An event-based approach to understanding decadal fluctuations in the Atlantic meridional overturning circulation
An event-based approach to understanding decadal fluctuations in the Atlantic meridional overturning circulation
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基于事件的方法来了解大西洋经向翻转环流的年代际波动
DOI：
10.1007/s00382-014-2271-9
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发表时间：
2014
期刊：
影响因子：
4.6
通讯作者：
Allison L
中科院分区：
文献类型：
--
作者：
Allison L
许多先前的研究表明，非强迫气候模式模拟大西洋纬向翻转环流（AMOC）表现出十年尺度的波动，这种变化可能会对地面气候场产生影响。然而，这些表面指纹在不同模型中的鲁棒性不太清楚。此外，由于耦合反馈可能会放大或抑制响应，因此不知道相关的气候信号是否与AMOC变化的强度线性相关，或者波动事件是否表现出相对于其强度或极性的非线性行为。为了探讨这些问题，我们介绍了一个客观和灵活的方法来确定最大的自然AMOC波动事件的多百年/多千年的各种耦合气候模式的模拟。对这些事件的特征进行了探讨，包括其规模、纬向相干性和空间结构，以及与海洋热输送和水平环流的联系。对海洋温度和盐度的表面指纹进行了检验，并与线性回归分析的结果进行了比较。结果发现，回归一般提供了一个很好的指示与最大的AMOC事件的表面变化。然而，也有一些例外，包括大气压力信号的非线性变化，特别是在高纬度地区，HadCM 3。在同一模型中，正AMOC事件和负AMOC事件的变化也存在不对称性。复合分析表明，在每个模型中，最大的AMOC事件中存在稳健的信号，这保证了与一个特定事件相关的表面变化将与回归分析所预期的相似。然而，不同模式下的AMOC指纹之间存在较大差异，这可能会阻碍现实中此类事件的预测和归因。
Many previous studies have shown that unforced climate model simulations exhibit decadal-scale fluctuations in the Atlantic meridional overturning circulation (AMOC), and that this variability can have impacts on surface climate fields. However, the robustness of these surface fingerprints across different models is less clear. Furthermore, with the potential for coupled feedbacks that may amplify or damp the response, it is not known whether the associated climate signals are linearly related to the strength of the AMOC changes, or if the fluctuation events exhibit nonlinear behaviour with respect to their strength or polarity. To explore these questions, we introduce an objective and flexible method for identifying the largest natural AMOC fluctuation events in multicentennial/multimillennial simulations of a variety of coupled climate models. The characteristics of the events are explored, including their magnitude, meridional coherence and spatial structure, as well as links with ocean heat transport and the horizontal circulation. The surface fingerprints in ocean temperature and salinity are examined, and compared with the results of linear regression analysis. It is found that the regressions generally provide a good indication of the surface changes associated with the largest AMOC events. However, there are some exceptions, including a nonlinear change in the atmospheric pressure signal, particularly at high latitudes, in HadCM3. Some asymmetries are also found between the changes associated with positive and negative AMOC events in the same model. Composite analysis suggests that there are signals that are robust across the largest AMOC events in each model, which provides reassurance that the surface changes associated with one particular event will be similar to those expected from regression analysis. However, large differences are found between the AMOC fingerprints in different models, which may hinder the prediction and attribution of such events in reality.
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影响因子：
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DOI：
--
发表时间：
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期刊：
影响因子：
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