TY - JOUR
T1 - Evaluation of GPM-era Global Satellite Precipitation Products over Multiple Complex Terrain Regions
AU - Derin, Yagmur
AU - Anagnostou, Emmanouil
AU - Berne, Alexis
AU - Borga, Marco
AU - Boudevillain, Brice
AU - Buytaert, Wouter
AU - Chang, Che Hao
AU - Chen, Haonan
AU - Delrieu, Guy
AU - Hsu, Yung Chia
AU - Lavado-Casimiro, Waldo
AU - Manz, Bastian
AU - Moges, Semu
AU - Nikolopoulos, Efthymios I.
AU - Sahlu, Dejene
AU - Salerno, Franco
AU - Rodríguez-Sánchez, Juan Pablo
AU - Vergara, Humberto J.
AU - Yilmaz, Koray K.
N1 - Publisher Copyright:
© 2019 by the authors.
PY - 2019/12/1
Y1 - 2019/12/1
N2 - The great success of the Tropical Rainfall Measuring Mission (TRMM) and its successor Global Precipitation Measurement (GPM) has accelerated the development of global high-resolution satellite-based precipitation products (SPP). However, the quantitative accuracy of SPPs has to be evaluated before using these datasets in water resource applications. This study evaluates the following GPM-era and TRMM-era SPPs based on two years (2014-2015) of reference daily precipitation data from rain gauge networks in ten mountainous regions: Integrated Multi-SatellitE Retrievals for GPM (IMERG, version 05B and version 06B), National Oceanic and Atmospheric Administration (NOAA)/Climate Prediction Center Morphing Method (CMORPH), Global Satellite Mapping of Precipitation (GSMaP), and Multi-SourceWeighted-Ensemble Precipitation (MSWEP), which represents a global precipitation data-blending product. The evaluation is performed at daily and annual temporal scales, and at 0.1 deg grid resolution. It is shown that GSMaPV07 surpass the performance of IMERGV06B Final for almost all regions in terms of systematic and random error metrics. The new orographic rainfall classification in the GSMaPV07 algorithm is able to improve the detection of orographic rainfall, the rainfall amounts, and error metrics. Moreover, IMERGV05B showed significantly better performance, capturing the lighter and heavier precipitation values compared to IMERGV06B for almost all regions due to changes conducted to the morphing, where motion vectors are derived using total column water vapor for IMERGV06B.
AB - The great success of the Tropical Rainfall Measuring Mission (TRMM) and its successor Global Precipitation Measurement (GPM) has accelerated the development of global high-resolution satellite-based precipitation products (SPP). However, the quantitative accuracy of SPPs has to be evaluated before using these datasets in water resource applications. This study evaluates the following GPM-era and TRMM-era SPPs based on two years (2014-2015) of reference daily precipitation data from rain gauge networks in ten mountainous regions: Integrated Multi-SatellitE Retrievals for GPM (IMERG, version 05B and version 06B), National Oceanic and Atmospheric Administration (NOAA)/Climate Prediction Center Morphing Method (CMORPH), Global Satellite Mapping of Precipitation (GSMaP), and Multi-SourceWeighted-Ensemble Precipitation (MSWEP), which represents a global precipitation data-blending product. The evaluation is performed at daily and annual temporal scales, and at 0.1 deg grid resolution. It is shown that GSMaPV07 surpass the performance of IMERGV06B Final for almost all regions in terms of systematic and random error metrics. The new orographic rainfall classification in the GSMaPV07 algorithm is able to improve the detection of orographic rainfall, the rainfall amounts, and error metrics. Moreover, IMERGV05B showed significantly better performance, capturing the lighter and heavier precipitation values compared to IMERGV06B for almost all regions due to changes conducted to the morphing, where motion vectors are derived using total column water vapor for IMERGV06B.
KW - Complex terrain
KW - Satellite-based precipitation product
KW - Validation
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U2 - 10.3390/rs11242936
DO - 10.3390/rs11242936
M3 - Article
AN - SCOPUS:85077899702
SN - 2072-4292
VL - 11
JO - Remote Sensing
JF - Remote Sensing
IS - 24
M1 - 2936
ER -