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Season-dependent predictability and error growth dynamics of Pacific Decadal Oscillation-related sea surface temperature anomalies

机译:太平洋年代际涛动相关海面温度异常的季节相关可预测性和误差增长动态

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摘要

By performing perfect model predictability experiments in a coupled general circulation model from the point of view of initial error growth, it is demonstrated that there may exist a "summer prediction barrier" (SPB) in the predictions of Pacific Decadal Oscillation-related sea surface temperature anomalies (PDO-related SSTA), which refers to the phenomenon that initial errors exhibit a significant season-dependent evolution, with the largest error growth occurring in the August-September-October (ASO) season. Due to the effect of the SPB, the prediction error of PDO-related SSTA events starts to grow rapidly during the ASO season and yields a positive (negative) prediction error for the warm (cold) events, essentially inducing a delay of the events. The SPB may be one of the main factors limiting the predictability of North Pacific sea surface temperature. The physical and dynamical mechanisms of the SPB are explored from two aspects: thermodynamics and dynamics. In terms of thermodynamics, we demonstrate that the fastest error growth of PDO-related SST cold (warm) events during the ASO season is mainly due to the largest anomalous release (absorption) of the latent heat flux in this season; while for dynamics, the effect of the vertical gradient of climatological mean sea temperature on the anomalous upwelling (downwelling) dominates the contribution of the dynamical temperature advections to the error growth of the PDO-related SST cold (warm) events during the ASO season. The anomalous release (absorption) of the latent heat flux and anomalous upwelling (downwelling) of the ocean currents are both related to the anomalous northwesterly or cyclonic (southeasterly or anticyclonic) wind over the PDO-related SSTA region, which indicates that the error growth associated with the SPB of PDO-related SST cold (warm) events is mainly driven by anomalous wind stress. The error growth associated with the SPB for PDO-related SSTA may also explain why the SSTA in the Kuroshio-Oyashio Extension is much less predictable than in other regions of the North Pacific, as shown by some state-of-the-art climate models.
机译:通过从初始误差增长的角度在耦合的一般环流模型中进行完美的模型可预测性实验,证明在太平洋年代际涛动相关海平面温度的预测中可能存在“夏季预测障碍”(SPB)异常(与PDO相关的SSTA),是指初始误差表现出明显的季节依赖性演变现象,最大的误差增长发生在8月-9月-10月(ASO)季节。由于SPB的影响,与PDO相关的SSTA事件的预测误差在ASO季节期间开始迅速增长,并为暖(冷)事件产生正(负)预测误差,从而导致事件延迟。 SPB可能是限制北太平洋海表温度可预测性的主要因素之一。从两个方面探讨了SPB的物理和动力学机理:热力学和动力学。在热力学方面,我们证明了在ASO季节,与PDO相关的SST冷(暖)事件的误差增长最快,主要是由于该季节潜热通量的最大异常释放(吸收)。而对于动力学而言,气候平均海温的垂直梯度对异常上升(下降)的影响支配着动态温度对流对ASO季节PDO相关的SST冷(暖)事件误差增长的贡献。潜热通量的异常释放(吸收)和洋流的异常上升(下降)都与PDO相关的SSTA区域上的西北风或气旋(南风或反气旋)异常有关,这表明误差增长与PDO相关的SST冷(暖)事件的SPB相关的主要是由异常的风应力驱动的。一些最新的气候模型显示,与PDO相关的SSTA的SPB相关的误差增长也可能解释了为什么黑潮-大矢潮扩展区中的SSTA比北太平洋其他地区的可预测性低得多。

著录项

  • 来源
    《Climate dynamics》 |2015年第4期|1053-1072|共20页
  • 作者

    Wansuo Duan; Yujie Wu;

  • 作者单位

    State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China;

    State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    North Pacific; Sea surface temperature; Predictability; Error growth;

    机译:北太平洋;海面温度;可预测性;错误增长;

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