Mathematics – Probability
Scientific paper
May 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011spd....42.2216l&link_type=abstract
American Astronomical Society, SPD meeting #42, #22.16; Bulletin of the American Astronomical Society, Vol. 43, 2011
Mathematics
Probability
Scientific paper
We have investigated solar flare probability depending on sunspot classification, its area, and its area change using only solar white light data. For this we used the McIntosh sunspot group classification and then selected most flare-productive six sunspot groups : DKI, DKC, EKI, EKC, FKI and FKC. For each group, we classified it into three sub-groups according to sunspot area change : increase, steady, and decrease. For sunspot data, we used the NOAA active region information for 19 years (from January 1992 to December 2010): daily sunspot class and its area corrected for the projection effect. As a result, we find that the mean flare rates and the flare probabilities for the "increase" sub-groups are noticeably higher than those for other sub-groups. In the case of the (M+X)-class flares of `kc’ groups, the mean flare rates of the "increase"sub-groups are more than two times than those of the "steady"sub-groups. In the case of DKC sunspot group, the (M+X)-class flare probability of the "increase" sub-group is 53% while the "decrease" and "steady" sub-groups are 27% and 24%, respectively. This is statistical evidence that magnetic flux emergence is an very important mechanism for triggering solar flares since sunspot area can be a good proxy of magnetic flux. In addition, we are examining the relationship between sunspot area and solar flare probability. For this, we classified each sunspot group into two sub-groups: large and small. In the case of compact group, the solar flare probabilities noticeably increase with its area. We are going to develop a flare probability model depending on sunspot class, its area, and its area change.
Lee Kang-Jin
Moon YaeEun
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