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首页> 外文期刊>Journal of Physical Oceanography >On Cabbeling and Thermobaricity in the Surface Mixed Layer
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On Cabbeling and Thermobaricity in the Surface Mixed Layer

机译：表面混合层中的滑移和热压性

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摘要

The surface mixed layer (ML) governs atmosphere-ocean fluxes, and thereby affects Earth's climate. Accurate representation of ML processes in ocean models remains a challenge, however. The O(100) m deep ML exhibits substantial horizontal thermohaline gradients, despite being near-homogenous vertically, making it an ideal location for processes that result from the nonlinearity of the equation of state, such as cabbeling and thermobaricity. Traditional approaches to investigate these processes focus on their roles in interior water-mass transformation and are ill suited to examine their influence on the ML. However, given the climatic significance of the ML, quantifying the extent to which cabbeling and thermobaricity influence the ML density field offers insight into improving ML representations in ocean models. A recent simplified equation of state of seawater allows the local effects of cabbeling and thermobaric processes in the ML to be expressed analytically as functions of the local temperature gradient and ML depth. These simplified expressions are used to estimate the extent to which cabbeling and thermobaricity contribute to local ML density differences. These estimates compare well with values calculated directly using the complete nonlinear equation of state. Cabbeling and thermobaricity predominantly influence the ML density field poleward of 30 degrees. Mixed layer thermobaricity is basin-scale and winter intensified, while ML cabbeling is perennial and localized to intense, zonally coherent regions associated with strong temperature fronts, such as the Antarctic Circumpolar Current and the Kuroshio and Gulf Stream Extensions. For latitudes between 40 degrees and 50 degrees in both hemispheres, the zonally averaged effects of ML cabbeling and ML thermobaricity can contribute on the order of 10% of the local ML density difference.
机译：表面混合层（ML）控制着海洋的通量，从而影响了地球的气候。但是，在海洋模型中准确表示机器学习过程仍然是一个挑战。尽管在垂直方向上近乎均匀，但O（100）m深的ML仍显示出相当大的水平热盐梯度，这使其成为由状态方程式非线性（如缆车晃动和热压）导致的过程的理想位置。研究这些过程的传统方法侧重于它们在内部水质转化中的作用，不适合检验它们对最大残留限量的影响。但是，考虑到ML的气候意义，量化滑坡和热压影响ML密度场的程度可提供深入了解海洋模型中ML表示的见解。最近使用的简化的海水状态方程式可以将ML中的缆车滑行和热压过程的局部影响解析为局部温度梯度和ML深度的函数。这些简化的表达式可用于估计布线和热压对局部ML密度差异的影响程度。这些估计值与使用完整的非线性状态方程直接计算出的值进行了比较。晃动和热压主要影响ML密度场的30度极化。混合层的热压强度是盆地规模的，冬季加剧了，而ML缆线是多年生的，并且局限于与强温度前沿相关的强烈的，区域性连贯的区域，例如南极绕极洋流，黑潮和墨西哥湾流扩展。对于两个半球之间40度到50度之间的纬度，ML缆线倾斜和ML热压强度的区域平均影响可以贡献局部ML密度差的10％左右。

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  • 来源
    《Journal of Physical Oceanography》 |2017年第7期|1775-1787|共13页
  • 作者

    Stewart K. D.; Haine T. W. N.; Hogg A. McC.; Roquet F.;

  • 作者单位

    Australian Natl Univ, Res Sch Earth Sci, Canberra, ACT, Australia|Australian Natl Univ, Australian Res Council Ctr Excellence Climate Sys, Canberra, ACT, Australia;

    Johns Hopkins Univ, Dept Earth & Planetary Sci, Baltimore, MD 21218 USA;

    Australian Natl Univ, Res Sch Earth Sci, Canberra, ACT, Australia|Australian Natl Univ, Australian Res Council Ctr Excellence Climate Sys, Canberra, ACT, Australia;

    Stockholm Univ, Dept Meteorol, Stockholm, Sweden;

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