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Nonlinear mean-field dynamo and prediction of solar activity
Ural Fed Univ, Dept Informat Technol & Automat, 19 Mira Str, Ekaterinburg 620002, Russia..
KTH, Centres, Nordic Institute for Theoretical Physics NORDITA. Ben Gurion Univ Negev, Dept Mech Engn, POB 653, IL-84105 Beer Sheva, Israel.
Ural Fed Univ, Dept Informat Technol & Automat, 19 Mira Str, Ekaterinburg 620002, Russia..
KTH, Centres, Nordic Institute for Theoretical Physics NORDITA. Ben Gurion Univ Negev, Dept Mech Engn, POB 653, IL-84105 Beer Sheva, Israel.
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2018 (English)In: Journal of Plasma Physics, ISSN 0022-3778, E-ISSN 1469-7807, Vol. 84, no 3, article id 735840306Article in journal (Refereed) Published
Abstract [en]

We apply a nonlinear mean-field dynamo model which includes a budget equation for the dynamics of Wolf numbers to predict solar activity. This dynamo model takes into account the algebraic and dynamic nonlinearities of the alpha effect, where the equation for the dynamic nonlinearity is derived from the conservation law for the magnetic helicity. The budget equation for the evolution of the Wolf number is based on a formation mechanism of sunspots related to the negative effective magnetic pressure instability. This instability redistributes the magnetic flux produced by the mean-field dynamo. To predict solar activity on the time scale of one month we use a method based on a combination of the numerical solution of the nonlinear mean-field dynamo equations and the artificial neural network. A comparison of the results of the prediction of the solar activity with the observed Wolf numbers demonstrates a good agreement between the forecast and observations.

Place, publisher, year, edition, pages
Cambridge University Press, 2018. Vol. 84, no 3, article id 735840306
Keywords [en]
astrophysical plasmas, plasma nonlinear phenomena, space plasma physics
National Category
Physical Sciences
Identifiers
URN: urn:nbn:se:kth:diva-239506DOI: 10.1017/S0022377818000600ISI: 000449834900001Scopus ID: 2-s2.0-85059455239OAI: oai:DiVA.org:kth-239506DiVA, id: diva2:1265812
Note

QC 20181126

Available from: 2018-11-26 Created: 2018-11-26 Last updated: 2019-03-18Bibliographically approved

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Rogachevskii, Igor

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