A Global Geography of Internal-Wave Strain and Mixing from WOCE CTD Hydrography

将使用18,000多条CTD(电导率、温度和深度)剖面的WOCE(世界海洋环流实验)水文数据集绘制全球海洋的内波应变和内波驱动的湍流混合图。将使用仅应变版本的细尺度参数化来估计日平均扩散系数，该版本已被发现与切变和应变版本在2倍以内。拟议的工作代表覆盖范围扩大了5倍以上。这些混合预测将与Luther和Decloedt(2010)在同一数据集上进行的密度颠覆分析的预测进行比较。本项目将根据最新的进展和见解对细尺度参数化进行改进。该项目扩展了以前使用~3500个降低的ADCP(声学多普勒水流剖面仪)和CTD剖面的剪切和应变的工作。这项工作发现：(I)大部分海洋的特征是扩散系数小，与直接但稀疏的微结构测量一致，(Ii)湍流极其不均匀，热点与陡峭的地形有关。采样足以从垂直平流扩散方程推断全球平均昼夜速度作为深度和纬度的函数。然而，大部分海洋采样不足，统计数据不足以描述个别盆地的经向翻转环流。拟议的分析将提供更全面的海洋混合地理信息。对逐个盆地的温盐环流的推断将检验大部分倾覆是否像预算所显示的那样发生在印度洋。有了更高的垂直分辨率，内波应变的更精细绑定将成为可能。通过与相同数据集的密度翻转分析进行比较，将解决对接近强强迫的比例不足的担忧。海洋混合是由微弱的、广泛的内波驱动的混合主导的，还是由非常强烈的热点所主导的，还有待观察。海洋混合的量化和理解仍然是物理海洋学中最令人头疼的问题之一。它在大气环流模式(GCM)中的正确参数化对于正确再现几个月到几千年的时间尺度上的广泛特征至关重要，它不仅与环流有关，而且与天气预报、生物地球化学循环和长期气候有关。作为气候过程小组在全球海洋模式中代表内波驱动的混合的成员，PI正在与数值模型师密切合作，以改进GCM中内波驱动的湍流混合的亚格子尺度参数化。与前面的工作一样，PI将可用于帮助其他研究人员在其他数据集中实现精细参数化。这项工作的预测将向社区公开提供。PI将与华盛顿州APL-U的外联资源合作，更好地教育普通公众关于波浪和混合在物理海洋学中的作用。

Internal-wave strain and internal-wave-driven turbulent mixing for the global ocean will be mapped using the WOCE (World Ocean Circulation Experiment) hydrographic data set of more than 18,000 CTD (Conductivity, Temperature and Depth) profiles. Diapycnal diffusivities will be estimated using a strain-only version of a fine-scale parameterization which has been found to agree with the shear-and-strain version to within a factor of 2. The proposed work represents a more than 5-fold expansion in coverage. These mixing predictions will be compared with those from density-overturn analysis being conducted by Luther and Decloedt (2010) on the same data set. Refinements to the fine-scale parameterization will be made based on recent advances and insights.This project expands on previous work which used shear and strain from ~3500 Lowered ADCP (Acoustic Doppler Current Profiler)and CTD profiles. That work found that (i) most of the ocean was characterized by small diffusivities consistent with direct but sparse microstructure measurements, and (ii) turbulence was extremely heterogeneous, with hotspots associated with abrupt topography. Sampling was sufficient to infer global-average diapycnal velocities as a function of depth and latitude from the vertical advective-diffusive equation. However, much of the ocean was undersampled and statistics were inadequate to characterize the meridional overturning circulation by individual basin. The proposed analysis will provide a much more comprehensive geography of ocean mixing. Inferences of the thermohaline circulation basin-by-basin will test if the bulk of the overturning occurs in the Indian Ocean as inverse budgets suggest. With higher vertical resolution, finer binning of internal wave strain will be possible. Concerns that the scaling falls short near strong forcing will be addressed by comparison with density-overturn analysis of the same data set. It remains to be seen whether ocean mixing is dominated by weak widespread internal-wave-driven mixing or very intense hotspots.Quantifying and understanding of ocean mixing remains one of the most vexing problems in physical oceanography. Its correct parameterization in general circulation models (GCMs) is critical to correctly reproducing a wide range of features on timescales of months to millennia, linking it not just to the circulation but also weather prediction, biogeochemical cycles and longterm climate. As a member of the Climate Processes Team on Representing Internal-Wave Driven Mixing in Global Ocean Models, the PI is working closely with numerical modelers to improve sub-grid-scale parameterizations for internal-wave-driven turbulent mixing in GCMs. As with the earlier work, the PI will be available to help other researchers with their implementations of the fine-scale parameterization in other data sets. Predictions from this work will be publicly available to the community. The PI will work with outreach resources at APL-U of Washington to better educate the general public in the roles of waves and mixing in physical oceanography.