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淮北夏半年大风预报方法的建立及检验
引用本文:周后福,张永芹,孙金贺,张屏,王苏瑶,邓淑梅.淮北夏半年大风预报方法的建立及检验[J].气象与环境学报,2013,29(6):37-41.
作者姓名:周后福  张永芹  孙金贺  张屏  王苏瑶  邓淑梅
作者单位:1.安徽省气象科学研究所,安徽 合肥 230031;2.淮北市气象局,安徽 淮北 2350373;3.安徽省大气科学与卫星遥感重点实验室,安徽 合肥 230031
基金项目:国家自然科学基金“超级单体风暴结构和中气旋参数差异性研究”(41140036)和淮北市科技项目“灾害大风监测预报技术研发与示范”共同资助.
摘    要:利用T639业务数值模式预报场和大风观测资料,分别采用IW雷暴大风指数和多个对流指数方法,计算相对应的指标值,建立淮北市夏半年大风预报方法,得到淮北市大风的短期预报结果,并对2011年的预报应用情况进行检验。结果表明:基于T639业务数值模式的IW大风指数与多指标的叠加,实现夏半年定量和定性的大风预报。将多种不稳定指标与T639数值模式相结合的叠加预报,当4个指标中有3个满足条件时预报淮北有大风出现,否则没有大风;IW大风指数的风速预报与实际极大风速较为接近。两种预报方法对淮北市的大风预报具有较好的指导作用,多数大风天气能够预报准确,但是容易空报,不太容易漏报。

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Development and verification of a method for strong wind forecast during summer half year in Huaibei
ZHOU Hou-fu,ZHANG Yong-qin,SUN Jin-he,ZHANG Ping,WANG Su-yao,DENG Shu-mei.Development and verification of a method for strong wind forecast during summer half year in Huaibei[J].Journal of Meteorology and Environment,2013,29(6):37-41.
Authors:ZHOU Hou-fu  ZHANG Yong-qin  SUN Jin-he  ZHANG Ping  WANG Su-yao  DENG Shu-mei
Institution:1'3 ( 1. Anhui Institute of Meteorological Sciences, Hefei 230031, China; 2. Huaibei Meteorological Service, Huaibei 235037, China; 3. Anhui Key Laboratory of Atmospheric Sciences and Satellite Remote Sensing, Hefei 230031, China)
Abstract:Based on the forecast field from the T639 numerical model and observational wind data, some indexes such as Iw and other convective indexes were computed. A method for strong wind forecast during the summer half year was established in Huaibei, and the forecast results in 2011 were examined. The results show that quantitative and qualitative wind prediction results are achieved during the summer half year based on Iw index from the T639 numerical model and some other indexes. Combining the various indexes and the simulated value from the T639 model,if three indexes are satisfied among four indexes, the strong wind will appear in Huaibei, otherwise it will not occur. Forecasted wind speed by Iw index is relatively close to observational maximum wind speed. The two methods are indicative to strong wind forecast in Huaibei. Most strong wind weather could be forecasted accurate- ly, while the false alarm is significant and the missing forecast is not significant.
Keywords:Strong wind prediction  Iw index  MICAPS form
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