Ensemble Forecasting of Major Solar Flares with Short-, Mid-, and Long-term Active Region Properties

Abstract

Abstract We apply an ensemble technique for major flare prediction by considering short-, mid-, and long-term active region (AR) properties and their relative contributions. For this, we consider magnetic parameters from Solar Dynamics Observatory/Helioseismic and Magnetic Imager and flare lists from Geostationary Operational Environmental Satellites. In this study, we simultaneously consider flaring rates during short- (1 day), mid- (several days), and long-term (several years) timeframes. In our model, the predicted rate is given by a weighted combination of the three rates such that the sum of their weights is 1. We calculate the Brier skill scores (BSSs) for investigating prediction performance and weights of these three terms to provide optimal results. The BSS (0.22) of the model with only long-term properties is higher than that with only short-term (0.07) or mid-term (0.08) properties. When short-/mid-term properties are additionally considered, the BSS is improved to 0.28/0.24. Our model has the best performance (BSS = 0.29) when all terms are considered, and their relative contributions to the short-, mid-, and long-term rates are 20%, 20%, and 60%, respectively. In addition, the model with three terms is more effective at predicting major flares in strong ARs. In view of the energy storage and release process, long-term magnetic properties may indicate the storage of magnetic free energy, while short- and mid-term flare history may reflect a recent trend of energy release process. Our results suggest that the performances of other existing flare models based on long-term properties should be improved by considering short- and/or mid-term flare history.