Reconstructing magnetotail reconnection events using data mining is feasible and repeatable (Dataset)

Dataset accompanying manuscript titled "Reconstructing magnetotail reconnection events using data mining is feasible and repeatable" Abstract: Recently, Stephens et al. (2023) utilized a data mining (DM) algorithm, applied to 26 years of magnetospheric magnetometer observations coupled with a flexible formulation of the magnetospheric magnetic field, to reconstruct the global configuration of the magnetotail when the Magnetospheric MultiScale (MMS) mission observed tail reconnection in situ. Of the 26 DM-reconstructed MMS reconnection events, 16 had a Bz=0 isocontour within ≈2 Earth radii (RE) of the observed reconnection location. Another eight had a Bz minimum region, identified using Bz=2 nT isocontours, within ≈2 RE. This consistency suggests that the structure of tail reconnection is correlated with the substorm/storm state of the magnetosphere, as reflected by geomagnetic indices and solar wind conditions. We verify these results using new validation methods and by comparing in-sample (including event data) to out-of-sample (excluding event data) reconstructions. We first benchmark the architecture of the reconstructed magnetic field using 100 randomly generated magnetic fields containing tail X- and O-lines, resolving 77 of them with three false positives. Next, we quantify the consistency of the reconstructions in resolving the reconnection location using a skill score relative to random chance. 88% of the in-sample and 75% of the out-of-sample scores are positive, confirming that the reconstructions resolve the location of tail reconnection better than random chance. Last, a bootstrapping analysis, which refits the model architecture to 100 random resamples of data, shows standard deviations in Bz of ⪅1 nT, indicating that the DM approach is not overly sensitive to the particular sampling of magnetometer records.配套于题为《利用数据挖掘重构磁尾重联事件具备可行性与可重复性》的研究手稿的数据集 摘要： 近期，Stephens等人（2023）将数据挖掘（data mining, DM）算法应用于26年的磁层磁强计观测数据，并结合磁层磁场的柔性参数化方案，在磁层多尺度（Magnetospheric MultiScale, MMS）任务原位观测到磁尾重联事件时，重构了磁尾的全球位形。在26个经DM重构的MMS重联事件中，有16个事件的Bz=0等值线位于观测重联位置约2个地球半径（Earth radii, RE）范围内；另有8个事件的Bz极小值区域（通过Bz=2纳特斯拉（nT）等值线识别）同样处于约2 RE范围内。这种一致性表明，磁尾重联的结构与磁层的亚暴/暴态存在关联，而这种关联可通过地磁指数与太阳风条件体现。 我们通过全新的验证方法，并对比样本内（包含事件数据）与样本外（排除事件数据）的重构结果，对上述结论进行了验证。我们首先利用100个随机生成的包含磁尾X线与O线的磁场数据集，对重构磁场的架构进行基准测试，成功识别出其中77个，同时产生了3例假阳性结果。随后，我们采用相对于随机猜测的技能评分，量化了重构结果在识别重联位置时的一致性。样本内得分中有88%为正值，样本外得分中有75%为正值，这证实重构结果对磁尾重联位置的识别效果优于随机猜测。最后，我们开展了自举分析：将模型架构重新拟合至100个随机重采样的数据集，结果显示Bz的标准差约≤1纳特斯拉（nT），这表明DM方法对磁强计记录的特定采样并不过度敏感。