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

尽管它在气候上具有重要意义，但由于观测有限，控制经向翻转环流强度的动力学仍然知之甚少。特别是，由于缺乏直接观测，深层混合的非均质性和空间变异性的原因仍然知之甚少。该项目将对全海洋深度微结构测量进行全球分析，以探索不同物理和动力体制下湍流混合率背后的量级、模式和物理过程。这项工作将利用在九次Go-Ship重复水文巡航中收集的1000多个新的微结构全深度剖面，包括横跨印度洋、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结构数据的现有稳健处理技术的基础上，将所有结果提供给海洋学研究界。该项目将使用新的Go-Ship X-Pod数据集，它提供了迄今为止最大的深部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与微结构的比较；探索不同物理和动力制度下观测到的湍流混合率背后的等级、模式和物理过程；并根据从X-Pod和FineScale参数化测量的混合计算平均盆地和全球扩散率。这一分析将使我们更好地了解广泛使用的FineScale参数化的局限性和适用性，这些参数化是基于内部波-波相互作用驱动的湍流假设。这些结果将提高对观察到的混合模式背后的过程的理解。最后，该项目将调查设定FineScale技术不适用的深层湍流混合率的过程所起的作用，包括内波平均流相互作用和双扩散。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.