraction in tropical clouds between −20 and −38 °C

    Directory of Open Access Journals (Sweden)

    D. L. Mitchell

    2012-07-01

    Full Text Available This study describes a satellite remote sensing method for directly retrieving the liquid water fraction in mixed phase clouds, and appears unique in this respect. The method uses MODIS split-window channels for retrieving the liquid fraction from cold clouds where the liquid water fraction is less than 50% of the total condensate. This makes use of the observation that clouds only containing ice exhibit effective 12-to-11 μm absorption optical thickness ratios (βeff that are quasi-constant with retrieved cloud temperature T. This observation was made possible by using two CO2 channels to retrieve T and then using the 12 and 11 μm channels to retrieve emissivities and βeff. Thus for T < −40 °C, βeff is constant, but for T > −40 °C, βeff slowly increases due to the presence of liquid water, revealing mean liquid fractions of ~ 10% around −22 °C from tropical clouds identified as cirrus by the cloud mask. However, the uncertainties for these retrievals are large, and extensive in situ measurements are needed to refine and validate these retrievals. Such liquid levels are shown to reduce the cloud effective diameter De such that cloud optical thickness will increase by more than 50% for a given water path, relative to De corresponding to pure ice clouds. Such retrieval information is needed for validation of the cloud microphysics in climate models. Since low levels of liquid water can dominate cloud optical properties, tropical clouds between −25 and −20 °C may be susceptible to the first aerosol indirect effect.

  13. Intercomparison of Satellite Dust Retrieval Products over the West African Sahara During the Fennec Campaign in June 2011

    Science.gov (United States)

    Banks, J.R.; Brindley, H. E.; Flamant, C.; Garay, M. J.; Hsu, N. C.; Kalashnikova, O. V.; Klueser, L.; Sayer, A. M.

    2013-01-01

    Dust retrievals over the Sahara Desert during June 2011 from the IASI, MISR, MODIS, and SEVIRI satellite instruments are compared against each other in order to understand the strengths and weaknesses of each retrieval approach. Particular attention is paid to the effects of meteorological conditions, land surface properties, and the magnitude of the dust loading. The period of study corresponds to the time of the first Fennec intensive measurement campaign, which provides new ground-based and aircraft measurements of the dust characteristics and loading. Validation using ground-based AERONET sunphotometer data indicate that of the satellite instruments, SEVIRI is most able to retrieve dust during optically thick dust events, whereas IASI and MODIS perform better at low dust loadings. This may significantly affect observations of dust emission and the mean dust climatology. MISR and MODIS are least sensitive to variations in meteorological conditions, while SEVIRI tends to overestimate the aerosol optical depth (AOD) under moist conditions (with a bias against AERONET of 0.31), especially at low dust loadings where the AOD<1. Further comparisons are made with airborne LIDAR measurements taken during the Fennec campaign, which provide further evidence for the inferences made from the AERONET comparisons. The effect of surface properties on the retrievals is also investigated. Over elevated surfaces IASI retrieves AODs which are most consistent with AERONET observations, while the AODs retrieved by MODIS tend to be biased low. In contrast, over the least emissive surfaces IASI significantly underestimates the AOD (with a bias of -0.41), while MISR and SEVIRI show closest agreement.

  14. 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

  15. Optimal estimation retrieval of aerosol microphysical properties from SAGE II satellite observations in the volcanically unperturbed lower stratosphere

    Directory of Open Access Journals (Sweden)

    T. Deshler

    2010-05-01

    Full Text Available Stratospheric aerosol particles under non-volcanic conditions are typically smaller than 0.1 μm. Due to fundamental limitations of the scattering theory in the Rayleigh limit, these tiny particles are hard to measure by satellite instruments. As a consequence, current estimates of global aerosol properties retrieved from spectral aerosol extinction measurements tend to be strongly biased. Aerosol surface area densities, for instance, are observed to be about 40% smaller than those derived from correlative in situ measurements (Deshler et al., 2003. An accurate knowledge of the global distribution of aerosol properties is, however, essential to better understand and quantify the role they play in atmospheric chemistry, dynamics, radiation and climate. To address this need a new retrieval algorithm was developed, which employs a nonlinear Optimal Estimation (OE method to iteratively solve for the monomodal size distribution parameters which are statistically most consistent with both the satellite-measured multi-wavelength aerosol extinction data and a priori information. By thus combining spectral extinction measurements (at visible to near infrared wavelengths with prior knowledge of aerosol properties at background level, even the smallest particles are taken into account which are practically invisible to optical remote sensing instruments. The performance of the OE retrieval algorithm was assessed based on synthetic spectral extinction data generated from both monomodal and small-mode-dominant bimodal sulphuric acid aerosol size distributions. For monomodal background aerosol, the new algorithm was shown to fairly accurately retrieve the particle sizes and associated integrated properties (surface area and volume densities, even in the presence of large extinction uncertainty. The associated retrieved uncertainties are a good estimate of the true errors. In the case of bimodal background aerosol, where the retrieved (monomodal size

  16. [Retrieval of Copper Pollution Information from Hyperspectral Satellite Data in a Vegetation Cover Mining Area].

    Science.gov (United States)

    Qu, Yong-hua; Jiao, Si-hong; Liu, Su-hong; Zhu, Ye-qing

    2015-11-01

    Heavy metal mining activities have caused the complex influence on the ecological environment of the mining regions. For example, a large amount of acidic waste water containing heavy metal ions have be produced in the process of copper mining which can bring serious pollution to the ecological environment of the region. In the previous research work, bare soil is mainly taken as the research target when monitoring environmental pollution, and thus the effects of land surface vegetation have been ignored. It is well known that vegetation condition is one of the most important indictors to reflect the ecological change in a certain region and there is a significant linkage between the vegetation spectral characteristics and the heavy metal when the vegetation is effected by the heavy metal pollution. It means the vegetation is sensitive to heavy metal pollution by their physiological behaviors in response to the physiological ecology change of their growing environment. The conventional methods, which often rely on large amounts of field survey data and laboratorial chemical analysis, are time consuming and costing a lot of material resources. The spectrum analysis method using remote sensing technology can acquire the information of the heavy mental content in the vegetation without touching it. However, the retrieval of that information from the hyperspectral data is not an easy job due to the difficulty in figuring out the specific band, which is sensitive to the specific heavy metal, from a huge number of hyperspectral bands. Thus the selection of the sensitive band is the key of the spectrum analysis method. This paper proposed a statistical analysis method to find the feature band sensitive to heavy metal ion from the hyperspectral data and to then retrieve the metal content using the field survey data and the hyperspectral images from China Environment Satellite HJ-1. This method selected copper ion content in the leaves as the indicator of copper pollution

  17. Data assimilation of satellite retrieved ozone, carbon monoxide and nitrogen dioxide with ECMWF's Composition-IFS

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    A. Inness

    2015-02-01

    Full Text Available Daily global analyses and 5 day forecasts are generated in the context of the European Monitoring Atmospheric Composition and Climate (MACC project using an extended version of the Integrated Forecasting System (IFS of the European Centre for Medium-Range Weather Forecasts (ECMWF. IFS now includes modules for chemistry, deposition and emission of reactive gases, aerosols, and greenhouse gases, and the 4-dimensional variational data assimilation scheme makes use of multiple satellite observations of atmospheric composition in addition to meteorological observations. This paper describes the data assimilation setup of the new Composition-IFS (C-IFS with respect to reactive gases and validates analysis fields of ozone (O3, carbon monoxide (CO, and nitrogen dioxide (NO2 for the year 2008 against independent observations and a control run without data assimilation. The largest improvement in CO by assimilation of MOPITT CO columns is seen in the lower troposphere of the Northern Hemisphere (NH Extratropics during winter, and during the South African biomass burning season. The assimilation of several O3 total column and stratospheric profile retrievals greatly improves the total column, stratospheric and upper tropospheric O3 analysis fields relative to the control run. The impact on lower tropospheric ozone, which comes from the residual of the total column and stratospheric profile O3 data, is smaller, but nevertheless there is some improvement particularly in the NH during winter and spring. The impact of the assimilation of OMI tropospheric NO2 columns is small because of the short lifetime of NO2, suggesting that NO2 observations would be better used to adjust emissions instead of initial conditions. The results further indicate that the quality of the tropospheric analyses and of the stratospheric ozone analysis obtained with the C-IFS system has improved compared to the previous "coupled" model system of MACC.

  18. Advantages of using satellite soil moisture estimates over precipitation products to assess regional vegetation water availability and activity

    Science.gov (United States)

    Chen, Tiexi

    2017-04-01

    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 receiving area in northeastern Australia during December 2008 to May 2009. In January 2009, monthly precipitation showed strong positive anomalies, which led to strong positive soil moisture anomalies. The precipitation anomalies disappeared within a month. In contrast, the soil moisture anomalies persisted for months. Positive anomalies of Normalized Difference Vegetation Index (NDVI) appeared in February, in response to water supply, and then persisted for several months. In addition to these temporal characteristics, the spatial patterns of NDVI anomalies were more similar to soil moisture patterns than to those of precipitation and land surface model output. The long memory of soil moisture mainly relates to the presence of clay-rich soils. Modeled soil moisture from four of five global land surface models failed to capture the memory length of soil moisture and all five models failed to present the influence of lateral inflow. This case study indicates that satellite-based soil moisture is a better predictor of vegetation water availability than precipitation in environments having a memory of several months and thus is able to persistently affect vegetation dynamics. These results illustrate the usefulness of satellite remotely sensed soil moisture in ecohydrology studies. This case study has the potential to be used as a benchmark for global land surface model evaluations. The advantages of using satellite remotely sensed soil moisture over gridded precipitation products are mainly expected in lateral-inflow and/or clay-rich regions worldwide.

  19. Retrieval and intercomparison of volcanic SO2 injection height and eruption time from satellite maps and ground-based observations

    Science.gov (United States)

    Pardini, Federica; Burton, Mike; de'Michieli Vitturi, Mattia; Corradini, Stefano; Salerno, Giuseppe; Merucci, Luca; Di Grazia, Giuseppe

    2017-02-01

    Syneruptive gas flux time series can, in principle, be retrieved from satellite maps of SO2 collected during and immediately after volcanic eruptions, and used to gain insights into the volcanic processes which drive the volcanic activity. Determination of the age and height of volcanic plumes are key prerequisites for such calculations. However, these parameters are challenging to constrain using satellite-based techniques. Here, we use imagery from OMI and GOME-2 satellite sensors and a novel numerical procedure based on back-trajectory analysis to calculate plume height as a function of position at the satellite measurement time together with plume injection height and time at a volcanic vent location. We applied this new procedure to three Etna eruptions (12 August 2011, 18 March 2012 and 12 April 2013) and compared our results with independent satellite and ground-based estimations. We also compare our injection height time-series with measurements of volcanic tremor, which reflects the eruption intensity, showing a good match between these two datasets. Our results are a milestone in progressing towards reliable determination of gas flux data from satellite-derived SO2 maps during volcanic eruptions, which would be of great value for operational management of explosive eruptions.

  20. Evaluating Frontal Precipitation with a Spectral Microphysics Mesoscale Model and a Satellite Simulator as Compared to Radar and Radiometer Observations

    Science.gov (United States)

    Han, M.; Braun, S. A.; Matsui, T.; Iguchi, T.; Williams, C. R.

    2013-12-01

    The Advanced Microwave Scanning Radiometer for EOS (AMSR-E) onboard NASA Aqua satellite and a ground-based precipitation profiling radar sampled a frontal precipitation event in the US west coast on 30 to 31 December 2005. Simulations with bulk microphysics schemes in the Weather Research and Forecast (WRF) model have been evaluated with those remote sensing data. In the current study, we continue similar work to evaluate a spectral bin microphysics (SBM) scheme, HUCM, in the WRF model. The Goddard-Satellite Data Simulation Unit (G-SDSU) is used to simulate quantities observed by the radar and radiometer. With advanced representation of cloud and precipitation microphysics processes, the HUCM scheme predicts distributions of 7 hydrometeor species as storms evolve. In this study, the simulation with HUCM well captured the structure of the precipitation and its microphysics characteristics. In addition, it improved total precipitation ice mass simulation and corrected, to a certain extent, the large low bias of ice scattering signature in the bulk scheme simulations. However, the radar reflectivity simulations with the HUCM scheme were not improved as compared to the bulk schemes. We conducted investigations to understand how microphysical processes and properties, such as snow break up parameter and particle fall velocities would influence precipitation size distribution and spectrum of water paths, and further modify radar and/or radiometer simulations. Influence by ice nuclei is going to be examined as well.

  1. Using R for analysing spatio-temporal datasets: a satellite-based precipitation case study

    Science.gov (United States)

    Zambrano-Bigiarini, Mauricio

    2017-04-01

    Increasing computer power and the availability of remote-sensing data measuring different environmental variables has led to unprecedented opportunities for Earth sciences in recent decades. However, dealing with hundred or thousands of files, usually in different vectorial and raster formats and measured with different temporal frequencies, impose high computation challenges to take full advantage of all the available data. R is a language and environment for statistical computing and graphics which includes several functions for data manipulation, calculation and graphical display, which are particularly well suited for Earth sciences. In this work I describe how R was used to exhaustively evaluate seven state-of-the-art satellite-based rainfall estimates (SRE) products (TMPA 3B42v7, CHIRPSv2, CMORPH, PERSIANN-CDR, PERSIAN-CCS-adj, MSWEPv1.1 and PGFv3) over the complex topography and diverse climatic gradients of Chile. First, built-in functions were used to automatically download the satellite-images in different raster formats and spatial resolutions and to clip them into the Chilean spatial extent if necessary. Second, the raster package was used to read, plot, and conduct an exploratory data analysis in selected files of each SRE product, in order to detect unexpected problems (rotated spatial domains, order or variables in NetCDF files, etc). Third, raster was used along with the hydroTSM package to aggregate SRE files into different temporal scales (daily, monthly, seasonal, annual). Finally, the hydroTSM and hydroGOF packages were used to carry out a point-to-pixel comparison between precipitation time series measured at 366 stations and the corresponding grid cell of each SRE. The modified Kling-Gupta index of model performance was used to identify possible sources of systematic errors in each SRE, while five categorical indices (PC, POD, FAR, ETS, fBIAS) were used to assess the ability of each SRE to correctly identify different precipitation intensities

  2. Performance of TMPA satellite precipitation product over the Northern Great Plains

    Science.gov (United States)

    Kharel, G.; Kirilenko, A.; Zhang, X.

    2011-12-01

    Satellite derived precipitation can be used as supplement and/or replacement to ground data in various applications including modeling and weather forecasting based on its accuracy, reliability and validity. We analyzed Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA) 3B42 v.6 Level 3 product (0.25° × 0.25°, 3-hour resolution) against the United States Historical Climatology Network (USHCN) ground data from 98 stations in the Northern Great Plains (NGP) over the period of seven years (2003 to 2009). NGP, comprised of Wyoming, Montana, North Dakota, Minnesota, South Dakota and Nebraska states of the US, is located between the latitudes 41° - 49° N and longitudes 94° - 113.5° E within the TMPA product latitude band (50° NS).The goal of this research was to investigate the performance of TMPA over the NGP region. Results showed that the TMPA daily data has poor rainfall detection ability (POD ~ 0.3), weak correlation with the meteorological data (ρ=0.46) and high root mean square deviation (RMSD = 4.9 mm/day). We also found noticeable seasonal differences in the daily TMPA product performance. It underperformed during cold season (November to March) with weaker correlation (0.25) and worse POD (~ 0.15), as compared to relatively modest correlation (0.47) and POD (~0.30) during warm season (April to October). Our analysis at monthly scale revealed significantly better performance of TMPA with higher correlation (0.82) and lower RMSD (0.72 mm/day). Based on our findings, the TMPA daily data might be a poor replacement to ground data, however, at a monthly scale, TMPA can be used to estimate spatial rainfall distribution in NGP and/or as an input to a stochastic daily weather generator.

  3. Using Artificial Intelligence to Retrieve the Optimal Parameters and Structures of Adaptive Network-Based Fuzzy Inference System for Typhoon Precipitation Forecast Modeling

    Directory of Open Access Journals (Sweden)

    Chien-Lin Huang

    2015-01-01

    Full Text Available This study aims to construct a typhoon precipitation forecast model providing forecasts one to six hours in advance using optimal model parameters and structures retrieved from a combination of the adaptive network-based fuzzy inference system (ANFIS and artificial intelligence. To enhance the accuracy of the precipitation forecast, two structures were then used to establish the precipitation forecast model for a specific lead-time: a single-model structure and a dual-model hybrid structure where the forecast models of higher and lower precipitation were integrated. In order to rapidly, automatically, and accurately retrieve the optimal parameters and structures of the ANFIS-based precipitation forecast model, a tabu search was applied to identify the adjacent radius in subtractive clustering when constructing the ANFIS structure. The coupled structure was also employed to establish a precipitation forecast model across short and long lead-times in order to improve the accuracy of long-term precipitation forecasts. The study area is the Shimen Reservoir, and the analyzed period is from 2001 to 2009. Results showed that the optimal initial ANFIS parameters selected by the tabu search, combined with the dual-model hybrid method and the coupled structure, provided the favors in computation efficiency and high-reliability predictions in typhoon precipitation forecasts regarding short to long lead-time forecasting horizons.

  4. The 2010 Eyja eruption evolution by using IR satellite sensors measurements: retrieval comparison and insights into explosive volcanic processes

    Science.gov (United States)

    Piscini, A.; Corradini, S.; Merucci, L.; Scollo, S.

    2010-12-01

    The 2010 April-May Eyja eruption caused an unprecedented disruption to economic, political and cultural activities in Europe and across the world. Because of the harming effects of fine ash particles on aircrafts, many European airports were in fact closed causing millions of passengers to be stranded, and with a worldwide airline industry loss estimated of about 2.5 billion Euros. Both security and economical issues require robust and affordable volcanic cloud retrievals that may be really improved through the intercomparison among different remote sensing instruments. In this work the Thermal InfraRed (TIR) measurements of different polar and geostationary satellites instruments as the Moderate Resolution Imaging Spectroradiometer (MODIS), the Advanced Very High Resolution Radiometer (AVHRR) and the Spin Enhanced Visible and Infrared Imager (SEVIRI), have been used to retrieve the volcanic ash and SO2 in the entire eruption period over Iceland. The ash retrievals (mass, AOD and effective radius) have been carried out by means of the split window BTD technique using the channels centered around 11 and 12 micron. The least square fit procedure is used for the SO2 retrieval by using the 7.3 and 8.7 micron channels. The simulated TOA radiance Look-Up Table (LUT) needed for both the ash and SO2 column abundance retrievals have been computed using the MODTRAN 4 Radiative Transfer Model. Further, the volcanic plume column altitude and ash density have been computed and compared, when available, with ground observations. The results coming from the retrieval of different IR sensors show a good agreement over the entire eruption period. The column height, the volcanic ash and the SO2 emission trend confirm the indentified different phases occurred during the Eyja eruption. We remark that the retrieved volcanic plume evolution can give important insights into eruptive dynamics during long-lived explosive activity.

  5. Tropospheric BrO column densities in the Arctic derived from satellite: retrieval and comparison to ground-based measurements

    Directory of Open Access Journals (Sweden)

    H. Sihler

    2012-11-01

    Full Text Available During polar spring, halogen radicals like bromine monoxide (BrO play an important role in the chemistry of tropospheric ozone destruction. Satellite measurements of the BrO distribution have become a particularly useful tool to investigate this probably natural phenomenon, but the separation of stratospheric and tropospheric partial columns of BrO is challenging. In this study, an algorithm was developed to retrieve tropospheric vertical column densities of BrO from data of high-resolution spectroscopic satellite instruments such as the second Global Ozone Monitoring Experiment (GOME-2. Unlike recently published approaches, the presented algorithm is capable of separating the fraction of BrO in the activated troposphere from the total BrO column solely based on remotely measured properties. The presented algorithm furthermore allows to estimate a realistic measurement error of the tropospheric BrO column. The sensitivity of each satellite pixel to BrO in the boundary layer is quantified using the measured UV radiance and the column density of the oxygen collision complex O4. A comparison of the sensitivities with CALIPSO LIDAR observations demonstrates that clouds shielding near-surface trace-gas columns can be reliably detected even over ice and snow. Retrieved tropospheric BrO columns are then compared to ground-based BrO measurements from two Arctic field campaigns in the Amundsen Gulf and at Barrow in 2008 and 2009, respectively. Our algorithm was found to be capable of retrieving enhanced near-surface BrO during both campaigns in good agreement with ground-based data. Some differences between ground-based and satellite measurements observed at Barrow can be explained by both elevated and shallow surface layers of BrO. The observations strongly suggest that surface release processes are the dominating source of BrO and that boundary layer meteorology influences the vertical distribution.

  6. Tropospheric BrO column densities in the Arctic from satellite: retrieval and comparison to ground-based measurements

    Directory of Open Access Journals (Sweden)

    H. Sihler

    2012-05-01

    Full Text Available During polar spring, halogen radicals like bromine monoxide (BrO play an important role in the chemistry of tropospheric ozone destruction. Satellite measurements of the BrO-distribution have become a particularly useful tool to investigate this probably natural phenomenon, but the separation of stratospheric and tropospheric partial columns of BrO is challenging. In this study, an algorithm was developed to retrieve tropospheric vertical column densities of BrO from data of high-resolution spectroscopic satellite instruments such as the second Global Ozone Monitoring Experiment (GOME-2. Unlike recently published approaches, the presented algorithm is capable of separating the fraction of BrO in the activated troposphere from the total BrO column solely based on remotely measured properties. The sensitivity of each satellite pixel to BrO in the boundary-layer is quantified using the measured UV-radiance and the column density of the oxygen collision complex O4. A comparison of the sensitivities with CALIPSO LIDAR observations demonstrates that clouds shielding near-surface trace-gas columns can be reliably detected even over ice and snow. Retrieved tropospheric BrO columns are then compared to ground-based BrO measurements from two Arctic field campaigns in the Amundsen Gulf and at Barrow in 2008 and 2009, respectively. Our algorithm was found to be capable of retrieving enhanced near-surface BrO during both campaigns in good agreement to ground-based data. Some differences between ground-based and satellite measurements observed at Barrow can be explained by both, elevated and shallow surface layers of BrO. The observations strongly suggest that surface release processes are the dominating source of BrO and that boundary-layer meteorology influences the vertical distribution.

