### 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 (2007) 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.