PCA Method On The Analysis Of Major Parameters In Solar Active Regions

With the rapid progress of science and technology and the need of human beings, we have space for a deeper understanding of space environment. As a source of light and heat, the sun’s activity has close relationship with the Earth and human beings. It is widely accepted that solar activity is closely related to the Sun-Earth system. There for, the analysis and prediction of solar activity is a very meaningful research.Solar active region has close relationship with solar flares and solar proton events. In order to better understand the complicated relations between them as well as build a concrete foundation for the forecasting of solar flares and solar proton events, the principal component analysis (PCA) method is adopted to analyze the main parameters of solar active regions during2007-2010. The parameters selected include sunspot magnetic classification, McIntosh classification, sunspot group area,10.7cm radio flux, flare index,proton flux, the position of proton flares and soft X-ray flare intensity.The results obtained81principal component scores compared with the solar proton event peak flow and annual average sunspot,10.7cm radio flux annual average, and it is found that the similarity is very high. Principal component score is fitted with proton flux, correlation coefficient is0.7752, confidence level is85%. The statistic results show that the principal component scores represent the strength of solar activity to some extent.