Abstract:Based on the precipitation observation data from 1 889 automatic meteorological stations in Xinjiang, this study assesses the applicability of the multi-source precipitation fusion product (with a spatial resolution of 1 km and a temporal resolution of 1 hour) released by the CMA Multi-source Precipitation Analysis System (CMPAS) for the warm season (May to September) from 2020 to 2023. The results show that the product has significantly improved in 2022-2023 compared to the 2020-2021 period across all evaluation indicators. The correlation coefficient (COR) and TS score in 2022-2023 increased from 0.86 and 0.648 to 0.939 and 0.854, respectively, representing an increase of 9.2% and 31.8%. The root mean square error decreased from 0.692 mm to 0.484 mm, a reduction of 30%. The false alarm rate dramatically decreased from 0.325 to 0.101, a reduction of 68.9%, while the missed rate showed no significant change. Among the months of the warm season, the comprehensive quality of the precipitation fusion product was the best in August. During periods of high actual precipitation (15:00-21:00), the correlation coefficient between the precipitation fusion product and the actual precipitation was relatively high and stable. However, the TS score was slightly lower due to the higher false alarm rate and missed rates. The performance of the multi-source precipitation fusion product deteriorated with increasing precipitation intensity, but the gap was trending downward annually. The areas with relatively poor precipitation fusion product quality are mainly located in the northwest of northern Xinjiang, the middle section of the Tianshan Mountains (both northern and southern slopes), the western part of southern Xinjiang, the northern slope of the Kunlun Mountains, the Altay Mountains, and the eastern Xinjiang region. Compared to the 2020-2021 period, the quality of the precipitation fusion product improved significantly in 2022-2023 across various time scales, precipitation intensities, and altitudinal ranges. This indicates that the optimization of the precipitation fusion product algorithm in the second half of 2021 has significantly enhanced the product accuracy and reliability.