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Entropy 2013, 15(11), 5022-5052;

Toward an Efficient Prediction of Solar Flares: Which Parameters, and How?

Research Center for Astronomy and Applied Mathematics (RCAAM), Academy of Athens, 4 Soranou Efesiou Street, Athens 11527, Greece
Marie Curie Fellow of the European Commission
Received: 31 July 2013 / Revised: 8 November 2013 / Accepted: 8 November 2013 / Published: 18 November 2013
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Solar flare prediction has become a forefront topic in contemporary solar physics, with numerous published methods relying on numerous predictive parameters, that can even be divided into parameter classes. Attempting further insight, we focus on two popular classes of flare-predictive parameters, namely multiscale (i.e., fractal and multifractal) and proxy (i.e., morphological) parameters, and we complement our analysis with a study of the predictive capability of fundamental physical parameters (i.e., magnetic free energy and relative magnetic helicity). Rather than applying the studied parameters to a comprehensive statistical sample of flaring and non-flaring active regions, that was the subject of our previous studies, the novelty of this work is their application to an exceptionally long and high-cadence time series of the intensely eruptive National Oceanic and Atmospheric Administration (NOAA) active region (AR) 11158, observed by the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. Aiming for a detailed study of the temporal evolution of each parameter, we seek distinctive patterns that could be associated with the four largest flares in the AR in the course of its five-day observing interval. We find that proxy parameters only tend to show preflare impulses that are practical enough to warrant subsequent investigation with sufficient statistics. Combining these findings with previous results, we conclude that: (i) carefully constructed, physically intuitive proxy parameters may be our best asset toward an efficient future flare-forecasting; and (ii) the time series of promising parameters may be as important as their instantaneous values. Value-based prediction is the only approach followed so far. Our results call for novel signal and/or image processing techniques to efficiently utilize combined amplitude and temporal-profile information to optimize the inferred solar-flare probabilities. View Full-Text
Keywords: frequentist data analysis; magnetic field; solar transients frequentist data analysis; magnetic field; solar transients

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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Georgoulis, M.K. Toward an Efficient Prediction of Solar Flares: Which Parameters, and How? Entropy 2013, 15, 5022-5052.

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