Measuring Mesoscale Mixing: Developing New Spatial Statistics to Analyze Ocean Observations

测量中尺度混合：开发新的空间统计来分析海洋观测

基本信息

批准号：
2023721
负责人：
Brodie Pearson
金额：
$ 41.72万
依托单位：
Oregon State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2023721&HistoricalAwards=false
关键词：
Measuring Mesoscale Mixing Developing New

项目摘要

Mesoscale ocean dynamics play a critical role in the Earth system by moving and mixing properties within the ocean and providing essential feedback mechanisms for the ocean's large-scale thermodynamics. This project will (1) use a hierarchy of numerical models to quantify the benefits of these novel statistics under different flow regimes and under sampling patterns consistent with observational platforms, (2) develop new structure functions (statistics that depend on spatial differences and cross-correlations of data) which increase the accuracy of mesoscale flux measurements and assess them in models, and (3) apply these statistics to a range of observations to explore their additional insights into mesoscale fluxes. This project will provide unprecedented quantification of mesoscale ocean fluxes and prepare scientists with the optimal tools to analyze future data sets. These observations will inform us about the energy pathways through the Earth system and will aid the evaluation of the fidelity of conceptual and numerical models, and the accuracy of their forecast capabilities.This project will use an array of structure functions to more accurately quantify mesoscale ocean fluxes of energy, enstrophy, and other dynamic properties. It result in optimal tools to analyze future data sets. These goals will be achieved through three concurrent research threads. First, a range of numerical models will simulate various dynamical regimes to identify and compare the utility of different structure functions for assessing both the full model fields and emulated observations from a range of measurement platforms. These models span from idealized two-dimensional dynamics to primitive equation models that include ocean-atmosphere coupling and the effects of dynamics outside of the mesoscale. Their hierarchy will diagnose the conditions under which different structure functions can quantify mesoscale fluxes, and the limitations of structure functions that result from sampling or measurement biases, or from multi-scale physical processes. Second, new structure functions will be developed which are tailored to maximize information from models and specific ocean data collection methods. As they are developed, these new structure functions will be included in our analysis of numerical models. Finally, the results of the numerical model analysis will guide a diagnosis of mesoscale fluxes from observational data sets by applying appropriate structure functions to these data sets.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.

中尺度海洋动力学通过移动和混合海洋内的特性并为海洋大尺度热力学提供必要的反馈机制，在地球系统中发挥着至关重要的作用。该项目将（1）使用层次化的数值模型来量化这些新颖的统计数据在不同流态和与观测平台一致的采样模式下的好处，（2）开发新的结构函数（依赖于空间差异和交叉的统计数据）数据的相关性），这提高了中尺度通量测量的准确性并在模型中对其进行评估，并且（3）将这些统计数据应用于一系列观测，以探索对中尺度通量的额外见解。该项目将为中尺度海洋通量提供前所未有的量化，并为科学家提供分析未来数据集的最佳工具。这些观测结果将告诉我们通过地球系统的能量路径，并将有助于评估概念和数值模型的保真度及其预测能力的准确性。该项目将使用一系列结构函数来更准确地量化中尺度海洋能量通量、熵和其他动态特性。它产生了分析未来数据集的最佳工具。这些目标将通过三个并行的研究线索来实现。首先，一系列数值模型将模拟各种动态状态，以识别和比较不同结构函数的效用，以评估完整的模型场和一系列测量平台的模拟观测结果。这些模型涵盖从理想化的二维动力学到原始方程模型，其中包括海洋-大气耦合和中尺度之外的动力学影响。他们的层次结构将诊断不同结构函数可以量化介尺度通量的条件，以及由于采样或测量偏差或多尺度物理过程而导致的结构函数的局限性。其次，将开发新的结构函数，以最大限度地利用模型和特定海洋数据收集方法的信息。随着它们的开发，这些新的结构函数将包含在我们的数值模型分析中。最后，数值模型分析的结果将通过对观测数据集应用适当的结构函数来指导对这些数据集的中尺度通量的诊断。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值进行评估，被认为值得支持以及更广泛的影响审查标准。