作者
Yanzhong Li,Haiwen Yan,Li Chen,Manjie Huang,Weiwei Shou,Liqin Zhu,Lin Zhao,Yincong Xing
摘要
Satellite-based precipitation products (SPPs) can provide crucial precipitation estimations for large-scale, near-real-time meteorological drought monitoring. However, the performances and uncertainties of SPPs in capturing drought information may vary greatly by product and climate region and are still poorly understood. In this study, we comprehensively evaluated the accuracy of five popular SPPs (MSWEP, TMPA 3B42, PERSIANN-CDR, CHIRPS, and COMRPH) in characterizing meteorological drought in mainland China. (1) Under global warming conditions, the standardized precipitation evapotranspiration index (SPEI) identified a significant decrease in drought associated with higher potential evapotranspiration (PET), which indicated the essential role of PET in determining drought evolution over different climate regions. (2) Among all the SPPs investigated, MSWEP, TMPA 3B42, and PERSIANN perform best in capturing the spatiotemporal pattern of the SPEI trend in the arid Tibetan Plateau regions, transition regions, and humid regions, respectively. In terms of drought category and drought characteristics, MSWEP and TMPA 3B42 perform very well for humid regions, and CHIRPS is better for cold and arid regions, with the poorest performance being found in CMORPH. However, no product performs well for all climate regions for drought monitoring. (3) The optimized parameters (OPs) are the dominant factor for drought uncertainties, followed by the interaction effect and SPPs, with great regional dependence. The OPs contributed the most to drought uncertainties over the relatively arid area of northern China, the interaction of OPs and SPPs did so in the humid area of China, and SPPs were found to contribute the most in the central Tibetan Plateau and some parts of humid regions. Our findings provide guidelines on the choice and application of existing SPP datasets for drought monitoring in different climate zones, as well as some clues to further improve the products over areas where they perform poorly.