Predicting Solar Filament Eruptions with HEK Filament Metadata

Solar filaments are cool, dark channels of partially-ionized plasma that lie above the chromosphere. Their structure follows the neutral line between local regions of opposite magnetic polarity. Previous research (e.g. Schmieder et al. 2013) has shown a positive correlation (80%) between the occurrence of filament eruptions and coronal mass ejections (CME's). If certain filament properties, such as length, chirality, and tilt, indicate a tendency towards filament eruptions, one may be able to further predict an oncoming CME. Towards this end, we present a novel algorithm based on spatiotemporal analysis that systematically correlates filament eruptions documented in the Heliophysics Event Knowledgebase (HEK) with HEK filaments that have been grouped together using a tracking algorithm developed at Georgia State University (e.g. Kempton et al. 2014). We also find filament tracks that are not correlated with eruptions to form a null data set in a similar fashion. Finally, we compare the metadata from erupting and non-erupting filament tracks to discover which filament properties may present signs of an eruption onset. Through statistical methods such as the two-sample Kolmogorov-Smirnov test and Random Forest Classifier, we find that a filament that is increasing in length or changing in tilt with respect to the equator may be a useful gauge to predict a filament eruption. However, the average values of length and tilt for both datasets follow similar distributions, leading us to conclude that these parameters do not indicate an eruption event. This work is supported by the NSF-REU solar physics program at SAO, grant number AGS-1263241, and NSF DIBBS grant number ACI-1443061.