Quantitative Characteristics of the Current Multi-Source Precipitation Products over Zhejiang Province, in Summer, 2019

Precipitation data with fine quality plays vital roles in hydrological-related applications. In this study, we choose the high-quality China Merged Analysis (CMPA) as benchmark for evaluating four satellite-based precipitation products (PERSIANN-CCS, FY4A QPE, GSMap_Gauge, IMERG-Final) and one model-based product (ERA5-Land), respectively, at 0.1°, hourly scales over Zhejiang province, China, summer, from June to August 2019. The main conclusions were follows—(1) all other demonstrate similar patterns CMPA (~325.60 mm/h, std ~0.07 mm/h), except QPE (~281.79 ~0.18 while, overall, PERSIANN-CCS underestimates against a mean value around 236.29 mm/h (std ~0.06 ERA5-Land, GSMap_Guage, IMERG-Final generally overestimate 370.00 mm/h). (2) GSMap_Gauge outperforms CC ~0.50 RMSE ~1.51 ~0.48 ~1.64 respectively. (3) significantly (CC ~0.26, bias ~?35.03%, ~1.81 probability of detection, POD, ~0.33, false alarm ratio, FAR, ~0.47), potentially due its weak abilities capture events estimate precipitation. (4) Though ERA5-Land has best ability (POD ~0.78), largest misjudgments (FAR ~0.54) result great uncertainties ~ 0.39, which performs worse than those IMERG-Final. (5) ranking products, terms general evaluation metrics, province is IMERG-Final, PERSIANN-CCS, provides valuable recommendations applying these various related application fields.