Inhomogeneous Ocean mean flows and energy spectra from sparse observations
Abstract
This proposal extends prior ONR-funded work on the physical modeling and mathematical analysis of wave-vortex energy decomposition methods, fusing them with newly developed abstract data analysis methods for sparse and unstructured data, and applying them the oceanic domains of interest, such as the Gulf Stream or the Kuroshio Current in the North Pacific. The overall aim is a significant sharpening and extension of practical tools to be used in the analysis and understanding of small-scale data arising in sub-mesoscale ocean dynamics.The kinematic description of the state of the ocean consists of the specification of the three-dimensional velocity field as a function of position and time. Since this field is highly inhomogeneous and comprises scales ranging from full ocean basins to the microscopic, it is convenient to decompose it into a large-scale mean field and a smaller-scale variability modeled as a stochastic process, with correlation functions that depend on distance and direction. Suchdescription faces challenges of two kinds: the sparsity of observations, and the need to reconcile the complex dynamics of the ocean with realistic models that are simple enough to be interpretable, not over fit the data, and yield useful predictions.The proposed work will develop a methodology to extract from sparse data a fairly complete description of the state of the ocean in terms of inhomogeneous mean fields and correlation functions, as well as a decomposition of the latter into their wave and vertical components. It will investigate oceanographic data sets based on unstructured horizontal velocity and buoyancy measurements, with analysis methods capable of detecting inhomogeneous mean flowsautomatically. This will allow for the first time the rational modeling of the statistical covariance structure of this kind of oceanographic data in the presence of non-trivial mean flows.Determining the amount of energy present in the ocean at each length scale in the form of wave action and in the vertical field is of clear relevance to the Navy. Past work focused on homogeneous flows and measurements taken along straight ship tracks. The new methodology proposed will perform this decomposition using unstructured sparse data from a variety of data sources, including Lagrangian tracer data obtained from floating devices.The new methodology also allows the computation of third-order statistical functions, which holds the promise of estimating energy fluxes from large to small scales, and of detecting how these fluxes can be attributed to internal waves on the one hand and quasi-geostrophic vortices on the other.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jun 13, 2019
- Source ID
- N000141912407
Entities
People
- Oliver Bühler
Organizations
- New York University
- Office of Naval Research
- United States Navy