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    葫芦岛“8·20”特大暴雨过程中融合降水资料适用性对比评估

    Application assessment of merged precipitation data during the “8·20” torrential rainstorm in Huludao

    • 摘要: 针对辽宁省葫芦岛市2024年8月20—21日特大暴雨事件(简称“8·20”特大暴雨),选取相关系数、多种误差指标,采用分级和不分级两种评估方法,对比5种降水融合资料(C3SPA_1km、C3SPA_5km、C2SPA_5km、C3SPA_1km_10m、L2SPA_1km_10m)分别在站点数据不缺测和缺测情况下的反演能力。结果表明:5种降水融合资料对累计降水实况均表现出不同程度的低估;随着短时强降水级别增大,降水融合资料低估情况随之增加,C3SPA_1km和C3SPA_5km在不缺测情况下反演能力最好,但二者在缺测情况下反演效果下滑更明显,L2SPA_1km_10m相较而言影响较弱;C3SPA_1km和C3SPA_5km较C2SPA_5km改善明显,L2SPA_1km_10m反演效果差于三源资料,明显优于二源资料;站点最近格点不一定准确反演该站降水,可能距站点2~3个格距内有更接近实况的值;可以考虑研发降水融合小时产品,综合研判减少观测盲区低估问题。

       

      Abstract: The torrential rainstorm that occurred in the city of Huludao,Liaoning Province,on 20-21 August,2024 (referred to as the "8·20" torrential rainstorm) was selected. The applicability of five merged precipitation datasets (C3SPA_1km,C3SPA_5km,C2SPA_5km,C3SPA_1km_10m,L2SPA_1km_10m) in the extreme rainstorm is compared and evaluated by using hierarchical and non-hierarchical assessment under the conditions of complete and missing observation. The results show that five merged precipitation datasets underestimate the actual cumulative precipitation to varying degrees,with the level of short-term heavy precipitation increases,the underestimation of merged precipitation data increases. Among the five datasets,the 3-source 1km data and 3-source 5 km data have the best reconstructing ability under the conditions of complete observation,but their reconstructing ability decreased more significantly under missing observation condition.The 3-source 1 km data and 3-source 5 km data are significantly better than the 2-source 5 km data,the reconstructing ability of Liaoning 1km data is worse than that of the 3-source datasets,it is significantly better than that of the 2-source 5 km data.The nearest grid point may not always accurately reconstruct precipitation at a station,and there may be a more accurate precipitation value within 2 to 3 grids distances from the station. It is suggested that hourly merged precipitation product should be developed to improve assessments and reduce underestimation in observation blind areas.

       

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