Optimal Identification Method of Squall Line and Thunderstorm Winds Analysis

  • LI Zhe ,
  • LI Guocui ,
  • LIU Liping ,
  • YANG Ji
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  • State Grid henan Electric Power Research Institute, Zhengzhou 450052, China;State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China;Shijiazhuang Meteorological Bureau, Shijiazhuang 050081, China;Jiangsu Institute of Meteorological of Sciences, Nanjing 210009, China

Received date: 2015-12-08

  Online published: 2017-06-28

Abstract

Squall line is an important system to produce thunderstorm wind, which has great strength and wide influence. Based on automatic identification of linear mesoscale convective system, optimal identification method of squall line is put forward. The main parameters are reflectivity factor, long axis length, area and linear degree. The radar echo is identified by using four groups single parameters, reflectivity factor is increased by 5 dBZ. It is the best result of optimal identification which has high linear degree and strongest echo. The performance of the method is evaluated and the corresponding wind is analyzed based on 140 body scan and 126 squall lines, the results show:The optimal identification method can identify strong and weak squall line at the same time, really response squall line at different stages of development, and the effect is improved more obviously than single parameter method. The hit rate of optimal identification method is improved 26. 3%, 10%, 40% and 89% than the method of four groups single parameters identification. Strong thunderstorm winds occur in strong echo band of squall line, bow echo edge and the gap between different storms, the area of squall line recognition and disaster winds is quite similar, and it can be used as a gale warning area. The wind direction of squall line is mostly along the moving direction of the storm.

Cite this article

LI Zhe , LI Guocui , LIU Liping , YANG Ji . Optimal Identification Method of Squall Line and Thunderstorm Winds Analysis[J]. Plateau Meteorology, 2017 , 36(3) : 801 -810 . DOI: 10.7522/j.issn.1000-0534.2016.00040

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