Evaluation and Correction of IMERG Late Run Precipitation Product in Rainstorm over the Southern Basin of China

Satellite precipitation products play an essential role in providing effective global or regional precipitation. However, there are still many uncertainties the performance of satellite products, especially extreme analysis. In this study, a Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) late run (LR) product was used to evaluate rainstorms southern basin China from 2015 2018. Three correction methods, multiple linear regression (MLR), artificial neural network (ANN), and geographically weighted (GWR), were get improve performance. This study found that IMERG LR’s ability characterize rainstorm events limited, significant underestimation. The observation error detection LR decrease gradually southeast coast northwest inland. test shows eastern coastal area (zone I II), central III), western inland IV V), optimal method is MLR, ANN, GWR, respectively. three slightly better compared with original LR. From zone V, correlation coefficient (CC) root mean square (RMSE) show decreasing trend. Zone II has highest relative bias (RB), deviation relatively large. categorical indices performed than area. product’s lower observed value April November 8.03%. higher values other months, average 12.27%. greater precipitation, uncertainty corrected result. variation showed had uncertainty, V lowest uncertainty. MLR high 9.72%. ANN GWR 7.74% 7.29%, aims generate set good accuracy through evaluation support research.