Kristóf Petrovay
Towards an algebraic method of solar cycle prediction
Petrovay, Kristóf; Nagy, Melinda; Yeates, Anthony R.
Abstract
We discuss the potential use of an algebraic method to compute the value of the solar axial dipole moment at solar minimum, widely considered to be the most reliable precursor of the activity level in the next solar cycle. The method consists of summing up the ultimate contributions of individual active regions to the solar axial dipole moment at the end of the cycle. A potential limitation of the approach is its dependence on the underlying surface flux transport (SFT) model details. We demonstrate by both analytical and numerical methods that the factor relating the initial and ultimate dipole moment contributions of an active region displays a Gaussian dependence on latitude with parameters that only depend on details of the SFT model through the parameter η/Δu where η is supergranular diffusivity and Δu is the divergence of the meridional flow on the equator. In a comparison with cycles simulated in the 2 × 2D dynamo model we further demonstrate that the inaccuracies associated with the algebraic method are minor and the method may be able to reproduce the dipole moment values in a large majority of cycles.
Citation
Petrovay, K., Nagy, M., & Yeates, A. R. (2020). Towards an algebraic method of solar cycle prediction. Journal of Space Weather and Space Climate, 10, Article 50. https://doi.org/10.1051/swsc/2020050
Journal Article Type | Article |
---|---|
Acceptance Date | Aug 31, 2020 |
Online Publication Date | Oct 14, 2020 |
Publication Date | 2020 |
Deposit Date | Oct 16, 2020 |
Publicly Available Date | Oct 16, 2020 |
Journal | Journal of Space Weather and Space Climate |
Electronic ISSN | 2115-7251 |
Publisher | EDP Open |
Peer Reviewed | Peer Reviewed |
Volume | 10 |
Article Number | 50 |
DOI | https://doi.org/10.1051/swsc/2020050 |
Public URL | https://durham-repository.worktribe.com/output/1289851 |
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Copyright Statement
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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