李娜,冉令坤,孙建华,李耀东. 2015. 基于NCEP/GFS资料的中国东部地区雷暴预报研究[J]. 气象学报, 73(3):459-470, doi:10.11676/qxxb2015.029
基于NCEP/GFS资料的中国东部地区雷暴预报研究
Research of the thunderstorm forecast in East China based on the NCEP/GFS data
投稿时间:2014-10-23  修订日期:2015-01-05
DOI:10.11676/qxxb2015.029
中文关键词:  对流参数  雷暴  动力因子  暴雨
英文关键词:Convective parameters  Thunderstorm  Dynamic factors  Torrential rainfall
基金项目:中国科学院重点部署项目(KZZD-EW-05)、国家重点基础研究发展计划项目(2013CB430105)、北京市自然科学基金项目(8142035)、国家自然科学基金项目(41175060)、南京信息工程大学气象灾害教育部重点实验室开放课题(KLME1408)。
作者单位E-mail
李娜 中国科学院大气物理研究所, 北京, 100029
南京信息工程大学气象灾害教育部重点实验室, 南京, 210044 
 
冉令坤 中国科学院大气物理研究所, 北京, 100029 rlk@mail.iap.ac.cn 
孙建华 中国科学院大气物理研究所, 北京, 100029  
李耀东 北京航空气象研究所, 北京, 100085  
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中文摘要:
      基于来自美国国家环境预测中心(NCEP)的GFS(Global Forecasting System)分析及预报场资料,将多个能够表征雷暴发生动力、热力环境的对流因子作为预报因子,通过费希尔判别准则及逐个引入因子法,建立集合多个对流参数的雷暴预报模型,从而进行较长时效(12—24 h)的区域性雷暴预报。依据临界成功指数(CSI)最高的原则,建立最优预报模型,不同地区所选用的对流参数不同,雷暴模型预报雷暴发生与否的临界值也不同,从而不仅能够得到较好的集合多个对流参数的雷暴区域性预报,还能充分考虑不同地区雷暴发生的地域性特点和气候背景。将建立的预报方法应用于2012年6和9月的两次强对流过程的预报,发现雷暴预报模型较好地预报出两次过程的雷暴落区。进一步,为了能够在强天气预报中客观有效地区分出雷暴与暴雨区,引入集合动力因子暴雨预报方法。集合动力因子暴雨预报方法在诊断和追踪强降水的发展演变中表现凸出,而集合对流参数雷暴预报方法则对包含短时强降水、冰雹、大风等在内的对流性天气有较好反映,综合两套预报方法各自的优势,建立了集成动力因子-对流参数强天气预报方法,用于降水和雷暴的预报,同时对雷暴加降水型、雷暴无降水型、降水无雷暴型等强天气进行区分预报。对中国多个典型城市的预报效果分析发现,该方法不仅能够较好地预报出较长时效(24 h)的雷暴和降水落区,对区分降水雷暴、无降水雷暴和无雷暴降水也表现出一定的能力。
英文摘要:
      A study of a relatively long period (12 -24 h) regional thunderstorm forecast is carried out based on the GFS analysis and the forecasting data from NCEP (National Centers for Environmental Prediction). The prediction factors in this study come from the convective indices that are often used to examine the dynamic and thermodynamic environments of thunderstorm occurrence. With the highest CSI (critical success index) as a criterion, the discriminant analysis method and stepwise regression method are used to build the optimal thunderstorm model for each grid in the forecasting region. Therefore, thunderstorm models and the corresponding critical values for the discrimination of the thunderstorm occurrence would change with the location so that the local environment and climate background of the thunderstorm occurrence can be considered. The newly-built thunderstorm forecast method that ensembles the convective parameters (called "ECTF" method) is used for the prediction of the two thunderstorm processes which respectively occur on June and September 2012. The results show that this method can basically predict the area of thunderstorm in East China. Further, to discriminate occurrence of thunderstorm and torrential rain effectively and objectively, the "Ensemble Dynamic Factors precipitation Forecasting method (EDFF)" is introduced. The EDFF method performs well on the diagnosis and tracing of severe precipitation, while the ECTF method is more capable of reflecting the convective weather, such as flash floods, hail, high wind and so on. Extracting the advantages of these two methods, they are integrated and an "integrated dynamic factors-convective parameters severe weather forecasting method" is built, which can be used in the forecast of precipitation and thunderstorm and can also discriminate, to some extent, among the precipitating thunderstorm, the non-precipitating thunderstorm and the non-thunderstorm precipitation.
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