Space Climate 7 Meeting Abstract
Solar cycles in the light of signal theory
Unto K. Laine (Aalto University)
Solar activity is monitored by counting the number of sunspots and sunspot groups on the visible disk of the sun. These numbers are combined and merged with many independent observations to form the final international sunspot number (SSN). Because the SSN sequence is the longest continuous record ever collected of any natural phenomena of our environment, it has evoked wide interest also from mathematical, information and signal theoretical points of view. The monthly sunspot numbers are considered in this study.
SSN sequence is quasiperiodic, where periodic components construct clear repeating structures that are partially masked by an additive noise component. All these aspects make the sequence demanding and interesting object of study for different time-series prediction methods. In such methods, the basic problem is to compress past observations into a functional model that can be used to make predictions for the future values of the SSN sequence.
The poster presents different signal theoretical methods applied to the SSN sequence analysis and modeling and presents a prediction for the coming cycle #25. It is shown that the recent cycle #24 is not as unique as often considered but can be modelled with a high accuracy based on the previous cycles. A novel model for even and odd numbered cycles are presented. The work also describes how to synchronize the sequences in order to find better coherency between them. The novel prediction method is based on a relatively simple multivariate regression method for modeling and prediction. The method predicts similar or slightly higher activity than the recent cycle based on the combinatory history of the preceding cycles. The result deviated quite much from a trigonometric model also considered in the poster.
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