  7. 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

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

    Science.gov (United States)

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

    2015-12-01

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

  9. Weather from 250 Miles Up: Visualizing Precipitation Satellite Data (and Other Weather Applications) Using CesiumJS

    Science.gov (United States)

    Lammers, Matt

    2017-01-01

    Geospatial weather visualization remains predominately a two-dimensional endeavor. Even popular advanced tools like the Nullschool Earth display 2-dimensional fields on a 3-dimensional globe. Yet much of the observational data and model output contains detailed three-dimensional fields. In 2014, NASA and JAXA (Japanese Space Agency) launched the Global Precipitation Measurement (GPM) satellite. Its two instruments, the Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI) observe much of the Earth's atmosphere between 65 degrees North Latitude and 65 degrees South Latitude. As part of the analysis and visualization tools developed by the Precipitation Processing System (PPS) Group at NASA Goddard, a series of CesiumJS [Using Cesium Markup Language (CZML), JavaScript (JS) and JavaScript Object Notation (JSON)] -based globe viewers have been developed to improve data acquisition decision making and to enhance scientific investigation of the satellite data. Other demos have also been built to illustrate the capabilities of CesiumJS in presenting atmospheric data, including model forecasts of hurricanes, observed surface radar data, and gridded analyses of global precipitation. This talk will present these websites and the various workflows used to convert binary satellite and model data into a form easily integrated with CesiumJS.

  10. 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.

  11. 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.

  12. Retrieval and satellite intercomparison of O3 measurements from ground-based FTIR Spectrometer at Equatorial Station: Addis Ababa, Ethiopia

    Directory of Open Access Journals (Sweden)

    T. von Clarmann

    2013-02-01

    Full Text Available Since May 2009, high-resolution Fourier Transform Infrared (FTIR solar absorption spectra have been recorded at Addis Ababa (9.01° N latitude, 38.76° E longitude, 2443 m altitude above sea level, Ethiopia. The vertical profiles and total column amounts of ozone (O3 are deduced from the spectra by using the retrieval code PROFFIT (V9.5 and regularly determined instrumental line shape (ILS. A detailed error analysis of the O3 retrieval is performed. Averaging kernels of the target gas shows that the major contribution to the retrieved information comes from the measurement. The degrees of freedom for signals is found to be 2.1 on average for the retrieval of O3 from the observed FTIR spectra. The ozone Volume Mixing Ratio (VMR profiles and column amounts retrieved from FTIR spectra are compared with the coincident satellite observations of Microwave Limb Sounding (MLS, Michelson Interferometer for Passive Atmospheric Sounding (MIPAS, Tropospheric Emission Spectrometer (TES, Ozone Monitoring Instrument (OMI, Atmospheric Infrared Sounding (AIRS and Global Ozone Monitoring Experiment (GOME-2 instruments. The mean relative differences in ozone profiles of FTIR from MLS and MIPAS are generally lower than 15% within the altitude range of 27 to 36 km, whereas difference from TES is lower than 1%. Comparisons of measurements of column amounts from the satellite and the ground-based FTIR show very good agreement as exhibited by relative differences within +0.2% to +2.8% for FTIR versus MLS and GOME-2; and −0.9 to −9.0% for FTIR versus OMI, TES and AIRS. The corresponding standard deviations are within 2.0 to 2.8% for FTIR versus MLS and GOME-2 comparisons whereas that of FTIR versus OMI, TES and AIRS are within 3.5 to 7.3%. Thus, the retrieved O3 VMR and column amounts from a tropical site, Addis Ababa, is found to exhibit very good agreement with all coincident satellite observations over an approximate 3-yr period.

  13. Retrieval and satellite intercomparison of O3 measurements from ground-based FTIR Spectrometer at Equatorial Station: Addis Ababa, Ethiopia

    Science.gov (United States)

    Takele Kenea, S.; Mengistu Tsidu, G.; Blumenstock, T.; Hase, F.; von Clarmann, T.; Stiller, G. P.

    2013-02-01

    Since May 2009, high-resolution Fourier Transform Infrared (FTIR) solar absorption spectra have been recorded at Addis Ababa (9.01° N latitude, 38.76° E longitude, 2443 m altitude above sea level), Ethiopia. The vertical profiles and total column amounts of ozone (O3) are deduced from the spectra by using the retrieval code PROFFIT (V9.5) and regularly determined instrumental line shape (ILS). A detailed error analysis of the O3 retrieval is performed. Averaging kernels of the target gas shows that the major contribution to the retrieved information comes from the measurement. The degrees of freedom for signals is found to be 2.1 on average for the retrieval of O3 from the observed FTIR spectra. The ozone Volume Mixing Ratio (VMR) profiles and column amounts retrieved from FTIR spectra are compared with the coincident satellite observations of Microwave Limb Sounding (MLS), Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), Tropospheric Emission Spectrometer (TES), Ozone Monitoring Instrument (OMI), Atmospheric Infrared Sounding (AIRS) and Global Ozone Monitoring Experiment (GOME-2) instruments. The mean relative differences in ozone profiles of FTIR from MLS and MIPAS are generally lower than 15% within the altitude range of 27 to 36 km, whereas difference from TES is lower than 1%. Comparisons of measurements of column amounts from the satellite and the ground-based FTIR show very good agreement as exhibited by relative differences within +0.2% to +2.8% for FTIR versus MLS and GOME-2; and -0.9 to -9.0% for FTIR versus OMI, TES and AIRS. The corresponding standard deviations are within 2.0 to 2.8% for FTIR versus MLS and GOME-2 comparisons whereas that of FTIR versus OMI, TES and AIRS are within 3.5 to 7.3%. Thus, the retrieved O3 VMR and column amounts from a tropical site, Addis Ababa, is found to exhibit very good agreement with all coincident satellite observations over an approximate 3-yr period.

  14. 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.

  15. Analysis of TRMM 3-Hourly Multi-Satellite Precipitation Estimates Computed in Both Real and Post-Real Time

    Science.gov (United States)

    Huffman, George J.; Adler, Robert F.; Stocker, Erich; Bolvin, David T.; Nelkin, Eric J.

    2002-01-01

    Satellite data form the core of the information available for estimating precipitation on a global basis. While it is possible to create such estimates solely from one sensor, researchers have increasingly moved to using combinations of sensors in an attempt to improve accuracy, coverage, and resolution. This poster updates a long-term project in which the authors are working to provide routine combined-sensor estimates of precipitation over the entire globe at relatively fine time and space intervals. The goal is to produce these globally complete precipitation estimates on a 25-km grid every 3 hours. Since late January 2002 we have been estimating precipitation for the latitude band 50 degrees N-S within about 6 hours of observation time. This work is 1 of only 2 or 3 such efforts in the world. Now we are preparing to provide similar estimates for the last 5 years. All of this work is being carried out as part of the Tropical Rainfall Measuring Mission (TRMM). Initially, TRMM was focused on providing excellent long-term averages of precipitation in tropical regions, but since its launch in November 1997 continued research has allowed the same satellite and data system to be used for addressing weather-scale problems as well.

  16. The high-resolution version of TM5-MP for optimized satellite retrievals: description and validation

    Science.gov (United States)

    Williams, Jason E.; Folkert Boersma, K.; Le Sager, Phillipe; Verstraeten, Willem W.

    2017-02-01

    We provide a comprehensive description of the high-resolution version of the TM5-MP global chemistry transport model, which is to be employed for deriving highly resolved vertical profiles of nitrogen dioxide (NO2), formaldehyde (CH2O), and sulfur dioxide (SO2) for use in satellite retrievals from platforms such as the Ozone Monitoring Instrument (OMI) and the Sentinel-5 Precursor, and the TROPOspheric Monitoring Instrument (tropOMI). Comparing simulations conducted at horizontal resolutions of 3° × 2° and 1° × 1° reveals differences of ±20 % exist in the global seasonal distribution of 222Rn, being larger near specific coastal locations and tropical oceans. For tropospheric ozone (O3), analysis of the chemical budget terms shows that the impact on globally integrated photolysis rates is rather low, in spite of the higher spatial variability of meteorological data fields from ERA-Interim at 1° × 1°. Surface concentrations of O3 in high-NOx regions decrease between 5 and 10 % at 1° × 1° due to a reduction in NOx recycling terms and an increase in the associated titration term of O3 by NO. At 1° × 1°, the net global stratosphere-troposphere exchange of O3 decreases by ˜ 7 %, with an associated shift in the hemispheric gradient. By comparing NO, NO2, HNO3 and peroxy-acetyl-nitrate (PAN) profiles against measurement composites, we show that TM5-MP captures the vertical distribution of NOx and long-lived NOx reservoirs at background locations, again with modest changes at 1° × 1°. Comparing monthly mean distributions in lightning NOx and applying ERA-Interim convective mass fluxes, we show that the vertical re-distribution of lightning NOx changes with enhanced release of NOx in the upper troposphere. We show that surface mixing ratios in both NO and NO2 are generally underestimated in both low- and high-NOx scenarios. For Europe, a negative bias exists for [NO] at the surface across the whole domain, with lower biases at 1° × 1° at only ˜ 20

  17. Exploiting the power law distribution properties of satellite fire radiative power retrievals: A method to estimate fire radiative energy and biomass burned from sparse satellite observations

    Science.gov (United States)

    Kumar, S. S.; Roy, D. P.; Boschetti, L.; Kremens, R.

    2011-10-01

    Instantaneous estimates of the power released by fire (fire radiative power, FRP) are available with satellite active fire detection products. The temporal integral of FRP provides an estimate of the fire radiative energy (FRE) that is related linearly to the amount of biomass burned needed by the atmospheric emissions modeling community. The FRE, however, is sensitive to satellite temporal and spatial FRP undersampling due to infrequent satellite overpasses, cloud and smoke obscuration, and failure to detect cool and/or small fires. Satellite FRPs derived over individual burned areas and fires have been observed to exhibit power law distributions. This property is exploited to develop a new way to derive FRE, as the product of the fire duration and the expected FRP value derived from the FRP power law probability distribution function. The method is demonstrated and validated by the use of FRP data measured with a dual-band radiometer over prescribed fires in the United States and by the use of FRP data retrieved from moderate resolution imaging spectroradiometer (MODIS) active-fire detections over Brazilian deforestation and Australian savanna fires. The biomass burned derived using the conventional FRP temporal integration and power law FRE estimation methods is compared with biomass burned measurements (prescribed fires) and available fuel load information reported in the literature (Australian and Brazilian fires). The results indicate that the FRE power law derivation method may provide more reliable burned biomass estimates under sparse satellite FRP sampling conditions and correct for satellite active-fire detection omission errors if the FRP power law distribution parameters and the fire duration are known.

  18. [Errors Analysis and Correction in Atmospheric Methane Retrieval Based on Greenhouse Gases Observing Satellite Data].

    Science.gov (United States)

    Bu, Ting-ting; Wang, Xian-hua; Ye, Han-han; Jiang, Xin-hua

    2016-01-01

    High precision retrieval of atmospheric CH4 is influenced by a variety of factors. The uncertainties of ground properties and atmospheric conditions are important factors, such as surface reflectance, temperature profile, humidity profile and pressure profile. Surface reflectance is affected by many factors so that it is difficult to get the precise value. The uncertainty of surface reflectance will cause large error to retrieval result. The uncertainties of temperature profile, humidity profile and pressure profile are also important sources of retrieval error and they will cause unavoidable systematic error. This error is hard to eliminate only using CH4 band. In this paper, ratio spectrometry method and CO2 band correction method are proposed to reduce the error caused by these factors. Ratio spectrometry method can decrease the effect of surface reflectance in CH4 retrieval by converting absolute radiance spectrometry into ratio spectrometry. CO2 band correction method converts column amounts of CH4 into column averaged mixing ratio by using CO2 1.61 μm band and it can correct the systematic error caused by temperature profile, humidity profile and pressure profile. The combination of these two correction methods will decrease the effect caused by surface reflectance, temperature profile, humidity profile and pressure profile at the same time and reduce the retrieval error. GOSAT data were used to retrieve atmospheric CH4 to test and validate the two correction methods. The results showed that CH4 column averaged mixing ratio retrieved after correction was close to GOSAT Level2 product and the retrieval precision was up to -0.24%. The studies suggest that the error of CH4 retrieval caused by the uncertainties of ground properties and atmospheric conditions can be significantly reduced and the retrieval precision can be highly improved by using ratio spectrometry method and CO2 hand correction method.

  19. Ozone ProfilE Retrieval Algorithm for nadir-looking satellite instruments in the UV-VIS

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    J. C. A. van Peet

    2013-10-01

    Full Text Available For the retrieval of the vertical distribution of ozone in the atmosphere the Ozone ProfilE Retrieval Algorithm (OPERA has been further developed. The new version (1.26 of OPERA is capable of retrieving ozone profiles from UV-VIS observations of most nadir looking satellite instruments like GOME, SCIAMACHY, OMI and GOME-2. The set-up of OPERA is described and results are presented for GOME and GOME-2 observations. The retrieved ozone profiles are globally compared to ozone sondes for the year 1997 and 2008. Relative differences between GOME/GOME-2 and ozone sondes are within the limits as specified by the user requirements from the Climate Change Initiative (CCI program of ESA. To demonstrate the performance of the algorithm under extreme circumstances the 2009 Antarctic ozone hole season was investigated in more detail using GOME-2 ozone profiles and lidar data, which showed an unusual persistence of the vortex over the Río Gallegos observing station (51° S, 69.3° W. By applying OPERA to multiple instruments a timeseries of ozone profiles from 1996 to 2013 from a single robust algorithm can be created.

  20. New Methods for Retrieval of Chlorophyll Red Fluorescence from Hyperspectral Satellite Instruments: Simulations and Application to GOME-2 and SCIAMACHY

    Science.gov (United States)

    Joiner, Joanna; Yoshida, Yasuko; Guanter, Luis; Middleton, Elizabeth M.

    2016-01-01

    Global satellite measurements of solar-induced fluorescence (SIF) from chlorophyll over land and ocean have proven useful for a number of different applications related to physiology, phenology, and productivity of plants and phytoplankton. Terrestrial chlorophyll fluorescence is emitted throughout the red and far-red spectrum, producing two broad peaks near 683 and 736nm. From ocean surfaces, phytoplankton fluorescence emissions are entirely from the red region (683nm peak). Studies using satellite-derived SIF over land have focused almost exclusively on measurements in the far red (wavelengths greater than 712nm), since those are the most easily obtained with existing instrumentation. Here, we examine new ways to use existing hyperspectral satellite data sets to retrieve red SIF (wavelengths less than 712nm) over both land and ocean. Red SIF is thought to provide complementary information to that from the far red for terrestrial vegetation. The satellite instruments that we use were designed to make atmospheric trace-gas measurements and are therefore not optimal for observing SIF; they have coarse spatial resolution and only moderate spectral resolution (0.5nm). Nevertheless, these instruments, the Global Ozone Monitoring Instrument 2 (GOME-2) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), offer a unique opportunity to compare red and far-red terrestrial SIF at regional spatial scales. Terrestrial SIF has been estimated with ground-, aircraft-, or satellite-based instruments by measuring the filling-in of atmospheric andor solar absorption spectral features by SIF. Our approach makes use of the oxygen (O2) gamma band that is not affected by SIF. The SIF-free O2 gamma band helps to estimate absorption within the spectrally variable O2 B band, which is filled in by red SIF. SIF also fills in the spectrally stable solar Fraunhofer lines (SFLs) at wavelengths both inside and just outside the O2 B band, which further helps

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

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    T. Cohen Liechti

    2011-08-01

    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 subbasin 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 mesh.

    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 by nearly 1.5 times the rainfall. The statistics of TRMM and FEWS estimates show quite similar results.

    Due to the its lower inter-correlation and longer data set, the TRMM 3B42 product is chosen as input for the hydraulic-hydrologic model of the basin.

  2. Retrieval of SO2 from thermal infrared satellite measurements: correction procedures for the effects of volcanic ash

    Directory of Open Access Journals (Sweden)

    A. J. Prata

    2009-02-01

    Full Text Available The simultaneous presence of SO2 and ash in a volcanic plume can lead to a significant error in the SO2 columnar abundance retrieval when multispectral Thermal InfraRed (TIR data are used. The ash particles within the plume with effective radii (from 1 to 10 μm reduce the Top Of Atmosphere (TOA radiance in the entire TIR spectral range, including the channels used for SO2 retrieval. The net effect is a significant SO2 overestimation. In this work the interference of ash is discussed and two correction procedures for satellite SO2 volcanic plume retrieval in the TIR spectral range are developed to achieve an higher computation speed and a better accuracy. The ash correction can be applied when the sensor spectral range includes the 7.3 and/or 8.7 μm SO2 absorption bands, and the split window bands centered around 11 and 12 μm required for ash retrieval. This allows the possibility of a simultaneous estimation of both volcanic SO2 and ash in the same data set. The proposed ash correction procedures have been applied to the Moderate Resolution Imaging Spectroradiometer (MODIS and the Spin Enhanced Visible and Infrared Imager (SEVIRI measurements. Data collected during the 24 November 2006 Mt. Etna eruption have been used to illustrate the technique. The SO2 and ash estimations are carried out by using a least squares fit method and the Brightness Temperature Difference (BTD procedures, respectively. The simulated TOA radiance Look-Up Table (LUT needed for the SO2 columnar abundance and the ash retrievals have been computed using the MODTRAN 4 Radiative Transfer Model. The results show the importance of the ash correction on SO2 retrieval at 8.7 μm – the SO2 columnar abundance corrected by the ash influence is less than one half of the values retrieved without the correction. The ash correction on SO2 retrieval at 7.3 μm is much less important and only significant for low SO2 columnar abundances. Results also show that the simplified and

  3. Intercomparison of daytime stratospheric NO2 satellite retrievals and model simulations

    NARCIS (Netherlands)

    Belmonte Rivas, M.; Veefkind, J.P.; Boersma, F.; Levelt, P.; Eskes, H.; Gille, J.

    2014-01-01

    This paper evaluates the agreement between stratospheric NO2 retrievals from infrared limb sounders (Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and High Resolution Dynamics Limb Sounder (HIRDLS)) and solar UV/VIS backscatter sensors (Ozone Monitoring Instrument (OMI), Scanning

  4. Impact of Three-Dimensional Radiative Effects on Satellite Retrievals of Cloud Droplet Sizes

    Science.gov (United States)

    Marshak, Alexander; Platnick, Steven; Varnai, Tamas; Wen, Guoyong; Cahalan, Robert F.

    2006-01-01

    There are several dozen papers that study the effects of cloud horizontal inhomogeneity on the retrievals of cloud optical thickness, but only a few of them deal with cloud droplet sizes. This paper is one of the first comprehensive attempts to fill this gap: It takes a close theoretical look at the radiative effects of cloud 3-D structure in retrievals of droplet effective radii. Under some general assumptions, it was found that ignoring subpixel (unresolved) variability produces a negative bias in the retrieved effective radius, while ignoring cloud inhomogeneity at scales larger than a pixel scale (resolved variability), on the contrary, leads to overestimation of the domain average droplet size. The theoretical results are illustrated with examples from Large Eddy Simulations (LES) of cumulus (Cu) and stratocumulus (Sc) cloud fields. The analysis of cloud drop size distributions retrieved from both LES fields confirms that ignoring shadowing in 1-D retrievals results in substantial overestimation of effective radii which is more pronounced for broken Cu than for Sc clouds. Collocated measurements of broken Cu clouds by Moderate Resolution Imaging Spectrometer (MODIS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) are used to check simulations and theory with observations. The analysis of ASTER and MODIS data and associated derived products recommends against blindly using retrieved effective radii for broken cloud fields, especially if one wants to relate aerosol amounts to cloud droplet sizes.

  5. Retrieval of ozone column content from airborne Sun photometer measurements during SOLVE II: comparison with coincident satellite and aircraft measurements

    Directory of Open Access Journals (Sweden)

    J. M. Livingston

    2005-01-01

    Full Text Available During the 2003 SAGE (Stratospheric Aerosol and Gas Experiment III Ozone Loss and Validation Experiment (SOLVE II, the fourteen-channel NASA Ames Airborne Tracking Sunphotometer (AATS-14 was mounted on the NASA DC-8 aircraft and measured spectra of total and aerosol optical depth (TOD and AOD during the sunlit portions of eight science flights. Values of ozone column content above the aircraft have been derived from the AATS-14 measurements by using a linear least squares method that exploits the differential ozone absorption in the seven AATS-14 channels located within the Chappuis band. We compare AATS-14 columnar ozone retrievals with temporally and spatially near-coincident measurements acquired by the SAGE III and the Polar Ozone and Aerosol Measurement (POAM III satellite sensors during four solar occultation events observed by each satellite. RMS differences are 19 DU (7% of the AATS value for AATS-SAGE and 10 DU (3% of the AATS value for AATS-POAM. In these checks of consistency between AATS-14 and SAGE III or POAM III ozone results, the AATS-14 analyses use airmass factors derived from the relative vertical profiles of ozone and aerosol extinction obtained by SAGE III or POAM III. We also compare AATS-14 ozone retrievals for measurements obtained during three DC-8 flights that included extended horizontal transects with total column ozone data acquired by the Total Ozone Mapping Spectrometer (TOMS and the Global Ozone Monitoring Experiment (GOME satellite sensors. To enable these comparisons, the amount of ozone in the column below the aircraft is estimated either by assuming a climatological model or by combining SAGE and/or POAM data with high resolution in-situ ozone measurements acquired by the NASA Langley Research Center chemiluminescent ozone sensor, FASTOZ, during the aircraft vertical profile at the start or end of each flight. Resultant total column ozone values agree with corresponding TOMS and GOME measurements to within 10

  6. Retrieval of ozone column content from airborne Sun photometer measurements during SOLVE II: comparison with coincident satellite and aircraft measurements

    Directory of Open Access Journals (Sweden)

    J. M. Livingston

    2005-01-01

    Full Text Available During the 2003 SAGE (Stratospheric Aerosol and Gas Experiment III Ozone Loss and Validation Experiment (SOLVE II, the fourteen-channel NASA Ames Airborne Tracking Sunphotometer (AATS-14 was mounted on the NASA DC-8 aircraft and measured spectra of total and aerosol optical depth (TOD and AOD during the sunlit portions of eight science flights. Values of ozone column content above the aircraft have been derived from the AATS-14 measurements by using a linear least squares method that exploits the differential ozone absorption in the seven AATS-14 channels located within the Chappuis band. We compare AATS-14 columnar ozone retrievals with temporally and spatially near-coincident measurements acquired by the SAGE III and the Polar Ozone and Aerosol Measurement (POAM III satellite sensors during four solar occultation events observed by each satellite. RMS differences are 19 DU (6% of the AATS value for AATS-SAGE and 10 DU (3% of the AATS value for AATS-POAM. In these checks of consistency between AATS-14 and SAGE III or POAM III ozone results, the AATS-14 analyses use airmass factors derived from the relative vertical profiles of ozone and aerosol extinction obtained by SAGE III or POAM III.

