A data assimilation algorithm for the subcritical surface quasi-geostrophic equation

TL;DR

This paper demonstrates that a data assimilation algorithm using feedback nudging can synchronize the surface quasi-geostrophic equation's surface temperature with the three-dimensional flow, despite nonlocal dissipation complexities.

Contribution

It introduces a novel data assimilation approach for the 3D quasi-geostrophic equation using boundary observations and addresses analytical challenges posed by nonlocal operators.

Findings

Successful synchronization of the 3D flow with boundary data

Handling of nonlocal dissipative operators in the analysis

Use of advanced mathematical tools like Littlewood-Paley decomposition

Abstract

In this article, we prove that data assimilation by feedback nudging can be achieved for the three-dimensional quasi-geostrophic equation in a simplified scenario using only large spatial scale observables on the dynamical boundary. On this boundary, a scalar unknown (buoyancy or surface temperature of the fluid) satisfies the surface quasi-geostrophic equation. The feedback nudging is done on this two-dimensional model, yet ultimately synchronizes the streamfunction of the three-dimensional flow. The main analytical difficulties are due to the presence of a nonlocal dissipative operator in the surface quasi-geostrophic equation. This is overcome by exploiting a suitable partition of unity, the modulus of continuity characterization of Sobolev space norms, and the Littlewood-Paley decomposition to ultimately establish various boundedness and approximation-of-identity properties for the observation operators.