Investigating The Reliability Of Solar Photospheric Eruptivity Proxies.
Abstract
Solar flares and coronal mass ejections (CMEs) are among the most energetic events in the solar system, impacting the near-Earth environment and thus our technologies. The European H2020 research project FLARECAST (Flare Likelihood and Region Eruption Forecasting) aims to develop a fully automated solar flare forecasting system with unmatched accuracy compared to existing facilities. FLARECAST will automatically extract magnetic-field parameters of solar active regions from solar magnetogram and white-light images to produce accurate predictions using the state-of-the-art forecasting techniques based on data-mining and machine learning. Flare productivity is empirically known to be correlated with the size and complexity of active regions. Several parameters, based on magnetic-field data from active regions have been tested in recent years. None of these parameters, or combination of thereof, have yet demonstrated an unambiguous eruption criterion. However, the predictability of these parameters has so far only been tested on observational data and never on controlled-cases, e.g., originating from numerical datasets. In the framework of the FLARECAST explorative research component, we use MHD numerical simulations of the formation of stable and unstable magnetic flux ropes (Leake et al. 2013, 2014) to evaluate the predictive potential of different magnetic parameters. Time series of magnetograms are used from parametric simulations of stable and unstable flux emergence, to compute a list of about 111 different parameters. This list includes parameters previously used for forecasting, as well as parameters used for the first time for this purpose. Our results indicate that only parameters measuring the total non-potentiality of active regions, such as Lssm and Lsgm and WLsg and the total length of the inversion line present significant preflare signatures, probably making them successful flare predictors.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFMSH11C2236G
- Keywords:
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- 4305 Space weather;
- NATURAL HAZARDSDE: 7594 Instruments and techniques;
- SOLAR PHYSICS;
- ASTROPHYSICS;
- AND ASTRONOMYDE: 7924 Forecasting;
- SPACE WEATHERDE: 7999 General or miscellaneous;
- SPACE WEATHER