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张立凤. 2024. 暴雨数值预报若干关键技术发展的回顾与思考[J]. 暴雨灾害, 43(3): 243-254. DOI: 10.12406/byzh.2023-230
引用本文: 张立凤. 2024. 暴雨数值预报若干关键技术发展的回顾与思考[J]. 暴雨灾害, 43(3): 243-254. DOI: 10.12406/byzh.2023-230
ZHANG Lifeng. 2024. Review and thinking on the development of several key technologies for heavy rainfall numerical weather prediction[J]. Torrential Rain and Disasters, 43(3): 243-254. DOI: 10.12406/byzh.2023-230
Citation: ZHANG Lifeng. 2024. Review and thinking on the development of several key technologies for heavy rainfall numerical weather prediction[J]. Torrential Rain and Disasters, 43(3): 243-254. DOI: 10.12406/byzh.2023-230

暴雨数值预报若干关键技术发展的回顾与思考

Review and thinking on the development of several key technologies for heavy rainfall numerical weather prediction

  • 摘要: 暴雨是导致洪涝灾害的重要天气,也是发生在我国的最主要自然灾害之一。随着高分辨率数值模式的发展,数值预报已成为暴雨预报的主要手段,然而数值预报的精度依赖于大气运动方程组的完备性、初始状态的准确性、物理过程的合理性以及计算方法的稳定性。由于大气是非线性的混沌系统,这些方面微小的误差均会产生预报结果的很大不确定性。因此,提升暴雨数值预报水平与资料同化、物理过程参数化和集合预报等技术和方法的发展密切相关,特别是产生降水的云微物理过程参数化方案在数值模式中的作用很重要。此外,为改进和完善数值模式,预报结果的评估方法研究也是暴雨数值预报技术研究不可缺少的重要内容。本文主要回顾了暴雨数值预报若干关键技术的发展,重点介绍了四维集合变分同化方法、云微物理参数化方案、集合预报模式扰动的后向动能散射方法,并提出了基于动能谱分析的模式结果评估方法,最后凝练出了这几个方面未来研究的方向。

     

    Abstract: Heavy rainfall is an important weather that causes flood disasters, and it is also one of the most important natural disasters in our country. With development of the high-resolution numerical models, numerical weather prediction has been the main method for heavy rainfall forecasting. However, the accuracy of the numerical prediction depends on the completeness of the atmospheric motion equations, the accuracy of the initial state, the reasonability of the physical process, and the robustness of the calculation method. As the atmosphere is a nonlinear chaotic system, the small errors in these aspects will cause significant uncertainty in the forecast results. Therefore, the improvement of the rainstorm numerical prediction is closely related to the development of data assimilation, parameterization of physical processes, and ensemble prediction, especially for the role of parameterization schemes of cloud microphysical processes that produce precipitation in numerical models. In addition, in order to improve and perfect the numerical model, the investigation of the evaluation method of the forecast results can also not be ignored and is a crucial part of the numerical prediction. This review describes the development of several key numerical weather prediction techniques. The four-dimensional ensemble variational assimilation method, the microphysics parameterization scheme, and the stochastic kinetic energy backscatter method of ensemble prediction model perturbation are highlighted. An evaluation method of model results based on kinetic energy spectrum analysis is also proposed. Finally, the future research directions in these aspects are summarized.

     

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