干旱区生态环境知识资源中心

Five satellite precipitation products, including Climate Prediction Center Morphing Technique (CMORPH), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Network (PERSIANN), Tropical Rainfall Measuring Missing (TRMM) Multisatellite Precipitation Analysis (TMPA) version 7 products 3B41RTV7, 3B42RTV7, and 3B42V7, are systematically evaluated by comparing to the daily precipitation data collected from similar to 2400 gauge stations over China during January 2000 to December 2014. Satellite estimates generally capture the overall spatial-temporal variation of precipitation over China with relatively better ability in warm seasons than in cold seasons. Meanwhile, satellite precipitation estimates also tend to show better agreement with gauge observations over humid regions than over arid and alpine regions. Analysis of the systematic and random error components suggests that the uncertainties in both TRMM3B42RTV7 and TRMM3B42V7 precipitation estimates are significantly reduced over most parts of China compared to the other three satellite products. Among the five products, the research product TRMM3B42V7 with bias adjustments agrees the most with the gauge observation in terms of spatiotemporal variation, amplitude and pattern of variability, occurrence of rainy events, and probability distribution function of the precipitation amount for different rain rates over most parts of China; the near-real-time product TRMM3B42RTV7 with the application of improved retrieval algorithms and more satellite data performs the second best over most subregions of eastern China. The improvements of TRMM3B42RTV7 without bias adjustments over eastern China relative to CMORPH, PERSIANN, and TRMM3B41RTV7 are encouraging and favorable for the operational applications.