Multivariate time series dataset for space weather data analytics

被引:91
作者
Angryk, Rafal A. [1 ]
Martens, Petrus C. [2 ]
Aydin, Berkay [1 ]
Kempton, Dustin [1 ]
Mahajan, Sushant S. [2 ]
Basodi, Sunitha [1 ]
Ahmadzadeh, Azim [1 ]
Cai, Xumin [1 ]
Filali Boubrahimi, Soukaina [1 ]
Hamdi, Shah Muhammad [1 ]
Schuh, Michael A. [1 ]
Georgoulis, Manolis K. [2 ,3 ]
机构
[1] Georgia State Univ, Dept Comp Sci, Atlanta, GA 30303 USA
[2] Georgia State Univ, Dept Phys & Astron, Atlanta, GA 30303 USA
[3] Acad Athens, RCAAM, Athens, Greece
基金
美国国家科学基金会;
关键词
MAGNETIC-FIELD PROPERTIES; SOLAR-FLARE PRODUCTIVITY; QUIET ACTIVE REGIONS; GRADIENT;
D O I
10.1038/s41597-020-0548-x
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:13
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