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气象:2017,43(1):46-55
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环渤海地区雾天气分型及预报方法
(1.兰州大学大气科学学院,甘肃省干旱气候变化与减灾重点实验室,兰州 730000 中国人民解放军65061部队,沈阳 110027 中国科学院遥感与数字地球研究所,北京 100094;2.兰州大学大气科学学院,甘肃省干旱气候变化与减灾重点实验室,兰州 730000;3.中国科学院遥感与数字地球研究所,北京 100094;4.兰州大学大气科学学院,甘肃省干旱气候变化与减灾重点实验室,兰州 730000 成都信息工程大学大气科学学院,成都 610103;5.中国人民解放军93123部队,辽阳 111000)
Classification of Fog Synoptic Situation and Forecasting Method Around Bohai Sea Coastal Areas
(1.College of Atmospheric Sciences, Lanzhou University, Key Laboratory of Arid Climatic Change and  Disaster Mitigation of Gansu Province, Lanzhou 730000 Unit 65061 of PLA, Shenyang 110027 Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094;2.College of Atmospheric Sciences, Lanzhou University, Key Laboratory of Arid Climatic Change and  〓Disaster Mitigation of Gansu Province, Lanzhou 730000;3.Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094;4.School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610103College of Atmospheric Sciences, Lanzhou University, Key Laboratory of Arid Climatic Change and  〓Disaster Mitigation of Gansu Province, Lanzhou 730000;5.Unit 93123 of PLA, Liaoyang 111000)
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投稿时间:2015-11-21    修订日期:2016-10-25
中文摘要: 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。
Abstract: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 and automatic identification system is designed. Furthermore, multiple moisture condition, stratification stability 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.
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基金项目: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NCMI SJSIS 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)及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
引用文本:
陈东辉,尚子溦,宁贵财,冯强,尚可政,王式功,曹建奎,2017.环渤海地区雾天气分型及预报方法[J].气象,43(1):46-55.
CHEN Donghui,SHANG Ziwei,NING Guicai,FENG Qiang,SHANG Kezheng,WANG Shigong,CAO Jiankui,2017.Classification of Fog Synoptic Situation and Forecasting Method Around Bohai Sea Coastal Areas[J].Meteor Mon,43(1):46-55.