基于SAL方法对四川盆地一次区域性暴雨过程多模式预报空间检验

Quantitative Verification for Multi-model Forecast of a Regional Heavy Rain Process in Sichuan Basin Based on SAL

  • 摘要: 针对2021年四川盆地一次区域性暴雨天气过程,对CMA_GFS、EC、SWC_WARM、SWC_WARR和EC集合预报高分辨率预报产品,用SAL方法进行检验对比。结果表明:EC集合预报对降水落区的结构把握最好,CMA_GFS预报的降水强度和实况观测最为接近,各个模式的位置预报误差都较小,其中SWC_WARM预报的降水落区位置最准确;TS评分与SAL检验结果有一定的联系,SAL单方面预报优势不能对应高TS评分,而三方面比较均衡时,TS评分较高;EC和CMA_GFS在结构、强度、位置的预报上有相对较好的稳定性,总体预报较为稳定,但08时起报的误差更小;而SWC_WARR三方面的预报随着时间临近预报误差越来越小,可为预报提供一定的参考性。

     

    Abstract: Aiming at a regional rainstorm weather process in Sichuan Basin in 2021, this paper uses SAL method to test and compare the high resolution forecast products of CMA_GFS, EC, SWC_WARM, SWC_WARR and EC ensemble forecast. The results shows EC ensemble forecast is the best in the structure prediction of rainfall area, and CMA_GFS is better in precipitation intensity prediction. The location prediction errors of all models are all small, and among them the error of SWC_WARM is minimal. There is a certain relationship between TS score and verified results by SAL, and the unilateral prediction advantage of SAL cannot correspond to the high TS score, while the TS score is higher when the three aspects of SAL are balanced. EC and CMA_GFS show better stability in the aspects of structure, intensity and location, and the overall prediction is relatively stable, but the error from 08: 00 is smaller. The prediction error of SWC_WARR is getting smaller and smaller over time, which can provide some reference for the prediction.

     

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