Magnetic reversals in a geodynamo model with a stably-stratified layer
Nicolás Pablo Müller, Christophe Gissinger, François Pétrélis
TL;DR
The paper demonstrates that a stably-stratified layer beneath the core–mantle boundary strengthens the axial dipole and raises the dipolar–multipolar transition threshold, due to a skin effect that damps high-order magnetic modes. When an axisymmetric heterogeneous heat flux is imposed at the CMB, equatorial symmetry is broken, producing hemispheric dynamos or triggering polarity reversals through dipole–quadrupole interactions. Kinematic dynamo analyses reveal near-degeneracy between dipole and quadrupole growth rates in the SSL, supporting a low-dimensional mechanism for reversals and aligning with a broader class of dynamo models. These results suggest that SSLs can stabilize or enable Earth-like reversals, though the study operates at higher $E$ and $Pm$ than Earth's core, highlighting the need for further exploration toward Earth-like parameters.
Abstract
We study the process of magnetic reversals in the presence of a stably-stratified layer below the core-mantle boundary using direct numerical simulations of the incompressible magnetohydrodynamics equations under the Boussinesq approximation in a spherical shell. We show that the dipolar-multipolar transition shifts to larger Rayleigh numbers in the presence of a stably-stratified layer, and that the dipolar strength of the magnetic field at the core-mantle boundary increases due to the skin effect. By imposing an heterogeneous heat flux at the outer boundary, we break the equatorial symmetry of the flow, and show that different heat flux patterns can trigger different dynamo solutions, such as hemispheric dynamos and polarity reversals. Using kinematic dynamo simulations, we show that the stably-stratified layer leads to similar growth rates of the dipole and quadrupole components of the magnetic field, playing the role of a conducting boundary layer, favouring magnetic reversals, and a dynamics predicted by low-dimensional models.
