Evaluation of Three Long-Term Remotely Sensed Precipitation Estimates for Meteorological Drought Monitoring over China

Remotely sensed precipitation estimates (RSPEs) play an essential role in monitoring drought, especially ungauged or sparsely gauged areas. In this study, we evaluated the ability of three popular long-term RSPEs (PERSIANN, CHIRPS, and MSWEP) capturing meteorological drought variations over 10 first-level water resource basins China, based on standardized index (SPI). Drought events were identified by run theory, characteristics (i.e., duration, severity, intensity) also compared with a gridded situ observational dataset (CMA). The results showed that could generally capture spatial patterns trends CMA better performance wetter basins. MSWEP had best for categorical skill POD, followed CHIRPS PERSIANN four timescales. SPI6 was optimal timescale identifying events. There large divergences characteristics. can efficiently reproduce distribution characteristics, similar metrics MDS, MDI, MDP, PERSIANN. Overall, no single product always outperformed other products underscoring necessity multiproduct ensemble applications. Our study’s findings may provide useful information areas complex terrain sparse rain-gauge networks.