Evaluation of the Accuracy of Multiple High-Spatial-and-Temporal- Resolution Precipitation Data in the “7·22” Heavy Rainstorm Event in the East of Northwest China

From July 22nd to 24th, 2024, Gansu Province was hit by an extremely rare torrential rain in history.A total of 12 stations accumulated rainfall exceeding 300 mm, with the maximum reaching 351.4 mm.The overall intensity was the strongest in the northwest region since 1961.Based on the Precipitation observation data from Automatic Weather Station (AWS), this study evaluated the CMA Multi-source Precipitation Analysis system in China (CMPA), Radar Quantitative Precipitation Estimation (Radar-QPE), Fengyun 4B Quantitative Precipitation Estimation (FY4B-QPE) and the European Centre for Medium Range Weather Forecasts Reanalysis v5 (ERA5) monitoring capabilities of four precipitation products during this extremely heavy rainstorm.The results showed that: (1) CMPA had the best performance in spatial distribution, which could accurately capture the precipitation and extreme value in the core area of rainstorm, with the least spatial variability, ME was only 0.002 mm·h-1.Radar-QPE could identify the location of the rainstorm area, but underestimate the precipitation in the core area, FY4B-QPE significantly overestimates the precipitation in the core area, while ERA5 underestimates the precipitation in the core area, ME was respectively -0.151, 0.192 and 0.08 mm·h-1.(2) CMPA was the most accurate in capturing time evolution with the smallest error, CORR was up to 0.999.Radar-QPE underestimated precipitation during heavy precipitation hours, and the error increased significantly with the increase of precipitation intensity, the errors of FY4B-QPE and ERA5 increased significantly during heavy precipitation hours, especially FY4B-QPE had worse behavior in the core area, CORR was respectively 0.96, 0.24 and 0.22.(3) The diurnal variation characteristics of CMPA and AWS were the closest.There were deviations in the peak value and distribution of precipitation in Radar-QPE.The peak position of FY4B-QPE was located to the east and north, and the precipitation time was advanced.There was no significant peak of ERA5 in the meridian direction, but showed a negative deviation in the zonal direction that was slightly northward.(4) CMPA and AWS were highly consistent in precipitation probability distribution, showing the best spatio-temporal consistency.Radar-QPE and ERA5 overestimated the first precipitation peak and underestimated the precipitation above 5.0 mm/h.FY4B-QPE underestimated weak precipitation and overestimates heavy precipitation.These results provided a detailed comparison of the monitoring capabilities of different precipitation products in rainstorm precipitation events, and offered a reference for the dynamic monitoring, early warning and hydrological application of rainstorm event.