Can satellite precipitation estimates capture the magnitude of extreme rainfall Events?

Abstract

With the increasing frequency of extreme rainfall events, the likelihood of rainfall disasters is also increasing, presenting serious risks of casualties and economic losses. Therefore, exploring the capability of Satellite-based Precipitation Products (SPPs) to capture the magnitudes of extreme rainfall events is significant for preventing precipitation-related disasters. Selecting ten heavy rainfall events in wet seasons over China, this study evaluated the performance of mainstream SPPs from the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) and Global Satellite Mapping of Precipitation (GSMaP) in determining the extreme values of heavy rainfall events. The main findings are as follows: (1) SPPs significantly underestimated the magnitudes of extreme rainfalls events, with the most underestimated and closest values for certain events reaching only one-tenth and 50% of ground station values, respectively; (2) the evaluation of the top 1% hourly precipitation presented similar evident errors, with mean relative bias (BIAS) and root mean square error (RMSE) of approximately -80% and 40 mm hour(-1); (3) the spatiotemporal patterns of IMERG-Final were closer to those of the ground station and GSMaP-Now captured more maximum values of the ten events. Nevertheless, the accuracy of these SPPs is still not sufficient for the analysis of extreme rain disasters.