Stochastic Resonance in a Thermally Driven Low-Dimensional Geodynamo Model

TL;DR

This study demonstrates how slow periodic modulation of a geodynamo model's control parameter can organize magnetic reversal times through stochastic resonance, revealing characteristic timescales linked to the modulation period.

Contribution

It introduces a numerical framework showing that slow modulation induces stochastic-resonance-like behavior in geomagnetic reversal statistics.

Findings

Probability density of reversal times shows peaks at multiples of the modulation period.

Peak positions depend linearly on their index, indicating characteristic timescales.

The model links slow control parameter modulation to organized reversal statistics.

Abstract

Geomagnetic field reversal sequences exhibit persistence times spanning a broad range, from a few $10^4$ years to superchrons lasting more than $10^7$ years. Despite extensive observational and theoretical work, the physical mechanisms governing how such reversals occur and how their broad temporal variability is organized are still not fully understood. Here we investigate the temporal variability of geomagnetic polarity in a thermally driven low-dimensional geodynamo model subject to a slow periodic modulation of the control parameter governing the large-scale induction, namely the $\alpha$-effect parameter. We find that the modulation generates a multipeaked probability density function of magnetic persistence times, with local maxima occurring at approximately integer multiples of the modulation timescale, as expected in a stochastic-resonance-like regime. The peak positions follow an approximately linear dependence on their index, showing that the characteristic timescales selected by the system are set by the imposed modulation period. These results provide a physically motivated numerical framework in which slow modulation of a geodynamo control parameter can organize reversal statistics through stochastic-resonance-like dynamics.