    We also compare AATS-14 ozone retrievals for measurements obtained during three DC-8 flights that included extended horizontal transects with total column ozone data acquired by the Total Ozone Mapping Spectrometer (TOMS and the Global Ozone Monitoring Experiment (GOME satellite sensors. To enable these comparisons, the amount of ozone in the column below the aircraft is estimated either by assuming a climatological model or by combining SAGE and/or POAM data with high resolution in-situ ozone measurements acquired by the NASA Langley Research Center chemiluminescent ozone sensor, FASTOZ, during the aircraft vertical profile at the start or end of each flight. Resultant total column ozone values agree with corresponding TOMS and GOME measurements to

  7. Precipitation effects on the selection of suitable non-variant targets intended for atmospheric correction of satellite remotely sensed imagery

    Science.gov (United States)

    Themistocleous, Kyriacos; Hadjimitsis, Diofantos G.; Retalis, Adrianos; Chrysoulakis, Nektarios; Michaelides, Silas

    2013-09-01

    One of the most well-established atmospheric correction methods of satellite imagery is the use of the empirical line method using non-variant targets. Non-variant targets serve as pseudo-invariant targets since their reflectance values are stable across time. A recent adaptation of the empirical line method incorporates the use of ground reflectance measurements of selected non-variant targets. Most of the users are not aware of the existing conditions of the pseudo-invariant targets; i.e., whether they are dry or wet. Any omission of such effects may cause erroneous results; therefore, remote sensing users must be aware of such effects. This study assessed the effects of precipitation on five types of commonly located surfaces, including asphalt, concrete and sand, intended as pseudo-invariant targets for atmospheric correction. Spectroradiometric measurements were taken in wet and dry conditions to obtain the spectral signatures of the targets, from January 2010 to May 2011 (46 campaigns). An atmospheric correction of eleven Landsat TM/ETM + satellite images using the empirical line method was conducted. To identify the effects of precipitation, a comparison was conducted of the atmospheric path radiance component for wet and dry conditions. It was found that precipitation conditions such as rainfall affected the reflectance values of the surfaces, especially sand. Therefore, precipitation conditions need to be considered when using non-variant targets in atmospheric correction methods.

  8. 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

  9. The source of discrepancies in aerosol-cloud-precipitation interactions between GCM and A-Train retrievals

    Science.gov (United States)

    Michibata, Takuro; Suzuki, Kentaroh; Sato, Yousuke; Takemura, Toshihiko

    2016-12-01

    Aerosol-cloud interactions are one of the most uncertain processes in climate models due to their nonlinear complexity. A key complexity arises from the possibility that clouds can respond to perturbed aerosols in two opposite ways, as characterized by the traditional "cloud lifetime" hypothesis and more recent "buffered system" hypothesis. Their importance in climate simulations remains poorly understood. Here we investigate the response of the liquid water path (LWP) to aerosol perturbations for warm clouds from the perspective of general circulation model (GCM) and A-Train remote sensing, through process-oriented model evaluations. A systematic difference is found in the LWP response between the model results and observations. The model results indicate a near-global uniform increase of LWP with increasing aerosol loading, while the sign of the response of the LWP from the A-Train varies from region to region. The satellite-observed response of the LWP is closely related to meteorological and/or macrophysical factors, in addition to the microphysics. The model does not reproduce this variability of cloud susceptibility (i.e., sensitivity of LWP to perturbed aerosols) because the parameterization of the autoconversion process assumes only suppression of rain formation in response to increased cloud droplet number, and does not consider macrophysical aspects that serve as a mechanism for the negative responses of the LWP via enhancements of evaporation and precipitation. Model biases are also found in the precipitation microphysics, which suggests that the model generates rainwater readily even when little cloud water is present. This essentially causes projections of unrealistically frequent and light rain, with high cloud susceptibilities to aerosol perturbations.

  10. Evaluation of Aerosol Pollution Determination From MODIS Satellite Retrievals for Semi-Arid Reno, NV, USA with In-Situ Measurements

    Science.gov (United States)

    Loria-Salazar, S. Marcela

    The aim of the present work is to carry out a detailed analysis of ground and columnar aerosol properties obtained by in-situ Photoacoustic and Integrated Nephelometer (PIN), Cimel CE-318 sunphotometer and MODIS instrument onboard Aqua and Terra satellites, for semi-arid Reno, Nevada, USA in the local summer months of 2012. Satellite determination of local aerosol pollution is desirable because of the potential for broad spatial and temporal coverage. However, retrieval of quantitative measures of air pollution such as Aerosol Optical Depth (AOD) from satellite measurements is challenging because of the underlying surface albedo being heterogeneous in space and time. Therefore, comparisons of satellite retrievals with measurements from ground-based sun photometers are crucial for validation, testing, and further development of instruments and retrieval algorithms. Ground-based sunphotometry and in-situ ground observations show that seasonal weather changes and fire plumes have great influence on the atmosphere aerosol optics. The Apparent Optical Height (AOH) follows the shape of the development of the Convective Boundary Layer (CBL) when fire conditions were not present. However, significant fine particle optical depth was inferred beyond the CBL thereby complicating the use of remote sensing measurements for near-ground aerosol pollution measurements. A meteorological analysis was performed to help diagnose the nature of the aerosols above Reno. The calculation of a Zephyr index and back trajectory analysis demonstrated that a local circulation often induces aerosol transport from Northern CA over the Sierra Nevada Mountains that doubles the Aerosol Optical Depth (AOD) at 500 nm. Sunphotometer measurements were used as a `ground truth' for satellite retrievals to evaluate the current state of the science retrievals in this challenging location. Satellite retrieved for AOD showed the presence of wild fires in Northern CA during August. AOD retrieved using the

  11. Satellite Sampling and Retrieval Errors in Regional Monthly Rain Estimates from TMI AMSR-E, SSM/I, AMSU-B and the TRMM PR

    Science.gov (United States)

    Fisher, Brad; Wolff, David B.

    2010-01-01

    Passive and active microwave rain sensors onboard earth-orbiting satellites estimate monthly rainfall from the instantaneous rain statistics collected during satellite overpasses. It is well known that climate-scale rain estimates from meteorological satellites incur sampling errors resulting from the process of discrete temporal sampling and statistical averaging. Sampling and retrieval errors ultimately become entangled in the estimation of the mean monthly rain rate. The sampling component of the error budget effectively introduces statistical noise into climate-scale rain estimates that obscure the error component associated with the instantaneous rain retrieval. Estimating the accuracy of the retrievals on monthly scales therefore necessitates a decomposition of the total error budget into sampling and retrieval error quantities. This paper presents results from a statistical evaluation of the sampling and retrieval errors for five different space-borne rain sensors on board nine orbiting satellites. Using an error decomposition methodology developed by one of the authors, sampling and retrieval errors were estimated at 0.25 resolution within 150 km of ground-based weather radars located at Kwajalein, Marshall Islands and Melbourne, Florida. Error and bias statistics were calculated according to the land, ocean and coast classifications of the surface terrain mask developed for the Goddard Profiling (GPROF) rain algorithm. Variations in the comparative error statistics are attributed to various factors related to differences in the swath geometry of each rain sensor, the orbital and instrument characteristics of the satellite and the regional climatology. The most significant result from this study found that each of the satellites incurred negative longterm oceanic retrieval biases of 10 to 30%.

  12. Retrieval of SO2 from thermal infrared satellite measurements: correction procedures for the effects of volcanic ash

    Directory of Open Access Journals (Sweden)

    S. Corradini

    2009-05-01

    Full Text Available The simultaneous presence of SO2 and ash in a volcanic plume can lead to a significant error in the SO2 column abundance retrieval when multispectral Thermal InfraRed (TIR data are used. The ash particles within the plume with effective radii from 1 to 10 μm reduce the Top Of Atmosphere (TOA radiance in the entire TIR spectral range, including the channels used for SO2 retrieval. The net effect is a significant SO2 overestimation. In this work the interference of ash is discussed and two correction procedures for satellite SO2 volcanic plume retrieval in the TIR spectral range are developed to achieve an higher computational speed and a better accuracy. The ash correction can be applied when the sensor spectral range includes the 7.3 and/or 8.7 μm SO2 absorption bands, and the split window bands centered around 11 and 12 μm required for ash retrieval. This allows the possibility of simultaneous estimation of both volcanic SO2 and ash in the same data set. The proposed ash correction procedures have been applied to the Moderate Resolution Imaging Spectroradiometer (MODIS and the Spin Enhanced Visible and Infrared Imager (SEVIRI measurements. Data collected during the 24 November 2006 Mt. Etna eruption have been used to illustrate the technique. The SO2 and ash estimation is carried out by using a best weighted least squares fit method and the Brightness Temperature Difference (BTD procedures, respectively. The simulated TOA radiance Look-Up Table (LUT needed for the SO2 column abundance and the ash retrievals have been computed using the MODTRAN 4 Radiative Transfer Model. The results show the importance of the ash correction on SO2 retrievals at 8.7 μm, where the corrected SO2 column abundance values are less than 50% of the uncorrected values. The ash correction on SO2 retrieval at 7.3 μm is much less important and only significant for low SO2 column abundances. Results also show that the simplified and faster correction procedure

  13. Comparative Assessment of Satellite-Retrieved Surface Net Radiation: An Examination on CERES and SRB Datasets in China

    Directory of Open Access Journals (Sweden)

    Xin Pan

    2015-04-01

    Full Text Available Surface net radiation plays an important role in land–atmosphere interactions. The net radiation can be retrieved from satellite radiative products, yet its accuracy needs comprehensive assessment. This study evaluates monthly surface net radiation generated from the Clouds and the Earth’s Radiant Energy System (CERES and the Surface Radiation Budget project (SRB products, respectively, with quality-controlled radiation data from 50 meteorological stations in China for the period from March 2000 to December 2007. Our results show that surface net radiation is generally overestimated for CERES (SRB, with a bias of 26.52 W/m2 (18.57 W/m2 and a root mean square error of 34.58 W/m2 (29.49 W/m2. Spatially, the satellite-retrieved monthly mean of surface net radiation has relatively small errors for both CERES and SRB at inland sites in south China. Substantial errors are found at northeastern sites for two datasets, in addition to coastal sites for CERES. Temporally, multi-year averaged monthly mean errors are large at sites in western China in spring and summer, and in northeastern China in spring and winter. The annual mean error fluctuates for SRB, but decreases for CERES between 2000 and 2007. For CERES, 56% of net radiation errors come from net shortwave (NSW radiation and 44% from net longwave (NLW radiation. The errors are attributable to environmental parameters including surface albedo, surface water vapor pressure, land surface temperature, normalized difference vegetation index (NDVI of land surface proxy, and visibility for CERES. For SRB, 65% of the errors come from NSW and 35% from NLW radiation. The major influencing factors in a descending order are surface water vapor pressure, surface albedo, land surface temperature, NDVI, and visibility. Our findings offer an insight into error patterns in satellite-retrieved surface net radiation and should be valuable to improving retrieval accuracy of surface net radiation. Moreover, our

  14. Real-Time Global Flood Estimation Using Satellite-Based Precipitation and a Coupled Land Surface and Routing Model

    Science.gov (United States)

    Wu, Huan; Adler, Robert F.; Tian, Yudong; Huffman, George J.; Li, Hongyi; Wang, JianJian

    2014-01-01

    A widely used land surface model, the Variable Infiltration Capacity (VIC) model, is coupled with a newly developed hierarchical dominant river tracing-based runoff-routing model to form the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model, which serves as the new core of the real-time Global Flood Monitoring System (GFMS). The GFMS uses real-time satellite-based precipitation to derive flood monitoring parameters for the latitude band 50 deg. N - 50 deg. S at relatively high spatial (approximately 12 km) and temporal (3 hourly) resolution. Examples of model results for recent flood events are computed using the real-time GFMS (http://flood.umd.edu). To evaluate the accuracy of the new GFMS, the DRIVE model is run retrospectively for 15 years using both research-quality and real-time satellite precipitation products. Evaluation results are slightly better for the research-quality input and significantly better for longer duration events (3 day events versus 1 day events). Basins with fewer dams tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, the probability of detection is approximately 0.9 and the false alarm ratio is approximately 0.6. In general, these statistical results are better than those of the previous system. Streamflow was evaluated at 1121 river gauges across the quasi-global domain. Validation using real-time precipitation across the tropics (30 deg. S - 30 deg. N) gives positive daily Nash-Sutcliffe Coefficients for 107 out of 375 (28%) stations with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. There were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation input.

  15. Application of satellite precipitation data to analyse and model arbovirus activity in the tropics

    Directory of Open Access Journals (Sweden)

    Corner Robert J

    2011-01-01

    Full Text Available Abstract Background Murray Valley encephalitis virus (MVEV is a mosquito-borne Flavivirus (Flaviviridae: Flavivirus which is closely related to Japanese encephalitis virus, West Nile virus and St. Louis encephalitis virus. MVEV is enzootic in northern Australia and Papua New Guinea and epizootic in other parts of Australia. Activity of MVEV in Western Australia (WA is monitored by detection of seroconversions in flocks of sentinel chickens at selected sample sites throughout WA. Rainfall is a major environmental factor influencing MVEV activity. Utilising data on rainfall and seroconversions, statistical relationships between MVEV occurrence and rainfall can be determined. These relationships can be used to predict MVEV activity which, in turn, provides the general public with important information about disease transmission risk. Since ground measurements of rainfall are sparse and irregularly distributed, especially in north WA where rainfall is spatially and temporally highly variable, alternative data sources such as remote sensing (RS data represent an attractive alternative to ground measurements. However, a number of competing alternatives are available and careful evaluation is essential to determine the most appropriate product for a given problem. Results The Tropical Rainfall Measurement Mission (TRMM Multi-satellite Precipitation Analysis (TMPA 3B42 product was chosen from a range of RS rainfall products to develop rainfall-based predictor variables and build logistic regression models for the prediction of MVEV activity in the Kimberley and Pilbara regions of WA. Two models employing monthly time-lagged rainfall variables showed the strongest discriminatory ability of 0.74 and 0.80 as measured by the Receiver Operating Characteristics area under the curve (ROC AUC. Conclusions TMPA data provide a state-of-the-art data source for the development of rainfall-based predictive models for Flavivirus activity in tropical WA. Compared to

  16. Satellite NO2 retrievals suggest China has exceeded its NOx reduction goals from the twelfth Five-Year Plan

    Science.gov (United States)

    de Foy, Benjamin; Lu, Zifeng; Streets, David G.

    2016-01-01

    China’s twelfth Five-Year Plan included pollution control measures with a goal of reducing national emissions of nitrogen oxides (NOx) by 10% by 2015 compared with 2010. Multiple linear regression analysis was used on 11-year time series of all nitrogen dioxide (NO2) pixels from the Ozone Monitoring Instrument (OMI) over 18 NO2 hotspots in China. The regression analysis accounted for variations in meteorology, pixel resolution, seasonal effects, weekday variability and year-to-year variability. The NO2 trends suggested that there was an increase in NO2 columns in most areas from 2005 to around 2011 which was followed by a strong decrease continuing through 2015. The satellite results were in good agreement with the annual official NOx emission inventories which were available up until 2014. This shows the value of evaluating trends in emission inventories using satellite retrievals. It further shows that recent control strategies were effective in reducing emissions and that recent economic transformations in China may be having an effect on NO2 columns. Satellite information for 2015 suggests that emissions have continued to decrease since the latest inventories available and have surpassed the goals of the twelfth Five-Year Plan. PMID:27786278

  17. Satellite NO2 retrievals suggest China has exceeded its NOx reduction goals from the twelfth Five-Year Plan.

    Science.gov (United States)

    de Foy, Benjamin; Lu, Zifeng; Streets, David G

    2016-10-27

    China's twelfth Five-Year Plan included pollution control measures with a goal of reducing national emissions of nitrogen oxides (NOx) by 10% by 2015 compared with 2010. Multiple linear regression analysis was used on 11-year time series of all nitrogen dioxide (NO2) pixels from the Ozone Monitoring Instrument (OMI) over 18 NO2 hotspots in China. The regression analysis accounted for variations in meteorology, pixel resolution, seasonal effects, weekday variability and year-to-year variability. The NO2 trends suggested that there was an increase in NO2 columns in most areas from 2005 to around 2011 which was followed by a strong decrease continuing through 2015. The satellite results were in good agreement with the annual official NOx emission inventories which were available up until 2014. This shows the value of evaluating trends in emission inventories using satellite retrievals. It further shows that recent control strategies were effective in reducing emissions and that recent economic transformations in China may be having an effect on NO2 columns. Satellite information for 2015 suggests that emissions have continued to decrease since the latest inventories available and have surpassed the goals of the twelfth Five-Year Plan.

  18. 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.

    2011-05-01

    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 2° decade-1 in June-July-August (JJA) in the Northern Hemisphere and 0.3-0.7° decade-1 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 (0.9-1.7° decade-1) 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.

  19. NDACC UV-visible total ozone measurements: improved retrieval and comparison with correlative satellite and ground-based observations

    Directory of Open Access Journals (Sweden)

    F. Hendrick

    2010-08-01

    Full Text Available Accurate long-term monitoring of total ozone is one of the most important requirements for identifying possible natural or anthropogenic changes in the composition of the stratosphere. For this purpose, the NDACC (Network for the Detection of Atmospheric Composition Change UV-visible Working Group has made recommendations for improving and homogenizing the retrieval of total ozone columns from twilight zenith-sky visible spectrometers. These instruments, deployed all over the world in about 35 stations, allow measurements of total ozone twice daily with little sensitivity to stratospheric temperature and cloud cover. The NDACC recommendations address both the DOAS retrieval parameters and the calculation of air mass factors (AMF needed for the conversion of O3 slant column densities into vertical column amounts. The most important improvement is the use of O3 AMF look-up tables calculated using the TOMS V8 O3 profile climatology, that allows accounting for the dependence of the O3 AMF on the seasonal and latitudinal variations of the O3 vertical distribution. To investigate their impact on the retrieved ozone columns, the recommendations have been applied to measurements from the NDACC/SAOZ (Système d'Analyse par Observation Zénithale network. The revised SAOZ ozone data from eight stations covering all latitude regions have been compared to TOMS, GOME-GDP4, SCIAMACHY-TOSOMI, OMI-TOMS, and OMI-DOAS satellite overpass observations, as well as to those of collocated Dobson and Brewer instruments. A significant improvement is obtained after applying the new O3 AMFs, although systematic seasonal differences between SAOZ and all other instruments remain. These are shown to mainly originate from i the temperature dependence of the ozone absorption cross sections in the UV being not or improperly corrected by some retrieval algorithms, and ii the longitudinal differences in

  20. Inelastic scattering in ocean water and its impact on trace gas retrievals from satellite data

    Directory of Open Access Journals (Sweden)

    M. Vountas

    2003-01-01

    Full Text Available Over clear ocean waters, photons scattered within the water body contribute significantly to the upwelling flux. In addition to elastic scattering, inelastic Vibrational Raman Scattering (VRS by liquid water is also playing a role and can have a strong impact on the spectral distribution of the outgoing radiance. Under clear-sky conditions, VRS has an influence on trace gas retrievals from space-borne measurements of the backscattered radiance such as from e.g. GOME (Global Ozone Monitoring Experiment. The effect is particularly important for geo-locations with small solar zenith angles and over waters with low chlorophyll concentration. In this study, a simple ocean reflectance model (Sathyendranath and Platt, 1998 accounting for VRS has been incorporated into a radiative transfer model. The model has been validated by comparison with measurements from a swimming-pool experiment dedicated to detect the effect of scattering within water on the outgoing radiation and also with selected data sets from GOME. The comparisons show good agreement between experimental and model data and highlight the important role of VRS. To evaluate the impact of VRS on trace gas retrieval, a sensitivity study was performed on synthetic data. If VRS is neglected in the data analysis, errors of more than 30% are introduced for the slant column (SC of BrO over clear ocean scenarios. Exemplarily DOAS retrievals of BrO from real GOME measurements including and excluding a VRS compensation led to comparable results as in the sensitivity study, but with somewhat smaller differences between the two analyses. The results of this work suggest, that DOAS retrievals of atmospheric trace species from measurements of nadir viewing space-borne instruments have to take VRS scattering into account over waters with low chlorophyll concentrations, and that a simple correction term is enough to reduce the errors to an acceptable level.

  1. Satellite retrievals of dust aerosol over the Red Sea and the Persian Gulf (2005–2015)

    KAUST Repository

    Banks, Jamie R.

