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Volume 29 Issue 4

Jul.  2012

Article Contents
Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2012 >  29(4): 705-716

The Time and Regime Dependencies of Sensitive Areas for Tropical Cyclone Prediction Using the CNOP Method

  • 1.

    Laboratory of Cloud-Precipitation Physics and Severe Storms, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;Key Laboratory of Ocean Circulation and Wave, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071


doi: 10.1007/s00376-012-1174-0

  • This study examines the time and regime dependencies of sensitive areas identified by the conditional nonlinear optimal perturbation (CNOP) method for forecasts of two typhoons. Typhoon Meari (2004) was weakly nonlinear and is herein referred to as the linear case, while Typhoon Matsa (2005) was strongly nonlinear and is herein referred to as the nonlinear case. In the linear case, the sensitive areas identified for special forecast times when the initial time was fixed resembled those identified for other forecast times. Targeted observations deployed to improve a special time forecast would thus also benefit forecasts at other times. In the nonlinear case, the similarities among the sensitive areas identified for different forecast times were more limited. The deployment of targeted observations in the nonlinear case would therefore need to be adapted to achieve large improvements for different targeted forecasts. For both cases, the closer the forecast time, the higher the similarities of the sensitive areas. When the forecast time was fixed, the sensitive areas in the linear case diverged continuously from the verification area as the forecast period lengthened, while those in the nonlinear case were always located around the initial cyclones. The deployment of targeted observations to improve a special forecast depends strongly on the time of deployment. An examination of the efficiency gained by reducing initial errors within the identified sensitive areas confirmed these results. In general, the greatest improvement in a special time forecast was obtained by identifying the sensitive areas for the corresponding forecast time period.
  • [1] 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
    [2] ZHOU Feifan, MU Mu, 2011: The Impact of Verification Area Design on Tropical Cyclone Targeted Observations Based on the CNOP Method, ADVANCES IN ATMOSPHERIC SCIENCES, 28, 997-1010.  doi: 10.1007/s00376-011-0120-x
    [3] Huizhen YU, Zhiyong MENG, 2022: The Impact of Moist Physics on the Sensitive Area Identification for Heavy Rainfall Associated Weather Systems, ADVANCES IN ATMOSPHERIC SCIENCES, 39, 684-696.  doi: 10.1007/s00376-021-0278-9
    [4] ZHOU Feifan, MU Mu, 2012: The Impact of Horizontal Resolution on the CNOP and on Its Identified Sensitive Areas for Tropical Cyclone Predictions, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 36-46.  doi: 10.1007/s00376-011-1003-x
    [5] CHEN Boyu, MU Mu, 2012: The Roles of Spatial Locations and Patterns of Initial Errors in the Uncertainties of Tropical Cyclone Forecasts, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 63-78.  doi: 10.1007/s00376-011-0201-x
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    [12] Lin DENG, Wenhua GAO, Yihong DUAN, Yuqing WANG, 2019: Microphysical Properties of Rainwater in Typhoon Usagi (2013): A Numerical Modeling Study, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 510-526.  doi: 10.1007/s00376-019-8170-6
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    [14] Angkool WANGWONGCHAI, ZHAO Sixiong, ZENG Qingcun, 2010: An Analysis of Typhoon Chanthu in June 2004 with Focus on the Impact on Thailand, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 14-32.  doi: 10.1007/s00376-009-8206-4
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    • Manuscript History

    Manuscript received: 10 July 2012
    Manuscript revised: 10 July 2012
    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

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    The Time and Regime Dependencies of Sensitive Areas for Tropical Cyclone Prediction Using the CNOP Method

    • 1. Laboratory of Cloud-Precipitation Physics and Severe Storms, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;Key Laboratory of Ocean Circulation and Wave, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071
    • Manuscript received: 2012-07-10
    • Manuscript revised: 2012-07-10

    Abstract: This study examines the time and regime dependencies of sensitive areas identified by the conditional nonlinear optimal perturbation (CNOP) method for forecasts of two typhoons. Typhoon Meari (2004) was weakly nonlinear and is herein referred to as the linear case, while Typhoon Matsa (2005) was strongly nonlinear and is herein referred to as the nonlinear case. In the linear case, the sensitive areas identified for special forecast times when the initial time was fixed resembled those identified for other forecast times. Targeted observations deployed to improve a special time forecast would thus also benefit forecasts at other times. In the nonlinear case, the similarities among the sensitive areas identified for different forecast times were more limited. The deployment of targeted observations in the nonlinear case would therefore need to be adapted to achieve large improvements for different targeted forecasts. For both cases, the closer the forecast time, the higher the similarities of the sensitive areas. When the forecast time was fixed, the sensitive areas in the linear case diverged continuously from the verification area as the forecast period lengthened, while those in the nonlinear case were always located around the initial cyclones. The deployment of targeted observations to improve a special forecast depends strongly on the time of deployment. An examination of the efficiency gained by reducing initial errors within the identified sensitive areas confirmed these results. In general, the greatest improvement in a special time forecast was obtained by identifying the sensitive areas for the corresponding forecast time period.

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