对三次浙江台风强降水过程的多模式预报评估

何牧; 余贞寿

doi:10.16032/j.issn.1004-4965.2025.070

对三次浙江台风强降水过程的多模式预报评估

doi: 10.16032/j.issn.1004-4965.2025.070

何牧^1,2,3,
余贞寿^2,3, ,

1. 贵州省山地气象科学研究所，贵阳 550081;
2. 浙江省气象科学研究所，杭州 310052;
3. 中国气象局新技术应用协同创新中心（浙江），杭州 310052

基金项目:

国家自然科学基金项目（U2342202）资助

详细信息

通讯作者:
余贞寿，男，浙江省人，硕士，研究员级高级工程师，主要从事灾害天气数值模拟与机理研究。E-mail：yuzhenshou@163.com

中图分类号: P426.62
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- 被引次数: 0
出版历程
- 收稿日期: 2024-07-25
- 修回日期: 2025-09-22
- 网络出版日期: 2025-09-25

Multiple Models Forecast Evaluation of Three Typhoon-induced Heavy Precipitation Events over Zhejiang Province

HE Mu^1,2,3,
YU Zhenshou^{2,3
, ,}

1. Guizhou Institute of Mountainous Environment and Climate, Guiyang 550081;
2. Zhejiang Institute of Meteorological Sciences, Hangzhou 310052;
3. China Meteorology Administration Collaborative Innovation Center on New Technology Application（Zhejiang）, Hangzhou 310052

摘要

摘要: 中国东南沿海地区台风强降水极易引发严重灾害，造成巨大的经济损失和人员伤亡。本文基于浙江省96个国家级观测台站的逐小时降水资料，评估了6个区域及3个全球业务数值天气预报模式在2021—2023年三次对浙江影响最大的台风强降水过程中的预报表现。结果表明，（1）对于24 h累计降水量，小雨及以上量级预报 ETS、综合评分方面区域模式略优于全球模式。而暴雨预报模式间差异较大，“烟花”和“杜苏芮”过程中ECMWF预报ETS最佳，“梅花”过程则为CMA-TRAMS9最好。（2）10 mm·(3h)^-1及以上强度降水是三次台风过程总降水的主要贡献者，3 km区域模式对该量级降水预报ETS略优于其余模式，其中CMA-MESO3对烟花和杜苏芮预报表现最好。（3）烟花和杜苏芮过程中，全球和区域模式均在浙江东部沿海台站预报出过多的降水，主要受模式中降水频率和强度高估的共同影响。各模式基本能预报出烟花登陆前降水的清晨峰值，但烟花登陆后降水日变化模式间预报差异较大，其中ECMWF、CMA-MESO3和CMA-BJ9对登陆后降水主峰值时间预报更为准确。而杜苏芮过程中，仅CMA-GD3对登陆后降水日变化的单峰结构和峰值时间预报最为准确，其余各模式对台风登陆前后降水日变化的预报均相对实况偏差明显。研究结果可为模式改进及台风预报服务提供一定参考。
- 台风降水 /
- 多模式 /
- 检验评估 /
- 短时强降水 /
- 降水量日变化
Abstract: The heavy precipitation which caused by typhoon may lead to huge societal and economic losses especially at coastal region of southeastern China. Based on the hourly rainfall data of 96 national stations in Zhejiang province, the ability of six regional and three global operational numerical weather prediction models for the typhoon-induced heavy precipitation during the 2021—2023 was evaluated. The results show: (1) for 24 hours accumulated precipitation, regional models demonstrate a higher Equitable threat score (ETS) and comprehensive scores in rainfall (greater than 0.1 mm) forecast than global models. While the obvious differences exist in torrential rain forecast. ECMWF shows the best ETS in the In-fa and Doksuri processes, while the CMA-TRAMS9 is the best for the Muifa. (2) precipitation with intensity higher than 10 mm · (3h)^-1 is the major contributor to accumulated precipitation. The ETS of 3 hours heavy precipitation shows that regional models with resolution of 3 km slightly outperform the other models, and CMA-MESO3 has the best skill during the In-fa and Doksuri. (3) Both global and regional models forecast excessive precipitation on eastern coast of Zhejiang during the In-fa and Doksuri. The overestimated precipitation frequency and intensity contributed to the positive bias of precipitation. All models can reasonably reproduce the early morning peak of precipitation amount before the landfall of In-fa, but the bias of the peak hour after the landfall of In-fa varies greatly between models, among which ECMWF, CMA-MESO3 and CMA-BJ9 are more accurate in predicting the main peak hour after landfall. On the other hand, the forecasts of the diurnal variation are worse in all models before and after the landfall of Doksuri except the CMA-GD3 after the landfall of Doksuri. The results can provide users with the bias features and accuracy of the precipitation forecast among operational models, which may be helpful in the improvement of model forecast skill and weather forecasting services.
- typhoon-induced precipitation /
- multi-model /
- Evaluation /
- short-term heavy precipitation /
- diurnal variation

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