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This study examines geomagnetic field reversals, which occur at highly irregular intervals ranging from tens of thousands to tens of millions of years, using a low-dimensional geodynamo model driven by thermal convection. The researchers introduced a slow periodic modulation to the alpha-effect parameter, which governs large-scale magnetic induction, and found that this modulation produces a characteristic multi-peaked distribution of polarity persistence times, with peaks appearing at approximately integer multiples of the modulation period. This behavior is consistent with stochastic resonance, a phenomenon in which periodic forcing interacts with noise to organize the timing of transitions in a nonlinear system.
Why it matters
Understanding what controls the statistical distribution of geomagnetic reversals has implications for paleomagnetism, Earth's core dynamics, and the long-term evolution of the geomagnetic shield that protects Earth's surface from charged particle radiation. This framework offers a physically grounded mechanism by which slow astronomical or internal forcing cycles could imprint regularity onto otherwise irregular reversal sequences.
arXiv:2605.13867v1 Announce Type: new
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.
Source: Stochastic Resonance in a Thermally Driven Low-Dimensional Geodynamo Model