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Thermohaline Modes of the Global Ocean

机译：全球海洋的热盐模式

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摘要

The first 2000 m of the global thermohaline structure of the ocean are statistically decomposed into vertical thermohaline modes, using a multivariate functional principal component analysis (FPCA). This method is applied on the Monthly Isopycnal and Mixed-Layer Ocean Climatology (MIMOC). The first three modes account for 92% of the joint temperature and salinity (T-S) variance, which yields a surprisingly good reduction of dimensionality. The first mode (69% of the variance) is related to the thermocline depth and delineates the subtropical gyres. The second mode (18%) is mostly driven by salinity and mainly displays the asymmetry between the North Pacific and Atlantic basins and the salty circumpolar deep waters in the Southern Ocean. The third mode (5%) identifies the low- and high-salinity intermediate waters, covarying with the freshwater inputs of the upper ocean. The representation of the ocean in the space defined by the first three modes offers a simple visualization of the global thermohaline structure that strikingly emphasizes the role of the Southern Ocean in linking and distributing water masses to the other basins. The vertical thermohaline modes offer a convenient framework for model and observation data comparison. This is illustrated by projecting the repeated Pacific section P16 together with profiles from the Array for Real-Time Geostrophic Oceanography (ARGO) global array of profiling floats on the modes defined with the climatology MIMOC. These thermohaline modes have a potential for water mass identification and robust analysis of heat and salt content.
机译：使用多元功能主成分分析（FPCA），将海洋中最初的2000 m海洋热盐结构统计分解为垂直热盐模式。该方法适用于等月和混合层海洋气候学（MIMOC）。前三种模式占关节温度和盐度（T-S）变化的92％，这令人惊讶地很好地减小了尺寸。第一模式（方差的69％）与跃层深度有关，并描绘了亚热带回旋。第二种模式（18％）主要是由盐度驱动的，并且主要表现出北太平洋和大西洋海盆之间以及南洋咸性绕极深水之间的不对称性。第三种模式（5％）确定了低盐度和高盐度的中间水域，与上层海洋的淡水输入共同变化。前三种模式定义的空间中海洋的表示形式提供了全球热盐结构的简单可视化，显着地强调了南大洋在将水团连接和分配到其他盆地中的作用。垂直热盐模式为模型和观测数据的比较提供了方便的框架。通过将重复的太平洋剖面P16与来自实时地转海洋学阵列（ARGO）的全球剖面浮标的轮廓一起投影到由MIMOC定义的模式中，可以说明这一点。这些热盐模式具有识别水质和对热量和盐含量进行可靠分析的潜力。

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