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

IF 2.7 3区 物理与天体物理 Q2 ASTRONOMY & ASTROPHYSICS
Lei Lu, Zhengyuan Tian, Li Feng, Jiahui Shan, Hui Li, Yang Su, Ying Li, Yu Huang, Youping Li, Jingwei Li, Jie Zhao, Beili Ying, Jianchao Xue, Ping Zhang, Dechao Song, Shuting Li, Guanglu Shi, Yingna Su, Qingmin Zhang, Yunyi Ge, Bo Chen, Qiao Li, Gen Li, Yue Zhou, Jun Tian, Xiaofeng Liu, Zhichen Jing, Weiqun Gan, Kefei Song, Lingping He, Shijun Lei
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Abstract

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.

Abstract Image

利用 ASO-S 飞行任务搭载的太阳盘成像仪自动探测太阳耀斑
我们介绍一种自动太阳耀斑探测软件工具,用于自动处理太阳观测图像,探测和跟踪太阳耀斑,并最终编制事件目录。它可以识别和跟踪同时发生或时间上接近的耀斑。识别耀斑的方法基于宏像素的局部强度变化。耀斑的时间和位置信息等基本特征是通过三重阈值方案确定的,第一重阈值(全局阈值)用于确定耀斑的发生(位置),第二重和第三重阈值(局部阈值)用于确定耀斑的实际开始和结束时间。我们将这一工具应用于先进天基太阳观测站(ASO-S)上的太阳盘成像仪(SDI)获得的一个月连续太阳紫外线(UV)图像,这些图像显示了耀斑、细丝或突出部以及太阳喷流等活跃现象。我们的自动工具共有效探测到 226 个太阳活动。经过目测,我们发现只有一个事件被错误识别(与活跃事件无关)。我们将探测到的事件与 GOES X 射线耀斑列表进行了比较,发现我们的工具可以探测到 81% 的 GOES M 级及以上耀斑(36 个中的 29 个),由此我们得出结论,SDI 紫外线图像中的强度增加可以被视为太阳耀斑的一个良好指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Solar Physics
Solar Physics 地学天文-天文与天体物理
CiteScore
5.10
自引率
17.90%
发文量
146
审稿时长
1 months
期刊介绍: Solar Physics was founded in 1967 and is the principal journal for the publication of the results of fundamental research on the Sun. The journal treats all aspects of solar physics, ranging from the internal structure of the Sun and its evolution to the outer corona and solar wind in interplanetary space. Papers on solar-terrestrial physics and on stellar research are also published when their results have a direct bearing on our understanding of the Sun.
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