Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-26T05:11:21.821Z Has data issue: false hasContentIssue false

Sandpile Models and Solar Flares: Eigenfunction Decomposition for Data Assimilation

Published online by Cambridge University Press:  24 July 2018

Antoine Strugarek
Affiliation:
Laboratoire AIM Paris-Saclay, CEA/Irfu Université Paris-Diderot CNRS/INSU, F- 91191 Gif-sur-Yvette email: [email protected] Département de physique, Université de Montréal, C.P. 6128 Succ. Centre-Ville, Montréal, QC H3C-3J7, Canada
Allan S. Brun
Affiliation:
Laboratoire AIM Paris-Saclay, CEA/Irfu Université Paris-Diderot CNRS/INSU, F- 91191 Gif-sur-Yvette email: [email protected]
Paul Charbonneau
Affiliation:
Département de physique, Université de Montréal, C.P. 6128 Succ. Centre-Ville, Montréal, QC H3C-3J7, Canada
Nicole Vilmer
Affiliation:
LESIA, Observatoire Paris, CNRS, UPMC, Universite Paris-Diderot, 5 place Jules Janssen, 92195 Meudon, France
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.

The largest solar flares, of class X and above, are often associated with strong energetic particle acceleration. Based on the self-similar distribution of solar flares, self-organized criticality models such as sandpiles can be used to successfully reproduce their statistics. However, predicting strong (and rare) solar flares turns out to be a significant challenge. We build here on an original idea based on the combination of minimalistic flare models (sandpiles) and modern data assimilation techniques (4DVar) to predict large solar flares. We discuss how to represent a sandpile model over a reduced set of eigenfunctions to improve the efficiency of the data assimilation technique. This improvement is model-independent and continues to pave the way towards efficient near real-time solutions for predicting solar flares.

Keywords

Type
Contributed Papers
Copyright
Copyright © International Astronomical Union 2018 

References

Aschwanden, M. J., Crosby, N. B., Dimitropoulou, M., et al. 2016, Space Sci Rev, 198, 47Google Scholar
Barnes, G., Leka, K. D., Schrijver, C. J., et al. 2016, ApJ, 829, 89Google Scholar
Bélanger, E., Vincent, A. & Charbonneau, P. 2007, Sol. Phys., 245, 141Google Scholar
Charbonneau, P. 2013, in Self-Organized Criticality Systems, ed. Aschwanden, M. J. (Open Academic Press), 404Google Scholar
Hung, C. P., Brun, A. S., Fournier, A., et al. 2017, ApJ submittedGoogle Scholar
Lu, E. T. & Hamilton, R. J. 1991, ApJL, 380, L89Google Scholar
Pulkkinen, T. 2007, LRSP, 4, 1Google Scholar
Schwenn, R. 2006, LRSP, 3, 2Google Scholar
Strugarek, A. & Charbonneau, P. 2014, Sol. Phys., 289, 4137Google Scholar
Strugarek, A., Charbonneau, P., Joseph, R. & Pirot, D. 2014, Sol. Phys., 289, 2993Google Scholar