Characterizing Ocean Flows with the Scattering Transform

TL;DR

This paper demonstrates that the scattering transform can effectively characterize complex ocean flow dynamics, distinguishing different types of motion beyond traditional spectral analysis, with applications to satellite and radar data.

Contribution

It introduces the use of the scattering transform for analyzing ocean flows, providing a new method to differentiate flow types with similar power spectra.

Findings

ST differentiates balanced dynamics, internal waves, and turbulence.

Applied to ocean model SSH data, ST identifies regions with distinct dynamics.

Framework applicable to satellite and radar spatial data.

Abstract

Upper-ocean flows are a multi-scale jigsaw puzzle of turbulence and waves. Characterizing these flows is essential for understanding their role in redistributing heat, carbon, and nutrients, yet power spectral analysis cannot always distinguish between types of motion. We show that the scattering transform (ST), a wavelet convolution method, can extract geometric information from flow fields, offering insights beyond the power spectrum. The ST distinguishes balanced dynamics, internal waves, and types of turbulence -- even when their power spectra are identical. Applied to sea surface height (SSH) fields from ocean models, the ST differentiates regions with distinct underlying dynamics. Our analysis offers a framework for interpreting SSH from satellite altimetry missions and for analyzing other spatial maps (e.g., from airborne and coastal radar). More generally, the ST is an appealing way to characterize complex fluid motion in a variety of geophysical contexts.