Can Solar Limb Flare Prediction Be Properly Made by Extreme-ultraviolet Intensities?

Abstract

We address the question of whether the solar limb flare prediction can be properly made by EUV intensity, which has less projection effects than solar white light and magnetogram data. We develop empirical and multilayer perceptron (MLP) models to forecast the probability of a major solar limb flare within a day. We use Solar Dynamics Observatory (SDO)/Atmospheric Imaging Assembly (AIA) 94 and 131 Å that have high correlations and large slopes with X-ray flare fluxes from 2010 to 2022. We select 240 flares stronger than or equal to the M1.0 class and located near the limb region (60° or more in heliographic longitude). For input data, we use the limb intensity as the sum of SDO/AIA intensities in the limb region and the total intensity of the whole image. We compare the model performances using metrics such as the receiver operating characteristic—area under the curve. Our major results are as follows. First, we can forecast major solar limb flare occurrences with only SDO/AIA 94 and/or 131 Å intensities. Second, our models show better probability prediction than the climatological model. Third, both empirical (AUC = 0.85) and MLP (AUC = 0.84) models have similar performances, which are much better than a random forecast (AUC = 0.50). Finally, it is interesting to note that our model can forecast the flaring probability of all 52 events during the test period, while the models in the NASA/CCMC flare scoreboard can forecast only 22 events. From the above results, we can answer that the solar limb flare prediction using EUV intensity can be properly made.

Keywords

• The Sun
• Solar extreme ultraviolet emission
• Solar flares
• Neural networks