青藏高原东部三种降水数据产品的适用性评估 postprint

Abstract: Based on the 2022 daily precipitation data from weather stations in the eastern Tibetan Plateau, thisstudy evaluated the accuracy of three datasets from the China Meteorological Administration: the Multi- source Precipitation Analysis System (CMPAS); Land Data Assimilation System (CLDAS); and Global Atmospheric Reanalysis (CRA)—via error indices and grading methods. The results indicate: (1) CMPAS exhibits the lowest error and highest correlation, making it the most reliable for annual precipitation analysis. (2) CMPAS monthly data align closely with observations, while CRA overestimates and CLDAS underestimates precipitation in most months. (3) During two large- scale precipitation events, CLDAS best captures accumulated rainfall, while CMPAS more accurately reflects precipitation centers, intensities, timing, and location. Overall, CMPAS is the most effective dataset for analyzing precipitation in the region, supporting improved monitoring of sparse areas and laying a solid foundation for climate operations and disaster prevention.