    2017-07-13

    The inter-annual variability of the dust aerosol presence over the Red Sea and the Persian Gulf is analysed over the period 2005-2015. Particular attention is paid to the variation in loading across the Red Sea, which has previously been shown to have a strong, seasonally dependent latitudinal gradient. Over the 11 years considered, the July mean 630 nm aerosol optical depth (AOD) derived from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) varies between 0.48 and 1.45 in the southern half of the Red Sea. In the north, the equivalent variation is between 0.22 and 0.66. The temporal and spatial pattern of variability captured by SEVIRI is also seen in AOD retrievals from the MODerate Imaging Spectroradiometer (MODIS), but there is a systematic offset between the two records. Comparisons of both sets of retrievals with ship-and land-based AERONET measurements show a high degree of correlation with biases of < 0.08. However, these comparisons typically only sample relatively low aerosol loadings. When both records are stratified by AOD retrievals from the Multi-angle Imaging SpectroRadiometer (MISR), opposing behaviour is revealed at high MISR AODs (> 1), with offsets of C 0.19 for MODIS and 0.06 for SEVIRI. Similar behaviour is also seen over the Persian Gulf. Analysis of the scattering angles at which retrievals from the SEVIRI and MODIS measurements are typically performed in these regions suggests that assumptions concerning particle sphericity may be responsible for the differences seen.

  2. An improved tropospheric NO2 retrieval for satellite observations in the vicinity of mountainous terrain

    Directory of Open Access Journals (Sweden)

    R. Dirksen

    2009-03-01

    Full Text Available We present an approach to reduce topography-related errors of vertical tropospheric columns (VTC of NO2 retrieved from the Ozone Monitoring Instrument (OMI in the vicinity of mountainous terrain. This is crucial for reliable estimates of air pollution levels over our particular area of interest, the Alpine region and the adjacent planes, where the operational OMI products exhibit significant biases due to the coarse resolution of surface parameters used in the retrieval. Our approach replaces the coarse-gridded surface pressures by accurate pixel-average values using a high-resolution topography data set, and scales the a priori NO2 profiles accordingly. NO2 VTC reprocessed in this way for the period 2006–2007 suggest that the current Dutch OMI NO2 product (DOMINO underestimates NO2 over the Po Valley in Italy and over the Swiss plateau by about 20% in winter and 5% in summer under clear-sky conditions (cloud radiance fraction <0.5. A sensitivity analysis shows that these seasonal differences are mainly due to the different a priori NO2 profile shapes and solar zenith angles in winter and summer. The comparison of NO2 columns from the original and the enhanced retrieval with corresponding columns deduced from ground-based in situ observations over the Swiss plateau and the Po Valley illustrates the promise of our new retrieval. It partially reduces the underestimation of the OMI VTCs at polluted sites in winter and fall and generally improves the agreement in terms of slope and correlation at rural stations. It does not solve, however, the issue that the OMI DOMINO product tends to overestimate very low columns observed at rural sites in spring and summer.

  3. Soil moisture and evapotranspiration of wetlands vegetation habitats retrieved from satellite images

    Science.gov (United States)

    Dabrowska-Zielinska, K.; Budzynska, M.; Kowalik, W.; Turlej, K.

    2010-08-01

    The research has been carried out in Biebrza Ramsar Convention test site situated in the N-E part of Poland. Data from optical and microwave satellite images have been analysed and compared to the detailed soil-vegetation ground truth measurements conducted during the satellite overpasses. Satellite data applied for the study include: ENVISAT.ASAR, ENVISAT.MERIS, ALOS.PALSAR, ALOS.AVNIR-2, ALOS.PRISM, TERRA.ASTER, and NOAA.AVHRR. Optical images have been used for classification of wetlands vegetation habitats and vegetation surface roughness expressed by LAI. Also, heat fluxes have been calculated using NOAA.AVHRR data and meteorological data. Microwave images have been used for the assessment of soil moisture. For each of the classified wetlands vegetation habitats the relationship between soil moisture and backscattering coefficient has been examined, and the best combination of microwave variables (wave length, incidence angle, polarization) has been used for mapping and monitoring of soil moisture. The results of this study give possibility to improve models of water cycle over wetlands ecosystems by adding information about soil moisture and surface heat fluxes derived from satellite images. Such information is very essential for better protection of the European sensitive wetland ecosystems. ENVISAT and ALOS images have been obtained from ESA for AO ID 122 and AOALO.3742 projects.

  4. [The arctic sea ice refractive index retrieval based on satellite AMSR-E observations].

    Science.gov (United States)

    Chen, Han-Yue; Bi, Hai-Bo; Niu, Zheng

    2012-11-01

    The refractive index of sea ice in the polar region is an important geophysical parameter. It is needed as a vital input for some numerical climate models and is helpful to classifying sea ice types. In the present study, according to Hong Approximation (HA), we retrieved the arctic sea ice refractive index at 6.9, 10.7, 23, 37, and 89 GHz in different arctic climatological conditions. The refractive indices of wintertime first year (FY) sea ice and summertime ice were derived with average values of 1.78 - 1.75 and 1.724 - 1.70 at different frequencies respectively, which are consistent with previous studies. However, for multiyear (MY) ice, the results indicated relatively large bias between modeled results since 10.7 GHz. At a higher frequency, there is larger MY ice refractive index difference. This bias is mainly attributed to the volume scattering effect on MY microwave radiation due to emergence of massive small empty cavities after the brine water in MY ice is discharged into sea. In addition, the retrieved sea ice refractive indices can be utilized to classify ice types (for example, the winter derivation at 89 GHz), to identify coastal polynyas (winter retrieval at 6.9 GHz), and to outline the areal extent of significantly melting marginal sea ice zone (MIZ) (summer result at 6.9 GHz). The investigation of this study suggests an effective tool of passive microwave remote sensing in monitoring sea ice refractive index variability.

  5. Observed and blended gauge-satellite precipitation estimates perspective on meteorological drought intensity over South Sulawesi, Indonesia

    Science.gov (United States)

    Setiawan, A. M.; Koesmaryono, Y.; Faqih, A.; Gunawan, D.

    2017-01-01

    South Sulawesi province as one of the rice production center for national food security are highly influenced by climate phenomenon that lead to drought condition. This paper quantifies meteorological drought based on Standardized Precipitation Index (SPI) recommended by the World Meteorological Organization (WMO) and Consecutive Dry Days (CDD) as one of the extreme indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). The indices were calculated by using (i) quality controlled daily and monthly observational precipitation data from 23 weather stations of various record lengths within 1967-2015 periods, and (ii) 0.05o x 0.05o blended gauge-satellite of daily and monthly precipitation estimates of the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) dataset. Meteorological drought intensity represented by Average Duration of Drought Intensity (ADI) from three-monthly SPI (SPI3) show spatial differences characteristic between eastern and western region. Observed and CHIRPS have relatively similar perspective on meteorological drought intensity over South Sulawesi. Relatively high values of ADI and longest CDD observed mainly over south western part of study area.

  6. Temporal disaggregation of satellite-derived monthly precipitation estimates and the resulting propagation of error in partitioning of water at the land surface

    Directory of Open Access Journals (Sweden)

    S.A. Margulis

    2001-01-01

    Full Text Available Global estimates of precipitation can now be made using data from a combination of geosynchronous and low earth-orbit satellites. However, revisit patterns of polar-orbiting satellites and the need to sample mixed-clouds scenes from geosynchronous satellites leads to the coarsening of the temporal resolution to the monthly scale. There are prohibitive limitations to the applicability of monthly-scale aggregated precipitation estimates in many hydrological applications. The nonlinear and threshold dependencies of surface hydrological processes on precipitation may cause the hydrological response of the surface to vary considerably based on the intermittent temporal structure of the forcing. Therefore, to make the monthly satellite data useful for hydrological applications (i.e. water balance studies, rainfall-runoff modelling, etc., it is necessary to disaggregate the monthly precipitation estimates into shorter time intervals so that they may be used in surface hydrology models. In this study, two simple statistical disaggregation schemes are developed for use with monthly precipitation estimates provided by satellites. The two techniques are shown to perform relatively well in introducing a reasonable temporal structure into the disaggregated time series. An ensemble of disaggregated realisations was routed through two land surface models of varying complexity so that the error propagation that takes place over the course of the month could be characterised. Results suggest that one of the proposed disaggregation schemes can be used in hydrological applications without introducing significant error. Keywords: precipitation, temporal disaggregation, hydrological modelling, error propagation

  7. Top-of-Atmosphere Albedo Estimation from Angular Distribution Models using Scene Identification from Satellite Cloud Property Retrievals

    Science.gov (United States)

    Loeb, N. G.; Parol, F.; Buriez, J.-C.; Vanbauce, C.

    2000-01-01

    The next generation of Earth radiation budget satellite instruments will routinely merge estimates of global top-of-atmosphere radiative fluxes with cloud properties. This information will offer many new opportunities for validating radiative transfer models and cloud parameterizations in climate models. In this study, five months of POLarization and Directionality of the Earth's Reflectances (POLDER) 670 nm radiance measurements are considered in order to examine how satellite cloud property retrievals can be used to define empirical Angular Distribution Models (ADMs) for estimating top-of-atmosphere (TOA) albedo. ADMs are defined for 19 scene types defined by satellite retrievals of cloud fraction and cloud optical depth. Two approaches are used to define the ADM scene types: The first assumes there are no biases in the retrieved cloud properties and defines ADMs for fixed discrete intervals of cloud fraction and cloud optical depth (fixed-tau approach). The second approach involves the same cloud fraction intervals, but uses percentile intervals of cloud optical depth instead (percentile-tau approach). Albedos generated using these methods are compared with albedos inferred directly from the mean observed reflectance field. Albedos based on ADMs that assume cloud properties are unbiased (fixed-tau approach) show a strong systematic dependence on viewing geometry. This dependence becomes more pronounced with increasing solar zenith angle, reaching approximately equals 12% (relative) between near-nadir and oblique viewing zenith angles for solar zenith angles between 60 deg and 70 deg. The cause for this bias is shown to be due to biases in the cloud optical depth retrievals. In contrast, albedos based on ADMs built using percentile intervals of cloud optical depth (percentile-tau approach) show very little viewing zenith angle dependence and are in good agreement with albedos obtained by direct integration of the mean observed reflectance field (less than 1

  8. Maritime Aerosol Network as a Component of AERONET - First Results and Comparison with Global Aerosol Models and Satellite Retrievals

    Science.gov (United States)

    Smirnov, A.; Holben, B. N.; Giles, D. M.; Slutsker, I.; O'Neill, N. T.; Eck, T. F.; Macke, A.; Croot, P.; Courcoux, Y.; Sakerin, S. M.; Smyth, T. J.; Zielinski, T.; Zibordi, G.; Goes, J. I.; Harvey, M. J.; Quinn, P. K.; Nelson, N. B.; Radionov, V. F.; Duarte, C. M.; Remer, L. A.; Kahn, R. A.; Kleidman, R. G.; Gaitley, B. J.; Tan, Q.; Diehl, T. L.

    2011-01-01

    The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. Over 80 cruises were completed through early 2010 with deployments continuing. Measurement areas included various parts of the Atlantic Ocean, the Northern and Southern Pacific Ocean, the South Indian Ocean, the Southern Ocean, the Arctic Ocean and inland seas. MAN deploys Microtops handheld sunphotometers and utilizes a calibration procedure and data processing traceable to AERONET. Data collection included areas that previously had no aerosol optical depth (AOD) coverage at all, particularly vast areas of the Southern Ocean. The MAN data archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we present results of AOD measurements over the oceans, and make a comparison with satellite AOD retrievals and model simulations.

  9. Evaluation of CMIP5 continental precipitation simulations relative to satellite-based gauge-adjusted observations

    Energy Technology Data Exchange (ETDEWEB)

    Mehran, Ali [Univ. of California, Irvine, CA (United States). Dept. of Civil and Environmental Engineering; AghaKouchak, Amir [Univ. of California, Irvine, CA (United States). Dept. of Civil and Environmental Engineering; Phillips, Thomas J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2014-02-25

    Numerous studies have emphasized that climate simulations are subject to various biases and uncertainties. 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 data 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 sub-continental regions (e.g., northern Eurasia, eastern Russia, central Australia) is problematical. Overall, the VHI of the multi-model ensemble mean and median also are superior to that of the individual CMIP5 models. However, at high quantiles of reference data (e.g., the 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, inter-model variations in bias over Australia and Amazonia are considerable. The Quantile Bias (QB) analyses indicate that CMIP5 simulations are even more biased at high quantiles of precipitation. Lastly, we found that a simple mean-field bias removal improves the overall B and VHI values, but does not make a significant improvement in these model performance metrics at high quantiles of precipitation.

  10. 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.

  11. Improved Ozone and Carbon Monoxide Profile Retrievals Using Multispectral Measurements from NASA "A Train", NPP, and TROPOMI Satellites

    Science.gov (United States)

    Fu, D.; Bowman, K. W.; Kulawik, S. S.; Miyazaki, K.; Worden, J. R.; Worden, H. M.; Livesey, N. J.; Payne, V.; Luo, M.; Natraj, V.; Veefkind, P.; Aben, I.; Landgraf, J.; Flynn, L. E.; Han, Y.; Liu, X.; Strow, L. L.; Kuai, L.

    2015-12-01

    Tropospheric ozone is at the juncture of air quality and climate. Ozone directly impacts human and plant health, and directly forces the climate system through absorption of thermal radiation. Carbon monoxide is a chemical precursor of greenhouse gases CO2 and tropospheric O3, and is also an ideal tracer of transport processes due to its medium life time (weeks to months). The Aqua-AIRS and Aura-OMI instruments in the NASA "A-Train", CrIS and OMPS instruments on the NOAA Suomi-NPP, IASI and GOME-2 on METOP and TROPOMI aboard the Sentinel 5 precursor (S5p) have the potential to provide the synoptic chemical and dynamical context for ozone necessary to quantify long-range transport at global scales and to provide an anchor to the near-term constellation of geostationary sounders: NASA TEMPO, ESA Sentinel 4, and the Korean GEMS. We introduce the JPL MUlti-SpEctral, MUlti-SpEcies, MUlti-SatEllite (MUSES) retrieval algorithm, which ingests panspectral observations across multiple platforms in a non-linear optimal estimation framework. MUSES incorporates advances in remote sensing science developed during the EOS-Aura era including rigorous error analysis diagnostics and observation operators needed for trend analysis, climate model evaluation, and data assimilation. Its performance has been demonstrated through prototype studies for multi-satellite missions (AIRS, CrIS, TROPOMI, TES, OMI, and OMPS). We present joint tropospheric ozone retrievals from AIRS/OMI and CrIS/OMPS over global scales, and demonstrate the potential of joint carbon monoxide profiles from TROPOMI/CrIS. These results indicate that ozone can be retrieved with ~2 degrees of freedom for signal (dofs) in the troposphere, which is similar to TES. Joint CO profiles have dofs similar to the MOPITT multispectral retrieval but with higher spatial resolution and coverage. Consequently, multispectral retrievals show promise in providing continuity with NASA EOS observations and pave the way towards a new

  12. The scientific basis for a satellite mission to retrieve CCN concentrations and their impacts on convective clouds

    Directory of Open Access Journals (Sweden)

    D. Rosenfeld

    2012-02-01

    Full Text Available The cloud -mediated radiative forcing is widely recognized as the main source of uncertainty in our knowledge of the anthropogenic climate forcing and in our understanding of climate sensitivity. Current outstanding challenges are (1 global measurements of cloud condensation nuclei (CCN in the cloudy boundary layer from space, and, (2 disentangling the effects of aerosols from the thermodynamic and meteorological effects on the clouds. Here we present a new concept for a way to overcome these two challenges, using relatively simple passive satellite measurements in the visible and IR. The idea is to use the clouds themselves as natural CCN chambers by retrieving simultaneously the number of activated aerosols at cloud base, Na, and the cloud base updraft speed. The Na is obtained by analyzing the distribution of cloud drop effective radius in convective elements as a function distance above cloud base. The cloud base updraft velocities are estimated by double stereoscopic viewing and tracking of the evolution of cloud surface features just above cloud base. In order to resolve the vertical dimension of the clouds, the field of view will be 100 m for the microphysical retrievals, and 50 m for the stereoscopic measurements. The viewing geometry will be 30 degrees off nadir eastward, with the Sun in the back at 30 degrees off zenith westward, which requires a Sun synchronous orbit at 14:00 LST. Having measured simultaneously the thermodynamic environment, the vertical motions of the clouds, their microstructure and the CCN concentration will allow separating the dynamic from the CCN effects. This concept is being applied in the proposed satellite mission named Clouds, Hazards and Aerosols Survey for Earth Researchers (CHASER.

  13. The scientific basis for a satellite mission to retrieve CCN concentrations and their impacts on convective clouds

    Directory of Open Access Journals (Sweden)

    D. Rosenfeld

    2012-08-01

    Full Text Available The cloud-mediated aerosol radiative forcing is widely recognized as the main source of uncertainty in our knowledge of the anthropogenic forcing on climate. The current challenges for improving our understanding are (1 global measurements of cloud condensation nuclei (CCN in the cloudy boundary layer from space, and (2 disentangling the effects of aerosols from the thermodynamic and meteorological effects on the clouds. Here, we present a new conceptual framework to help us overcome these two challenges, using relatively simple passive satellite measurements in the visible and infared (IR. The idea is to use the clouds themselves as natural CCN chambers by retrieving simultaneously the number of activated aerosols at cloud base, Na, and the cloud base updraft speed. The Na is obtained by analyzing the distribution of cloud drop effective radius in convective elements as a function of distance above cloud base. The cloud base updraft velocities are estimated by double stereoscopic viewing and tracking of the evolution of cloud surface features just above cloud base. In order to resolve the vertical dimension of the clouds, the field of view will be 100 m for the microphysical retrievals, and 50 m for the stereoscopic measurements. The viewing geometry will be eastward and 30 degrees off nadir, with the Sun in the back at 30 degrees off zenith westward, requiring a Sun-synchronous orbit at 14 LST. Measuring simultaneously the thermodynamic environment, the vertical motions of the clouds, their microstructure and the CCN concentration will allow separating the dynamics from the CCN effects. This concept is being applied in the proposed satellite mission named Clouds, Hazards and Aerosols Survey for Earth Researchers (CHASER.

  14. Real time retrieval of volcanic cloud particles and SO2 by satellite using an improved simplified approach

    Science.gov (United States)

    Pugnaghi, Sergio; Guerrieri, Lorenzo; Corradini, Stefano; Merucci, Luca

    2016-07-01

    Volcanic plume removal (VPR) is a procedure developed to retrieve the ash optical depth, effective radius and mass, and sulfur dioxide mass contained in a volcanic cloud from the thermal radiance at 8.7, 11, and 12 µm. It is based on an estimation of a virtual image representing what the sensor would have seen in a multispectral thermal image if the volcanic cloud were not present. Ash and sulfur dioxide were retrieved by the first version of the VPR using a very simple atmospheric model that ignored the layer above the volcanic cloud. This new version takes into account the layer of atmosphere above the cloud as well as thermal radiance scattering along the line of sight of the sensor. In addition to improved results, the new version also offers an easier and faster preliminary preparation and includes other types of volcanic particles (andesite, obsidian, pumice, ice crystals, and water droplets). As in the previous version, a set of parameters regarding the volcanic area, particle types, and sensor is required to run the procedure. However, in the new version, only the mean plume temperature is required as input data. In this work, a set of parameters to compute the volcanic cloud transmittance in the three quoted bands, for all the aforementioned particles, for both Mt. Etna (Italy) and Eyjafjallajökull (Iceland) volcanoes, and for the Terra and Aqua MODIS instruments is presented. Three types of tests are carried out to verify the results of the improved VPR. The first uses all the radiative transfer simulations performed to estimate the above mentioned parameters. The second one makes use of two synthetic images, one for Mt. Etna and one for Eyjafjallajökull volcanoes. The third one compares VPR and Look-Up Table (LUT) retrievals analyzing the true image of Eyjafjallajökull volcano acquired by MODIS aboard the Aqua satellite on 11 May 2010 at 14:05 GMT.

  15. Comparison between CNA and energetic electron precipitation: simultaneous observation by Poker Flat Imaging Riometer and NOAA satellite

    Directory of Open Access Journals (Sweden)

    Y.-M. Tanaka

    2005-07-01

    Full Text Available The cosmic noise absorption (CNA is compared with the precipitating electron flux for 19 events observed in the morning sector, using the high-resolution data obtained during the conjugate observations with the imaging riometer at Poker Flat Research Range (PFRR; 65.11° N, 147.42° W, Alaska, and the low-altitude satellite, NOAA 12. We estimate the CNA, using the precipitating electron flux measured by NOAA 12, based on a theoretical model assuming an isotropic pitch angle distribution, and quantitatively compare them with the observed CNA. Focusing on the eight events with a range of variation larger than 0.4dB, three events show high correlation between the observed and estimated CNA (correlation coefficient (r0>0.7 and five events show low correlation (r0<0.5. The estimated CNA is often smaller than the observed CNA (72% of all data for 19 events, which appears to be the main reason for the low-correlation events. We examine the assumption of isotropic pitch angle distribution by using the trapped electron flux measured at 80° zenith angle. It is shown that the CNA estimated from the trapped electron flux, assuming an isotropic pitch angle distribution, is highly correlated with the observed CNA and is often overestimated (87% of all data. The underestimate (overestimate of CNA derived from the precipitating (trapped electron flux can be interpreted in terms of the anisotropic pitch angle distribution similar to the loss cone distribution. These results indicate that the CNA observed with the riometer may be quantitatively explained with a model based on energetic electron precipitation, provided that the pitch angle distribution and the loss cone angle of the electrons are taken into account.

