Evaluation of satellite rainfall estimates over Ethiopian river basins

High resolution satellite-based rainfall estimates (SREs) have enormous potential for use in hydrological applications, particularly in the developing world as an alternative to conventional rain gauges which are typically sparse. In this study, three SREs have been evaluated against collocated rain...

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Main Authors: T. G. Romilly, M. Gebremichael
Format: Article
Language:English
Published: Copernicus Publications 2011-05-01
Series:Hydrology and Earth System Sciences
Online Access:http://www.hydrol-earth-syst-sci.net/15/1505/2011/hess-15-1505-2011.pdf
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spelling doaj-78143bac2c6e4f6e93b466bb0a4abe242020-11-24T22:40:25ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382011-05-011551505151410.5194/hess-15-1505-2011Evaluation of satellite rainfall estimates over Ethiopian river basinsT. G. RomillyM. GebremichaelHigh resolution satellite-based rainfall estimates (SREs) have enormous potential for use in hydrological applications, particularly in the developing world as an alternative to conventional rain gauges which are typically sparse. In this study, three SREs have been evaluated against collocated rain gauge measurements in Ethiopia across six river basins that represent different rainfall regimes and topography. The comparison is made using five-year (2003–2007) averages, and results are stratified by river basin, elevation and season. The SREs considered are: the Climate Prediction Center morphing method (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Neural Networks (PERSIANN) and the real-time version of the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42RT. Overall, the microwave-based products TMPA 3B42RT and CMORPH outperform the infrared-based product PERSIANN: PERSIANN tends to underestimate rainfall by 43 %, while CMORPH tends to underestimate by 11 % and TMPA 3B42RT tends to overestimate by 5 %. The bias in the satellite rainfall estimates depends on the rainfall regime, and, in some regimes, the elevation. In the northwest region, which is characterized mainly by highland topography, a humid climate and a strong Intertropical Convergence Zone (ITCZ) effect, elevation has a strong influence on the accuracy of the SREs: TMPA 3B42RT and CMORPH tend to overestimate at low elevations but give reasonably accurate results at high elevations, whereas PERSIANN gives reasonably accurate values at low elevations but underestimates at high elevations. In the southeast region, which is characterized mainly by lowland topography, a semi-arid climate and southerly winds, elevation does not have a significant influence on the accuracy of the SREs, and all the SREs underestimate rainfall across almost all elevations.http://www.hydrol-earth-syst-sci.net/15/1505/2011/hess-15-1505-2011.pdf
collection DOAJ
language English
format Article
sources DOAJ
author T. G. Romilly
M. Gebremichael
spellingShingle T. G. Romilly
M. Gebremichael
Evaluation of satellite rainfall estimates over Ethiopian river basins
Hydrology and Earth System Sciences
author_facet T. G. Romilly
M. Gebremichael
author_sort T. G. Romilly
title Evaluation of satellite rainfall estimates over Ethiopian river basins
title_short Evaluation of satellite rainfall estimates over Ethiopian river basins
title_full Evaluation of satellite rainfall estimates over Ethiopian river basins
title_fullStr Evaluation of satellite rainfall estimates over Ethiopian river basins
title_full_unstemmed Evaluation of satellite rainfall estimates over Ethiopian river basins
title_sort evaluation of satellite rainfall estimates over ethiopian river basins
publisher Copernicus Publications
series Hydrology and Earth System Sciences
issn 1027-5606
1607-7938
publishDate 2011-05-01
description High resolution satellite-based rainfall estimates (SREs) have enormous potential for use in hydrological applications, particularly in the developing world as an alternative to conventional rain gauges which are typically sparse. In this study, three SREs have been evaluated against collocated rain gauge measurements in Ethiopia across six river basins that represent different rainfall regimes and topography. The comparison is made using five-year (2003–2007) averages, and results are stratified by river basin, elevation and season. The SREs considered are: the Climate Prediction Center morphing method (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Neural Networks (PERSIANN) and the real-time version of the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42RT. Overall, the microwave-based products TMPA 3B42RT and CMORPH outperform the infrared-based product PERSIANN: PERSIANN tends to underestimate rainfall by 43 %, while CMORPH tends to underestimate by 11 % and TMPA 3B42RT tends to overestimate by 5 %. The bias in the satellite rainfall estimates depends on the rainfall regime, and, in some regimes, the elevation. In the northwest region, which is characterized mainly by highland topography, a humid climate and a strong Intertropical Convergence Zone (ITCZ) effect, elevation has a strong influence on the accuracy of the SREs: TMPA 3B42RT and CMORPH tend to overestimate at low elevations but give reasonably accurate results at high elevations, whereas PERSIANN gives reasonably accurate values at low elevations but underestimates at high elevations. In the southeast region, which is characterized mainly by lowland topography, a semi-arid climate and southerly winds, elevation does not have a significant influence on the accuracy of the SREs, and all the SREs underestimate rainfall across almost all elevations.
url http://www.hydrol-earth-syst-sci.net/15/1505/2011/hess-15-1505-2011.pdf
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