Forward and adjoint quasi-geostrophic models of the geomagnetic secular variation

TL;DR

This paper develops a quasi-geostrophic core dynamics model incorporating non-zonal motions, and demonstrates its use with variational data assimilation and adjoint models to infer hidden core processes from geomagnetic data.

Contribution

It introduces a novel quasi-geostrophic model with adjoint-based data assimilation for core dynamics, extending previous models by including non-zonal motions and magnetic field interactions.

Findings

Adjoint model effectively retrieves unobserved core variables.

Model successfully links core surface magnetic data to interior dynamics.

Data assimilation improves core flow and magnetic field estimates.

Abstract

We introduce a quasi-geostrophic model of core dynamics, which aims at describing core processes on geomagnetic secular variation timescales. It extends the formalism of Alfv\'en torsional oscillations by incorporating non-zonal motions. Within this framework, the magnetohydrodynamics takes place in the equatorial plane; it involves quadratic magnetic quantities, which are averaged along the direction of rotation of the Earth. In addition, the equatorial flow is projected on the core-mantle boundary. It interacts with the magnetic field at the core surface, through the radial component of the magnetic induction equation. That part of the model connects the dynamics and the observed secular variation, with the radial component of the magnetic field acting as a passive tracer. We resort to variational data assimilation to construct formally the relationship between model predictions and observations. Variational data assimilation seeks to minimize an objective function, by computing its sensitivity to its control variables. The sensitivity is efficiently calculated after integration of the adjoint model. We illustrate that framework with twin experiments, performed first in the case of the kinematic core flow inverse problem, and then in the case of Alfv\'en torsional oscillations. In both cases, using the adjoint model allows us to retrieve core state variables which, while taking part in the dynamics, are not directly sampled at the core surface. We study the effect of several factors on the solution (width of the assimilation time window, amount and quality of data), and we discuss the potential of the model to deal with real geomagnetic observations.