Multivariate time series dataset for space weather data analytics
Multivariate time series dataset for space weather data analytics
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DOI：
10.1038/s41597-020-0548-x
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发表时间：
2020-07-10
期刊：
影响因子：
9.8
通讯作者：
Georgoulis, Manolis K.
中科院分区：
文献类型：
--
作者：
Angryk, Rafal A.;Martens, Petrus C.;Georgoulis, Manolis K.
我们介绍了一个综合的多变量时间序列(MVTS)数据集，该数据集是从Spaceweet HMI Active Region Patch(SHARP)系列的太阳光球层矢量磁图中提取的。我们的数据集还包括一个交叉核对的NOAA太阳耀斑目录，该目录立即有助于太阳耀斑预测工作。我们讨论了太阳活动区和耀斑数据的数据采集、清洗和预处理方法，并进一步描述了一种新的数据集成和采样方法。我们的数据集涵盖2010年5月至2018年12月期间从活动区域收集的4,098个MVTS数据，包括51个耀斑预测参数，并集成了10,000多个耀斑报告。文中还解释了时间序列的可能扩展方向，即“水平方向”--通过添加更多预测专用参数，或者“垂直”--通过将耀斑推广到综合太阳喷发预测中。传播的数据集带来的直接任务包括：优化太阳耀斑预测和对难以捉摸的耀斑预报器或前兆进行详细调查，并在未来可能带来业务(研究对业务)和基础研究(业务对研究)的好处。
We introduce and make openly accessible a comprehensive, multivariate time series (MVTS) dataset extracted from solar photospheric vector magnetograms in Spaceweather HMI Active Region Patch (SHARP) series. Our dataset also includes a cross-checked NOAA solar flare catalog that immediately facilitates solar flare prediction efforts. We discuss methods used for data collection, cleaning and pre-processing of the solar active region and flare data, and we further describe a novel data integration and sampling methodology. Our dataset covers 4,098 MVTS data collections from active regions occurring between May 2010 and December 2018, includes 51 flare-predictive parameters, and integrates over 10,000 flare reports. Potential directions toward expansion of the time series, either "horizontally" - by adding more prediction-specific parameters, or "vertically" - by generalizing flare into integrated solar eruption prediction, are also explained. The immediate tasks enabled by the disseminated dataset include: optimization of solar flare prediction and detailed investigation for elusive flare predictors or precursors, with both operational (research-to-operations), and basic research (operations-to-research) benefits potentially following in the future.