Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-10T14:45:58.568Z Has data issue: false hasContentIssue false
  • English
  • Français

Global evolution of solar magnetic fields and prediction of activity cycles

Published online by Cambridge University Press:  24 September 2020

Irina N. Kitiashvili Open the ORCID record for Irina N. Kitiashvili [Opens in a new window]
Irina N. Kitiashvili*
Affiliation:
NASA Ames Research Center, Moffett Field, MS 258-6, Mountain View, USA email: mailto:irina.n.kitiashvili@nasa.gov
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Prediction of solar activity cycles is challenging because physical processes inside the Sun involve a broad range of multiscale dynamics that no model can reproduce and because the available observations are highly limited and cover mostly surface layers. Helioseismology makes it possible to probe solar dynamics in the convective zone, but variations in differential rotation and meridional circulation are currently available for only two solar activity cycles. It has been demonstrated that sunspot observations, which cover over 400 years, can be used to calibrate the Parker-Kleeorin-Ruzmaikin dynamo model, and that the Ensemble Kalman Filter (EnKF) method can be used to link the modeled magnetic fields to sunspot observations and make reliable predictions of a following activity cycle. However, for more accurate predictions, it is necessary to use actual observations of the solar magnetic fields, which are available only for the last four solar cycles. In this paper I briefly discuss the influence of the limited number of available observations on the accuracy of EnKF estimates of solar cycle parameters, the criteria to evaluate the predictions, and application of synoptic magnetograms to the prediction of solar activity.

Keywords

Sun: interiormagnetic fieldssunspotsstars: activitymethods: data analysisstatistical
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 15 , Symposium S354: Solar and Stellar Magnetic Fields: Origins and Manifestations , June 2019 , pp. 147 - 156
Copyright
© International Astronomical Union 2020

References

Bracewell, R. N. 1988, MNRAS, 230, 535CrossRefGoogle Scholar
Cameron, R. & Schüssler, M. 2007, ApJ, 659, 801CrossRefGoogle Scholar
Choudhuri, A. R., Chatterjee, P., & Jiang, J. 2007, Physical Review Letters, 98, 131103CrossRefGoogle Scholar
Covas, E., Peixinho, N., & Fernandes, J. 2019, Sol. Phys., 294, 24CrossRefGoogle Scholar
Dikpati, M. & Gilman, P. A. 2007, New Journal of Physics, 9, 297CrossRefGoogle Scholar
Evensen, G. 1997, Data Assimilation: The Ensemble Kalman Filter (Springer)Google Scholar
Harvey, J., Gillespie, B., Miedaner, P., & Slaughter, C. 1980, NASA STI/Recon Technical Report N, 81Google Scholar
Jiang, J. & Cao, J. 2018, Journal of Atmospheric and Solar-Terrestrial Physics, 176, 34CrossRefGoogle Scholar
Jouve, L., Brun, A. S., & Talagrand, O. 2011, ApJ, 735, 31CrossRefGoogle Scholar
Kalnay, E. 2002, Atmospheric Modeling, Data Assimilation and Predictability (Cambridge University Press), 364CrossRefGoogle Scholar
Karak, B. B. & Choudhuri, A. R. 2013, Research in Astronomy and Astrophysics, 13, 1339CrossRefGoogle Scholar
Keller, C. U., Harvey, J. W., & Giampapa, M. S. 2003, in, Vol. 4853, Innovative Telescopes and Instrumentation for Solar Astrophysics, ed. Keil, S. L. & Avakyan, S. V., 194–204Google Scholar
Kitiashvili, I. & Kosovichev, A. G. 2008, ApJ, 688, L49CrossRefGoogle Scholar
Kitiashvili, I. N. 2016, ApJ, 831, 15CrossRefGoogle Scholar
Kitiashvili, I. N. 2020a, https://arxiv.org/abs/2001.09376Google Scholar
Kitiashvili, I. N. 2020b, ApJ, 890, 36CrossRefGoogle Scholar
Kitiashvili, I. N. & Kosovichev, A. G. 2009, Geophysical and Astrophysical Fluid Dynamics, 103, 53CrossRefGoogle Scholar
Kleeorin, N. I. & Ruzmaikin, A. A. 1982, Magnetohydrodynamics, 18, 116Google Scholar
Labonville, F., Charbonneau, P., & Lemerle, A. 2019, Sol. Phys., 294, 82CrossRefGoogle Scholar
Macario-Rojas, A., Smith, K. L., & Roberts, P. C. E. 2018, MNRAS, 479, 3791CrossRefGoogle Scholar
Scherrer, P. H., Bogart, R. S., Bush, R. I., et al. 1995, Sol. Phys., 162, 129CrossRefGoogle Scholar
Scherrer, P. H., Schou, J., Bush, R. I., et al. 2012, Sol. Phys., 275, 207CrossRefGoogle Scholar
Upton, L. A. & Hathaway, D. H. 2018, Geophys. Res. Lett., 45, 8091CrossRefGoogle Scholar
Weiss, N. O., Cattaneo, F., & Jones, C. A. 1984, Geophysical and Astrophysical Fluid Dynamics, 30, 305CrossRefGoogle Scholar
Worden, J. & Harvey, J. 2000, Sol. Phys., 195, 247CrossRefGoogle Scholar