    Keywords. Energetic particles, precipitating – Energetic particles, trapped – Ionosphere-magnetosphere interactions

  16. Representativeness of total column water vapour retrievals from instruments on polar orbiting satellites

    Science.gov (United States)

    Diedrich, Hannes; Wittchen, Falco; Preusker, René; Fischer, Jürgen

    2016-07-01

    The remote sensing of total column water vapour (TCWV) from polar orbiting, sun-synchronous satellite spectrometers such as the Medium Resolution Imaging Spectrometer (MERIS) on board of ENVISAT and the Moderate Imaging Spectroradiometer (MODIS) on board of Aqua and Terra enables observations on a high spatial resolution and a high accuracy over land surfaces. The observations serve studies about small-scale variations of water vapour as well as the detection of local and global trends. However, depending on the swath width of the sensor, the temporal sampling is low and the observations of TCWV are limited to cloud-free land scenes. This study quantifies the representativeness of a single TCWV observation at the time of the satellite overpass under cloud-free conditions by investigating the diurnal cycle of TCWV using 9 years of a 2-hourly TCWV data set from global GNSS (Global Navigation Satellite Systems) stations. It turns out that the TCWV observed at 10:30 local time (LT) is generally lower than the daily mean TCWV by 0.65 mm (4 %) on average for cloud-free cases. Averaging over all GNSS stations, the monthly mean TCWV at 10:30 LT, constrained to cases that are cloud-free, is 5 mm (25 %) lower than the monthly mean TCWV at 10:30 LT of all cases. Additionally, the diurnal variability of TCWV is assessed. For the majority of GNSS stations, the amplitude of the averaged diurnal cycle ranges between 1 and 5 % of the daily mean with a minimum between 06:00 and 10:00 LT and maximum between 16:00 and 20:00 LT. However, a high variability of TCWV on an individual day is detected. On average, the TCWV standard deviation is about 15 % regarding the daily mean.

  17. USING A SATELLITE TELEPHONE TO RETRIEVE TSUNAMI DATA FROM TIDE SITES IN THE PACIFIC BASIN

    Directory of Open Access Journals (Sweden)

    T.J.Sokolowski

    2001-01-01

    Full Text Available The tsunami warning centers require accurate, timely and reliable tide data during a large potentially tsunamigenic earthquake. At the present time tide gauge data in remote parts of the Pacific Basin are often not availableto view during a potential tsunami event or the data may be transmitted hours after the expected tsunami arrival time. This delay can adversely affect state and local emergency officials who require lead times for placing their areas in awarning status.The West Coast/Alaska Tsunami Warning Center conduct eda feasibility study, which showed that a satellite telephone link can be used to collect tide gauge data from remote sites in a timely manner.

  18. Intercomparison of daytime stratospheric NO2 satellite retrievals and model simulations

    Science.gov (United States)

    Belmonte Rivas, M.; Veefkind, P.; Boersma, F.; Levelt, P.; Eskes, H.; Gille, J.

    2014-07-01

    This paper evaluates the agreement between stratospheric NO2 retrievals from infrared limb sounders (Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and High Resolution Dynamics Limb Sounder (HIRDLS)) and solar UV/VIS backscatter sensors (Ozone Monitoring Instrument (OMI), Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) limb and nadir) over the 2005-2007 period and across the seasons. The observational agreement is contrasted with the representation of NO2 profiles in 3-D chemical transport models such as the Whole Atmosphere Community Climate Model (WACCM) and TM4. A conclusion central to this work is that the definition of a reference for stratospheric NO2 columns formed by consistent agreement among SCIAMACHY, MIPAS and HIRDLS limb records (all of which agree to within 0.25 × 1015 molecules cm-2 or better than 10%) allows us to draw attention to relative errors in other data sets, e.g., (1) WACCM overestimates NO2 densities in the extratropical lower stratosphere, particularly in the springtime and over northern latitudes by up to 35% relative to limb observations, and (2) there are remarkable discrepancies between stratospheric NO2 column estimates from limb and nadir techniques, with a characteristic seasonally and latitudinally dependent pattern. We find that SCIAMACHY nadir and OMI stratospheric columns show overall biases of -0.5 × 1015 molecules cm-2 (-20%) and +0.6 × 1015 molecules cm-2 (+20%) relative to limb observations, respectively. It is argued that additive biases in nadir stratospheric columns are not expected to affect tropospheric retrievals significantly, and that they can be attributed to errors in the total slant column density, related either to algorithmic or instrumental effects. In order to obtain accurate and long-term time series of stratospheric NO2, an effort towards the harmonization of currently used differential optical absorption spectroscopy (DOAS) approaches to nadir

  19. Four dimensional variational data assimilation of species-resolved satellite-retrieved aerosol optical thickness

    Science.gov (United States)

    Nieradzik, Lars Peter; Elbern, Hendrik

    2010-05-01

    Aerosols play an increasingly important role in atmospheric modelling. They have a strong influence on the radiative transfer balance and a significant impact on human health. Their origin is various and so are its effects. Most of the measurement sites in Europe only account for an integrated aerosol load PMx (Particulate Matter of less than x μm in diameter) which does not give any qualitative information on the composition of the aerosol. Since very different constituents like mineral dust derived from desert storms and sea salt contribute to PMx it is necessary to make aerosol forcasts not only of load, but also type resolved. The source of information chosen for this study is the aerosol retrieval system SYNAER (SYNergetic AErosol Retrieval) from DLR-DFD that retrieves BLAOT (Boundary Layer Aerosol Optical Thickness) making use of both AATSR/SCIAMACHY and AVHRR/GOME-2 data respectively. Its strengths are a large spatial coverage, near real-time availability, and the classification of five intrinsic aerosol species, namely water-solubles, water-insolubles, soot, sea salt, and mineral dust which are furthermore size resolved in terms of modes. A widely known technique to enhance forecast skills of CTMs (Chemistry-Transport-Models) by ingesting in-situ and, especially, remote-sensing measurements is the method of four dimensional variational data assimilation (4Dvar). The EURAD-IM (EURopean Air pollution Dispersion - Inverse Model), containing a full adjoint gas-phase model, has been expanded with an adjoint of the MADE (Modal Aerosol Dynamics model for Europe) to optimise initial and boundary values for aerosols using 4Dvar. A forward and an adjoint radiative transfer model is driven by the EURAD-IM as mapping between BLAOT and internal aerosol species. Furthermore, its condensation scheme has been bypassed by an HDMR (High-Dimensional-Model-Representation) to ensure differentiability, and a time saving online NMC-module for the generation of the background

  20. 利用地基北斗站反演大气水汽总量的精度检验%The Accuracy Test of Retrieved Precipitation Water Vapor Based on Beidou Observations

    Institute of Scientific and Technical Information of China (English)

    郭巍; 尹球; 杜明斌; 刘敏; 朱雪松

    2015-01-01

    The Beidou Navigation Satellite System is an independent system under construction in China.Obser-vations of Beidou can be used to retrieve atmospheric precipitation water vapor (PWV)and provide infor-mation of water vapor with high precise and high real time.Beidou meteorological observation network is built by Shanghai Meteorological Bureau with PANDA (position and navigation data analysist)and M300C GNSS,UNICORE-UB240 Beidou receivers,and the atmospheric precipitation water vapor is acquired. First,satellite data is received by Beidou meteorological observations and satellite orbit files are download-ed synchronously,and then zenith total delay (ZTD)is calculated by PANDA modules,and at last the PWV is retrieved based on surface meteorological parameters observed by automatic weather stations. Results of PWV retrieved by Beidou data (W BD )are compared with both PWV retrieved by GPS data (W GPS )and radiosonde data (W Radio ),as the technology of them are mature.W GPS is retrieved by two meth-ods:One is GAMIT (GPS at MIT)with the method of double difference phase observation,the other is PANDA with the method of precise point positioning.W Radio is retrieved by the method of water vapor inte-gration from different pressure levels.The horizontal distance difference between corresponding observa-tions is no more than 10 km,the elevation difference between GPS and Beidou observations is no more than 5 m,and the elevation difference between radiosonde and Beidou observations is about 30 m.Results show that the root mean square error (RMSE)between W BD and W GPS is no more than 3.5 mm,the correlation coefficient between them is over 0.95,and the RMSE between W BD and W GPS-P is smaller than that between W BD and W GPS-G ,which means that the retrieve method has certain influence on results of PWV.The RMSE between WBD and W GPS-Radio is about 3.6 mm,the correlation coefficient between them is over 0.96, and W BD is on the high side compared with W GPS-Radio .W BD can

  1. 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.

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

    Directory of Open Access Journals (Sweden)

    L. Fita

    2009-08-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-07-01

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

  4. How reliable are satellite precipitation estimates for driving hydrological models: a verification study over the Mediterranean area

    Science.gov (United States)

    Camici, Stefania; Ciabatta, Luca; Massari, Christian; Brocca, Luca

    2017-04-01

    Floods are one of the most common and dangerous natural hazards, causing every year thousands of casualties and damages worldwide. The main tool for assessing flood risk and reducing damages is represented by hydrologic early warning systems that allow to forecast flood events by using real time data obtained through ground monitoring networks (e.g., raingauges and radars). However, the use of such data, mainly rainfall, presents some issues firstly related to the network density and to the limited spatial representativeness of local measurements. A way to overcome these issues may be the use of satellite-based rainfall products (SRPs) that nowadays are available on a global scale at ever increasing spatial/temporal resolution and accuracy. However, despite the large availability and increased accuracy of SRPs (e.g., the Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA); the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF); and the recent Global Precipitation Measurement (GPM) mission), remotely sensed rainfall data are scarcely used in hydrological modeling and only a small number of studies have been carried out to outline some guidelines for using satellite data as input for hydrological modelling. Reasons may be related to: 1) the large bias characterizing satellite precipitation estimates, which is dependent on rainfall intensity and season, 2) the spatial/temporal resolution, 3) the timeliness, which is often insufficient for operational purposes, and 4) a general (often not justified) skepticism of the hydrological community in the use of satellite products for land applications. The objective of this study is to explore the feasibility of using SRPs in a lumped hydrologic model (MISDc, "Modello Idrologico Semi-Distribuito in continuo", Masseroni et al., 2017) over 10 basins in the Mediterranean area with different sizes and physiographic characteristics. Specifically

  5. The precipitation products generation chain for the EUMETSAT Hydrological Satellite Application Facility at C.N.M.C.A.

    Science.gov (United States)

    Biron, Daniele; Melfi, Davide; Zauli, Francesco

    2008-08-01

    The EUMETSAT Satellite Application Facility in support to Hydrology (H-SAF) focuses on 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, carried on 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 architectural status of the H-SAF precipitation group and stress the component of operations. It is shown the full correspondence with the EUMETSAT approved H-SAF documents, in particular the Algorithm Theoretical Design Document (ATDD), where products characteristics are referenced. Are also reported the first results, produced during the first H-SAF Workshop, held in Rome in October 2007, of validation activities performed on version 1 products, and last results of products distribution to beta-users in preparation of distributing version 2.

  6. Retrieval of Black Carbon Absorption from Proposed Satellite Measurements Over the Ocean Glint

    Science.gov (United States)

    Kaufman, Y. J.; Matins, J. V.; Remer, L. A.; Schoeberl, M. R.; Yamasoe, M. A.; Lau, William K. M. (Technical Monitor)

    2001-01-01

    Haze and air pollution includes many chemicals that together form small particles suspended in the air called aerosols. One of the main ingredients found to affect climate and human health is Black Carbon. Black particles emitted from engines that do not burn the fuel completely, e.g. old trucks. Black carbon absorption of sunlight emerges as one of the key components of man-made forcing of climate. However, global characterization of black carbon emissions, distribution and pathways in which it can affect the amount of solar radiation absorbed by the atmosphere is very uncertain. A new method is proposed to measure sunlight absorption by fine aerosol particles containing black carbon over the ocean glint from a satellite mission designed for this purpose. The satellite will scan the same spot over the ocean in the glint plane and a plane 40 degrees off-glint a minute apart, collecting measurements of the reflected light across the solar spectrum. First the dark ocean off the glint is used to derive aerosol properties. Then the black carbon absorption is derived prop the attenuation of the bright glint by the aerosol layer. Such measurements if realized in a proposed future mission - COBRA are expected to produce global monthly climatology of black carbon absorption with high accuracy (110 to 15%) that can show their effect on climate.

  7. Contemporary ground-based and satellite precipitating system characterization for desertification studies in Southern Italy

    Directory of Open Access Journals (Sweden)

    M. Casazza

    2008-07-01

    Full Text Available During the research project RIADE (Ricerca Integrata per l'Applicazione di tecnologie e processi innovativi per la lotta alla DEsertificazione, devoted to the study on the potential risk of desertification in Southern Italy, a particular attention has been paid also to the analysis of precipitations from three surface stations (Licata, Sicily; Rotondella, Basilicata; Surigheddu, Sardinia in order to improve the knowledge derived from the most modern climatological studies related to this subject. The point of view adopted is to better define the precipitation microphysical properties (in particular, the Drop Size Distribution, DSD, and its moments, which are deeply related to the cloud system that generates the precipitation events. In particular we have used a newly introduced Convective Stratiform discrimination technique, that allowed us to observe a prevalence of events, concentrated along Winter (Wi season, of different microphysical nature. In fact the prevailing Stratiform nature is related to Licata station, while for Surigheddu and for Rotondella the nature is mainly Convective. This distinction is related to the presence of drops of bigger dimensions and more intense precipitations in the latter case, while, in the former case, a prevalence of smaller drops and a less intense precipitation is recorded. This confirms the distinctive belonging to three different climatic regions, as indicated in the study by Brunetti et al. (2006. Our findings are important in the framework of desertification studies, because the cause of desertification can be related either to fertile soils removal (in the case of Convective events or to lack of precipitated water (in the case of Stratiform events. We have also analysed a sub-set of ten events, with contemporary presence of data from VIS/IR channels of METEOSAT-7, SSM/I data from F13 and MODIS data from Terra platform. This has been done both to confirm the findings of PLUDIX data analysis (which

  8. A satellite rainfall retrieval technique over northern Algeria based on the probability of rainfall intensities classification from MSG-SEVIRI

    Science.gov (United States)

    Lazri, Mourad; Ameur, Soltane

    2016-09-01

    In this paper, an algorithm based on the probability of rainfall intensities classification for rainfall estimation from Meteosat Second Generation/Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) has been developed. The classification scheme uses various spectral parameters of SEVIRI that provide information about cloud top temperature and optical and microphysical cloud properties. The presented method is developed and trained for the north of Algeria. The calibration of the method is carried out using as a reference rain classification fields derived from radar for rainy season from November 2006 to March 2007. Rainfall rates are assigned to rain areas previously identified and classified according to the precipitation formation processes. The comparisons between satellite-derived precipitation estimates and validation data show that the developed scheme performs reasonably well. Indeed, the correlation coefficient presents a significant level (r:0.87). The values of POD, POFD and FAR are 80%, 13% and 25%, respectively. Also, for a rainfall estimation of about 614 mm, the RMSD, Bias, MAD and PD indicate 102.06(mm), 2.18(mm), 68.07(mm) and 12.58, respectively.

  9. Quick look tools for magnetic field retrievals from Swarm satellite data

    DEFF Research Database (Denmark)

    Kotsiaros, Stavros; Plank, Gernot; Haagmans, Roger

    The objective of the Swarm mission is to provide the best ever survey of the geomagnetic field and its temporal dependency, and to gain new insights into improving our knowledge of the Earth’s interior and climate. The Swarm concept consists of a constellation of three satellites in three different...... near polar orbits between 300 and 550 km altitude. Goal of the current study is to achieve a fast diagnosis of the Swarm system performance in orbit during commission phase and operations of the spacecraft. With the help of a specially developed software package datasets are analyzed in terms...... of a closed loop simulation and the effects on the reconstruction of the magnetic field resulting from various error sources acting on the spacecraft are investigated. At first, the simplest noise-free case is examined and then more complex scenarios which include attitude errors, position errors and spectral...

  10. Surface Emissivity Maps for Use in Satellite Retrievals of Longwave Radiation

    Science.gov (United States)

    Wilber, Anne C.; Kratz, David P.; Gupta, Shashi K.

    1999-01-01

    Accurate accounting of surface emissivity is essential for the retrievals of surface temperature from remote sensing measurements, and for the computations of longwave (LW) radiation budget of the Earth?s surface. Past studies of the above topics assumed that emissivity for all surface types, and across the entire LW spectrum is equal to unity. There is strong evidence, however, that emissivity of many surface materials is significantly lower than unity, and varies considerably across the LW spectrum. We have developed global maps of surface emissivity for the broadband LW region, the thermal infrared window region (8-12 micron), and 12 narrow LW spectral bands. The 17 surface types defined by the International Geosphere Biosphere Programme (IGBP) were adopted as such, and an additional (18th) surface type was introduced to represent tundra-like surfaces. Laboratory measurements of spectral reflectances of 10 different surface materials were converted to corresponding emissivities. The 10 surface materials were then associated with 18 surface types. Emissivities for the 18 surface types were first computed for each of the 12 narrow spectral bands. Emissivities for the broadband and the window region were then constituted from the spectral band values by weighting them with Planck function energy distribution.

  11. Three years of greenhouse gas column-averaged dry air mole fractions retrieved from satellite – Part 1: Carbon dioxide

    Directory of Open Access Journals (Sweden)

    O. Schneising

    2008-07-01

    Full Text Available Carbon dioxide (CO2 and methane (CH4 are the two most important anthropogenic greenhouse gases. SCIAMACHY on ENVISAT is the first satellite instrument whose measurements are sensitive to concentration changes of the two gases at all altitude levels down to the Earth's surface where the source/sink signals are largest. We have processed three years (2003–2005 of SCIAMACHY near-infrared nadir measurements to simultaneously retrieve vertical columns of CO2 (from the 1.58 μm absorption band, CH4 (1.66 μm and oxygen (O2 A-band at 0.76 μm using the scientific retrieval algorithm WFM-DOAS. We show that the latest version of WFM-DOAS, version 1.0, which is used for this study, has been significantly improved with respect to its accuracy compared to the previous versions while essentially maintaining its high processing speed (~1 min per orbit, corresponding to ~6000 single measurements, and per gas on a standard PC. The greenhouse gas columns are converted to dry air column-averaged mole fractions, denoted XCO2 (in ppm and XCH4 (in ppb, by dividing the greenhouse gas columns by simultaneously retrieved dry air columns. For XCO2 dry air columns are obtained from the retrieved O2 columns. For XCH4 dry air columns are obtained from the retrieved CO2 columns because of better cancellation of light path related errors compared to using O2 columns retrieved from the spectrally distant O2 A-band. Here we focus on a discussion of the XCO2 data set. The XCH4 data set is discussed in a separate paper (Part 2. In order to assess the quality of the retrieved XCO2 we present comparisons with Fourier Transform Spectroscopy (FTS XCO2 measurements at two northern hemispheric mid-latitude ground stations. To assess the quality globally, we present detailed comparisons with

  12. On evaluation of ShARP passive rainfall retrievals over snow-covered land surfaces and coastal zones

    CERN Document Server

    Ebtehaj, Ardeshir M; Foufoula-Georgiou, Efi

    2015-01-01

    For precipitation retrievals over land, using satellite measurements in microwave bands, it is important to properly discriminate the weak rainfall signals from strong and highly variable background surface emission. Traditionally, land rainfall retrieval methods often rely on a weak signal of rainfall scattering on high-frequency channels (85 GHz) and make use of empirical thresholding and regression-based techniques. Due to the increased ground surface signal interference, precipitation retrieval over radiometrically complex land surfaces, especially over snow-covered lands, deserts and coastal areas, is of particular challenge for this class of retrieval techniques. This paper evaluates the results by the recently proposed Shrunken locally linear embedding Algorithm for Retrieval of Precipitation (ShARP), over a radiometrically complex terrain and coastal areas using the data provided by the Tropical Rainfall Measuring Mission (TRMM) satellite. To this end, the ShARP retrieval experiments are performed ove...

  13. Impact of rain-induced sea surface roughness variations on salinity retrieval from the Aquarius/SAC-D satellite

    Institute of Scientific and Technical Information of China (English)

    MA Wentao; YANG Xiaofeng; YU Yang; LIU Guihong; LI Ziwei; JING Cheng

    2015-01-01

    Rainfall has two significant effects on the sea surface, including salinity decreasing and surface becoming rougher, which have further influence on L-band sea surface emissivity. Investigations using the Aquarius and TRMM 3B42 matchup dataset indicate that the retrieved sea surface salinity (SSS) is underestimated by the present Aquarius algorithm compared to numerical model outputs, especially in cases of a high rain rate. For example, the bias between satellite-observed SSS and numerical model SSS is approximately 2 when the rain rate is 25 mm/h. The bias can be eliminated by accounting for rain-induced roughness, which is usually modeled by rain-generated ring-wave spectrum. The rain spectrum will be input into the Small Slope Approximation (SSA) model for the simulation of sea surface emissivity influenced by rain. The comparison with theoretical model indicated that the empirical model of rain spectrumis more suitable to be used in the simulation. Further, the coefficients of the rain spectrum are modified by fitting the simulations with the observations of the 2–year Aquarius and TRMM matchup dataset. The calculations confirm that the sea surface emissivity increases with the wind speed and rain rate. The increase induced by the rain rate is rapid in the case of low rain rate and low wind speed. Finally, a modified model of sea surface emissivity including the rain spectrum is proposed and validated by using the matchup dataset in May 2014. Compared with observations, the bias of the rain-induced sea surface emissivity simulated by the modified modelis approximately 1e–4, and the RMSE is slightly larger than 1e–3. With using more matchup data, thebias between model retrieved sea surface salinities and observationsmay be further corrected, and the RMSE may be reduced to less than 1 in the cases of low rain rate and low wind speed.

  14. Novel Algorithms for Retrieval of Hydrology and Ice Regimes of Middle-sized Inland Water Bodies from Satellite Altimetry

    Science.gov (United States)

    Troitskaya, Y. I.; Rybushkina, G. V.; Kuznetsova, A. M.; Baidakov, G. A.; Soustova, I.

