A Statistical Analysis of Magnetic Parameters in Solar Source Regions of Halo-CMEs with and without SEP events

TL;DR

This study analyzes magnetic parameters in solar source regions of halo-CMEs to distinguish between those associated with SEP events and those without, revealing key differences in magnetic energy and source region characteristics.

Contribution

It introduces a statistical analysis of magnetic parameters in halo-CME source regions, identifying variables that could improve SEP event forecasting.

Findings

CME speed effectively discriminates SEP from No-SEP events.

SEP source regions have higher magnetic free energy and reconnection flux.

SEP regions are smaller in magnetic twist and shear angles.

Abstract

Large SEPs can cause adverse space weather hazard to humans technology and such events are especially associated with halo coronal mass ejections (CMEs). But in turn, a significant portion of halo-CMEs are not associated with large SEPs. The objective of this study is to gain an understanding of the source region distinctions between halo-CMEs in SEP and No-SEP events. Among the 176 halo-CMEs observed from 2010-2024, we screen out 45 large SEP events and 131 No-SEP events from this dataset. It is revealed that CME speed is a good discriminator between SEP and No-SEP events. Through classifying the source regions of all the halo-CMEs, we find that 53\% of SEP events originate from ``Single AR'', and 47\% from ``Multiple ARs'' or ``Outside of ARs''. The corresponding proportion for No-SEP events is 70\% and 30\%. This suggests that SEP source regions are more likely to originate from large-scale sources. We have also calculated the relevant magnetic parameters of the source regions and found that SEP source regions have higher magnetic free energy and reconnection flux compared to No-SEP source regions. However, SEP source regions are smaller in terms of the intensive magnetic parameters such as mean characteristic magnetic twist $\alpha$ and mean shear angles. Our statistical results can provide new potential variables for forecasting SEPs.