Research Progress on the Spatial and Temporal Distribution, Formation Mechanism and Forecasting Methods of Severe Convective Wind

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  • (1. Key Laboratory of Cloud-Precipitation Physics and Severe Storms (LACS), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; 2. University of the Chinese Academy of Sciences, Beijing 100049, China; 3. National Meteorological Center, Beijing 100081, China; 4. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081; 5. Anhui Meteorological Observatory, Hefei 230031, China)
First author: SUN Jianhua, research areas include mesoscale meteorology and disaster weather. E-mail: sjh@mail.iap.ac.cn

Online published: 2024-12-19

Supported by

Project supported by the National Natural Science Program (Grant No. 42375008); The Beijing Municipal Natural Science Foundation (Grant No. 8222079); Jianghuai Meteorological Joint Project of Anhui Natural Science Foundation (Grant No. 2208085UQ11).

Abstract

Abstract:To improve the understanding of the formation mechanism and forecast accuracy of severe convective winds(SCWs), the important achievements of the formation mechanism and forecasting methods of severe convective winds and related convective systems were reviewed. Firstly, the spatial and temporal distribution characteristics of severe convective wind in the world are briefly introduced. SCWs in China mainly occur in the eastern region, with high-frequency areas in northern North China, central and southern Northeast China, and Guangdong Province. Then, the relationship between the organizational modes and structural features of the parent convective systems that generates SCWs, the influence of atmospheric environmental conditions, forecasting methods are summarized. Squall lines and bow echoes are important convective systems that generate SCWs, especially strong SCWs. The rear inflow jet and meso-γ-scale vortices in squall lines or bow echoes are important structural features that generate SCWs. The environmental conditions and forecasting methods for SCWs are summarized. The environmental thermal and dynamic factors can affect the generation and intensity of SCWs, but the intensity of convective activity mainly depends on the covariant relationship between convective effective potential energy and vertical wind shear. Numerical model forecasting, physics-based methods (ingredients-based method), and deep learning/machine learning methods are currently the main methods used in short-term forecasting operations for SCWs. Finally, it is indicated that the following issues associated with SCWs in China should be studied, including detailed spatiotemporal distribution characteristics, formation mechanisms of SCWs under different environmental conditions, and forecasting methods.

Cite this article

SUN Jianhua, TIAN Fuyou, XIA Rudi, ZHENG Linlin, HUANG Yue . Research Progress on the Spatial and Temporal Distribution, Formation Mechanism and Forecasting Methods of Severe Convective Wind[J]. Advances in Earth Science, 0 : 1 . DOI: 10.11867/j.issn.1001-8166.2024.082.

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