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环渤海地区雾天气分型及预报方法 被引量:11

Classification of Fog Synoptic Situation and Forecasting Method Around Bohai Sea Coastal Areas
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摘要 利用环渤海地区常规气象观测资料和NCEP位势高度、风速再分析资料,采用天气学方法分析了环渤海地区雾天气过程。结果表明:环渤海区域性雾天气出现时500 hPa高空天气形势有3种:纬向气流型、低槽型、高压脊型;地面形势有4种:锋面气旋型、高压前部型、均压场型、弱高压型。针对天气形势的槽脊和高、低压中心等特点设计客观自动识别系统,进而基于T639模式输出产品计算了多个水汽条件、层结稳定条件和风速条件因子,经过诊断分析及相关分析后选取1000 hPa温度露点差、1000 hPa风速、925与850 hPa温度差和M指数4个参数作为物理量诊断因子,建立天气形势自动识别与T639模式输出物理量诊断相结合的预报系统,给出环渤海地区雾天气出现时间和空间范围未来1~3 d的预报,试验结果表明取得了较好效果。 Based on the conventional observation data, NCEP geopotential height and wind reanalysis data from National Centers for Environmental Prediction, the process of fog is analyzed by taking use of the method of synoptic meteorology. It turns out that there are three types of synoptic situation at 500 hPa when the regional fog around the Bohai Sea coastal areas occurs, which are zonal flow, low trough, high pressure ridge, and four types of surface synoptic situation, which are frontal cyclone, high pressure forepart, uniform pressure field and weak high pressure. According to the characteristics of the ridges and troughs, high and low pressure centers, an objective thermore, multiple moisture condition, stratification and automatic identification system is designed. Furstability condition and wind speed condition are calculated on the basis of T639 model output. The 1000 hPa depression of dew point, 1000 hPa wind speed, temperature difference between 925 hPa and 850 hPa, and M index are selected as physical diagnosis factors after diagnostic and correlation analyses. Thus, a forecasting system combining automatic identification of synoptic situation and T639 is established, which can forecast the space and time of the fog around the Bohai Sea coastal areas within the next 1-3 days. Experimental results show that good results have been achieved.
出处 《气象》 CSCD 北大核心 2017年第1期46-55,共10页 Meteorological Monthly
基金 中国气象局北京城市气象研究所项目(20141125) 国家基础科技条件平台建设专项(NCMI-SBS17-201607 2016NCMIZX09和NCMISJSIS-201607) 公益性行业(气象)科研专项(GYHY201306047) 中国科学技术协会灾害风险综合研究项目(IRDR2012-I01) 中国科学院与发展中国家科学院空间减灾卓越中心国际合作研究项目(常规类)(SDIM-Y3YI2701KB)共同资助
关键词 T639数值产品 天气形势 自动识别 预报 fog, T639 output, synoptic situation, automatic identification, forecast
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