Turbulent Pumping of Magnetic Flux Reduces Solar Cycle Memory and thus Impacts Predictability of the Sun's Activity

TL;DR

This study shows that turbulent pumping of magnetic flux in the solar dynamo reduces its memory to one cycle, limiting the predictability of solar activity and emphasizing the need for early data assimilation for accurate forecasts.

Contribution

It demonstrates through simulations that turbulent pumping shortens the solar dynamo memory, explaining diverging forecasts and improving understanding of solar cycle predictability.

Findings

Turbulent pumping reduces solar dynamo memory to one cycle.

Stronger pumping further degrades predictability.

Reliable predictions require data assimilation and early minimum observations.

Abstract

Prediction of the Sun's magnetic activity is important because of its effect on space environment and climate. However, recent efforts to predict the amplitude of the solar cycle have resulted in diverging forecasts with no consensus. Yeates et al. (2008) have shown that the dynamical memory of the solar dynamo mechanism governs predictability and this memory is different for advection- and diffusion-dominated solar convection zones. By utilizing stochastically forced, kinematic dynamo simulations, we demonstrate that the inclusion of downward turbulent pumping of magnetic flux reduces the memory of both advection- and diffusion-dominated solar dynamos to only one cycle; stronger pumping degrades this memory further. Thus, our results reconcile the diverging dynamo-model-based forecasts for the amplitude of solar cycle 24. We conclude that reliable predictions for the maximum of solar activity can be made only at the preceding minimum--allowing about 5 years of advance planning for space weather. For more accurate predictions, sequential data assimilation would be necessary in forecasting models to account for the Sun's short memory.