Spectrum of Near-Storm Environments for Significant Severe Right-Moving Supercells in the Contiguous United States

Spectrum of Near-Storm Environments for Significant Severe Right-Moving Supercells in the Contiguous United States
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美国本土严重右移超级单体的近风暴环境谱

DOI:
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发表时间:
2021
影响因子:
3.2
通讯作者:
Richard L. Thompson
Richard L. Thompson
中科院分区:
地球科学2区
文献类型:
--
作者:
R. Warren;H. Richter;Richard L. Thompson

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长期以来,近距离声音探索了温度,湿度和风的垂直结构如何影响对流风暴及其相关的危害,并在严重的雷暴研究中,对流参数通常用于总结一定的声音,而这些参数无法描述富裕的复杂性为了保留更多这些细节,本研究使用自组织图(SOM)根据其完整的垂直结构进行分组。导致一组九个hodograph和九个偏斜图代表了圆锥体中严重严重的右键超级细胞的近态环境,这表明这可以很好地表示关键的对流的变异性从相关的危害,与风暴模式和中clone强度的关系以及它们的空间和临时变异性方面的特征。
Proximity soundings have long been used to explore how the vertical structure of temperature, humidity, and winds influence convective storms and their associated hazards. In severe thunderstorm research and forecasting, convective parameters are often used to summarize certain characteristics of the sounding. While extremely useful, these parameters are unable to describe the rich complexity that is readily apparent in hodographs and skew-T diagrams. Motivated by a desire to retain more of these details, the present study uses self-organizing maps (SOMs) to group soundings based on their full vertical structure. The analysis makes use of a sample of more than 10,000 model proximity soundings for right-moving supercells associated with tornadoes and significant severe hail and straight-line winds in the Contiguous United States (CONUS). Separate SOMs are developed for the wind and thermodynamic profiles, each with 3×3 nodes, resulting in a set of nine hodographs and nine skew-T diagrams that broadly represent the spectrum of near-storm environments for significant severe right-moving supercells in the CONUS. Both SOMs are shown to provide a good representation of the variability in key convective parameters, although, for the thermodynamic SOM, variations in LCL heights and mid-level lapse rates are somewhat limited. Based on the soundings assigned to them, the SOM nodes are characterized in terms of their associated hazards, their relationship with storm mode and mesocyclone strength, and their spatial and temporal variability. Potential applications of the SOMs in severe weather forecasting and idealized numerical simulations are also highlighted.
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