中国物理B ›› 2004, Vol. 13 ›› Issue (3): 413-422.doi: 10.1088/1009-1963/13/3/028

• • 上一篇    

Application of retrospective time integration scheme to the prediction of torrential rain

封国林1, 董文杰2, 贾晓静2   

  1. (1)Institute of Atmospheric Physics, Chinese Academy of Science, Beijing 100029, China; Department of Physics, Yangzhou University, Yangzhou 225009, China; (2)National Climate Center of China, Beijing 100081, China
  • 收稿日期:2003-05-09 修回日期:2003-09-24 出版日期:2004-03-06 发布日期:2005-07-06
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant Nos 40275031 and 40231006), the Innovation Project of Chinese Academy of Sciences (Grant No ZKCX 2-SW-210) and the K. C. Wong Education Foundation, Hong Kong.

Application of retrospective time integration scheme to the prediction of torrential rain

Feng Guo-Lin (封国林)ab, Dong Wen-Jie (董文杰)c, Jia Xiao-Jing (贾晓静)c   

  1. a Institute of Atmospheric Physics, Chinese Academy of Science, Beijing 100029, Chinab Department of Physics, Yangzhou University, Yangzhou 225009, China; c National Climate Center of China, Beijing 100081, China
  • Received:2003-05-09 Revised:2003-09-24 Online:2004-03-06 Published:2005-07-06
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant Nos 40275031 and 40231006), the Innovation Project of Chinese Academy of Sciences (Grant No ZKCX 2-SW-210) and the K. C. Wong Education Foundation, Hong Kong.

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摘要： The retrospective time integration scheme presented on the principle of the self-memory of the atmosphere is applied to the mesoscale grid model MM5, constructing a mesoscale self-memorial model SMM5, and then the short-range prediction experiments of torrential rain are performed in this paper. Results show that in comparison with MM5 the prediction accuracy of SMM5 is obviously improved due to its utilization of multiple time level past observations, and the precipitation area and intensity predicted by SMM5 are closer to observational fields than those by MM5.

关键词: mesoscale numerical model, short-range weather prediction, atmospheric self-memory, retrospective time integration scheme, torrential rain

Abstract: The retrospective time integration scheme presented on the principle of the self-memory of the atmosphere is applied to the mesoscale grid model MM5, constructing a mesoscale self-memorial model SMM5, and then the short-range prediction experiments of torrential rain are performed in this paper. Results show that in comparison with MM5 the prediction accuracy of SMM5 is obviously improved due to its utilization of multiple time level past observations, and the precipitation area and intensity predicted by SMM5 are closer to observational fields than those by MM5.

Key words: mesoscale numerical model, short-range weather prediction, atmospheric self-memory, retrospective time integration scheme, torrential rain

中图分类号:  (Precipitation)

  • 92.40.Ea
92.60.Jq (Water in the atmosphere)