Automatic Solar Flare Detection Using the Solar Disk Imager Onboard the ASO-S Mission

We present an automated solar flare detection software tool to automatically process solar observed images, detect and track solar flares, and finally compile an event catalog. It can identify and track flares that happen simultaneously or temporally close together. The method to identify a flare is...

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Veröffentlicht in:Solar physics 2024-05, Vol.299 (5), p.72, Article 72
Hauptverfasser: Lu, Lei, Tian, Zhengyuan, Feng, Li, Shan, Jiahui, Li, Hui, Su, Yang, Li, Ying, Huang, Yu, Li, Youping, Li, Jingwei, Zhao, Jie, Ying, Beili, Xue, Jianchao, Zhang, Ping, Song, Dechao, Li, Shuting, Shi, Guanglu, Su, Yingna, Zhang, Qingmin, Ge, Yunyi, Chen, Bo, Li, Qiao, Li, Gen, Zhou, Yue, Tian, Jun, Liu, Xiaofeng, Jing, Zhichen, Gan, Weiqun, Song, Kefei, He, Lingping, Lei, Shijun
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Sprache:eng
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Zusammenfassung:We present an automated solar flare detection software tool to automatically process solar observed images, detect and track solar flares, and finally compile an event catalog. It can identify and track flares that happen simultaneously or temporally close together. The method to identify a flare is based on the local intensity changes in macropixels. The basic characteristics, such as the time and location information of a flare, are determined with a triple-threshold scheme, with the first threshold (global threshold) to determine the occurrence (location) of the flare and the second and third thresholds (local thresholds) to determine the real start and end times of the flare. We have applied this tool to one month of continuous solar ultraviolet (UV) images obtained by the Solar Disk Imager (SDI) onboard the Advanced Space-based Solar Observatory (ASO-S), which show active phenomena such as flares, filaments or prominences, and solar jets. Our automated tool efficiently detected a total number of 226 solar events. After a visual inspection, we found that only one event was misidentified (unrelated to an active event). We compared the detected events with the GOES X-ray flare list and found that our tool can detect 81% of GOES M-class and above flares (29 out of 36), from which we conclude that the intensity increase in SDI UV images can be considered as a good indicator of a solar flare.
ISSN:0038-0938
1573-093X
DOI:10.1007/s11207-024-02310-1