华南前汛期降水延伸期预报的研究进展

胡娅敏; 丁一汇; 姜晓岑; 谢洁宏; 王娟怀; 汪明圣; 杜晖; 雷旗浩

doi:10.16032/j.issn.1004-4965.2025.051

华南前汛期降水延伸期预报的研究进展

doi: 10.16032/j.issn.1004-4965.2025.051

1.
广东省气候中心，广东广州 510641
2.
国家气候中心，北京 100081
3.
东莞市气象局，广东东莞 523082
4.
中山大学大气科学学院，广东珠海 519082

基金项目:

广东省基础与应用基础研究重大专项 2020B0301030004

国家自然科学基金项目 U2142205

国家自然科学基金项目 42075173

中国气象局创新发展专项基金项目 CXFZ2023J027

中国气象局复盘总结专项 FPZJ2025-096

广东省气象联合基金项目 2024A1515510011

详细信息

通讯作者:
丁一汇，男，山东省人，研究员，主要从事灾害性天气气候预测研究。E-mail: dingyh@cma.gov.cn

中图分类号: P426.613
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- 被引次数: 0
出版历程
- 收稿日期: 2024-04-08
- 修回日期: 2025-07-18
- 网络出版日期: 2025-11-26
- 刊出日期: 2025-10-20

A Review on Extended-range Precipitation Forecast During the First Rainy Season over South China

1.
Guangdong Climate Center, Guangzhou 510641, China
2.
National Climate Center, Beijing 100081, China
3.
Dongguan Meteorological Bureau, Dongguan, Guangdong 523082, China
4.
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, Guangdong 519082, China

摘要

摘要: 华南前汛期降水量大，且常出现持续3天以上、甚至长达10天以上的持续性强降水事件(Persistent Heavy Rainfall Event，PHRE)，给该地区带来严重的洪涝灾害，提升前汛期降水的延伸期(提前10~30天或2~6候)预报水平至关重要。重点论述华南降水延伸期预报可预报性的来源，以及当前数值模式、动力-统计释用和机器学习在延伸期预报领域的应用情况，以期了解华南前汛期降水延伸期预报的主要进展。
- 华南前汛期 /
- 持续性强降水 /
- 延伸期预报 /
- 人工智能 /
- 机器学习 /
- 深度学习
Abstract: The first rainy season precipitation in South China is often characterized by heavy rainfall events lasting for more than 3 days, and even up to 10 days or more. These events, known as Persistent Heavy Rainfall Events (PHRE), result in severe flooding disasters in the region. Improving extended-range (10-30 days or 2-6 weeks in advance) precipitation forecast skill for the first rainy season is crucial. This paper focuses on the precipitation predictability sources of the first rainy season in South china, as well as the current application of numerical models, dynamical-statistical downscaling, and machine learning in the field of extended-range forecasting. The aim is to synthesize major advancements in extended-range precipitation forecasting for the first rainy season in South China.
- the first-rainy season in South China /
- Persistent Heavy Rainfall Events(PHRE) /
- extendedrange forecasting /
- artificial intelligence /
- machine learning /
- deep learning

HTML全文

图 1 ECMWF S2S模式集合平均预测全球降水距平的时间相关分布图

预报时效为1~4周^[117]。

下载: 全尺寸图片幻灯片

图 2 ECMWF S2S(第1列)、FuXi-S2S(第2列)、FuXi-S2S和ECMWFS2S的差值(第3列)提前第3~4周 (第1行和第3行)和第5~6周(第2行和第4行)预测总降水量的平均排名概率技能得分(RPSS)(第1行和第2行)和Brier技能得分(BSS)(第3行和第4行)的对比^[80]

下载: 全尺寸图片幻灯片

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