基于观测与数值模式互动的华东地面气象观测站遴选布局

AWS Selection and Layout in East China Based on the Interaction with Observation and Numerical Weather Prediction

采用WRF四维变分同化系统,针对华东地区台风、梅雨、强对流典型天气个例,设计开展了不同密度地面站数据同化敏感性试验,并综合评估了对数值预报的影响,得出能较好满足数值预报需求又经济高效的华东地面站布局。结果表明:(1)地面站资料对中尺度数值预报模式在华东区域的预报结果有直接影响,且以正贡献为主,总体而言同化站点越密,改进效果越好。(2)华东地面站平均布局间距在20 km时出现对数值模式影响正贡献相对高值。(3)地面站对数值模式影响的程度和效果与天气系统的特点有直接关系。(4)在华东地区现有区域站中,遴选1532个增补到519个国家站网中,形成总站数2051个、平均间距约20 km、天气系统关键区适度加密的华东地面站网,在控制站网规模的同时,能较好地满足区域数值预报需求。

In this paper,an assimilation sensitivity test is designed and performed,which focuses on typhoon,Meiyu and severe convective weather in East China,by usingWRF4D-VAR assimilation method.By evaluating the impact of AWS data on NWP with different AWS density conditions,a reasonable layout of AWS in East China is proposed.It can scientifically and efficiently meet the needs of regional NWP.The study shows that:(1)AWS data has a positive correlation with the performance of NWP in East China.The greater the AWS density is,the better the NWP’s positive effect will be.(2)The correlation coefficient presents a relatively high value when the average distance between different stations is about20KM.(3)The impact of the AWS on the NWP is directly related to the characteristics of different weather systems.(4)A relatively reasonable layout of AWSs in East China is proposed that there are total sites,include519national stations and1532regional stations with average distance about20KM,while the density is slightly greater for the key areas.