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

尽管其在气候上具有很大的重要性，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，对深层混合的异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状态下湍流混合率的大小、模式和物理过程。这项工作将利用9次GO-SHIP重复水文学巡航中收集的1000多个新的微结构全深度剖面，包括印度洋，太平洋和大西洋的纬向和纬向剖面。这项工作将建立在现有的强大的处理技术，为这种新型的微观结构数据，使所有结果提供给海洋研究界，该项目将使用新的GO-SHIP chi-pod数据集，提供最大的综合数据集的深湍流测量到目前为止，以促进了解深海混合。该项目将评估细尺度参数化在深海中的应用，并与微结构进行比较;探索在不同物理和动力机制中观察到的湍流混合率的幅度、模式和物理过程;并根据chi-pod和细尺度参数化的混合测量值计算平均盆地和全球扩散率。分析将导致更好地了解广泛使用的细尺度参数化的限制和适用性，这些参数化是基于内部波-波相互作用驱动的湍流的假设。这些结果将提高对所观察到的混合模式的基本过程的理解。最后，该项目将调查的作用，设置深湍流混合率的细尺度技术不适用的过程，包括内波平均流相互作用和双diffusion.This奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

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.