Page 298 - 《高原气象》2026年第1期
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高     原      气     象                                 45 卷
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                     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



                                                                                  1
                            FU Jing , HUANG Wubin , DUAN Bolong , HUANG Yuxia , FU Zhengxu     1
                                   1
                                                                   1
                                                   2, 1
                                 (1. Lanzhou Central Meteorological Observatory, Lanzhou  730020, Gansu, China;
                                     2. Dunhuang Meteorological Bureau, Dunhuang  736200, Gansu, China)
             Abstract: 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 over‐
             all 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 sys‐
             tem 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 Reanaly‐
             sis 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 . Radar-QPE could identify the location of the rainstorm area, but underestimate the precipitation
                         -1
             in the core area, FY4B-QPE significantly overestimates the precipitation in the core area, while ERA5 underesti‐
             mates the precipitation in the core area, ME was respectively -0. 151, 0. 192 and 0. 08 mm·h .(2) CMPA was
                                                                                              -1
             the most accurate in capturing time evolution with the smallest error, CORR was up to 0. 999. Radar-QPE under‐
             estimated 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 consisten‐
             cy. 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 pre‐
             cipitation events, and offered a reference for the dynamic monitoring, early warning and hydrological applica‐
             tion of rainstorm event.
             Key words: 7·22 rainstorm; CMPA; Radar-QPE; FY4B-QPE; accuracy evaluation
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