Evaluation and comparison of precipitation estimates and hydrologic utility of CHIRPS, TRMM 3B42 V7 and PERSIANN-CDR products in various climate regimes

Abstract Evaluation of satellite-based quantitative precipitation estimates (QPEs) with reliable and independent ground-based measurements is important for both product developers and users. Here, we present a comprehensive evaluation on 3 high-resolution QPEs, namely, the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS), the latest non-real-time post-processing version of Tropical Rainfall Measuring Mission (TRMM 3B42 V7), and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), in 3 basins with different climates in China. The accuracy of 3 QPEs in reproducing the spatial extent of daily and monthly precipitation (PR) as well as extreme PR indices was evaluated. Two simulation scenarios were utilized to evaluate the efficiency of hydrologic events forecasting of these 3 QPEs quantitatively. The results indicated that the 3 QPEs generally show high accuracy in estimating monthly PR in 3 basins, among which TRMM 3B42 V7 performs best (coefficient of determination R2