热带气旋降水模拟研究进展及展望

苏鹏; 徐伟; 陶凯; 翟广然; 廖新利; 孟晨娜

doi:10.13928/j.cnki.wrahe.2025.05.010

水利水电技术（中英文） ›› 2025, Vol. 56 ›› Issue (5) : 123 -133. DOI: 10.13928/j.cnki.wrahe.2025.05.010

水文水资源

热带气旋降水模拟研究进展及展望

苏鹏 ¹^,²^,³ ,
徐伟 ¹^,²^,³^,⁴ ,
陶凯 ¹^,²^,³ ,
翟广然 ¹^,²^,³ ,
廖新利 ¹^,²^,³ ,
孟晨娜 ¹^,²^,³

作者信息 +

Research progress and prospects of tropical cyclone precipitation modelling

Peng SU ¹^,²^,³ ,
Wei XU ¹^,²^,³^,⁴ ,
Kai TAO ¹^,²^,³ ,
Guangran ZHAI ¹^,²^,³ ,
Xinli LIAO ¹^,²^,³ ,
Chenna MENG ¹^,²^,³

Author information +

文章历史 +

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摘要

【目的】热带气旋降水模拟评估是热带气旋预警和风险评估的基础。针对热带气旋降水模拟方法差异不清等问题，【方法】通过文献分析，从热带气旋数值天气预报模型、统计模型、物理模型和机器学习模型角度，系统综述了四类模型的特点、进展、适用性以及代表模型，并进行对比分析，最后对四类模型的发展做出建议与展望。【结果】结果表明：数值天气预报模型模拟信度较高，适用于热带气旋降水的预报工作；统计模型能够构建大量仿真热带气旋，适用于热带气旋降水重现期的估计；物理模型能在简化计算的基础上，较好地解释热带气旋降水物理机制；机器学习模型灵活性强，能和其他模型组合使用，具有较高的发展潜力。【结论】未来除进一步完善相关模型外，还需加强降水与次生灾害之间的协同以及新技术在降水模拟上的应用，实现热带气旋降水的快速与精准预估，更好地为区域热带气旋预警和风险防范提供支撑。

Abstract

[Objective] The modelling and assessment of tropical cyclone precipitation serves as the foundation for tropical cyclone warning and risk evaluation. This paper aims to address issues such as unclear differences in tropical cyclone precipitation modelling method. [Methods] Through literature review, this paper provides a systematic review of the characteristics, progress, applicability, and representative models of four types of models, including numerical weather prediction models, statistical models, physical models, and machine learning models. A comparative analysis is conducted, followed by suggestions and prospects for the development of these four types of models. [Results] The results show that numerical weather prediction models have high reliability and are suitable for forecasting tropical cyclone precipitation. Statistical models can generate numerous simulated tropical cyclones, making them suitable for estimating precipitation return periods. Physical models, based on simplified calculations, provide a good explanation for the mechanisms of tropical cyclone precipitation. Machine learning models exhibit strong flexibility and can be integrated with other models, showing significant potential for future development. [Conclusion] In the future, in addition to further improving relevant models, it is essential to strengthen the synergy between precipitation and secondary disasters, as well as the application of new technologies in precipitation modelling. This can enable rapid and accurate estimation of tropical cyclone precipitation, providing better support for regional tropical cyclone warning and risk prevention.