Flare to CME Association Integration

For integrating CME data to their solar sources, we perform a confidence-based scoring process that involves spatial and temporal data integration. For each GOES >C1.0 flare, we identify the likely CME candidate(s) with a temporal search using the start and peak times of flares and first detection time of CMEs. In this step, we check if the CMEs’ first detection time is between 30 minutes before the flare’s start time and 60 minutes after the flare’s peak time. Then, for each potential CME candidate, if any, we generate a confidence score between 1 to 5 (from lowest to highest) based on checking four additional criteria where each criteria gives an extra confidence point for the association:
1. Determine a potential one-to-one mapping between a given flare and a CME, in the case of only a single CME that satisfies the temporal search.
2. Check if the flare’s principal angle is in the same solar-disk quadrant as the CME’s principal angle, which is assumed as a 8 degree margin for boundary conditions.
3. Check if the difference between the flare’s principal angle and the CME’s principal angle (i.e., difference angle) is less than the CME’s observed width.
4. Check if the difference angle is less than 60 degrees threshold where such threshold is designated for wide CMEs (i.e., Halo and partial Halo) whose width almost always fulfill the width-based criterion in the previous criteria and aims to provide a more strict level of confidence.

At the end of the integration procedure, CMEs are associated with flares using the maximum confidence score and therefore are connected to their most likely solar source. If there are multiple CMEs with the same high score, only those with the lowest difference angle between flare and the CME will be connected. Due to the fact that this process is not manually verified, we expect to generate certain ‘noisy’ data points. However, for overall model building, these data points should have a minimal statistical significance and hence a minimal impact.

为将日冕物质抛射（Coronal Mass Ejection，CME）数据与其太阳源进行关联匹配，我们采用基于置信度的评分流程，该流程整合了空间与时间维度的数据信息。针对每一颗地球静止业务环境卫星（Geostationary Operational Environmental Satellite，GOES）观测到的C1.0级以上太阳耀斑，我们借助耀斑的起始时刻、峰值时刻以及CME的首次探测时刻开展时间检索，以识别潜在的CME候选体。此步骤中，我们将校验CME的首次探测时刻是否处于耀斑起始时刻前30分钟至耀斑峰值时刻后60分钟的时间区间内。随后，针对每一个符合条件的CME候选体（若存在），我们将基于四项额外判定标准生成1至5分的置信评分（分值由1到5依次代表置信度从低到高），每满足一项判定标准即可为该耀斑与CME的关联关系增加1个置信分值：1. 若仅存在单个满足时间检索条件的CME，则判定该耀斑与该CME之间存在潜在的一对一映射关系；2. 校验耀斑的主角度与CME的主角度是否处于同一太阳盘面象限，边界条件允许8度的误差余量；3. 校验耀斑主角度与CME主角度的差值（即角度差）是否小于CME的观测宽度；4. 校验该角度差是否小于60度阈值：该阈值针对宽幅CME（即晕状CME与部分晕状CME）设定，此类CME通常已满足前一项基于宽度的判定标准，设置该阈值旨在进一步提升置信度判定的严格程度。在整个关联整合流程结束时，我们将以最高置信评分为依据，将CME与耀斑进行关联匹配，从而使CME与其最可能的太阳源建立连接。若存在多个置信评分相同的高得分候选体，则仅选取耀斑与CME间角度差最小的那些进行关联。由于该流程未经过人工校验，我们预计会生成一定数量的“噪声”数据点。但针对整体模型构建而言，此类数据点的统计显著性较低，因此对模型的影响也相对有限。