Global Non-Potential Magnetic Models of the Solar Corona During the March 2015 Eclipse View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-08

AUTHORS

Anthony R. Yeates, Tahar Amari, Ioannis Contopoulos, Xueshang Feng, Duncan H. Mackay, Zoran Mikić, Thomas Wiegelmann, Joseph Hutton, Christopher A. Lowder, Huw Morgan, Gordon Petrie, Laurel A. Rachmeler, Lisa A. Upton, Aurelien Canou, Pierre Chopin, Cooper Downs, Miloslav Druckmüller, Jon A. Linker, Daniel B. Seaton, Tibor Török

ABSTRACT

Seven different models are applied to the same problem of simulating the Sun’s coronal magnetic field during the solar eclipse on 2015 March 20. All of the models are non-potential, allowing for free magnetic energy, but the associated electric currents are developed in significantly different ways. This is not a direct comparison of the coronal modelling techniques, in that the different models also use different photospheric boundary conditions, reflecting the range of approaches currently used in the community. Despite the significant differences, the results show broad agreement in the overall magnetic topology. Among those models with significant volume currents in much of the corona, there is general agreement that the ratio of total to potential magnetic energy should be approximately 1.4. However, there are significant differences in the electric current distributions; while static extrapolations are best able to reproduce active regions, they are unable to recover sheared magnetic fields in filament channels using currently available vector magnetogram data. By contrast, time-evolving simulations can recover the filament channel fields at the expense of not matching the observed vector magnetic fields within active regions. We suggest that, at present, the best approach may be a hybrid model using static extrapolations but with additional energization informed by simplified evolution models. This is demonstrated by one of the models. More... »

PAGES

99

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11214-018-0534-1

DOI

http://dx.doi.org/10.1007/s11214-018-0534-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106056836


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