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鲁西南一次春季大雾天气特征分析及探讨
引用本文:李芳,郭卫华,赵京峰,李永果,李莉,张方方.鲁西南一次春季大雾天气特征分析及探讨[J].中国农学通报,2014,30(5):268-271.
作者姓名:李芳  郭卫华  赵京峰  李永果  李莉  张方方
作者单位:1. 济宁市气象局2. 山东省济宁市气象局3. 江苏省徐州市气象局
基金项目:山东省气象局专项项目,近10年鲁西南大雾天气研究
摘    要:为了进一步提高鲁西南大雾的预报准确率,利用常规观测资料、数值预报和卫星云图资料,分析了2012年3月17日鲁西南大雾的成因。结果表明:(1)逆温层的高度及强度与雾的浓度关系密切,弱冷暖平流有利于产生雾;(2)近地层1000 hPa的相对湿度变化对大雾的影响最明显,当近地面层存在明显逆温层,且1000 hPa相对湿度≥80%时,地面上容易出现大雾;(3)地面温度露点差(T-Td)≤2℃时,近地面易产生大雾;(4)模式产品能提供雾形成的环境条件;(5)红外云图、可见光云图有助于预测雾的形成、发展、消散过程。

关 键 词:生物表面活性剂  生物表面活性剂  
收稿时间:4/7/2013 12:00:00 AM
修稿时间:7/2/2013 12:00:00 AM

Analysis and Study on the Features of A Spring Dense Fog Weather in Southwest Shandong Province
Li Fang,Li Yongguo,Guo Weihua,Zhao Jingfeng,Li Li,Zhang Fangfang.Analysis and Study on the Features of A Spring Dense Fog Weather in Southwest Shandong Province[J].Chinese Agricultural Science Bulletin,2014,30(5):268-271.
Authors:Li Fang  Li Yongguo  Guo Weihua  Zhao Jingfeng  Li Li  Zhang Fangfang
Institution:1 Jining Meteorological Bureau of Shandong Province, Jining Shandong 272000; 2Xuzhou Meteorological Bureau of Jiangsu Province, Xuzhou Jiangsu 221000)
Abstract:In order to improve the forecast accuracy of fog in southwest Shandong, by using conventional observation data, numerical prediction model products and satellite cloud image, the causes of the heavy fog in March 17, 2012 at Jining City was analyzed .The results showed that: (1) the height and strength of inversion layer had close relationship with the concentration of fog, the weak cold and warm advection might be beneficial to produced fog; (2) The heavy fog showed significant influence from the change of relative humidity on 1000 hPa, the fog would occur if the surface layer had inversion and relative humidity≥80% on 1000 hPa; (3) The dew-point deficit in land (T-T d)≤2℃ could easily produce the heavy fog; (4) The environmental condition of forming fog provided by numerical forecasting pattern products; (5) Infrared images and visible cloud picture were helpful to prediction the formation, development, dissipation of fog.
Keywords:physical diagnostic
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