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Optimal Precursors Triggering the Kuroshio Extension State Transition Obtained by the Conditional Nonlinear Optimal Perturbation Approach

机译:通过条件非线性最优摄动方法获得触发黑潮扩展状态转变的最优前体

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摘要

In this study,the initial perturbations that are the easiest to trigger the Kuroshio Extension (KE) transition connecting a basic weak jet state and a strong,fairly stable meandering state,are investigated using a reduced-gravity shallow water ocean model and the CNOP (Conditional Nonlinear Optimal Perturbation) approach.This kind of initial perturbation is called an optimal precursor (OPR).The spatial structures and evolutionary processes of the OPRs are analyzed in detail.The results show that most of the OPRs are in the form of negative sea surface height (SSH) anomalies mainly located in a narrow band region south of the KE jet,in basic agreement with altimetric observations.These negative SSH anomalies reduce the meridional SSH gradient within the KE,thus weakening the strength of the jet.The KE jet then becomes more convoluted,with a high-frequency and large-amplitude variability corresponding to a high eddy kinetic energy level;this gradually strengthens the KE jet through an inverse energy cascade.Eventually,the KE reaches a high-energy state characterized by two well defined and fairly stable anticyclonic meanders.Moreover,sensitivity experiments indicate that the spatial structures of the OPRs are not sensitive to the model parameters and to the optimization times used in the analysis.
机译:在这项研究中,使用重力降低的浅水海洋模型和CNOP研究了最容易触发连接基本弱射流状态和强烈,相当稳定的曲折状态的黑潮扩展(KE)的初始扰动(条件非线性最优摄动)方法,这种初始摄动称为最优前兆(OPR),详细分析了OPR的空间结构和演化过程,结果表明大多数OPR都是负海形式表面高度(SSH)异常主要位于KE喷气机以南的窄带区域,与高空观测基本吻合。这些负SSH异常降低了KE内子午SSH梯度,从而削弱了喷气机的强度。然后变得更加复杂,具有高涡动能级的高频率和大振幅变化;这通过一个渐进线逐渐增强了KE射流。最终,KE达到高能态,具有两个定义明确且相当稳定的反气旋弯道。此外,敏感性实验表明,OPR的空间结构对模型参数和所用的优化时间不敏感在分析中。

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  • 来源
    《大气科学进展(英文版)》 |2017年第6期|685-699|共15页
  • 作者单位

    Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China;

    University of Chinese Academy of Sciences, Beijing 100049, China;

    Institute of Atmospheric Sciences, Fudan University, Shanghai 200433, China;

    Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China;

    Function Laboratory for Ocean Dynamics and Climate, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China;

    Department of Science and Technology, Parthenope University of Naples, Naples, 80143, Italy;

  • 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 eng
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