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夏丽花, 于超, 何小宁, 陈德花, 黄美金. 2012: 福建一次持续性强对流天气过程诊断分析. 暴雨灾害, 31(3): 280-286.
引用本文: 夏丽花, 于超, 何小宁, 陈德花, 黄美金. 2012: 福建一次持续性强对流天气过程诊断分析. 暴雨灾害, 31(3): 280-286.
XIA Lihua, YU Chao, HE Xiaoning, CHEN Dehua, HUANG Meijin. 2012: Diagnostic analysis of a persistent severe convective weather process in Fujian province. Torrential Rain and Disasters, 31(3): 280-286.
Citation: XIA Lihua, YU Chao, HE Xiaoning, CHEN Dehua, HUANG Meijin. 2012: Diagnostic analysis of a persistent severe convective weather process in Fujian province. Torrential Rain and Disasters, 31(3): 280-286.

福建一次持续性强对流天气过程诊断分析

Diagnostic analysis of a persistent severe convective weather process in Fujian province

  • 摘要:  利用加密地面观测资料、 自动站资料、 常规观测资料和NCEP再分析资料, 分析了2012年4月10—12日福建省持续性强对流天气过程的形成机制。结果表明, 此强对流天气过程是在稳定的大尺度环流背景条件下产生的, 低层辐合和高层辐散相叠置、 良好的水汽输送、 大气层结不稳定和高CAPE值为强对流发展提供了必要的热动力条件; 地面中尺度辐合线触发对流发展, 而中层冷空气的侵入加剧了大气层结的不稳定, 使对流发展加强; 最大上升运动中心高于0 ℃层高度以及强的风垂直切变, 有利于冰雹形成。强对流天气潜势预报分析和卫星、 雷达及自动站资料的跟踪分析是做好强对流天气预报预警的有效方法。

     

    Abstract: This paper analyzes the formation mechanism of strong convective weather in Fujian 10-12 April 2012 by using the intensive ground observation data, automatic station data, conventional observation data and the reanalysis data of NCEP. The results show that this severe convective weather process occurred against the stable large-scale circulation background. The superposition of low-level convergence and upper level divergence, the good water vapor transmission, the unstable atmospheric stratification and the high CAPE value provided the necessary thermodynamic conditions for the development of strong convection. The surface mesoscale convergence line touched off the development of convection, and the invasion of middle-level cold air increased the instability of atmospheric stratification strengthening the development of convection. The maximum upward motion level of the center was higher than 0 ℃ level and strong vertical wind shear are conducive to the formation of hail. The potential forecast analysis of severe convective weather and the trace analysis with satellite, radar and automatic station data are an effective way to do severe convective weather forecast warning.

     

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