The growth rate of solar activity in the early phase of a solar cycle has been known to be well correlated with the subsequent amplitude （solar maximum）. It provides very useful information for a new solar cycle as its variation reflects the temporal evolution of the dynamic process of solar magnetic activities from the initial phase to the peak phase of the cycle. The correlation coefficient between the solar maximum （Rmax） and the rising rate （βa） at Am months after the solar minimum （Rmin） is studied and shown to increase as the cycle progresses with an inflection point （r = 0.83） at about Am = 20 months. The prediction error of Rmax based on βa is found within estimation at the 90% level of confidence and the relative prediction error will be less than 20% when Am ≥ 20. From the above relationship, the current cycle （24） is preliminarily predicted to peak around October, 2013 with a size of Rmax = 84 ＋ 33 at the 90% level of confidence.
An ensemble prediction model of solar proton events （SPEs）, combining the information of solar flares and coronal mass ejections （CMEs）, is built. In this model, solar flares are parameterized by the peak flux, the duration and the longitude. In addition, CMEs are parameterized by the width, the speed and the measurement position angle. The importance of each parameter for the occurrence of SPEs is estimated by the information gain ratio. We find that the CME width and speed are more informative than the flare’s peak flux and duration. As the physical mechanism of SPEs is not very clear, a hidden naive Bayes approach, which is a probability-based calculation method from the field of machine learning, is used to build the prediction model from the observational data. As is known, SPEs originate from solar flares and/or shock waves associated with CMEs. Hence, we first build two base prediction models using the properties of solar flares and CMEs, respectively. Then the outputs of these models are combined to generate the ensemble prediction model of SPEs. The ensemble prediction model incorporating the complementary information of solar flares and CMEs achieves better performance than each base prediction model taken separately.
Using the Hilbert-Huang Transform method, we investigate the periodic- ity in the monthly occurrence numbers and monthly mean energy of coronal mass ejections （CMEs） observed by the Large Angle and Spectrometric Coronagraph Experiment on board the Solar and Heliographic Observatory from 1999 March to 2009 December. We also investigate the periodicity in the monthly occurrence numbers of Hα flares and monthly mean flare indices from 1996 January to 2008 December. The results show the following. （1） The period of 5.66 yr is found to be statistically significant in the monthly occurrence numbers of CMEs; the period of 10.5 yr is found to be statistically significant in the monthly mean energy of CMEs. （2） The periods of 3.05 and 8.70 yr are found to be statistically significant in the monthly occurrence numbers of Hα flares; the period of 9.14 yr is found to be statistically significant in the monthly mean flare indices.
We examine the solar cycle distribution of major geomagnetic storms （Dst ≤ -100 nT）, including intense storms at the level of -200 nT〈 Dst ≤ -100 nT, great storms at -300 nT〈 Dst ≤-200 nT, and super storms at Dst ≤ -300 nT, which occurred during the period of 1957-2006, based on Dst indices and smoothed monthly sunspot numbers. Statistics show that the majority （82%） of the geomagnetic storms at the level of Dst≤ -100 nT that occurred in the study pe- riod were intense geomagnetic storms, with 12.4% ranked as great storms and 5.6% as super storms. It is interesting to note that about 27% of the geomagnetic storms that occurred at all three intensity levels appeared in the ascending phase of a solar cycle, and about 73% in the descending one. Statistics also show that 76.9% of the intense storms, 79.6% of the great storms and 90.9% of the super storms occurred during the two years before a solar cycle reached its peak, or in the three years after it. The correlation between the size of a solar cycle and the percentage of major storms that occurred, during the period from two years prior to maximum to three years af- ter it, is investigated. Finally, the properties of the multi-peak distribution for major geomagnetic storms in each solar cycle is investigated.
Gui-Ming LeZi-Yu CaiHua-Ning WangZhi-Qiang YinPeng Li
This is a study designed to analyze the relationship between ground level enhancements（GLEs）and their associated solar active regions during solar cycles 22and 23.Results show that 90.3%of the GLE events that are investigated are accompanied by X-class flares,and that 77.4%of the GLE events originate from super active regions.It is found that the intensity of a GLE event is strongly associated with the specific position of an active region where the GLE event occurs.As a consequence,the GLE events having a peak increase rate exceeding 50%occur in a longitudinal range from W20 to W100.Moreover,the largest GLE events occur in a heliographic longitude at roughly W60.Additionally,an analysis is made to understand the distributional pattern of the Carrington longitude of the active regions that have generated the GLE events.
