SH43A-4171:
Study of Quasi-Homologous Coronal Mass Ejections from Super Active Regions in Solar Cycle 23

Thursday, 18 December 2014
Lijuan Liu, Yuming Wang, Chenglong Shen, Rui Liu, Pinzhong Ye and Shui Wang, USTC University of Science and Technology of China, Hefei, China
Abstract:
Coronal Mass Ejections are most severe eruptive phenomenon in the solar atmosphere and are believed as the major energy source of the Near-Earth Space Environment. The study of CMEs is very important for the Space Weather forecast. The active regions , especially super-active regions, containing lots of magnetic free energy, are considered as the most important source regions of CMEs. Knowing why and how may some active regions (ARs) frequently produce CMEs is one of the key questions to deepen our understanding of the mechanisms and processes of energy accumulation and sudden release in ARs as well as improving our capability of space weather prediction.

Based on above, we have done two parts of work: the first one is selecting all 37 SARs in the entire 23 solar cycle, using data provided by SOHO/LASCO C2|EIT|MDI, manually determining 285 CMEs produced by those SARs; second, we use the term ‘quasi-homologous’to refer to successive CMEs originating from the same ARs within a short interval, analyze the rules of quasi-homologous CMEs' generation. Finally, we got two conclusions.

1. The waiting times of quasi-homologous CMEs have a two-component distribution with a separation at about 18 hours. The first component is a Gaussian-like distribution with a peak at about 7 hours, which indicates a tight physical connection between these quasi-homologous CMEs. The likelihood of occurrences of two or more CMEs faster than 1200 km /s from the same AR within 18 hours is about 20%.

2. The correlation analysis among CME waiting times, CME speeds and CME occurrence rates reveals that these quantities are independent to each other, suggesting that the perturbation by preceding CMEs rather than free energy input be the direct cause of quasi-homologous CMEs. The peak waiting time of 7 hours probably characterize the time scale of the growth of instabilities triggered by preceding CMEs. This study uncovers more clues from a statistical perspective for us to understand quasi-homologous CMEs as well as CME-rich ARs.