A Stochastically Forced Time Delay Solar Dynamo Model: Self-Consistent Recovery from a Maunder-like Grand Minimum Necessitates a Mean-Field Alpha Effect

TL;DR

This paper introduces a stochastic delay differential equation model for solar magnetic activity, revealing that recovery from grand minima requires a mean-field alpha-effect alongside the Babcock-Leighton mechanism.

Contribution

The study demonstrates that a combined model including a mean-field alpha-effect is essential for realistic simulation of solar cycle recovery from grand minima.

Findings

Babcock-Leighton mechanism alone cannot recover from grand minima.

Mean-field alpha-effect is necessary for cycle recovery.

Model captures the physics of magnetic flux transport with delays.

Abstract

Fluctuations in the Sun's magnetic activity, including episodes of grand minima such as the Maunder minimum have important consequences for space and planetary environments. However, the underlying dynamics of such extreme fluctuations remain ill-understood. Here we use a novel mathematical model based on stochastically forced, non-linear delay differential equations to study solar cycle fluctuations, in which, time delays capture the physics of magnetic flux transport between spatially segregated dynamo source regions in the solar interior. Using this model we explicitly demonstrate that the Babcock-Leighton poloidal field source based on dispersal of tilted bipolar sunspot flux, alone, can not recover the sunspot cycle from a grand minimum. We find that an additional poloidal field source effective on weak fields--the mean-field alpha-effect driven by helical turbulence--is necessary for self-consistent recovery of the sunspot cycle from grand minima episodes.