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The Roles of Spatial Locations and Patterns of Initial Errors in the Uncertainties of Tropical Cyclone Forecasts

机译:空间位置和初始误差模式在热带气旋预报不确定性中的作用

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摘要

In this study,a series of sensitivity experiments were performed for two tropical cyclones (TCs),TC Longwang (2005) and TC Sinlaku (2008),to explore the roles of locations and patterns of initial errors in uncertainties of TC forecasts.Specifically,three types of initial errors were generated and three types of sensitive areas were determined using conditional nonlinear optimal perturbation (CNOP),first singular vector (FSV),and composite singular vector (CSV) methods.Additionally,random initial errors in randomly selected areas were considered.Based on these four types of initial errors and areas,we designed and performed 16 experiments to investigate the impacts of locations and patterns of initial errors on the nonlinear developments of the errors,and to determine which type of initial errors and areas has the greatest impact on TC forecasts.Overall,results from the experiments indicate the following:(1) The impact of random errors introduced into the sensitive areas was greater than that of errors themselves fixed in the randomly selected areas.From the perspective of statistical analysis,and by comparison,the impact of random errors introduced into the CNOP target area was greatest.(2) The initial errors with CNOP,CSV,or FSV patterns were likely to grow faster than random errors.(3) The initial errors with CNOP patterns in the CNOP target areas had the greatest impacts on the final verification forecasts.
机译:在这项研究中,对两个热带气旋(TC),TC Longwang(2005)和TC Sinlaku(2008)进行了一系列敏感性实验,以探讨初始误差的位置和模式在TC预报不确定性中的作用。使用条件非线性最优摄动(CNOP),第一奇异矢量(FSV)和复合奇异矢量(CSV)方法生成了三种类型的初始误差并确定了三种类型的敏感区域。此外,随机选择区域中的随机初始误差为基于这四种类型的初始误差和区域,我们设计并执行了16个实验,以研究初始误差的位置和模式对误差的非线性发展的影响,并确定哪种类型的初始误差和区域具有初始误差和区域。总体而言,实验结果表明:(1)引入敏感区域的随机误差的影响更大。从统计分析的角度,通过比较,将随机误差引入CNOP目标区域的影响最大。(2)CNOP,CSV或FSV引起的初始误差(3)CNOP目标区域中CNOP模式的初始误差对最终验证预测的影响最大。

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  • 来源
    《大气科学进展(英文版)》 |2012年第1期|63-78|共16页
  • 作者

    CHEN Boyu; MU Mu;

  • 作者单位

    National Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics,Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;

    Graduate University of Chinese Academy of Sciences, Beijing 100049;

    National Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics,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;

  • 收录信息 中国科学引文数据库(CSCD);中国科技论文与引文数据库(CSTPCD);
  • 原文格式 PDF
  • 正文语种 chi
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