中山大学学报自然科学版 ›› 2019, Vol. 58 ›› Issue (5): 80-93.doi: 10.13471/j.cnki.acta.snus.2019.05.011

• 论文 • 上一篇    下一篇

雷达和卫星资料同化在一次华南暴雨预报中的应用

张少婷1,4,王东海2,于星2,陈权亮1,丁伟钰3   

  1. 1.成都信息工程大学大气科学学院,四川 成都 610225;
    2.中山大学大气科学学院,广东 珠海 519082;
    3.中国气象局广州热带海洋气象研究所,广东 广州 510080;
    4.佛山市气象局,广东 佛山 528000
  • 收稿日期:2018-04-12 出版日期:2019-09-25 发布日期:2019-09-25
  • 通讯作者: 王东海(1965年生),男;研究方向:中小尺度数值模拟;E-mail:wangdh7@mail.sysu.edu.cn

Application of radar and satellite data assimilation in a rainstorm forecast in Southern China

ZHANG Shaoting1,4, WANG Donghai2, YU Xing2, CHEN Quanliang1,DING Weiyu3   

  1. 1.School of Atmospheric Sciences, Chengdu University of Information and Technology, Chengdu 610225, China;
    2. School of Atmospheric Sciences, Sun Yatsen University, Zhuhai 519082, China;
    3. Guangzhou Institute of Tropical and Marine Meteorology, CMA, Guangzhou 510080, China;
    4. Meteorological Bureau of Foshan,Foshan 528000,China
  • Received:2018-04-12 Online:2019-09-25 Published:2019-09-25

摘要:

利用WRF模式和GSI同化系统,搭建了一套可以业务运行的预报系统,实现了对多普勒天气雷达反射率和径向风、葵花(Himawari-8)气象卫星等资料的同化功能。基于本系统,针对同化非常规资料可能带来的资料应用和预报效果问题,设计了多组同化方案,对2017年7月17~18日发生在华南的一次强降水过程进行模拟分析和同化效果评估。结果表明:分别同化常规资料、雷达径向风、雷达反射率反射率、卫星资料均对预报效果有所改进,特别是同化卫星资料,可以改善系统对云水物质的分析能力,进而提高海上天气过程的降水预报。基于分类试验同化的结果,对整体同化常规资料、雷达径向风、雷达反射率和卫星资料等对温度、风向风速、相对湿度和降水等模拟技巧进行评估后发现,整体同化对强降水的发生时间和强度预报有改进,但并非在所有方面都优于单独同化某一类资料的结果。

关键词: WRFGSI预报系统, 资料同化, 雷达径向风, 雷达反射率, 卫星资料

Abstract:

ARW-WRF and GSI 3D-Var methods were used to build a set of operational prediction systems and assimilate Doppler Weather Radar (DWR) reflectivity and velocity, Himawari-8 meteorological satellite AHI data. Regarding problems of data application and forecasting effect of unconventional data, multiple sets of comparative experiments were designed to perform simulation analysis and assessment of data assimilation (DA) results based on a case of severe precipitation process in southern China. The results show that during the heavy precipitation period in the coastal areas of Guangdong on 17-18 July 2017, the system can grasp the scope and intensity of precipitation and the simulation of radar reflectivity. Particularly, the assimilation of satellite data has ability to analyze cloud-water materials and weather process on the sea. Assimilating conventional data, radial velocity, reflectivity, and satellite data can improve simulation tactics such as temperature, wind vector, humidity, and precipitation. However, their prediction results are not absolutely superior to the test of certain types of data.

Key words: WRF-GSI system, data assimilation, radial velocity, radial reflectivity, satellite data

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