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Variational Data Assimilation Experiments of Mei-Yu Front Rainstorms in China


doi: 10.1007/BF02915726

  • The numerical forecasts of mei-yu front rainstorms in China has been an important issue. The intensity and pattern of the frontal rainfall are greatly influenced by the initial fields of the numerical model. The 4-dimensional variational data assimilation technology (4DVAR) can effectively assimilate all kinds of observed data, including rainfall data at the observed stations, so that the initial fields and the precipitation forecast can both be greatly improved. The non-hydrostatic meso-scale model (MM5) and its adjoint model are used to study the development of the mei-yu front rainstorm from 1200 UTC 25June to 0600 UTC 26 June 1999. By numerical simulation experiments and assimilation experiments, the T106 data and the observed 6-hour rainfall data are assimilated. The influences of many factors, such as the choice of the assimilated variables and the weighting coefficient, on the precipitation forecast results are studied. The numerical results show that 4DVAR is valuable and important to mei-yu front rainfall prediction.
  • [1] CHU Kekuan, TAN Zhemin, Ming XUE, 2007: Impact of 4DVAR Assimilation of Rainfall Data on the Simulation of Mesoscale Precipitation Systems in a Mei-yu Heavy Rainfall Event, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 281-300.  doi: 10.1007/s00376-007-0281-9
    [2] Xiangjun TIAN, Xiaobing FENG, 2019: An Adjoint-Free CNOP-4DVar Hybrid Method for Identifying Sensitive Areas in Targeted Observations: Method Formulation and Preliminary Evaluation, ADVANCES IN ATMOSPHERIC SCIENCES, , 721-732.  doi: 10.1007/s00376-019-9001-5
    [3] Jincheng WANG, Xingwei JIANG, Xueshun SHEN, Youguang ZHANG, Xiaomin WAN, Wei HAN, Dan WANG, 2023: Assimilation of Ocean Surface Wind Data by the HY-2B Satellite in GRAPES: Impacts on Analyses and Forecasts, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 44-61.  doi: 10.1007/s00376-022-1349-2
    [4] Wang Yunfeng, Wu Rongsheng, Wang Yuan, Pan Yinong, 2000: A Simple Method of Calculating the Optimal Step Size in 4DVAR Technique, ADVANCES IN ATMOSPHERIC SCIENCES, 17, 433-444.  doi: 10.1007/s00376-000-0034-5
    [5] LIU Juan, WANG Bin, LIU Hailong, YU Yongqiang, 2008: A New Global Four-Dimensional Variational Ocean Data Assimilation System and Its Application, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 680-691.  doi: 10.1007/s00376-008-0680-6
    [6] WANG Bin, LIU Juanjuan, WANG Shudong, CHENG Wei, LIU Juan, LIU Chengsi, Qingnong XIAO, Ying-Hwa KUO, 2010: An Economical Approach to Four-dimensional Variational Data Assimilation, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 715-727.  doi: 10.1007/s00376-009-9122-3
    [7] Zhu Jiang, Wang Hui, Masafumi Kamachi, 2002: The Improvement Made by a Modified TLM in 4DVAR with a Geophysical Boundary Layer Model, ADVANCES IN ATMOSPHERIC SCIENCES, 19, 563-582.  doi: 10.1007/s00376-002-0001-4
    [8] JIANG Jianying, NI Yunqi, 2004: Diagnostic Study on the Structural Characteristics of a Typical Mei-yu Front System and Its Maintenance Mechanism, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 802-813.  doi: 10.1007/BF02916376
    [9] Zipeng YUAN, Xiaoyong ZHUGE, Yuan WANG, 2020: The Forced Secondary Circulation of the Mei-yu Front, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 766-780.  doi: 10.1007/s00376-020-9177-8
    [10] YANG Shuai, GAO Shouting, Chungu LU, 2015: Investigation of the Mei-yu Front Using a New Deformation Frontogenesis Function, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 635-647.  doi: 10.1007/s00376-014-4147-7
    [11] CHU Ke-Kuan, TAN Zhe-Min, 2010: Mesoscale Moist Adjoint Sensitivity Study of a Mei-yu Heavy Rainfall Event, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 1415-1424.  doi: 10.1007/s00376-010-9213-1
    [12] XU Zhifang, GE Wenzhong, DANG Renqing, Toshio IGUCHI, Takao TAKADA, 2003: Application of TRMM/PR Data for Numerical Simulations with Mesoscale Model MM5, ADVANCES IN ATMOSPHERIC SCIENCES, 20, 185-193.  doi: 10.1007/s00376-003-0003-x
    [13] QIN Danyu, LI Bo, and HUANG Yong, 2014: Transition from the Southern Mode of the Mei-yu Front Cloud System to Other Leading Modes, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 948-961.  doi: 10.1007/s00376-013-3045-8
    [14] ZHAI Guoqing, ZHOU Lingli, WANG Zhi, 2007: Analysis of a Group of Weak Small-Scale Vortexes in the Planetary Boundary Layer in the Mei-yu Front, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 399-408.  doi: 10.1007/s00376-007-0399-9
    [15] ZHANG Feng, ZHAO Sixiong, 2004: A Study of Formation and Development of One Kind of Cyclone on the Mei-yu (Baiu) Front, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 741-754.  doi: 10.1007/BF02916371
    [16] SUN Jianhua, ZHANG Xiaoling, QI Linlin, ZHAO Sixiong, 2005: An Analysis of a Meso-β System in a Mei-yu Front Using the Intensive Observation Data During CHeRES 2002, ADVANCES IN ATMOSPHERIC SCIENCES, 22, 278-289.  doi: 10.1007/BF02918517
    [17] Qiwei WANG, Yi ZHANG, Kefeng ZHU, Zhemin TAN, Ming XUE, 2021: A Case Study of the Initiation of Parallel Convective Lines Back-Building from the South Side of a Mei-yu Front over Complex Terrain, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 717-736.  doi: 10.1007/s00376-020-0216-2
    [18] LIU Jianyong, TAN Zhe-Min, 2009: Mesoscale Predictability of Mei-yu Heavy Rainfall, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 438-450.  doi: 10.1007/s00376-009-0438-9
    [19] MA Yan, CHEN Shang, 2007: Validation of the Polar MM5 for Use in the Simulation of the Arctic River Basins, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 863-874.  doi: 10.1007/s00376-007-0863-6
    [20] Tingting LI, Xiaofan LI, 2016: Barotropic Processes Associated with the Development of the Mei-yu Precipitation System, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 593-598.  doi: 10.1007/s00376-015-5146-z

