Collaborative Research: Quantifying regional variability in abyssal mixing from Ship-based Chi-pod measurements

尽管经向翻转环流在气候上具有重要意义，但由于观测资料有限，控制其强度的动力学仍然知之甚少。特别是，由于缺乏直接观测，对深层混合的异质性和空间变异的原因仍然知之甚少。该项目将对全海洋深度微观结构测量进行全球分析，以探索不同物理和动力制度下湍流混合率的幅度、模式和物理过程。这项工作将利用9次GO-SHIP重复水文巡航收集的1000多个新的微观结构全深度剖面，包括印度洋、太平洋和大西洋的纬向和经向剖面。这项工作将建立在对这种新型微观结构数据的现有强大处理技术的基础上，使所有结果都可用于海洋学研究界。该项目将使用新的GO-SHIP chi-pod数据集，该数据集提供了迄今为止最大的深海湍流测量综合数据集，以促进对深海混合的理解。该项目将评估细尺度参数化在深海中的应用，并与微观结构进行比较；探索在不同的物理和动力制度下观察到的湍流混合率的幅度、模式和物理过程；并通过chi-pods和精细尺度参数化的混合测量计算平均流域和全球扩散率。该分析将有助于更好地理解广泛使用的细尺度参数化的局限性和适用性，这些参数化是基于由内波-波相互作用驱动的湍流的假设。研究结果将提高对观测到的混合模式背后的过程的理解。最后，该项目将研究精细尺度技术不适用的深层湍流混合率的过程，包括内波平均流相互作用和双重扩散的作用。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Despite its large climatic importance, the dynamics controlling the strength of the meridional overturning circulation remain poorly understood due to limited observations. In particular, the heterogeneity of deep mixing and the cause of spatial variability is still poorly understood due to a lack of direct observations. This project will conduct a global analysis of full ocean-depth microstructure measurements to explore the magnitude, patterns, and physical processes underlying turbulent mixing rates across different physical and dynamical regimes. The work will capitalize on over 1000 new microstructure full-depth profiles collected on nine GO-SHIP repeat hydrography cruises, including zonal and meridional sections across the Indian, Pacific and Atlantic oceans. The work will build on existing robust processing techniques for this novel type of microstructure data, making all results available to the oceanographic research community.This project will use the new GO-SHIP chi-pod data set, which offers the largest comprehensive dataset of deep turbulence measurements to date, to advance understanding of deep ocean mixing. The project will evaluate the application of fine scale parameterizations in the deep ocean compared to microstructure; explore the magnitude, patterns, and physical processes underlying observed turbulent mixing rates across different physical and dynamical regimes; and calculate mean basin and global rates of diffusivity from measurements of mixing from the chi-pods and finescale parameterizations. The analysis will lead to a better understanding of the limits and applicability of widely used finescale parameterizations which are based on assumptions of turbulence driven by internal wave-wave interactions. The results will improve understanding of the processes underlying observed patterns of mixing. Finally, the project will investigate the role of processes that set deep turbulent mixing rates for which the finescale technique does not apply, including internal-wave mean flow interaction and double diffusion.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.