Space Weather Related to Solar Eruptions With the ASO-S Mission

Feng, Li; Gan, Weiqun; Liu, Siqing; Wang, Huaning; Li, Hui; Xu, Long; Zong, Weiguo; Zhang, Xiaoxing; Zhu, Yaguang; Wu, Haiyan; Chen, Anqin; Cui, Yanmei; Dai, Xinghua; Guo, J.; He, Han; Huang, Xin; Lu, Lei; Song, Qiao; Wang, Jingjing; Zhong, Qing; Chen, Ling; Du, Zhanle; Guo, Xingliang; Yu, Haitao; Li, Hu; Liu, Ying; Senlin, Xiong; Yang, Shenggao; Bao, Ying

doi:10.3389/fphy.2020.00045

Cited by 5 publications

(1 citation statement)

References 97 publications

(109 reference statements)

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“…A solar flare is an intense burst of electromagnetic radiation through magnetic reconnection and plasma instability coming from the release of magnetic energy associated with active regions (AR) and they transpire as a sudden brightening of light on the Sun's corona Toriumi and Wang (2019). Coronal mass ejections (CMEs), which are often associated with solar flares, have comparable energies, and can release large amounts of mass resulting into major geomagnetic storms which creates intense currents in the Earth's magnetosphere, changes in the radiation belts, and in the ionosphere Feng et al (2020). When particles emitted by the Sun are accelerated during a flare or by a CME event and reach the Earth along interplanetary magnetic field lines, Solar energetic particle (SEP) events are produced Núñez and Paul-Pena (2020).…”

Section: Introductionmentioning

confidence: 99%

Towards coupling full-disk and active region-based flare prediction for operational space weather forecasting

Pandey

Angryk

et al. 2022

Front. Astron. Space Sci.

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Solar flare prediction is a central problem in space weather forecasting and has captivated the attention of a wide spectrum of researchers due to recent advances in both remote sensing as well as machine learning and deep learning approaches. The experimental findings based on both machine and deep learning models reveal significant performance improvements for task specific datasets. Along with building models, the practice of deploying such models to production environments under operational settings is a more complex and often time-consuming process which is often not addressed directly in research settings. We present a set of new heuristic approaches to train and deploy an operational solar flare prediction system for ≥M1.0-class flares with two prediction modes: full-disk and active region-based. In full-disk mode, predictions are performed on full-disk line-of-sight magnetograms using deep learning models whereas in active region-based models, predictions are issued for each active region individually using multivariate time series data instances. The outputs from individual active region forecasts and full-disk predictors are combined to a final full-disk prediction result with a meta-model. We utilized an equal weighted average ensemble of two base learners’ flare probabilities as our baseline meta learner and improved the capabilities of our two base learners by training a logistic regression model. The major findings of this study are: 1) We successfully coupled two heterogeneous flare prediction models trained with different datasets and model architecture to predict a full-disk flare probability for next 24 h, 2) Our proposed ensembling model, i.e., logistic regression, improves on the predictive performance of two base learners and the baseline meta learner measured in terms of two widely used metrics True Skill Statistic (TSS) and Heidke Skill Score (HSS), and 3) Our result analysis suggests that the logistic regression-based ensemble (Meta-FP) improves on the full-disk model (base learner) by ∼9% in terms TSS and ∼10% in terms of HSS. Similarly, it improves on the AR-based model (base learner) by ∼17% and ∼20% in terms of TSS and HSS respectively. Finally, when compared to the baseline meta model, it improves on TSS by ∼10% and HSS by ∼15%.

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Section: Introductionmentioning

confidence: 99%

Towards coupling full-disk and active region-based flare prediction for operational space weather forecasting

Pandey

Angryk

et al. 2022

Front. Astron. Space Sci.

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Solar Flare Catalogue from 3 Years of Chandrayaan-2 XSM Observations

Valluvan,

Goyal,

Jain

et al. 2024

Sol Phys

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Chirality and magnetic configuration associated with two-ribbon solar flares: AR 10930 versus AR 11158

Wang

Yan

et al. 2020

Advances in Space Research

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The magnetic configuration of flare-bearing active regions (ARs) is one key aspect for understanding the initiation of solar flares. In this paper, we perform a comparative analysis on the chiral characteristics and the magnetic configurations of two X-class two-ribbon flares happening in AR 10930 and AR 11158, whose photospheric magnetic fields were observed by the Hinode and SDO satellites, respectively. The corresponding coronal magnetic fields were calculated based on the nonlinear forcefree field model. It is found that both the flares were initiated in local areas with extremely strong electric current density. The chirality of the magnetic field (indicated by the sign of force-free factor α) along the main polarity inversion line (PIL) is opposite for the two ARs, that is, left-handed (α < 0) for AR 10930 and right-handed (α > 0) for AR 11158. The analysis shows that, for both flare events, prominent magnetic connectivity (indicated by both high α and strong current distributions) was formed above the main PIL before the flare and was totally broken after the flare eruption. Yet the two branches of broken magnetic connectivity, combined with the isolated electric current at the magnetic connectivity breaking site, compose the opposite magnetic configurations for the two ARs owing to their opposite chiral characteristics. That is, Z-shaped configuration for AR 10930 with negative α and left-handed chirality, and inverse Z-shaped configuration for AR 11158 with positive α and right-handed chirality. We speculate that two-ribbon flares can be generally classified to these two magnetic configurations by chirality (α sign) of ARs.

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Space Weather Related to Solar Eruptions With the ASO-S Mission

Cited by 5 publications

References 97 publications

Towards coupling full-disk and active region-based flare prediction for operational space weather forecasting

Towards coupling full-disk and active region-based flare prediction for operational space weather forecasting

Solar Flare Catalogue from 3 Years of Chandrayaan-2 XSM Observations

Chirality and magnetic configuration associated with two-ribbon solar flares: AR 10930 versus AR 11158

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