基于关键对流参数分级的强对流潜势预报
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国家重点研发计划(2018YFC1507601)、上海市科委科研计划项目(16DZ1206100)和上海市气象局强对流创新团队共同资助


Severe Convective Potential Forecast Based on Key Convective Parameter Classification
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    摘要:

    通过对上海地区1998—2009年4—9月各类强对流天气的统计分析,选取42个对流参数及其时间变量,采用逐步回归方法建立了针对各类强对流天气的0~12 h潜势预报方程。在此基础上,提出了基于关键对流参数进行分级的强对流潜势预报方法,选取K〖WTBZ〗指数、SI〖WTBZ〗指数、PWV〖WTBZ〗(大气可降水含量)指数和θsedif85〖WTBZ〗(500 hPa和850 hPa假相当位温差)等反映大气热力和水汽条件的关键对流参数,根据对流分布情况将各对流参数分别分为3个等级,并分级建立了针对不同强对流天气的潜势预报方程。与未分级方程对比表明:基于关键对流参数分级的预报方程对雷雨大风、强雷电和所有对流等预报效果上有明显提升,采用如下组合评分更佳:雷雨大风的预报采用SI〖WTBZ〗分类方程,强雷电和所有对流采用PWV〖WTBZ〗分类方程。将基于关键对流参数分级的强对流潜势预报方法在数值预报模式中进行了业务应用,取得了较好效果。

    Abstract:

    Through the statistical analysis of different types of severe convective weather from April to September from 1998 to 2009 in Shanghai, a stepwise regression method is used to develop 0 to 12 hour potential forecast equations for all types of severe convective weather by using 42 convection parameters and their time variation. A new approach to convective potential forecasting based on the classification of four key convective parameters is designed. The key convective parameters are K index, SI, PWV (Precipitable Water Vapor) and θsedif85 (difference between 500 and 850 hPa in pseudo equivalent temperature), which depict the atmospheric thermal and water vapor conditions, respectively. According to the distributions of different types of convection, these four convective parameters are classified into 3 levels, and convective potential forecast equations are developed for each level, respectively. In comparison with the original equations, the forecast equations based on classified convective parameters are with dramatic increasing validity in the forecasting of thunderstorms, high winds, severe thunders and all types of convective weather. In addition, better performance would be granted with the following combinations: the classified SIbased equations for forecasting thunderstorms, classified PWVbased equations for forecasting severe thunder cases and all types of convective weather. The optimal combination method of severe convective potential forecasting based on the classification of key convection parameters has been used in routine application of numerical weather prediction model outputs.

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周方媛,戴建华,陈雷.基于关键对流参数分级的强对流潜势预报[J].气象科技,2020,48(2):229~241

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历史
  • 收稿日期:2019-04-01
  • 定稿日期:2019-08-27
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  • 在线发布日期: 2020-04-29
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