Monthly sunspot numbers forecast with artificial neural network combined with dynamo model: Comparison with modern methods

Abstract

In this paper we propose a novel method for a monthly forecast of the total sunspot number time series, based on the combination of a dynamo model with an artificial neural network. The nonlinear autoregressive scheme is used with exo-genous input, consisting of two parts: the prior real observations and the corresponding model estimations at the same time-point. The results of the monthly forecast have been compared to all the modern sunspot forecasting methods, including data assimilation techniques, showing the higher accuracy of the proposed method when using one-step prediction and monthly corrections.