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Prediction of the Sun's magnetic activity is important because of its effecton space environment and climate. However, recent efforts to predict theamplitude of the solar cycle have resulted in diverging forecasts with noconsensus. Yeates et al. (2008) have shown that the dynamical memory of thesolar dynamo mechanism governs predictability and this memory is different foradvection- and diffusion-dominated solar convection zones. By utilizingstochastically forced, kinematic dynamo simulations, we demonstrate that theinclusion of downward turbulent pumping of magnetic flux reduces the memory ofboth advection- and diffusion-dominated solar dynamos to only one cycle;stronger pumping degrades this memory further. Thus, our results reconcile thediverging dynamo-model-based forecasts for the amplitude of solar cycle 24. Weconclude that reliable predictions for the maximum of solar activity can bemade only at the preceding minimum--allowing about 5 years of advance planningfor space weather. For more accurate predictions, sequential data assimilationwould be necessary in forecasting models to account for the Sun's short memory.

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