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Multivariate time series dataset for space weather data analytics.

Rafal A AngrykPetrus C MartensBerkay AydinDustin KemptonSushant S MahajanSunitha BasodiAzim AhmadzadehXumin CaiSoukaina Filali BoubrahimiShah Muhammad HamdiMichael A SchuhManolis K Georgoulis
Published in: Scientific data (2020)
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.
Keyphrases
  • big data
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  • working memory