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

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 about 20KM. (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, include 519 national stations and 1532 regional stations with average distance about 20KM, while the density is slightly greater for the key areas.