Extremely heavy rain storms caused by typhoon usually lead to significant losses in economic infrastructure and human life in urban agglomeration. Accurate precipitation estimation from satellites is of great importance for hydrology, meteorology, climate change, and ecological research due to its extensive spatial coverage, consistent measurements over land and oceanic areas. In this research, gauge observations are used as ground true to evaluated the capacity of near real-time precipitation estimates from Integrated Multi-satellite Retrievals for GPM extent (IMERG_ER, IMERG hereafter) during three heavy rainfall storms. These storms were brought by typhoon Hato, Pakhar and Mawar, which landed Guangdong Province successively in August and September of 2017. Six commonly used skill scores are used for quantitative analysis. These scores include Correlation Coefficient (CC), Relative Bias (RB), Root-Mean-Squared Error (RMSE), Probability of Detection (POD), False Alarm Ratio (FAR) and Critical Success Index (CSI). Results show that:(1) IMERG generally captures overall characteristics of storm-based accumulated precipitation with CC about 0.80, 0.68, and 0.47, respectively, underestimates rainfall in three cases in different degrees with different RB (-12.00%, -47.06% and -29.10%), and show different uncertainties with RMSE about 33.00, 40.03 and 26.40 mm, which may be caused by complex terrain and rapid variation of moisture transport; (2) IMERG's ability on estimation of extreme heavy rain is unstable according to result of CC(0.59, 0.48 and 0.33), RB(2.21%, -43.58% and -25.94%), RMSE(44.34, 51.04 and 40.64 mm) and scatter diagram; (3) IMERG grasps the magnitude of hourly rainfall caused by typhoons themselves, but underestimates precipitation derived from southwest monsoon trough, owing to limitation of PMW's low temporal resolution and IR's low accuracy; (4) IMERG has better value of POD, FAR and CSI in rainfall center. Despite the apparent differences with gauge measurements, the conclusions in this study highlight that IMERG has great potential to provide high-resolution precipitation information around the whole earth area, especially applied to tropical storms. The analysis result shows that bias of heavy rain plays main roles on the whole deviation of typhoon events.
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