J. Space Weather Space Clim.
Volume 10, 2020
Topical Issue - Space climate: The past and future of solar activity
|Number of page(s)||9|
|Published online||02 October 2020|
Towards an algebraic method of solar cycle prediction
II. Reducing the need for detailed input data with ARDoR
Department of Astronomy, Eötvös Loránd University, 1053 Budapest, Hungary
2 Département de Physique, Université de Montréal, H3T 1J4 Montréal, QC, Canada
3 Bois-de-Boulogne College, H4N 1L4 Montréal, QC, Canada
* Corresponding author: K.Petrovay@astro.elte.hu
Accepted: 31 August 2020
An algebraic method for the reconstruction and potentially prediction of the solar dipole moment value at sunspot minimum (known to be a good predictor of the amplitude of the next solar cycle) was suggested in the first paper in this series. The method sums up the ultimate dipole moment contributions of individual active regions in a solar cycle: for this, detailed and reliable input data would in principle be needed for thousands of active regions in a solar cycle. To reduce the need for detailed input data, here we propose a new active region descriptor called ARDoR (Active Region Degree of Rogueness). In a detailed statistical analysis of a large number of activity cycles simulated with the 2 × 2D dynamo model we demonstrate that ranking active regions by decreasing ARDoR, for a good reproduction of the solar dipole moment at the end of the cycle it is sufficient to consider the top N regions on this list explicitly, where N is a relatively low number, while for the other regions the ARDoR value may be set to zero. For example, with N = 5 the fraction of cycles where the dipole moment is reproduced with an error exceeding ±30% is only 12%, significantly reduced with respect to the case N = 0, i.e. ARDoR set to zero for all active regions, where this fraction is 26%. This indicates that stochastic effects on the intercycle variations of solar activity are dominated by the effect of a low number of large “rogue” active regions, rather than the combined effect of numerous small ARs. The method has a potential for future use in solar cycle prediction.
Key words: solar cycle / cycle prediction / rogue sunspots / surface flux transport modeling
© M. Nagy et al., Published by EDP Sciences 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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