Evidence for a Strong Correlation of Solar Proton Events with Solar Radio Bursts

A statistical analysis is made on the correlation between solar proton events with energies >10Mev and solar radio bursts during the four-year period from 1997 November to 2000 November. We examine 28 solar proton events and their corresponding solar radio bursts at 15400, 8800, 4995, 2695, 1415, 606, 410 and 245 MHz. The statistical result shows that there is a close association between solar proton events and ≥3 solar radio bursts occurring at several frequencies, one or two days before. In particular, it is noteworthy that proton events occurring in pairs within the same month are preceded 1-2 days by individual radio bursts and most of the radio bursts of solar flares occur at all eight frequencies. Those 245 MHz radio bursts associated with proton events have intense peak fluxes (up to 67000 sfu). Solar proton events are preceded 1 or 2 days by≥ 3 radio bursts at several frequencies and proton events occurring in pairs within the same month are preceded 1 or 2 days by some individual radio bursts. These correlations may be used for providing short-term or medium-term prediction of solar proton events.

Detection of solar radio burst intensity based on a mod ified multifactor SVM algorithm

To realize the automatic detection of solar radio burst(SRB)intensity,detection based on a modified multifactor support vector machine(SVM)algorithm is proposed.First,the influence of SRB on global navigation satellite system(GNSS)signals is analyzed.Feature vectors,which can reflect the SRB intensity of stations,are also extracted.SRB intensity is classified according to the solar radio flux,and different class labels correspond to different SRB intensity types.The training samples are composed of feature vectors and their corresponding class labels.Second,training samples are input into SVM classifiers to one-against-one training to obtain the optimal classification models.Finally,the optimal classification model is synthesized into a modified multifactor SVM classifier,which is used to automatically detect the SRB intensity of new data.Experimental results indicate that for historical SRB events,the average accuracy of SRB intensity detection is greater than 90%when the solar incident angle is higher than 20°.Compared with other methods,the proposed method considers many factors with higher accuracy and does not rely on radio telescopes,thereby saving cost.

Radio observations of the fine structure inside a post-CME current sheet

A solar radio burst was observed in a coronal mass ejection/flare event by the Solar Broadband Radio Spectrometer at the Huairou Solar Observing Station on2004 December 1. The data exhibited various patterns of plasma motions, suggestive of the interaction between sunward moving plasmoids and the flare loop system during the impulsive phase of the event. In addition to the radio data, the associated whitelight, Hα, extreme ultraviolet light, and soft and hard X-rays were also studied.

Automatic Detection of Solar Radio Spectrum Based on Codebook Model

Space weather can affect human production and life,and solar radio burst will seriously affect space weather.Automatic detection of solar radio bursts in real time has a positive effect on space weather warning and prediction.Codebook model is used to simulate solar background radio to achieve automatic detection of solar radio bursts in this paper.Firstly,channel normalization was used to eliminate channel difference of original radio data.Then,a new automatic detection method for solar radio bursts based on codebook model was proposed to detect radio bursts.Finally,morphological processing was implemented to obtain burst parameters by detecting binary burst area.The experimental results show that the proposed method is effective.