Can meridional flow variations explain the observed rising/declining phase asymmetry in the solar cycle?
Authors
Soumitra Hazra
Allan Sacha Brun
Laurene Jouve
Abstract
Accurate prediction of the 11-year solar cycle remains a major challenge in solar physics and is important for space weather forecasting. A persistent property of the cycle is its asymmetry: the rise phase is usually much shorter than the decay phase. This asymmetry is often linked to variations in the Sun's meridional circulation, but it is unclear whether these variations are mainly deterministic, produced by Lorentz-force feedback, or stochastic in nature. We investigate this question using kinematic flux-transport dynamo simulations that include three types of time-dependent meridional flow: deterministic variations, stochastic fluctuations, and hybrid combinations of both. We evaluate cycle asymmetry using the ratio of rise to decay times and correlations of cycle amplitude with rise time, rise rate, and decay rate. Our results show that the temporal evolution of the meridional flow strongly controls cycle asymmetry. When both the meridional circulation and the Babcock-Leighton mechanism vary stochastically, the model does not produce cycles in which the decay phase is consistently longer than the rise phase. In contrast, deterministic variations motivated by Lorentz-force feedback and linked to the latitude of maximum toroidal field reproduce the observed asymmetry. In these cases, the meridional flow weakens near cycle maximum, stays reduced for some time, and then recovers, producing a longer decay phase. Hybrid models that mix deterministic and stochastic variability also match the observed rise-decay asymmetry. Across all simulations, cycle amplitude correlates strongly with rise rate, while correlations with rise time and decay rate are weaker but remain significant. These results highlight the key role of meridional flow variability in shaping solar cycle asymmetry and show that incorporating such variability can improve forecasting tools such as Solar Predict.