曾明剑,王桂臣,吴海英,谌芸,李昕. 2015. 基于中尺度数值模式的分类强对流天气预报方法研究[J]. 气象学报, 73(5):868-882, doi:10.11676/qxxb2015.055
基于中尺度数值模式的分类强对流天气预报方法研究
Study of the forecasting method for the classified severe convection weather based on a meso-scale numerical model
投稿时间：2015-03-05  修订日期：2015-04-17
DOI：10.11676/qxxb2015.055
中文关键词:  强对流天气  对流参数  中尺度数值模式  分类预报方法
英文关键词:Severe convection  Convective parameters  Meso-scale numerical model  Classified forecasting method
基金项目:国家公益性行业(气象)科研专项(GYHY201206004)、江苏省科技支撑计划项目(BE2013730、BE2015731)、江苏省气象局重点科研基金项目(KZ201502)和国家科技支撑计划项目(2011BAK21B04)。
作者单位
曾明剑 江苏省气象科学研究所, 南京, 210009
中国气象局交通气象重点开发实验室, 南京, 210009 
王桂臣 江苏省连云港市气象台, 连云港, 222006 
吴海英 江苏省气象台, 南京, 210008 
谌芸 国家气象中心, 北京, 100081 
李昕 江苏省气象科学研究所, 南京, 210009
中国气象局交通气象重点开发实验室, 南京, 210009 
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中文摘要:
      针对雷暴大风、短时强降水、冰雹和龙卷等强对流天气短期预报,采用0.25°×0.2°每天4次日本气象厅(JMA)东亚地区再分析资料计算的百余类对流参数(物理量)及其15 d滑动平均值,根据“邻(临)近”原则对江苏2001—2009年2—9月各类强对流天气进行时间和站点的匹配后,应用相对偏差模糊矩阵评价技术,对上述对流参数进行权重分配和逐次筛选,获得了既体现强对流与气候平均态间明显差异,又体现自身相对稳定的特征对流参数序列。同时,根据历史分类强对流个例中各特征对流参数的频谱分布获得各对流参数的频率分布分段函数,然后基于中尺度数值模式预报的对流参数,综合历史频率分布和权重分配,构建了分类强对流天气预报概率,并以优势概率作为分类判据,做出强对流分类预报。最后建立了业务化系统,以全自动方式提供分类强对流客观预报产品,投入到日常业务和南京青年奥林匹克运动会气象保障服务工作。
英文摘要:
      For severe convective weather short-term forecasting of thunderstorm-gale, short-time severe rain, hail and tornado, the hundreds of convective parameters (physical quantities) and their 15 days moving average values were calculated based on the 0.25°×0.2° reanalysis data of the East Asia region from Japan Meteorological Agency (JMA), These parameters were adopted to gain the featured convective parameter sequence reflecting both the obvious difference between severe convection and climatic mean state and their own relative stability, after the time and site matching of the severe convective weather events during February to September 2001-2009 in Jiangsu Province with the proximity principle as well as the weight distribution and successive screening of the above parameters by the fuzzy relative deviation matrix evaluation technology. Meanwhile, according to the spectrum distribution of the featured convective parameters in the historical cases of classified severe convection, the piecewise function of the frequency distribution of the convective parameters was obtained. Then, the convective parameters forecasts were calculated with a meso-scale numerical model, and comprehensively considering the historical frequency distribution and weight allocation of the above parameters, the classified severe convective weather forecast probability was constructed. Taking the advantage probability as a classification criterion, the classified severe convective weather forecast was made. Finally, the operational system was established to provide objective forecast products of classified severe convection in a fully automatic mode to the daily business and meteorological service work of the Youth Olympic Games in Nanjing.
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