Análise das Estimativas da Precipitação Diária do Produto GPM-IMERG na Bacia Hidrográfica do Rio Sapucaí, Região Sudeste do Brasil

Tendo em vista que as estimativas de precipitação (PP) por satélite são importantes fontes de informações para modelos hidrológicos, o objetivo deste estudo é avaliar os acumulados diários de PP do produto Integrated Multisatellite Retrievals for the Global Precipitation Measurement (IMERG) - Early Run do Global Precipitation Measurement (GPM) na Bacia Hidrográfica do Rio Sapucaí (BHRS) que se encontra localizada no sudeste do Brasil. Para realizar essa avaliação foram utilizadas métricas estatísticas de performance e de contingência. Os dados utilizados na validação foram os acumulados diários de PP das estações pluviométricas da Agência Nacional de Águas (ANA). O período analisado no estudo compreende os verões dos anos de 2015 a 2019. No geral, os resultados indicaram que o IMERG subestima em média 27% a PP diária sobre a bacia, sendo que o RMSE é da ordem de 12,9 a 28,5 mm/dia. Além disso, foi observado também que os valores do coeficiente de correlação de Pearson na maioria dos pontos de grade analisados ficaram abaixo de 0,7. Isso indica que não existe uma boa correlação entre os dados do IMERG com os dados das estações pluviométricas. As métricas estatísticas de contingência mostraram que o IMERG - Early Run possui baixa capacidade para descrever os eventos de chuva na BHRS. Portanto, pode-se inferir que o produto Early Run do GPM-IMERG possui dificuldades em estimar a PP diária na BHRS durante os meses de verão

Evaluation of Satellite-Based Precipitation Products from IMERG V04A and V03D, CMORPH and TMPA with Gauged Rainfall in Three Climatologic Zones in China

A critical evaluation of the newly released precipitation data set is very important for both the end users and data developers. Meanwhile, the evaluation may provide a benchmark for the product’s continued development and future improvement. To these ends, the four precipitation estimates including IMERG (the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement) V04A, IMERG V03D, CMORPH (the Climate Prediction Center Morphing technique)-CRT and TRMM (the Tropical Rainfall Measuring Mission) 3B42 are systematically evaluated against the gauge precipitation estimates at multiple spatiotemporal scales from 1 June 2014 to 30 November 2015 over three different topographic and climatic watersheds in China. Meanwhile, the statistical methods are utilized to quantize the performance of the four satellite-based precipitation estimates. The results show that: (1) over the Tibetan Plateau cold region, among all products, IMERG V04A underestimates precipitation with the largest RB (−46.98%) during the study period and the similar results are seen at the seasonal scale. However, IMERG V03D demonstrates the best performance according to RB (7.46%), RMSE (0.44 mm/day) and RRMSE (28.37%). Except for in summer, TRMM 3B42 perform better than CMORPH according to RMSEs, RRMSEs and Rs; (2) within the semi-humid Huaihe River Basin, IMERG V04A has a slight advantage over the other three satellite-based precipitation products with the lowest RMSE (0.32 mm/day) during the evaluation period and followed by IMERG V03D, TRMM 3B42 and CMORPH orderly; (3) over the arid/semi-arid Weihe River Basin, in comparison with the other three products, TRMM 3B42 demonstrates the best performance with the lowest RMSE (0.1 mm/day), RRMSE (8.44%) and highest R (0.92) during the study period. Meanwhile, IMERG V03D perform better than IMERG V04A according all the statistical indicators; (4) in winter, IMERG V04A and IMERG V03D tend to underestimate the total precipitation with RBs (−70.62% vs. −6.47% over the Tibetan Plateau, −46.92% vs. −0.66% over the Weihe River Basin, respectively); and (5) overall, except for IMERG V04A in Tibetan Plateau, all satellite-based precipitation captured the gauge-based precipitation well over the three regions according to RRMSEs, Rs and Rbs during the study period. IMERG V03D performs better than its predecessors-TRMM 3B42 and CMORPH over the Tibetan Plateau region and the Huaihe River Basin, while IMERG V04A only does so over the latter. Between the two IMERG products, IMERG V04A does not show an advantage over IMERG V03D over the Tibetan Plateau region and the Weihe River Basin. In particular, over the former, IMERG V04A performs far worse than IMERG V03D. These findings provide valuable feedback for both IMERG algorithm developers and data users