| 摘要: |
| 【目的】为衡量不同数值模式对盆地南部暴雨过程的预报能力。【方法】利用中国智能网格三源融合降水产品(CMPAS)，针对SCMOC、ECthin和CMA-MESO模式对盆地南部2020—2021年23次暴雨过程进行SAL检验和精细化预报检验。【结果】（1）SCMOC、ECthin和CMA-MESO模式对盆地南部暴雨过程的降水范围预报均偏大（S>0），ECthin和CMA-MESO模式08时起报对降水结构预报最优；ECthin对降水强度预报偏小(A<0)，SCMOC和CMA-MESO模式对降水强度预报偏大(A>0)，且ECthin08时起报降水强度预报偏差最小；（2）对于大雨量级以上降水预报的TS检验，各模式不同起报时次的TS评分均呈单峰型，23—02时TS评分最高，14—20时之间的评分较低；（3）各模式对泸州降水频率预报较好，但对自贡和宜宾降水频率中心区域预报显著偏南；（4）ECthin和SCMOC对降水的最易开始和结束时间预报偏差基本在3 h（1个时效）以内，以SCMOC08时起报对盆地南部降水开始和结束时间预报最好，但对偏南区域的降水结束时间预报偏早。【结论】该研究深入分析了不同模式对盆地南部暴雨过程的预报特征，对提高强降水的精细化预报能力有一定的指导意义。 |
| 关键词: CMPAS;SAL检验;精细化检验 |
| DOI： |
| 投稿时间：2023-11-07修订日期：2024-06-18 |
| 基金项目:(SCQXKJQN202107)：基于CLDAS格点实况的盆地南部强降雨预报检验。 |
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| The SAL and Refined verification on multi-model heavy rainfall forecast in southern Sichuan Basin from 2020 to 2021 |
| yuqinkun,XU Yuan,OU Yihan,LI Yuchun |
| (Zigong meteorological observatory;Ganzi meteorological observatory) |
| Abstract: |
| Abstract: In order to measure the forecasting capability of different numerical models for heavy rainfall processes in the southern Sichuan Basin, SAL and refined forecast verification were compared in 23 precipitation processes for a 2-year (2020—2021) period based on the CMA Multi-source Precipitation Analysis System (CMPAS) data. The results show that: (1) the SCMOC, ECthin and CMA-MESO models all overestimated the precipitation area (S>0), with ECthin and CMA-MESO showing the best performance in forecasting the precipitation structure starting from 08:00. ECthin underestimated the precipitation intensity (A<0), while SCMOC and CMA-MESO overestimated it (A>0), with ECthin having the smallest deviation in precipitation intensity forecasting starting from 08:00. (2) For precipitation forecasts above the large rainfall threshold, the Threat Score (TS) for each model were unimodal, with the highest scores occurring between 23:00 and 02:00, and the lowest scores occurring between 14:00 and 20:00. (3) All models performed well in forecasting the precipitation frequency in Luzhou, but their predictions for the central regions of precipitation frequency in Zigong and Yibin are significantly southward. (4) ECthin and SCMOC had biases within 3 hours (1 time interval) for the most likely start and end times of precipitation, with SCMOC at 08:00 showing the best performance in forecasting the start and end times of precipitation in the southern Sichuan Basin, but tends to forecast the end of precipitation too early in the more southern regions. The research provides an in-depth analysis of the forecasting characteristics of different models for heavy rainfall processes in the southern Sichuan Basin, offering guidance for improving the refined forecasting capability of intense precipitation. |
| Key words: CMPAS; SAL test; Refined test |
