4.2 Is model-based cycle prediction feasible?

As it can be seen even from the very brief and sketchy presentation given above, all current solar dynamo models are based on a number of quite arbitrary assumptions and depend on a number of free parameters, the functional form and amplitude of which is far from being well constrained. For this reason, Bushby and Tobias (2007Jump To The Next Citation Point) rightfully say that all current solar dynamo models are only of “an illustrative nature”. This would suggest that as far as solar cycle prediction is concerned, the best we should expect from dynamo models is also an “illustrative” reproduction of a series of solar cycles with the same kind of long-term variations (qualitatively and, in the statistical sense, quantitatively) as seen in solar data. Indeed, Bushby and Tobias (2007) demonstrated that even a minuscule stochastic variation in the parameters of a particular flux transport model can lead to large, unpredictable variations in the cycle amplitudes. And even in the absence of stochastic effects, the chaotic nature of nonlinear dynamo solutions seriously limits the possibilities of prediction, as the authors find in a particular interface dynamo model: even if the very same model is used to reproduce the results of one particular run, the impossibility of setting initial conditions exactly representing the system implies that predictions are impossible even for the next cycle. Somewhat better results are achieved by an alternative method, based on the phase space reconstruction of the attractor of the nonlinear system – this is, however, a purely empirical time series analysis technique for which no knowledge of the detailed underlying physics is needed. (Cf. Section 3.3 above.)

Despite these very legitimate doubts regarding the feasibility of model-based prediction of solar cycles, in recent years several groups have claimed to be able to predict solar cycle 24 on the basis of dynamo models with a high confidence. So let us consider these claims.


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