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Manuscript History

Manuscript received: 10 July 2004
Manuscript revised: 10 July 2004
通讯作者: 陈斌, bchen63@163.com
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Variational Data Assimilation Experiments of Mei-Yu Front Rainstorms in China

  • 1. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics,Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;Institute of Meteorology, PLA University of Science and Technology, Nanjing 21,State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics,Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029,Institute of Meteorology, PLA University of Science and Technology, Nanjing 211101,Institute of Meteorology, PLA University of Science and Technology, Nanjing 211101,Institute of Meteorology, PLA University of Science and Technology, Nanjing 211101,Institute of Meteorology, PLA University of Science and Technology, Nanjing 211101,Institute of Meteorology, PLA University of Science and Technology, Nanjing 211101,Institute of Meteorology, PLA University of Science and Technology, Nanjing 211101

Abstract: The numerical forecasts of mei-yu front rainstorms in China has been an important issue. The intensity and pattern of the frontal rainfall are greatly influenced by the initial fields of the numerical model. The 4-dimensional variational data assimilation technology (4DVAR) can effectively assimilate all kinds of observed data, including rainfall data at the observed stations, so that the initial fields and the precipitation forecast can both be greatly improved. The non-hydrostatic meso-scale model (MM5) and its adjoint model are used to study the development of the mei-yu front rainstorm from 1200 UTC 25June to 0600 UTC 26 June 1999. By numerical simulation experiments and assimilation experiments, the T106 data and the observed 6-hour rainfall data are assimilated. The influences of many factors, such as the choice of the assimilated variables and the weighting coefficient, on the precipitation forecast results are studied. The numerical results show that 4DVAR is valuable and important to mei-yu front rainfall prediction.

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