  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.
