Improved and Interpretable Solar Flare Predictions With Spatial and Topological Features of the Polarity Inversion Line Masked Magnetograms
Improved and Interpretable Solar Flare Predictions With Spatial and Topological Features of the Polarity Inversion Line Masked Magnetograms
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DOI：
10.1029/2021sw002837
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发表时间：
2021-11
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影响因子：
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通讯作者：
Hu Sun;W. Manchester;Yang Chen
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文献类型：
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作者：
Hu Sun;W. Manchester;Yang Chen
目前的许多研究工作使用空间气象HMI活动区域补丁（SHARP）参数作为预测因子来进行太阳耀斑分类任务。SHARP参数是基于从矢量磁场导出的物理量的空间平均或积分的标量，其丢失了场和相关量的二维空间分布的信息。在本文中，我们构建了两个新的空间特征集，以扩展用于耀斑分类任务的特征集。第一组使用拓扑数据分析的思想来总结各种SHARP量在活动区域上分布的几何信息。第二组利用来自空间统计的工具来分析垂直磁场分量Br，并总结其空间变化和聚类模式。所有功能的极性反转线（PIL）附近的区域内构建和使用新功能的分类性能进行比较，对那些使用SHARP参数（也沿着PIL）。我们发现，使用新的功能可以提高耀斑分类模型的技能得分和新的功能往往有更高的功能重要性，特别是空间统计功能。这可能表明，即使使用单个磁场分量Br而不是所有SHARP参数，仍然可以导出用于耀斑分类的强预测特征。
Many current research efforts undertake the solar flare classification task using the Space‐weather HMI Active Region Patch (SHARP) parameters as the predictors. The SHARP parameters are scalar quantities based on spatial average or integration of physical quantities derived from the vector magnetic field, which loses information of the two‐dimensional spatial distribution of the field and related quantities. In this paper, we construct two new sets of spatial features to expand the feature set used for the flare classification task. The first set uses the idea of topological data analysis to summarize the geometric information of the distributions of various SHARP quantities across active regions. The second set utilizes tools coming from spatial statistics to analyze the vertical magnetic field component Br and summarize its spatial variations and clustering patterns. All features are constructed within regions near the polarity inversion lines (PILs) and classification performances using the new features are compared against those using SHARP parameters (also along the PIL). We found that using the new features can improve the skill scores of the flare classification model and new features tend to have higher feature importance, especially the spatial statistics features. This potentially suggests that even using a single magnetic field component, Br, instead of all SHARP parameters, one can still derive strongly predictive features for flare classification.