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Guennou Chloé, Pariat Etienne, Leake J. E., Vilmer Nicole

Testing predictors of eruptivity using parametric flux emergence simulations

Journal of Space Weather and Space Climate, 2017, vol. 7

Référence DOI : 10.1051/swsc/2017015
Référence ADS : 2017JSWSC...7A..17G

Résumé :

Solar flares and coronal mass ejections (CMEs) are among the most energetic events in the solar system, impacting the near-Earth environment. Flare productivity is empirically known to be correlated with the size and complexity of active regions. Several indicators, based on magnetic field data from active regions, have been tested for flare forecasting in recent years. None of these indicators, or combinations thereof, have yet demonstrated an unambiguous eruption or flare criterion. Furthermore, numerical simulations have been only barely used to test the predictability of these parameters. In this context, we used the 3D parametric magnetohydrodynamic (MHD) numerical simulations of the self-consistent formation of the flux emergence of a twisted flux tube, inducing the formation of stable and unstable magnetic flux ropes of Leake et al. (2013, 2014). We use these numerical simulations to investigate the eruptive signatures observable in various magnetic scalar parameters and provide highlights on data analysis processing. Time series of 2D photospheric-like magnetograms are used from parametric simulations of stable and unstable flux emergence, to compute a list of about 100 different indicators. This list includes parameters previously used for operational forecasting, physical parameters used for the first time, as well as new quantities specifically developed for this purpose. Our results indicate that only parameters measuring the total non-potentiality of active regions associated with magnetic inversion line properties, such as the Falconer parameters L<SUB>ss</SUB>, WL<SUB>ss</SUB>, L<SUB>sg</SUB>, and WL<SUB>sg</SUB>, as well as the new current integral WL<SUB>sc</SUB> and length L<SUB>sc</SUB> parameters, present a significant ability to distinguish the eruptive cases of the model from the non-eruptive cases, possibly indicating that they are promising flare and eruption predictors. A preliminary study about the effect of noise on the detection of the eruptive signatures is also proposed.

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