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| 精细化监测资料在山西暴雨预报模型改进中的应用 | |
| 引用本文： | 苗爱梅,郝振荣,贾利冬,李苗,逯张禹,韩龙.精细化监测资料在山西暴雨预报模型改进中的应用[J].气象,2012,38(7):786-794. |
| 作者姓名： | 苗爱梅 郝振荣 贾利冬 李苗 逯张禹 韩龙 |
| 作者单位： | 1. 山西省气象台,太原,030006 2. 山西省气象信息中心,太原,030006 3. 山西省气象局,太原,030002 4. 山西省气象服务中心,太原,030002 5. 山西省农业科学院农业科技信息研究所,太原,030006 |
| 基金项目： | 山西省科技攻关项目（20090311083）、公益性行业(气象)科研专项（GYHY200906011）、中国气象局关键技术集成与应用项目（CMAGJ2011M11）和(CMAGJ2012M09)、以及中国气象局预报员专项（CMAYBY2011 004）和（CMAYBY2012 007）共同资助 |
| 摘 要： | 利用近3年5—9月山西63个GPS/MET临测站反演的逐时气柱水汽总量空间分布图与对应的459天气象观测资料、12个暴雨日的暴雨落区以及对应的流型配置图,对比分析发现:(1)当气柱水汽总量空间分布的水平梯度在25～40 mm/l经(纬)度时,未来12～36小时,在水平梯度的大值区及其南北(东西)0.5～1.0个经(纬)度的范围内,暴雨及其以上天气出现的概率达100%,当气柱水汽总量空间分布的水平梯度≥40 mm/l经(纬)度时,在水平梯度的大值区及其南北(东西)0.5个经(纬)度的范围内出现大暴雨的慨率为63.6%;(2)暴雨落区在气柱水汽总量空间分布图中水汽含量水平梯度大值区及其以北(西)还是以南(东)0.5～1.0)个经(纬)度的范围出现,不同的流型配置会出现不同的结果。应用逐时GPS/MET资料和逐时自动气象站极大风速风场资料,依据暴雨出现在气柱水汽总量空间分布图中水汽含量水平梯度大值区的不同位置,建立不同流型配置下的多种暴雨概念模型;采用轮廓识别技术在C/S架构下,对12～36小时暴雨落区预报模型进行改进并实现了自动化运行,2011年进行准业务使用证明效果良好。 |
| 关 键 词： | 气柱水汽总量 暴雨落区 预报模型 改进技术 |
| 收稿时间： | 2012/1/18 0:00:00 |
| 修稿时间： | 2012/4/25 0:00:00 |
The Application of Meticulous Monitoring Data to Shanxi Rainstorm Forecasting Model Improvement |
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| MIAO Aimei,HAO Zhenrong,JIA Lidong,LI Miao,LU Zhangyu and HAN Long.The Application of Meticulous Monitoring Data to Shanxi Rainstorm Forecasting Model Improvement[J].Meteorological Monthly,2012,38(7):786-794. | |
| Authors: | MIAO Aimei HAO Zhenrong JIA Lidong LI Miao LU Zhangyu and HAN Long |
| Institution: | 1 Shanxi Meteorological Observatory,Taiyuan 030006 2 Shanxi Meteorological Information Centre,Taiyuan 030006 3 Shanxi Meteorological Service,Taiyuan 030002 4 Shanxi Meteorological Service Center,Taiyuan 030002 5 Information Institute of the Shanxi Academy of Agricultural Sciences,Taiyuan 030006 |
| Abstract: | The authors contrasted and analyzed the spatial distribution map of hourly air column vapor content retrieved from the 63 GPS/MET monitoring stations from May to September during 2009—2011 in Shanxi,and the corresponding meteorological observation data in 459 days,and the rainstorm falling area in 42 rainstorm days,and the corresponding flow pattern configuration map,and discovered that:(1) When the horizontal gradents of the air column vapor content spatial distribution are between 25 to 40 mm/ latitude(longitude),in the next 12—36 hours,the probability of rainstorm and above is 100 percent in the big value area of horizontal gradents and its neighboring 0.5—1.0 latitude and longitude range from south to north(east to west);when the horizontal gradents of the air column vapor content spatial distribution is≥40 mm/latitude(longitude),the probability of rainstorm is 63.6 percent in the big value area and its neighboring 0.5 latitude and longitude range from south to north(east to west);(2) The rainstorm falling area appears in the south(east) or north(west) 0.5—1.0 latitude and longitude of the horizontal gradents big value area of the air column vapor content spatial distribution,different flow pattern configuration would be a different result.Using the hourly GPS/MET data and hourly automatic weather station (AWS) maximum wind speed data,and based on the different location of rainstorm appearing in the horizontal gradents big value area in air column vapor content spatial distribution map,the authors built several rainstorm conceptual models in different flow pattern configurations;under C/S construction,the authors improved rainstorm falling area 12—36 h forecasting model with the contour recognition technology, and achieved automatic operation runs,and the quasi-operation run in 2011 proved good effects. |
| Keywords: | air column vapor content rainstorm falling area forecasting model improvement technology |
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