    2014-12-01

    A novel method of regional adaptive re-tracking based on constructing a theoretical model describing the formation of telemetric waveforms by reflection from the piecewise constant model surface corresponding to the geography of the region is considered. The algorithm includes four consecutive steps: a) constructing a local piecewise model of a reflecting surface in the neighbourhood of the reservoir; b) solving a direct problem by calculating the reflected waveforms within the framework of the model; c) imposing restrictions and validity criteria for the algorithm based on waveform modelling; d) solving the inverse problem by retrieving a tracking point by the improved threshold algorithm. The results obtained on the basis of standard algorithm and method for adaptive re-tracking at Rybinsk , Gorky, Kuibyshev, Saratov and Volgograd reservoirs and middle-sized lakes of Russia: Chany, Segozero, Hanko, Onego, Beloye are compared to each other and to the field data of hydrological stations in reservoirs and lakes. The possibility of determination of significant wave height (SWH) in the lakes through a two-step adaptive retracking is investigated. Comparing results of retracting of SGDR data and ground measurements shows, that retrieving wave parameters in medium sized water bodies still meets difficulties. The direction of improvement of the existing algorithm is associated with comprehensive use of altimetry data, field studies and numerical modeling of high resolution. A simple method for timing of water freezing and ice break-up in lakes based on analysis of along-track dependencies of brightness temperatures at 18.7 and 34 GHz registered by microwave radiometer of altimetry satellite Jason-2. Comparison with in situ data of Russian Register of hydraulic structures on the example of reservoirs of the Volga River and the Don River confirms ability of the proposed method to determine quantitatively the freezing and break-up times for middle-sized inland water bodies.

  15. Retrieval algorithm for densities of mesospheric and lower thermospheric metal and ion species from satellite borne limb emission signals

    Science.gov (United States)

    Langowski, M.; Sinnhuber, M.; Aikin, A. C.; von Savigny, C.; Burrows, J. P.

    2013-05-01

    Meteoroids bombard the earth's atmosphere during its orbit around the sun, depositing a highly varying and significant amount of matter into the thermosphere and mesosphere. The strength of the material source needs to be characterized and its impact on atmospheric chemistry assessed. In this study an algorithm for the retrieval of metal and metal ion number densities for a two-dimensional (latitude, altitude) grid is described and explained. Dayglow emission spectra of the mesosphere and lower thermosphere are used, which are obtained by passive satellite remote sensing with the SCIAMACHY instrument on Envisat. The limb scans cover the tangent altitude range from 50 to 150 km. Metals and metal ions are strong emitters in this region and form sharply peaked layers with a FWHM of several 10 km in the mesosphere and lower thermosphere with peak altitudes between 90 to 110 km. The emission signal is first separated from the background signal, arising from Rayleigh and Raman scattering of solar radiation by air molecules. A forward radiative transfer model calculating the slant column density (SCD) from a given vertical distribution was developed. This non-linear model is inverted in an iterative procedure to yield the vertical profiles for the emitting species. Several constraints are applied to the solution, for numerical stability reasons and to get physically reasonable solutions. The algorithm is applied to SCIAMACHY limb-emission observations for the retrieval of Mg and Mg+ using emission signatures at 285.2 and 279.6/280.4 nm, respectively. Results are presented for these three lines as well as error estimations and sensitivity tests on different constraint strength and different separation approaches for the background signal.

  16. Constraint of anthropogenic NOx emissions in China from different sectors: a new methodology using multiple satellite retrievals

    Directory of Open Access Journals (Sweden)

    K. F. Boersma

    2009-09-01

    Full Text Available A new methodology is developed to constrain Chinese anthropogenic emissions of nitrogen oxides (NOx from four major sectors (industry, power plants, mobile and residential in July 2008. It combines tropospheric NO2 column retrievals from GOME-2 and OMI, taking advantage of their different passing time over China (9:30 a.m. local time versus 1:30 p.m., and explicitly accounts for diurnal variations in anthropogenic emissions of NOx as well as their tropospheric lifetime and column concentrations. The approach is based on the daytime variation of NOx (when its lifetime is relatively short alone; and potential errors in inverse modeling by neglecting horizontal transport are minimized. Separation of anthropogenic sectors relies on the estimated diurnal profiles and budget uncertainties. Our best top-down estimate suggests a national budget of 6.8 Tg N/yr (5.5 Tg N/yr for East China, close to the a priori bottom-up emission estimate from the INTEX-B mission. The top-down emissions are lower than the a priori near Beijing, in the northeastern provinces and along the east coast; yet they exceed the a priori over many inland regions. Systematic errors in satellite retrievals are estimated to lead to underestimation of top-down emissions by at most 17% (most likely 10%. Effects of other factors on the top-down estimate are typically less than 15%, including lightning, soil emissions, mixing in planetary boundary layer, anthropogenic emissions of carbon monoxide and volatile organic compounds, assumptions on emission diurnal variations, and uncertainties in the four sectors. The a posteriori emission budget is 5.7 Tg N/yr for East China.

  17. Patterns of Precipitation and Convection Occurrence over the Mediterranean Basin Derived from a Decade of Microwave Satellite Observations

    Directory of Open Access Journals (Sweden)

    Bahjat Alhammoud

    2014-05-01

    Full Text Available The Mediterranean region is characterized by its vulnerability to changes in the water cycle, with the impact of global warming on the water resources being one of the major concerns in social, economical and scientific ambits. Even if precipitation is the best-known term of the Mediterranean water budget, large uncertainties remain due to the lack of suitable offshore observational data. In this study, we use the data provided by the Advanced Microwave Sounding Unit-B (AMSU-B on board NOAA satellites to detect and analyze precipitating and convective events over the last decade at spatial resolution of 0.2° latitude × 0.2° longitude. AMSU-B observation shows that rain occurrence is widespread over the Mediterranean in wintertime while reduced in the eastern part of the basin in summer. Both precipitation and convection occurrences display a weak diurnal cycle over sea. In addition, convection occurrences, which are essentially located over land during summertime, shift to mostly over the sea during autumn with maxima in the Ionian sub-basin and the Adriatic Sea. Precipitation occurrence is also inferred over the sea from two other widely used climatological datasets, HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data and the European Centre for Medium-Range Weather Forecasts (ECMWF reanalysis interim (ERA-Interim. There is generally a rather fair agreement between these climatologies for describing the large-scale patterns such as the strong latitudinal gradient of rain and eastward rain signal propagation. Furthermore, the higher spatial resolution of AMSU-B measurements (16 km at nadir gives access to mesoscale details in the region (e.g., coastal areas. AMSU-B measurements show less rain occurrences than HOAPS during wintertime, thereby suggesting that some of the thresholds used in our method might be too stringent during this season. We also observed that convection occurrences in ERA-Interim are systematically

  18. Retrieval algorithm for CO2 and CH4 column abundances from short-wavelength infrared spectral observations by the Greenhouse Gases Observing Satellite

    Directory of Open Access Journals (Sweden)

    I. Morino

    2010-11-01

    Full Text Available The Greenhouse gases Observing SATellite (GOSAT was launched on 23 January 2009 to monitor the global distributions of carbon dioxide and methane from space. It has operated continuously since then. Here we describe a retrieval algorithm for column abundances of these gases from the short-wavelength infrared spectra obtained by the Thermal And Near infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS. The algorithm consists of three steps. First, cloud-free observational scenes are selected by several cloud-detection methods. Then, column abundances of carbon dioxide and methane are retrieved based on the optimal estimation method. Finally, the retrieval quality is examined to exclude low-quality and/or aerosol-contaminated results. Most of the retrieval random errors come from the instrumental noise. The interferences by auxiliary parameters retrieved simultaneously with gas abundances are small. The evaluated precisions of the retrieved column abundances for single observations are less than 1% in most cases. The interhemispherical differences and the temporal variation patterns of the retrieved column abundances agree well with the current state of knowledge.

  19. Retrieval algorithm for CO2 and CH4 column abundances from short-wavelength infrared spectral observations by the Greenhouse gases observing satellite

    Directory of Open Access Journals (Sweden)

    I. Morino

    2011-04-01

    Full Text Available The Greenhouse gases Observing SATellite (GOSAT was launched on 23 January 2009 to monitor the global distributions of carbon dioxide and methane from space. It has operated continuously since then. Here, we describe a retrieval algorithm for column abundances of these gases from the short-wavelength infrared spectra obtained by the Thermal And Near infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS. The algorithm consists of three steps. First, cloud-free observational scenes are selected by several cloud-detection methods. Then, column abundances of carbon dioxide and methane are retrieved based on the optimal estimation method. Finally, the retrieval quality is examined to exclude low-quality and/or aerosol-contaminated results. Most of the retrieval random errors come from instrumental noise. The interferences due to auxiliary parameters retrieved simultaneously with gas abundances are small. The evaluated precisions of the retrieved column abundances for single observations are less than 1% in most cases. The interhemispherical differences and temporal variation patterns of the retrieved column abundances show features similar to those of an atmospheric transport model.

  20. Modelling the angular effects on satellite retrieved LST at global scale using a land surface classification

    Science.gov (United States)

    Ermida, Sofia; DaCamara, Carlos C.; Trigo, Isabel F.; Pires, Ana C.; Ghent, Darren

    2017-04-01

    Land Surface Temperature (LST) is a key climatological variable and a diagnostic parameter of land surface conditions. Remote sensing constitutes the most effective method to observe LST over large areas and on a regular basis. Although LST estimation from remote sensing instruments operating in the Infrared (IR) is widely used and has been performed for nearly 3 decades, there is still a list of open issues. One of these is the LST dependence on viewing and illumination geometry. This effect introduces significant discrepancies among LST estimations from different sensors, overlapping in space and time, that are not related to uncertainties in the methodologies or input data used. Furthermore, these directional effects deviate LST products from an ideally defined LST, which should represent to the ensemble of directional radiometric temperature of all surface elements within the FOV. Angular effects on LST are here conveniently estimated by means of a kernel model of the surface thermal emission, which describes the angular dependence of LST as a function of viewing and illumination geometry. The model is calibrated using LST data as provided by a wide range of sensors to optimize spatial coverage, namely: 1) a LEO sensor - the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board NASA's TERRA and AQUA; and 2) 3 GEO sensors - the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board EUMETSAT's Meteosat Second Generation (MSG), the Japanese Meteorological Imager (JAMI) on-board the Japanese Meteorological Association (JMA) Multifunction Transport SATellite (MTSAT-2), and NASA's Geostationary Operational Environmental Satellites (GOES). As shown in our previous feasibility studies the sampling of illumination and view angles has a high impact on the obtained model parameters. This impact may be mitigated when the sampling size is increased by aggregating pixels with similar surface conditions. Here we propose a methodology where land surface is

  1. Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery

    Science.gov (United States)

    Beguet, Benoit; Guyon, Dominique; Boukir, Samia; Chehata, Nesrine

    2014-10-01

    The main goal of this study is to design a method to describe the structure of forest stands from Very High Resolution satellite imagery, relying on some typical variables such as crown diameter, tree height, trunk diameter, tree density and tree spacing. The emphasis is placed on the automatization of the process of identification of the most relevant image features for the forest structure retrieval task, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features. The main drawback of this well-known texture representation is the underlying parameters which are extremely difficult to set due to the spatial complexity of the forest structure. To tackle this major issue, an automated feature selection process is proposed which is based on statistical modeling, exploring a wide range of parameter values. It provides texture measures of diverse spatial parameters hence implicitly inducing a multi-scale texture analysis. A new feature selection technique, we called Random PRiF, is proposed. It relies on random sampling in feature space, carefully addresses the multicollinearity issue in multiple-linear regression while ensuring accurate prediction of forest variables. Our automated forest variable estimation scheme was tested on Quickbird and Pléiades panchromatic and multispectral images, acquired at different periods on the maritime pine stands of two sites in South-Western France. It outperforms two well-established variable subset selection techniques. It has been successfully applied to identify the best texture features in modeling the five considered forest structure variables. The RMSE of all predicted forest variables is improved by combining multispectral and panchromatic texture features, with various parameterizations, highlighting the potential of a multi-resolution approach for retrieving forest structure

  2. Can key vegetation parameters be retrieved at the large-scale using LAI satellite products and a generic modelling approach ?

    Science.gov (United States)

    Dewaele, Helene; Calvet, Jean-Christophe; Carrer, Dominique; Laanaia, Nabil

    2016-04-01

    In the context of climate change, the need to assess and predict the impact of droughts on vegetation and water resources increases. The generic approaches permitting the modelling of continental surfaces at large-scale has progressed in recent decades towards land surface models able to couple cycles of water, energy and carbon. A major source of uncertainty in these generic models is the maximum available water content of the soil (MaxAWC) usable by plants which is constrained by the rooting depth parameter and unobservable at the large-scale. In this study, vegetation products derived from the SPOT/VEGETATION satellite data available since 1999 are used to optimize the model rooting depth over rainfed croplands and permanent grasslands at 1 km x 1 km resolution. The inter-annual variability of the Leaf Area Index (LAI) is simulated over France using the Interactions between Soil, Biosphere and Atmosphere, CO2-reactive (ISBA-A-gs) generic land surface model and a two-layer force-restore (FR-2L) soil profile scheme. The leaf nitrogen concentration directly impacts the modelled value of the maximum annual LAI. In a first step this parameter is estimated for the last 15 years by using an iterative procedure that matches the maximum values of LAI modelled by ISBA-A-gs to the highest satellite-derived LAI values. The Root Mean Square Error (RMSE) is used as a cost function to be minimized. In a second step, the model rooting depth is optimized in order to reproduce the inter-annual variability resulting from the drought impact on the vegetation. The evaluation of the retrieved soil rooting depth is achieved using the French agricultural statistics of Agreste. Retrieved leaf nitrogen concentrations are compared with values from previous studies. The preliminary results show a good potential of this approach to estimate these two vegetation parameters (leaf nitrogen concentration, MaxAWC) at the large-scale over grassland areas. Besides, a marked impact of the

  3. Retrieval of short scale geophysical signals and improved coastal data from SAR satellite altimetry

    Science.gov (United States)

    Fenoglio-Marc, Luciana; Buchhaupt, Christopher; Dinardo, Salvatore; Scharroo, Remko; Benveniste, Jerome; Becker, Matthias

    2016-04-01

    The Delay Doppler/Synthetic Aperture Radar (SAR) altimeter offers a new quality of observational data in comparison to the pulse-limited low resolution mode (LRM) data collected over the past twenty years. Due to the reduced noise in the measurements an improved retrieval of the geophysical signal is expected in SAR. The goal of this study is to characterize these improvements both in open ocean and coastal zone using standard Level 2 and Level 1 data reprocessed with improved algorithms. We have carried out, from CryoSat-2 Level 1a Full Bit Rate (L1a FBR) data, a Delay-Doppler processing and waveform retracking tailored specifically for coastal zone by applying Hamming Window and Zero-Padding, using an extended vertical swath window in order to minimize tracker errors and a dedicated SAMOSA-based coastal retracker (named SAMOSA+). SAMOSA+ accepts mean square slope as free parameter and the epoch's first guess fitting value is decided according to the peak in correlation between 20 consecutive waveforms (in order to mitigate land off-ranging effect). Those products can be extracted from ESA-ESRIN GPOD service (named SARvatore). In order to quantify the improvement with respect to pulse-limited altimetry, we build 20 Hz PLRM (pseudo-LRM) data from CryoSat-1 L1a FBR and retrack them with numerical convolutional Brown-based retracker. Hence, here, PLRM is used as a proxy for real pulse-limited products (LRM), since there is no direct comparison of SAR and LRM possible otherwise. The PLRM data are built and retracked by Technical University of Darmstadt (TUDa). In the open ocean the study consists on the retrieval of short scale geophysical, as the swell signals. The selected areas are the CryoSat-2 Pacific and Atlantic Boxes in which it operated in SAR mode. In the coastal zone of the North Sea the study concentrates on the reduction of land and ships contamination by dedicated procedures including improved retracking. Effects of different options and retracking

  4. Optimizing Satellite-Based Precipitation Estimation for Nowcasting of Rainfall and Flash Flood Events over the South African Domain

    OpenAIRE

    Estelle de Coning

    2013-01-01

    The South African Weather Service is mandated to issue warnings of hazardous weather events, including those related to heavy precipitation, in order to safeguard life and property. Flooding and flash flood events are common in South Africa. Frequent updates and real-time availability of precipitation data are crucial to support hydrometeorological warning services. Satellite rainfall estimation provides a very important data source for flash flood guidance systems as well as nowcasting of pr...

  5. Atmospheric inertia-gravity waves retrieved from level-2 data of the satellite microwave limb sounder Aura/MLS

    Science.gov (United States)

    Hocke, Klemens; Lainer, Martin; Moreira, Lorena; Hagen, Jonas; Fernandez Vidal, Susana; Schranz, Franziska

    2016-09-01

    The temperature profiles of the satellite experiment Aura/MLS are horizontally spaced by 1.5° or 165 km along the satellite orbit. These level-2 data contain valuable information about horizontal fluctuations in temperature, which are mainly induced by inertia-gravity waves. Wave periods of 2-12 h, horizontal wavelengths of 200-1500 km, and vertical wavelengths of 6-30 km efficiently contribute to the standard deviation of the horizontal temperature fluctuations. The study retrieves and discusses the global distributions of inertia-gravity waves in the stratosphere and mesosphere during July 2015 and January 2016. We find many patterns that were previously present in data of TIMED/SABER, Aura/HIRDLS, and ECMWF analysis. However, it seems that Aura/MLS achieves a higher vertical resolution in the gravity wave maps since the maps are derived from the analysis of horizontal fluctuations along the orbit of the sounding volume. The zonal mean of the inertia-gravity wave distribution shows vertical modulations with scales of 10-20 km. Enhanced wave amplitudes occur in regions of increased zonal wind or in the vicinity of strong wind gradients. Further, we find a banana-like shape of enhanced inertia-gravity waves above the Andes in the winter mesosphere. We find areas of enhanced inertia-gravity wave activity above tropical deep convection zones at 100 hPa (z ˜ 13 km). Finally, we study the temporal evolution of inertia-gravity wave activity at 100 hPa in the African longitude sector from December 2015 to February 2016.

  6. 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.

  7. Evaluating the performance of real-time streamflow forecasting using multi-satellite precipitation products in the Upper Zambezi, Africa

    Science.gov (United States)

    Demaria, E. M.; Valdes, J. B.; Wi, S.; Serrat-Capdevila, A.; Valdés-Pineda, R.; Durcik, M.

    2016-12-01

    In under-instrumented basins around the world, accurate and timely forecasts of river streamflows have the potential of assisting water and natural resource managers in their management decisions. The Upper Zambezi river basin is the largest basin in southern Africa and its water resources are critical to sustainable economic growth and poverty reduction in eight riparian countries. We present a real-time streamflow forecast for the basin using a multi-model-multi-satellite approach that allows accounting for model and input uncertainties. Three distributed hydrologic models with different levels of complexity: VIC, HYMOD_DS, and HBV_DS are setup at a daily time step and a 0.25 degree spatial resolution for the basin. The hydrologic models are calibrated against daily observed streamflows at the Katima-Mulilo station using a Genetic Algorithm. Three real-time satellite products: Climate Prediction Center's morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Tropical Rainfall Measuring Mission (TRMM-3B42RT) are bias-corrected with daily CHIRPS estimates. Uncertainty bounds for predicted flows are estimated with the Inverse Variance Weighting method. Because concentration times in the basin range from a few days to more than a week, we include the use of precipitation forecasts from the Global Forecasting System (GFS) to predict daily streamflows in the basin with a 10-days lead time. The skill of GFS-predicted streamflows is evaluated and the usefulness of the forecasts for short term water allocations is presented.

  8. Long-term analysis of aerosol optical depth over Northeast Asia using a satellite-based measurement: MI Yonsei Aerosol Retrieval Algorithm (YAER)

    Science.gov (United States)

    Kim, Mijin; Kim, Jhoon; Yoon, Jongmin; Chung, Chu-Yong; Chung, Sung-Rae

    2017-04-01

    In 2010, the Korean geostationary earth orbit (GEO) satellite, the Communication, Ocean, and Meteorological Satellite (COMS), was launched including the Meteorological Imager (MI). The MI measures atmospheric condition over Northeast Asia (NEA) using a single visible channel centered at 0.675 μm and four IR channels at 3.75, 6.75, 10.8, 12.0 μm. The visible measurement can also be utilized for the retrieval of aerosol optical properties (AOPs). Since the GEO satellite measurement has an advantage for continuous monitoring of AOPs, we can analyze the spatiotemporal variation of the aerosol using the MI observations over NEA. Therefore, we developed an algorithm to retrieve aerosol optical depth (AOD) using the visible observation of MI, and named as MI Yonsei Aerosol Retrieval Algorithm (YAER). In this study, we investigated the accuracy of MI YAER AOD by comparing the values with the long-term products of AERONET sun-photometer. The result showed that the MI AODs were significantly overestimated than the AERONET values over bright surface in low AOD case. Because the MI visible channel centered at red color range, contribution of aerosol signal to the measured reflectance is relatively lower than the surface contribution. Therefore, the AOD error in low AOD case over bright surface can be a fundamental limitation of the algorithm. Meanwhile, an assumption of background aerosol optical depth (BAOD) could result in the retrieval uncertainty, also. To estimate the surface reflectance by considering polluted air condition over the NEA, we estimated the BAOD from the MODIS dark target (DT) aerosol products by pixel. The satellite-based AOD retrieval, however, largely depends on the accuracy of the surface reflectance estimation especially in low AOD case, and thus, the BAOD could include the uncertainty in surface reflectance estimation of the satellite-based retrieval. Therefore, we re-estimated the BAOD using the ground-based sun-photometer measurement, and

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

    Science.gov (United States)

    Liu, Zhong; Heo, Gil

    2015-01-01

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

  10. 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.

    rainfall. The next most important error, due to fair weather bias, arises due to the lack of precipitation measurements caused by the lows, depressions and cyclones, which most of the ships try to avoid. This problem is especially true in the case... of the Bay of Bengal, which is frequented by lows, depressions and cyclones throughout the year. Major drawbacks to studies of the rainfall over a particular area or region are the coverage of the instruments and their accuracy in measuring the areal...

