Dynamic-Mode Decomposition of Geostrophically Balanced Motions from SWOT Altimetry

TL;DR

This paper demonstrates how dynamic-mode decomposition (DMD) can effectively separate geostrophically balanced motions from unbalanced motions in ocean surface height data, using simulations and SWOT satellite observations.

Contribution

It introduces a novel application of DMD to distinguish balanced and unbalanced ocean motions from high-resolution SSH data, including SWOT observations.

Findings

DMD successfully separates sub-inertial and super-inertial modes.

Sub-inertial modes correspond to geostrophically balanced motions.

DMD can extract internal tides and gravity waves from SSH fields.

Abstract

The decomposition of oceanic flow into its balanced and unbalanced motions carries theoretical and practical significance for the oceanographic community. These two motions have distinct dynamical characteristics and affect the transport of tracers differently from one another. The launch of Surface Water and Ocean Topography (SWOT) satellite provides a prime opportunity to diagnose the surface balanced and unbalanced motions on a global scale at an unprecedented spatial resolution. Here, we apply dynamic-mode decomposition (DMD), a linear-algebraic data-driven method, to a tidally-forced numerical simulation and one-day-repeat SWOT observations of sea-surface height (SSH) in the Gulf Stream extension. DMD is able to separate out the spatial modes associated with sub-inertial periods from super-inertial periods. The sub-inertial modes of DMD can be used to extract geostrophically balanced motions from SSH fields, which have an imprint of internal tides and gravity waves. We utilize the statistical relation between relative vorticity and strain rate as the metric to gauge the extraction of geostrophy.