We use machine learning methods to predict whether an active region (AR) which produces flares will lead to a solar energetic particle (SEP) event using Space-Weather Michelson Doppler Imager (MDI) Active Region Patches (SMARPs). This new data product is derived from maps of the solar surface magnetic field taken by the Michelson Doppler Imager (MDI) aboard the Solar and Heliospheric Observatory (SOHO). We survey the SMARP active regions associated with flares that appear on the solar disk between June 5, 1996 and August 14, 2010, label those that produced SEPs as positive and the rest as negative. The AR SMARP features that correspond to each flare are used to train two different types of machine learning methods, the support vector machines (SVMs) and the regression models. The results show that the SMARP data can predict whether a flare will lead to an SEP with accuracy (ACC) {less than or equal to}0.72{plus minus}0.12 while allowing for a competitive leading time of 55.3{plus minus}28.6 minutes for forecasting the SEP events.

The Solar Dynamics Observatory (SDO) is a solar mission in an inclined geosynchronous orbit. Since commissioning, images acquired by Atmospheric Imaging Assembly (AIA) instrument on-board the SDO have frequently displayed “spikes”, pixel regions yielding extreme number of digital counts. These are theorized to occur from energetic electron collisions with the instrument detector system. These spikes are regularly removed from AIA Level 1.0 images to produce clean and reliable data. A study of historical data has found over 100 trillion spikes in the past decade. This project correlates spike detection frequency with radiation environment parameters in order to generate an augmented data product from SDO. We conduct a correlation study between SDO/AIA data and radiation belt activity within the SDO’s orbit. By extracting radiation “spike” data from the SDO/AIA images, we produce a comprehensive data product which is correlated not only with geomagnetic parameters such as Kp, Ap and Sym-H but also with the electron and proton fluxes measured by the GOES-14 satellite. As a result, we find that AIA spikes are highly correlated with the GOES-14 electrons detected by the MAGED and EPEAD instruments at the equator (where the two satellites meet) with Spearman’s Correlation values of ρ=0.73 and ρ=0.53 respectively, while a weaker correlation of ρ=0.47 is shown with MAGPD protons for the two year period where both missions returned data uninterruptedly. This correlation proves that the SDO spike data can be proven useful for characterizing the Van Allen radiation belt, especially at areas where other satellites cannot.