  11. Photosynthetically active radiation retrieval based on HJ-1A/B satellite data

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Photosynthetically active radiation(PAR) is essential for plant photosynthesis and carbon cycle,and is also important for meteorological and environmental monitoring.To advance China’s disaster and environmental monitoring capabilities,the HJ-1A/B satellites have been placed in Earth orbit.One of their environmental monitoring objectives is the study of PAR.We simulated direct solar,scattered and environment radiation between 400 and 700 nm under different atmospheric parameters(solar zenith angle,atmospheric water vapor,atmospheric ozone,aerosol optical thickness,surface elevation and surface albedo),and then established a look-up table between these input parameters and PAR.Based on the look-up table,we used HJ-1A/B aerosol and surface albedo outputs to derive the corresponding PAR.Validation of inversed instantaneous and observed PAR values using HJ-1 Heihe experimental data had a root mean square error of 25.2 W m-2,with a relative error of 5.9%.The root mean square error for accumulated daily PAR and observed values was 0.49 MJ m-2,with a relative error of 3.5%.Our approach improved significantly the computational efficiency,compared with using directly radiation transfer equations.We also studied the sensitivity of various input parameters to photosynthetically active radiation,and found that solar zenith angle and atmospheric aerosols were sensitive PAR parameters.Surface albedo had some effect on PAR,but water vapor and ozone had minimal impact on PAR.

  12. Urban aerosol properties, their radiative effects and the verification of different satellite retrievals of urban aerosol pollution

    Science.gov (United States)

    Chubarova, Nataly; Sviridenkov, Mikhail; Kopeikin, Vladimir; Emilenko, Alexander; Verichev, Konstantin; Skorokhod, Andrei; Semutnikova, Evgenia

    2013-04-01

    The effects of urban pollution on different aerosol properties and their year-to-year-changes in various atmospheric conditions were studied according to long-term simultaneous measurements by the collocated AERONET CIMEL sun/sky photometers in Moscow (large megacity) and at Zvenigorod (nearby clean area) for 2006-2012 year period. Additional measurements of PM10 and PM2.5, as well as soot content observations were used for evaluating the effects of local urban sources and their influence on columnar aerosol properties (single scattering albedo, aerosol optical thickness, etc.) and, hence, on radiative properties of aerosol. We discuss the results of the comparisons between RT modeling and high quality ground-based radiative measurements, which provide validation of the obtained urban radiative effects for different aerosols in clear-sky conditions. Special attention was paid to testing the retrievals of several aerosol parameters (AOT, single scattering albedo, Angstrom exponent, etc) over the urban area and the detection of the urban aerosol pollution by different satellite instruments (MISR, MODIS, SEAWIFS, OMI) against the data of collocated AERONET CIMEL sun/sky photometers in different atmospheric conditions over snow and snow-free surfaces.

  13. 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.

  14. Disentangling the Relationships between Net Primary Production and Precipitation in Southern Africa Savannas Using Satellite Observations from 1982 to 2010

    Directory of Open Access Journals (Sweden)

    Jane Southworth

    2013-08-01

    Full Text Available To obtain a better understanding of the variability in net primary production (NPP in savannas is important for the study of the global carbon cycle and the management of this particular ecosystem. Using satellite and precipitation data sets, we investigated the variations in NPP in southern African savannas from 1982 to 2010, and disentangled the relationships between NPP and precipitation by land cover classes and mean annual precipitation (MAP gradients. Specifically, we evaluate the utility of the third generation Global Inventory Monitoring and Modeling System (GIMMS3g normalized difference vegetation index (NDVI dataset, in comparison with Moderate-resolution Imaging Spectroradiometer (MODIS derived NPP products, and find strong relationships between the overlapping data periods (2000–2010, such that we can apply our model to derive NPP estimates to the full 29-year NDVI time-series. Generally, the northern portion of the study area is characterized by high NPP and low variability, whereas the southern portion is characteristic of low NPP and high variability. During the period 1982 through 2010, NPP has reduced at a rate of −2.13 g∙C∙m−2∙yr−1 (p < 0.1, corresponding to a decrease of 6.7% over 29 years, and about half of bush and grassland savanna has experienced a decrease in NPP. There is a significant positive relationship between mean annual NPP and MAP in bush and grassland savannas, but no significant relationship is observed in tree savannas. The relationship between mean annual NPP and MAP varies with increases in MAP, characterized as a linear relationship that breaks down when MAP exceeding around 850–900 mm.

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

    Science.gov (United States)

    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 resolution, specifically designed for hydrological modeling. The design philosophy of MSWEP was to optimally merge the highest quality P data sources available as a function of timescale and location. The long-term mean of MSWEP was based on the CHPclim dataset but replaced with more accurate regional datasets where available. A correction for gauge under-catch and orographic effects was introduced by inferring catchment-average P from streamflow (Q) observations at 13 762 stations across the globe. The temporal variability of MSWEP was determined by weighted averaging of P anomalies from seven datasets; two based solely on interpolation of gauge observations (CPC Unified and GPCC), three on satellite remote sensing (CMORPH, GSMaP-MVK, and TMPA 3B42RT), and two on atmospheric model reanalysis (ERA-Interim and JRA-55). For each grid cell, the weight assigned to the gauge-based estimates was calculated from the gauge network density, while the weights assigned to the satellite- and reanalysis-based estimates were calculated from their comparative performance at the surrounding gauges. The quality of MSWEP was compared against four state-of-the-art gauge-adjusted P datasets (WFDEI-CRU, GPCP-1DD, TMPA 3B42, and CPC Unified) using independent P data from 125 FLUXNET tower stations around the globe. MSWEP obtained the highest daily correlation coefficient (R) among the five P datasets for 60.0 % of the stations and a median R of 0.67 vs. 0.44-0.59 for the other datasets. We further evaluated the performance of MSWEP using hydrological modeling for 9011 catchments (http://www.gloh2o.org.

  16. Precipitation Ground Validation over the Oceans

    Science.gov (United States)

    Klepp, C.; Bakan, S.

    2012-04-01

    State-of-the-art satellite derived and reanalysis based precipitation climatologies show remarkably large differences in detection, amount, variability and temporal behavior of precipitation over the oceans. The uncertainties are largest for light precipitation within the ITCZ and for cold season high-latitude precipitation including snowfall. Our HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite data, www.hoaps.org) precipitation retrieval exhibits fairly high accuracy in such regions compared to our ground validation data. However, the statistical basis for a conclusive validation has to be significantly improved with comprehensive ground validation efforts. However, existing in-situ instruments are not designed for precipitation measurements under high wind speeds on moving ships. To largely improve the ground validation data basis of precipitation over the oceans, especially for snow, the systematic data collection effort of the Initiative Pro Klima funded project at the KlimaCampus Hamburg uses automated shipboard optical disdrometers, called ODM470 that are capable of measuring liquid and solid precipitation on moving ships with high accuracy. The main goal of this project is to constrain the precipitation retrievals for HOAPS and the new Global Precipitation Measurement (GPM) satellite constellation. Currently, three instruments are long-term mounted on the German research icebreaker R/V Polarstern (Alfred Wegner Institut) since June 2010, on R/V Akademik Ioffe (P.P.Shirshov Institute of Oceanology, RAS, Moscow, Russia) since September 2010 and on R/V Maria S. Merian (Brise Research, University of Hamburg) since December 2011. Three more instruments will follow shortly on further ships. The core regions for these long-term precipitation measurements comprise the Arctic Ocean, the Nordic Seas, the Labrador Sea, the subtropical Atlantic trade wind regions, the Caribbean, the ITCZ, and the Southern Oceans as far south to Antarctica. This

  17. GMTR: two-dimensional geo-fit multitarget retrieval model for michelson interferometer for passive atmospheric sounding/environmental satellite observations.

    Science.gov (United States)

    Carlotti, Massimo; Brizzi, Gabriele; Papandrea, Enzo; Prevedelli, Marco; Ridolfi, Marco; Dinelli, Bianca Maria; Magnani, Luca

    2006-02-01

    We present a new retrieval model designed to analyze the observations of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), which is on board the ENVironmental SATellite (ENVISAT). The new geo-fit multitarget retrieval model (GMTR) implements the geo-fit two-dimensional inversion for the simultaneous retrieval of several targets including a set of atmospheric constituents that are not considered by the ground processor of the MIPAS experiment. We describe the innovative solutions adopted in the inversion algorithm and the main functionalities of the corresponding computer code. The performance of GMTR is compared with that of the MIPAS ground processor in terms of accuracy of the retrieval products. Furthermore, we show the capability of GMTR to resolve the horizontal structures of the atmosphere. The new retrieval model is implemented in an optimized computer code that is distributed by the European Space Agency as "open source" in a package that includes a full set of auxiliary data for the retrieval of 28 atmospheric targets.

  18. Satellite Retrievals of Karenia brevis Harmful Algal Blooms in the West Florida Shelf Using Neural Networks and Comparisons with Other Techniques

    Directory of Open Access Journals (Sweden)

    Ahmed El-habashi

    2016-05-01

    Full Text Available We describe the application of a Neural Network (NN previously developed by us, to the detection and tracking, of Karenia brevis Harmful Algal Blooms (KB HABs that plague the coasts of the West Florida Shelf (WFS using Visible Infrared Imaging Radiometer Suite (VIIRS satellite observations. Previous approaches for the detection of KB HABs in the WFS primarily used observations from the Moderate Resolution Imaging Spectroradiometer Aqua (MODIS-A satellite. They depended on the remote sensing reflectance signal at the 678 nm chlorophyll fluorescence band (Rrs678 needed for both the normalized fluorescence height (nFLH and Red Band Difference algorithms (RBD currently used. VIIRS which has replaced MODIS-A, unfortunately does not have a 678 nm fluorescence channel so we customized the NN approach to retrieve phytoplankton absorption at 443 nm (aph443 using only Rrs measurements from existing VIIRS channels at 486, 551 and 671 nm. The aph443 values in these retrieved VIIRS images, can in turn be correlated to chlorophyll-a concentrations [Chla] and KB cell counts. To retrieve KB values, the VIIRS NN retrieved aph443 images are filtered by applying limiting constraints, defined by (i low backscatter at Rrs 551 nm and (ii a minimum aph443 value known to be associated with KB HABs in the WFS. The resulting filtered residual images, are then used to delineate and quantify the existing KB HABs. Comparisons with KB HABs satellite retrievals obtained using other techniques, including nFLH, as well as with in situ measurements reported over a four year period, confirm the viability of the NN technique, when combined with the filtering constraints devised, for effective detection of KB HABs.

  19. Inter-comparison of model-simulated and satellite-retrieved componential aerosol optical depths in China

    Science.gov (United States)

    Li, Shenshen; Yu, Chao; Chen, Liangfu; Tao, Jinhua; Letu, Husi; Ge, Wei; Si, Yidan; Liu, Yang

    2016-09-01

    China's large aerosol emissions have major impacts on global climate change as well as regional air pollution and its associated disease burdens. A detailed understanding of the spatiotemporal patterns of aerosol components is necessary for the calculation of aerosol radiative forcing and the development of effective emission control policy. Model-simulated and satellite-retrieved aerosol components can support climate change research, PM2.5 source appointment and epidemiological studies. This study evaluated the total and componential aerosol optical depth (AOD) from the GEOS-Chem model (GC) and the Global Ozone Chemistry Aerosol Radiation and Transport model (GOCART), and the Multiangle Imaging Spectroradiometer (MISR) from 2006 to 2009 in China. Linear regression analysis between the GC and AErosol RObotic NETwork (AERONET) in China yielded similar correlation coefficients (0.6 daily, 0.71 monthly) but lower slopes (0.41 daily, 0.58 monthly) compared with those in the U.S. This difference was attributed to GC's underestimation of water-soluble AOD (WAOD) west of the Heihe-Tengchong Line, the dust AOD (DAOD) in the fall and winter, and the soot AOD (SAOD) throughout the year and throughout the country. GOCART exhibits the strongest dust estimation capability among all datasets. However, the GOCART soot distribution in the Northeast and Southeast has significant errors, and its WAOD in the polluted North China Plain (NCP) and the South is underestimated. MISR significantly overestimates the water-soluble aerosol levels in the West, and does not capture the high dust loadings in all seasons and regions, and the SAOD in the NCP. These discrepancies can mainly be attributed to the uncertainties in the emission inventories of both models, the poor performance of GC under China's high aerosol loading conditions, the omission of certain aerosol tracers in GOCART, and the tendency of MISR to misidentify dust and non-dust mixtures.

  20. Sensitivity of Satellite-Based Skin Temperature to Different Surface Emissivity and NWP Reanalysis Sources Demonstrated Using a Single-Channel, Viewing-Angle-Corrected Retrieval Algorithm

    Science.gov (United States)

    Scarino, B. R.; Minnis, P.; Yost, C. R.; Chee, T.; Palikonda, R.

    2015-12-01

    Single-channel algorithms for satellite thermal-infrared- (TIR-) derived land and sea surface skin temperature (LST and SST) are advantageous in that they can be easily applied to a variety of satellite sensors. They can also accommodate decade-spanning instrument series, particularly for periods when split-window capabilities are not available. However, the benefit of one unified retrieval methodology for all sensors comes at the cost of critical sensitivity to surface emissivity (ɛs) and atmospheric transmittance estimation. It has been demonstrated that as little as 0.01 variance in ɛs can amount to more than a 0.5-K adjustment in retrieved LST values. Atmospheric transmittance requires calculations that employ vertical profiles of temperature and humidity from numerical weather prediction (NWP) models. Selection of a given NWP model can significantly affect LST and SST agreement relative to their respective validation sources. Thus, it is necessary to understand the accuracies of the retrievals for various NWP models to ensure the best LST/SST retrievals. The sensitivities of the single-channel retrievals to surface emittance and NWP profiles are investigated using NASA Langley historic land and ocean clear-sky skin temperature (Ts) values derived from high-resolution 11-μm TIR brightness temperature measured from geostationary satellites (GEOSat) and Advanced Very High Resolution Radiometers (AVHRR). It is shown that mean GEOSat-derived, anisotropy-corrected LST can vary by up to ±0.8 K depending on whether CERES or MODIS ɛs sources are used. Furthermore, the use of either NOAA Global Forecast System (GFS) or NASA Goddard Modern-Era Retrospective Analysis for Research and Applications (MERRA) for the radiative transfer model initial atmospheric state can account for more than 0.5-K variation in mean Ts. The results are compared to measurements from the Surface Radiation Budget Network (SURFRAD), an Atmospheric Radiation Measurement (ARM) Program ground

  1. A Numerical Testbed for Remote Sensing of Aerosols, and its Demonstration for Evaluating Retrieval Synergy from a Geostationary Satellite Constellation of GEO-CAPE and GOES-R

    Science.gov (United States)

    Wang, Jun; Xu, Xiaoguang; Ding, Shouguo; Zeng, Jing; Spurr, Robert; Liu, Xiong; Chance, Kelly; Mishchenko, Michael I.

    2014-01-01

    We present a numerical testbed for remote sensing of aerosols, together with a demonstration for evaluating retrieval synergy from a geostationary satellite constellation. The testbed combines inverse (optimal-estimation) software with a forward model containing linearized code for computing particle scattering (for both spherical and non-spherical particles), a kernel-based (land and ocean) surface bi-directional reflectance facility, and a linearized radiative transfer model for polarized radiance. Calculation of gas absorption spectra uses the HITRAN (HIgh-resolution TRANsmission molecular absorption) database of spectroscopic line parameters and other trace species cross-sections. The outputs of the testbed include not only the Stokes 4-vector elements and their sensitivities (Jacobians) with respect to the aerosol single scattering and physical parameters (such as size and shape parameters, refractive index, and plume height), but also DFS (Degree of Freedom for Signal) values for retrieval of these parameters. This testbed can be used as a tool to provide an objective assessment of aerosol information content that can be retrieved for any constellation of (planned or real) satellite sensors and for any combination of algorithm design factors (in terms of wavelengths, viewing angles, radiance and/or polarization to be measured or used). We summarize the components of the testbed, including the derivation and validation of analytical formulae for Jacobian calculations. Benchmark calculations from the forward model are documented. In the context of NASA's Decadal Survey Mission GEOCAPE (GEOstationary Coastal and Air Pollution Events), we demonstrate the use of the testbed to conduct a feasibility study of using polarization measurements in and around the O2 A band for the retrieval of aerosol height information from space, as well as an to assess potential improvement in the retrieval of aerosol fine and coarse mode aerosol optical depth (AOD) through the

  2. Improvement of Aerosol Optical Depth Retrieval over Hong Kong from a Geostationary Meteorological Satellite Using Critical Reflectance with Background Optical Depth Correction

    Science.gov (United States)

    Kim, Mijin; Kim, Jhoon; Wong, Man Sing; Yoon, Jongmin; Lee, Jaehwa; Wu, Dong L.; Chan, P.W.; Nichol, Janet E.; Chung, Chu-Yong; Ou, Mi-Lim

    2014-01-01

    Despite continuous efforts to retrieve aerosol optical depth (AOD) using a conventional 5-channelmeteorological imager in geostationary orbit, the accuracy in urban areas has been poorer than other areas primarily due to complex urban surface properties and mixed aerosol types from different emission sources. The two largest error sources in aerosol retrieval have been aerosol type selection and surface reflectance. In selecting the aerosol type from a single visible channel, the season-dependent aerosol optical properties were adopted from longterm measurements of Aerosol Robotic Network (AERONET) sun-photometers. With the aerosol optical properties obtained fromthe AERONET inversion data, look-up tableswere calculated by using a radiative transfer code: the Second Simulation of the Satellite Signal in the Solar Spectrum (6S). Surface reflectance was estimated using the clear sky composite method, awidely used technique for geostationary retrievals. Over East Asia, the AOD retrieved from the Meteorological Imager showed good agreement, although the values were affected by cloud contamination errors. However, the conventional retrieval of the AOD over Hong Kong was largely underestimated due to the lack of information on the aerosol type and surface properties. To detect spatial and temporal variation of aerosol type over the area, the critical reflectance method, a technique to retrieve single scattering albedo (SSA), was applied. Additionally, the background aerosol effect was corrected to improve the accuracy of the surface reflectance over Hong Kong. The AOD retrieved froma modified algorithmwas compared to the collocated data measured by AERONET in Hong Kong. The comparison showed that the new aerosol type selection using the critical reflectance and the corrected surface reflectance significantly improved the accuracy of AODs in Hong Kong areas,with a correlation coefficient increase from0.65 to 0.76 and a regression line change from tMI [basic algorithm] = 0

  3. Influence of aerosols and surface reflectance on satellite NO2 retrieval: seasonal and spatial characteristics and implications for NOx emission constraints

    Science.gov (United States)

    Lin, J.-T.; Liu, M.-Y.; Xin, J.-Y.; Boersma, K. F.; Spurr, R.; Martin, R.; Zhang, Q.

    2015-10-01

    Satellite retrievals of vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) normally do not explicitly account for aerosol optical effects and surface reflectance anisotropy that vary with space and time. Here, we conduct an improved retrieval of NO2 VCDs over China, called the POMINO algorithm, based on measurements from the Ozone Monitoring Instrument (OMI), and we test the importance of a number of aerosol and surface reflectance treatments in this algorithm. POMINO uses a parallelized LIDORT-driven AMFv6 package to derive tropospheric air mass factors via pixel-specific radiative transfer calculations with no look-up tables, taking slant column densities from DOMINO v2. Prerequisite cloud optical properties are derived from a dedicated cloud retrieval process that is fully consistent with the main NO2 retrieval. Aerosol optical properties are taken from GEOS-Chem simulations constrained by MODIS aerosol optical depth (AOD) data. MODIS bi-directional reflectance distribution function (BRDF) data are used for surface reflectance over land. For the present analysis, POMINO level-2 data for 2012 are aggregated into monthly means on a 0.25° long. × 0.25° lat. grid. POMINO-retrieved annual mean NO2 VCDs vary from 15-25 × 1015 cm-2 over the polluted North China Plain (NCP) to below 1015 cm-2 over much of western China. Using POMINO to infer Chinese emissions of nitrogen oxides leads to annual anthropogenic emissions of 9.05 TgN yr-1, an increase from 2006 (Lin, 2012) by about 19 %. Replacing the MODIS BRDF data with the OMLER v1 monthly climatological albedo data affects NO2 VCDs by up to 40 % for certain locations and seasons. The effect on constrained NOx emissions is small. Excluding aerosol information from the retrieval process (this is the traditional "implicit" treatment) enhances annual mean NO2 VCDs by 15-40 % over much of eastern China. Seasonally, NO2 VCDs are reduced by 10-20 % over parts of the NCP in spring and over northern China

  4. Overview of the relativistic electron precipitations (REP) observed on LEO satellites and ISS by Bulgarian build instruments

    Science.gov (United States)

    Dachev, Tsvetan

    Relativistic electron precipitation (REP) are observed by the R3D B2/B3 and RD3-B3 instruments during the flights of the Foton M2/M3 and “BION-M” № 1 satellite in 2005, 2007 and 2013, and by the R3DE/R instruments at the EXPOSE-E facility of the European Columbus module and at the EXPOSE-R facility of the Russian Zvezda module of the International Space Station (ISS) in the period from February 2008 till August 2010. The obtained dose rates strongly depend by the external and internal shielding of the detectors in the instruments. The highest dose rate reaching more than 20 mGy h (-1) was observed outside the ISS Zvezda module during the REP in April 2010 being the second largest in GOES history with a >2 MeV electron fluence event. REP doses behind relatively thick shielding are too small but may play considerable role during extra vehicular activity (EVA) when the cosmonauts/astronauts body is shielded only by the space suit.

  5. 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.

