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投稿时间：2020-08-10 修订日期：2021-03-23
投稿时间：2020-08-10 修订日期：2021-03-23
中文摘要: 下击暴流是对流风暴最常发生的天气现象，预报其初始爆发是强对流风暴预报中最具挑战性的内容之一。提出一种综合使用雷达和探空观测资料的下击暴流临近预报算法。在对雷达基数据进行地物杂波抑制和径向速度退模糊以及对探空资料进行处理得到0℃、-20℃和最小相当位温高度的基础上，该算法首先进行风暴单体识别追踪和冰雹指数的计算；然后进行中层径向辐合特征和中气旋识别，并使之与识别的风暴单体相关联；最后提取诸多风暴单体的雷达特征量，经批量下击暴流和非下击暴流个例统计分析后挑选出下击暴流的雷达先兆因子9个作为模糊逻辑法的输入，建立下击暴流临近预报方程。使用2015年6月1日发生在湖北监利导致“东方之星”客轮倾覆的下击暴流个例对该算法进行了测试，结果表明从20:41—21:21共有8个体扫时次预报了引起沉船事件的那个风暴单体将会产生下击暴流，首次预报时间比客轮侧翻时间21:28 早47 min。使用2019年6—8月发生在湖北省的所有雷暴大风个例对下击暴流临近预报算法进行了效果评估,结果表明该算法预报下击暴流的击中率为86.4%，平均预报时效为39 min。按回波形态分类评估，则飑线类、线状对流类（飑线除外）和非线状对流类风暴的下击暴流临近预报击中率分别为93.2%、90.5%和75.6%。该算法模块已集成到中国气象局武汉暴雨研究所研发的分类强对流天气自动识别预警系统中，并于2019年开始投入业务运行。
中文关键词: 下击暴流，临近预报算法，天气雷达
Abstract:Downburst is the most common weather phenomenon of convective storm, and forecasting its initial outbreak is one of the most challenging contents in severe convective storm forecasting. In this paper, a downburst nowcasting algorithm based on radar and radiosonde observation data was proposed. On the basis of ground clutter suppression and radial velocity dealiasing of radar base data and processing of sounding data to obtain 0℃, -20℃ and minimum equivalent potential temperature heights, the algorithm first identifies and tracks storm cells and calculates the hail indexes, then identifies the mid-level radial convergence characteristics and mesocyclone, making them associated with the identified storm cell. After that, many radar characteristics of storm cells are extracted. After statistical analysis of downburst and non-downburst cases, nine radar precursor factors of downburst were selected as the input of fuzzy logic method, and the nowcasting equation of downburst was established. The algorithm was tested with a downburst case which occurred in Jianli of Hubei Province on 1 June 2015, responsible for the “Oriental Star” cruise ship capsizing. The results show that the algorithm has predicted 8 times in 20:41-21:21 BT that the storm cell having caused the shipwreck will produce downburst. The first prediction time is 47 minutes earlier than that of the cruise ship capsizing at 21:28 BT. In addition, the effectiveness of the downburst nowcasting algorithm was evaluated by using all thunderstorm gales in Hubei Province from June to August 2019. The results show that the hit rate of downburst is 86.4%, and the average forecast time is 39 min. According to the echo pattern, the hit rates of downburst nowcasting for squall line, linear convection and non-linear convection are 93.2%, 90.5% and 75.6%, respectively. Actually, the algorithm module has been integrated into the automatic identification and warning system of classified severe convective weather developed by Wuhan Institute of Heavy Rain of CMA, and has been put into operation since 2019. The algorithm will be continuously optimized in the forecasting operation application in the future.
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基金项目:国家重点研发计划（2018YFC1507503和2016YFE0109400）共同资助
引用文本：
肖艳姣,王珏,王志斌,冷亮,付志康,2021.基于S波段新一代天气雷达观测的下击暴流临近预报方法[J].气象,47(8):919-931.
XIAO Yanjiao,WANG Jue,WANG Zhibin,LENG Liang,FU Zhikang,2021.A Downburst Nowcasting Method Based on Observations of S-Band New Generation Weather Radar[J].Meteor Mon,47(8):919-931.
肖艳姣,王珏,王志斌,冷亮,付志康,2021.基于S波段新一代天气雷达观测的下击暴流临近预报方法[J].气象,47(8):919-931.
XIAO Yanjiao,WANG Jue,WANG Zhibin,LENG Liang,FU Zhikang,2021.A Downburst Nowcasting Method Based on Observations of S-Band New Generation Weather Radar[J].Meteor Mon,47(8):919-931.