  6. Operational tools and applications of EO satellite data to retrieve surface fluxes in semi-arid countries

    Science.gov (United States)

    Tanguy, Maliko

    The objective of the thesis is to develop and evaluate useful tools and applications of Earth Observation (EO) satellite data to estimate surface fluxes in semi-arid countries. In a first part (Chapter 4), we assess the performance of a new parameterisation scheme of ground heat flux (G) to be used in remote sensing (RS) evapotranspiration (ET) estimation methods. The G-parameterisation optimized with AMMA flux data performs well and improves the sensible heat flux (H) and ET retrieved by means of the triangle method (Jiang & Islam, 2001). In a second part (Chapter 5), the triangle method is compared with ET estimated by means of a land surface model (JULES). An attempt is made to calibrate JULES using the triangle method through Monte Carlo simulations, but the two methods supply rather different results, indicating that further intercomparison tasks should be carried out to assess the performance of RS-based algorithms and land surface models in estimating the components of the land surface energy balance. Chapter 6 presents a set of operational examples for retrieving surface fluxes using RS data. The first example is the study of temporal evolution of ET-maps in Western Africa under monsoonal influence. In a second example, we apply the new scheme proposed in Chapter 4 to retrieve and analyse the long term evolution (2000-2009) of the surface energy balance components, G, H and ET at several sites of the Segura Basin (S-E Spain) using MODIS-Terra data (land surface temperature and NDVI). Temporal and spatial distribution of evapotranspiration reveals different controls on ET. (Chapter 6). In the last example, MODIS-Aqua Sea Surface Temperature (SST) is used to validate a mathematical model to retrieve surface fluxes in a Mediterranean coastal lagoon (Mar Menor, S-E Spain). El objetivo de esta tesis es de desarrollar y evaluar herramientas y aplicaciones de la teledetección para estimar flujos de superficie en zonas semiáridas. En una primera parte (Cap

  7. A Nano-satellite Mission to Study Charged Particle Precipitation from the Van Allen Radiation Belts caused due to Seismo-Electromagnetic Emissions

    CERN Document Server

    Sivadas, Nithin; Kannapan, Deepti; Yalamarthy, Ananth Saran; Dhiman, Ankit; Bhagoji, Arjun; Shankar, Athreya; Prasad, Nitin; Ramachandran, Harishankar; Koilpillai, R David

    2014-01-01

    In the past decade, several attempts have been made to study the effects of seismo-electromagnetic emissions - an earthquake precursor, on the ionosphere and the radiation belts. The IIT Madras nano-satellite (IITMSAT) mission is designed to make sensitive measurements of charged particle fluxes in a Low Earth Orbit to study the nature of charged particle precipitation from the Van Allen radiation belts caused due to such emissions. With the Space-based Proton Electron Energy Detector on-board a single nano-satellite, the mission will attempt to gather statistically significant data to verify possible correlations with seismo-electromagnetic emissions before major earthquakes.

  8. A statistical inference approach for the retrieval of the atmospheric ozone profile from simulated satellite measurements of solar backscattered ultraviolet radiation

    Science.gov (United States)

    Bonavito, N. L.; Gordon, C. L.; Inguva, R.; Serafino, G. N.; Barnes, R. A.

    1994-01-01

    NASA's Mission to Planet Earth (MTPE) will address important interdisciplinary and environmental issues such as global warming, ozone depletion, deforestation, acid rain, and the like with its long term satellite observations of the Earth and with its comprehensive Data and Information System. Extensive sets of satellite observations supporting MTPE will be provided by the Earth Observing System (EOS), while more specific process related observations will be provided by smaller Earth Probes. MTPE will use data from ground and airborne scientific investigations to supplement and validate the global observations obtained from satellite imagery, while the EOS satellites will support interdisciplinary research and model development. This is important for understanding the processes that control the global environment and for improving the prediction of events. In this paper we illustrate the potential for powerful artificial intelligence (AI) techniques when used in the analysis of the formidable problems that exist in the NASA Earth Science programs and of those to be encountered in the future MTPE and EOS programs. These techniques, based on the logical and probabilistic reasoning aspects of plausible inference, strongly emphasize the synergetic relation between data and information. As such, they are ideally suited for the analysis of the massive data streams to be provided by both MTPE and EOS. To demonstrate this, we address both the satellite imagery and model enhancement issues for the problem of ozone profile retrieval through a method based on plausible scientific inferencing. Since in the retrieval problem, the atmospheric ozone profile that is consistent with a given set of measured radiances may not be unique, an optimum statistical method is used to estimate a 'best' profile solution from the radiances and from additional a priori information.

  9. Assessment of Quantitative Precipitation Forecasts from Operational NWP Models (Invited)

    Science.gov (United States)

    Sapiano, M. R.

    2010-12-01

    Previous work has shown that satellite and numerical model estimates of precipitation have complimentary strengths, with satellites having greater skill at detecting convective precipitation events and model estimates having greater skill at detecting stratiform precipitation. This is due in part to the challenges associated with retrieving stratiform precipitation from satellites and the difficulty in resolving sub-grid scale processes in models. These complimentary strengths can be exploited to obtain new merged satellite/model datasets, and several such datasets have been constructed using reanalysis data. Whilst reanalysis data are stable in a climate sense, they also have relatively coarse resolution compared to the satellite estimates (many of which are now commonly available at quarter degree resolution) and they necessarily use fixed forecast systems that are not state-of-the-art. An alternative to reanalysis data is to use Operational Numerical Weather Prediction (NWP) model estimates, which routinely produce precipitation with higher resolution and using the most modern techniques. Such estimates have not been combined with satellite precipitation and their relative skill has not been sufficiently assessed beyond model validation. The aim of this work is to assess the information content of the models relative to satellite estimates with the goal of improving techniques for merging these data types. To that end, several operational NWP precipitation forecasts have been compared to satellite and in situ data and their relative skill in forecasting precipitation has been assessed. In particular, the relationship between precipitation forecast skill and other model variables will be explored to see if these other model variables can be used to estimate the skill of the model at a particular time. Such relationships would be provide a basis for determining weights and errors of any merged products.

  10. AERONET-based models of smoke-dominated aerosol near source regions and transported over oceans, and implications for satellite retrievals of aerosol optical depth

    Science.gov (United States)

    Sayer, A. M.; Hsu, N. C.; Eck, T. F.; Smirnov, A.; Holben, B. N.

    2014-10-01

    Smoke aerosols from biomass burning are an important component of the global aerosol system. Analysis of Aerosol Robotic Network (AERONET) retrievals of aerosol microphysical/optical parameters at 10 sites reveals variety between biomass burning aerosols in different global source regions, in terms of aerosol particle size and single scatter albedo (SSA). Case studies of smoke observed at coastal/island AERONET sites also mostly lie within the range of variability at the near-source sites. Differences between sites tend to be larger than variability at an individual site, although optical properties for some sites in different regions can be quite similar. Across the sites, typical midvisible SSA ranges from ~ 0.95-0.97 (sites dominated by boreal forest or peat burning, typically with larger fine-mode particle radius and spread) to ~ 0.88-0.9 (sites most influenced by grass, shrub, or crop burning, typically smaller fine-mode particle radius and spread). The tropical forest site Alta Floresta (Brazil) is closer to this second category, although with intermediate SSA ~ 0.92. The strongest absorption is seen in southern African savannah at Mongu (Zambia), with average midvisible SSA ~ 0.85. Sites with stronger absorption also tend to have stronger spectral gradients in SSA, becoming more absorbing at longer wavelengths. Microphysical/optical models are presented in detail so as to facilitate their use in radiative transfer calculations, including extension to UV (ultraviolet) wavelengths, and lidar ratios. One intended application is to serve as candidate optical models for use in satellite aerosol optical depth (AOD) retrieval algorithms. The models presently adopted by these algorithms over ocean often have insufficient absorption (i.e. too high SSA) to represent these biomass burning aerosols. The underestimates in satellite-retrieved AOD in smoke outflow regions, which have important consequences for applications of these satellite data sets, are consistent with

  11. A probabilistic approach for assessing landslide-triggering event rainfall in Papua New Guinea, using TRMM satellite precipitation estimates

    Science.gov (United States)

    Robbins, J. C.

    2016-10-01

    Large and numerous landslides can result in widespread impacts which are felt particularly strongly in the largely subsistence-orientated communities residing in the most landslide-prone areas of Papua New Guinea (PNG). Understanding the characteristics of rainfall preceding these landslide events is essential for the development of appropriate early warning systems and forecasting models. Relationships between rainfall and landslides are frequently complex and uncertainties tend to be amplified by inconsistent and incomplete landslide catalogues and sparse rainfall data availability. To address some of these uncertainties a modified Bayesian technique has been used, in conjunction with the multiple time frames method, to produce thresholds of landslide probability associated with rainfall events of specific magnitude and duration. Satellite-derived precipitation estimates have been used to derive representative rainfall accumulations and intensities over a range of different rainfall durations (5, 10, 15, 30, 45, 60, 75 and 90 days) for rainfall events which resulted in landslides and those which did not result in landslides. Of the two parameter combinations (accumulation-duration and intensity-duration) analysed, rainfall accumulation and duration provide the best scope for identifying probabilistic thresholds for use in landslide warning and forecasting in PNG. Analysis of historical events and rainfall characteristics indicates that high accumulation (>250 mm), shorter duration (75 days), high accumulation (>1200 mm) rainfall events are more likely to lead to moderate- to high-impact landslides. This analysis has produced the first proxy probability thresholds for landslides in PNG and their application within an early warning framework has been discussed.

  12. Evaluating the Height of Biomass Burning Smoke Aerosols Retrieved from Synergistic Use of Multiple Satellite Sensors Over Southeast Asia

    Science.gov (United States)

    Lee, Jaehwa; Hsu, N. Christina; Bettenhausen, Corey; Sayer, Andrew M.; Seftor, Colin J.; Jeong, Myeong-Jae; Tsay, Si-Chee; Welton, Ellsworth J.; Wang, Sheng-Hsiang; Chen, Wei-Nai

    2016-01-01

    This study evaluates the height of biomass burning smoke aerosols retrieved from a combined use of Visible Infrared Imaging Radiometer Suite (VIIRS), Ozone Mapping and Profiler Suite (OMPS), and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations. The retrieved heights are compared against space borne and ground-based lidar measurements during the peak biomass burning season (March and April) over Southeast Asia from 2013 to 2015. Based on the comparison against CALIOP, a quality assurance (QA) procedure is developed. It is found that 74 (8184) of the retrieved heights fall within 1 km of CALIOP observations for unfiltered (QA-filtered) data, with root-mean-square error (RMSE) of 1.1 km (0.81.0 km). Eliminating the requirement of CALIOP observations from the retrieval process significantly increases the temporal coverage with only a slight decrease in the retrieval accuracy; for best QA data, 64 of data fall within 1 km of CALIOP observations with RMSE of 1.1 km. When compared with Micro-Pulse Lidar Network (MPLNET) measurements deployed at Doi Ang Khang, Thailand, the retrieved heights show RMSE of 1.7 km (1.1 km) for unfiltered (QA-filtered) data for the complete algorithm, and 0.9 km (0.8 km) for the simplified algorithm.

  13. Global Characterization of CO2 Column Retrievals from Shortwave-Infrared Satellite Observations of the Orbiting Carbon Observatory-2 Mission

    Directory of Open Access Journals (Sweden)

    Charles Miller

    2011-02-01

    Full Text Available The global characteristics of retrievals of the column-averaged CO2 dry air mole fraction, XCO2, from shortwave infrared observations has been studied using the expected measurement performance of the NASA Orbiting Carbon Observatory-2 (OCO-2 mission. This study focuses on XCO2 retrieval precision and averaging kernels and their sensitivity to key parameters such as solar zenith angle (SZA, surface pressure, surface type and aerosol optical depth (AOD, for both nadir and sunglint observing modes. Realistic simulations have been carried out and the single sounding retrieval errors for XCO2 have been derived from the formal retrieval error covariance matrix under the assumption that the retrieval has converged to the correct answer and that the forward model can adequately describe the measurement. Thus, the retrieval errors presented in this study represent an estimate of the retrieval precision. For nadir observations, we find single-sounding retrieval errors with values typically less than 1 part per million (ppm over most land surfaces for SZAs less than 70° and up to 2.5 ppm for larger SZAs. Larger errors are found over snow/ice and ocean surfaces due to their low albedo in the spectral regions of the CO2 absorption bands and, for ocean, also in the O2 A band. For sunglint observations, errors over the ocean are significantly smaller than in nadir mode with values in the range of 0.3 to 0.6 ppm for small SZAs which can decrease to values as small as 0.15 for the largest SZAs. The vertical sensitivity of the retrieval that is represented by the column averaging kernel peaks near the surface and exhibits values near unity throughout most of the troposphere for most anticipated scenes. Nadir observations over dark ocean or snow/ice surfaces and observations with large AOD and large SZA show a decreased sensitivity to near-surface CO2. All simulations are carried out for a mid-latitude summer atmospheric profile, a given aerosol type and

  14. New methods for the retrieval of chlorophyll red fluorescence from hyperspectral satellite instruments: simulations and application to GOME-2 and SCIAMACHY

    Science.gov (United States)

    Joiner, Joanna; Yoshida, Yasuko; Guanter, Luis; Middleton, Elizabeth M.

    2016-08-01

    Global satellite measurements of solar-induced fluorescence (SIF) from chlorophyll over land and ocean have proven useful for a number of different applications related to physiology, phenology, and productivity of plants and phytoplankton. Terrestrial chlorophyll fluorescence is emitted throughout the red and far-red spectrum, producing two broad peaks near 683 and 736 nm. From ocean surfaces, phytoplankton fluorescence emissions are entirely from the red region (683 nm peak). Studies using satellite-derived SIF over land have focused almost exclusively on measurements in the far red (wavelengths > 712 nm), since those are the most easily obtained with existing instrumentation. Here, we examine new ways to use existing hyperspectral satellite data sets to retrieve red SIF (wavelengths unique opportunity to compare red and far-red terrestrial SIF at regional spatial scales. Terrestrial SIF has been estimated with ground-, aircraft-, or satellite-based instruments by measuring the filling-in of atmospheric and/or solar absorption spectral features by SIF. Our approach makes use of the oxygen (O2) γ band that is not affected by SIF. The SIF-free O2 γ band helps to estimate absorption within the spectrally variable O2 B band, which is filled in by red SIF. SIF also fills in the spectrally stable solar Fraunhofer lines (SFLs) at wavelengths both inside and just outside the O2 B band, which further helps to estimate red SIF emission. Our approach is then an extension of previous approaches applied to satellite data that utilized only the filling-in of SFLs by red SIF. We conducted retrievals of red SIF using an extensive database of simulated radiances covering a wide range of conditions. Our new algorithm produces good agreement between the simulated truth and retrievals and shows the potential of the O2 bands for noise reduction in red SIF retrievals as compared with approaches that rely solely on SFL filling. Biases seen with existing satellite data, most likely

  15. Review and Development on the Studies of Chinese Meteorological Satellite and Satellite Meteorology

    Institute of Scientific and Technical Information of China (English)

    FANG Zongyi; XU Jianmin; ZHAO Fengsheng

    2006-01-01

    Meteorological satellite and satellite meteorology are the fastest developing new branches in the atmospheric sciences. Today the meteorological satellite has become a key element in the global atmospheric sounding system while the satellite meteorology is covering the main components of earth's system science.This article describes the major achievements that China has made in these fields in the past 30 years.The following contents are involved: (1) History and present status of China's meteorological satellites. It covers the development, launch, operation, technical parameters of China's polar and geostationary meteorological satellites. (2) Major achievements on remote sensing principle and method. It describes the retrieval of atmospheric temperature and humidity profiles, cloud character retrieval, aerosol character retrieval, precipitation retrieval as well as the generation of cloud wind. (3) Achievement on the studies of meteorological satellite data application. This part covers the applications of meteorological satellite data to weather analysis and forecast, numerical forecast, climate monitoring, and prediction of short-term climate change. Besides, the new results on data assimilation, climate monitoring, and forecast are also included.

  16. Towards stochastically downscaled precipitation in the Tropics based on a robust 1DD combined satellite product and a high resolution IR-based rain mask

    Science.gov (United States)

    Guilloteau, Clement; Roca, Rémy; Gosset, Marielle

    2015-04-01

    In the Tropics where the ground-based rain gauges network is very sparse, satellite rainfall estimates are becoming a compulsory source of information for various applications: hydrological modeling, water resources management or vegetation-monitoring. The tropical Tropical Amount of Precipitation with Estimate of Error (TAPEER) algorithm, developed within the framework of Megha-Tropiques satellite mission is a robust estimate of surface rainfall accumulations at the daily, one degree resolution. TAPEER validation in West Africa has proven its accuracy. Nevertheless applications that involve non-linear processes (such as surface runoff) require finer space / time resolution than one degree one day, or at least the statistical characterization of the sub-grid rainfall variability. TAPEER is based on a Universally Adjusted Global Precipitation Index (UAGPI) technique. The one degree, one day estimation relies on the combination of observations from microwave radiometers embarked on the 7 platforms forming the GPM constellation of low earth orbit satellites together with geostationary infra-red (GEO-IR) imagery. TAPEER provides as an intermediate product a high-resolution rain-mask based on the GEO-IR information (2.8 km, 15 min in Africa). The main question of this work is, how to use this high-resolution mask information as a constraint for downscaling ? This work first presents the multi-scale evaluation of TAPEER's rain detection mask against ground X-band polarimetric radar data and TRMM precipitation radar data in West Africa, through wavelet transform. Other algorithms (climate prediction center morphing technique CMORPH, global satellite mapping of precipitation GSMaP, multi-sensor precipitation estimate MPE) detection capabilities are also evaluated. Spatio-temporal wavelet filtering of the detection mask is then used to compute precipitation probability at the GEO-IR resolution. The wavelet tool is finally used to stochastically generate rain / no rain field

  17. AERONET-based microphysical and optical properties of smoke-dominated aerosol near source regions and transported over oceans, and implications for satellite retrievals of aerosol optical depth

    Science.gov (United States)

    Sayer, A. M.; Hsu, N. C.; Eck, T. F.; Smirnov, A.; Holben, B. N.

    2013-09-01

    Smoke aerosols from biomass burning are an important component of the global aerosol cycle. Analysis of Aerosol Robotic Network (AERONET) retrievals of size distribution and refractive index reveals variety between biomass burning aerosols in different global source regions, in terms of aerosol particle size and single scatter albedo (SSA). Case studies of smoke transported to coastal/island AERONET sites also mostly lie within the range of variability at near-source sites. Two broad ''families'' of aerosol properties are found, corresponding to sites dominated by boreal forest burning (larger, broader fine mode, with midvisible SSA ∼0.95), and those influenced by grass, shrub, or crop burning with additional forest contributions (smaller, narrower particles with SSA ∼0.88-0.9 in the midvisible). The strongest absorption is seen in southern African savannah at Mongu (Zambia), with average SSA ∼0.85 in the midvisible. These can serve as candidate sets of aerosol microphysical/optical properties for use in satellite aerosol optical depth (AOD) retrieval algorithms. The models presently adopted by these algorithms over ocean are often insufficiently absorbing to represent these biomass burning aerosols. A corollary of this is an underestimate of AOD in smoke outflow regions, which has important consequences for applications of these satellite datasets.

  18. Influence of aerosols and surface reflectance on satellite NO2 retrieval: seasonal and spatial characteristics and implications for NOx emission constraints

    Science.gov (United States)

    Lin, J.-T.; Liu, M.-Y.; Xin, J.-Y.; Boersma, K. F.; Spurr, R.; Martin, R.; Zhang, Q.

    2015-04-01

    Satellite retrievals of vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) normally do not explicitly account for aerosol optical effects and surface reflectance anisotropy that vary with space and time. Here, we conduct an improved retrieval of NO2 VCDs over China, called the POMINO algorithm, based on measurements from the Ozone Monitoring Instrument (OMI), and we test the importance of a number of aerosol and surface reflectance treatments in this algorithm. POMINO uses a parallelized LIDORT-driven AMFv6 package to derive tropospheric air mass factors via pixel-specific radiative transfer calculations with no look-up tables, taking slant column densities from DOMINO v2. Prerequisite cloud optical properties are derived from a dedicated cloud retrieval process that is fully consistent with the main NO2 retrieval. Aerosol optical properties are taken from GEOS-Chem simulations constrained by MODIS AOD values. MODIS bi-directional reflectance distribution function (BRDF) data are used for surface reflectance over land. For the present analysis, POMINO level-2 data for 2012 are aggregated into monthly means on a 0.25° long. × 0.25° lat. grid. POMINO-retrieved annual mean NO2 VCDs vary from 15-25 × 1015 cm-2 over the polluted North China Plain (NCP) to below 1015 cm-2 over much of west China. The subsequently-constrained Chinese annual anthropogenic emissions are 9.05 TgN yr-1, an increase from 2006 (Lin, 2012) by about 19%. Replacing the MODIS BRDF data with the OMLER v1 monthly climatological albedo data affects NO2 VCDs by up to 40% for certain locations and seasons. The effect on constrained NOx emissions is small. Excluding aerosol information from the retrieval process (this is the traditional "implicit" treatment) enhances annual mean NO2 VCDs by 15-40% over much of east China. Seasonally, NO2 VCDs are reduced by 10-20% over parts of the NCP in spring and over north China in winter, despite the general enhancements in summer and fall

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

    Science.gov (United States)

    Hou, Arthur Y.

    2012-01-01

    The Global Precipitation Measurement (GPM) Mission is an international satellite mission specifically designed to unify and advance precipitation measurements from a constellation of research and operational microwave sensors. NASA and JAXA will deploy a Core Observatory in 2014 to serve as a reference satellite to unify precipitation measurements from the constellation of sensors. The GPM Core Observatory will carry a Ku/Ka-band Dual-frequency Precipitation Radar (DPR) and a conical-scanning multi-channel (10-183 GHz) GPM Microwave Radiometer (GMI). The DPR will be the first dual-frequency radar in space to provide not only measurements of 3-D precipitation structures but also quantitative information on microphysical properties of precipitating particles. The DPR and GMI measurements will together provide a database that relates vertical hydrometeor profiles to multi-frequency microwave radiances over a variety of environmental conditions across the globe. This combined database will be used as a common transfer standard for improving the accuracy and consistency of precipitation retrievals from all constellation radiometers. For global coverage, GPM relies on existing satellite programs and new mission opportunities from a consortium of partners through bilateral agreements with either NA