Comparing the Heliospheric Cataloging, Analysis, and Techniques Service (HELCATS) Manual and Automatic Catalogues of Coronal Mass Ejections Using Solar Terrestrial Relations Observatory/Heliospheric Imager (STEREO/HI) Data

Rodriguez, L.; Barnes, David; Hosteaux, Skralan; Davies, J. A.; Willems, Sam; Pant, Vaibhav; Harrison, R. A.; Berghmans, D.; Bothmer, V.; Eastwood, J. P.; Gallagher, Peter T.; Kilpua, Emilia; Magdalenić, Jasmina; Mierla, M.; Möstl, Christian; Rouillard, A. P.; Odstrčil, D.; Poedts, Stefaan

doi:10.1007/s11207-022-01959-w

Cited by 4 publications

(1 citation statement)

References 49 publications

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“…However, it is important to note that most of the techniques mentioned above are not automated, hence the resulting parameters are highly dependent on the specific user that utilizes them. On the other hand, thus far automated or semi-automated techniques are not trustworthy enough compared to fitting by a human-e.g., automated routines may split one CME into multiple CMEs (Riley et al, 2018;Rodriguez et al, 2022). To the best of our knowledge, there is no published literature that explores how subjectivity affects the 3D CME parameters that are obtained from any reconstruction technique.…”

Section: Introductionmentioning

confidence: 99%

Quantifying errors in 3D CME parameters derived from synthetic data using white-light reconstruction techniques

Verbeke

Mays

Kay

et al. 2023

Advances in Space Research

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Section: Introductionmentioning

confidence: 99%

Quantifying errors in 3D CME parameters derived from synthetic data using white-light reconstruction techniques

Verbeke

Mays

Kay

et al. 2023

Advances in Space Research

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Analysis of Geoeffective Impulsive Events on the Sun During the First Half of Solar Cycle 24

et al. 2023

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A coronal mass ejection (CME) is an impulsive event that emerges rapidly from the Sun. We observed a quiet Sun without many spectacular episodes during the last decade. Although some fast halo and partial halo CMEs had taken place, among them was the backside CME on 23 July 2012. In this work, we verify the link between the variability of solar-wind, heliospheric and geomagnetic parameters and the transmission grid failures registered in southern Poland during 2010 – 2014 when many geomagnetic storms appeared, caused by halo and partial halo CMEs. We aim to apply three machine learning methods: Principal Components Analysis, Self-Organizing Maps, and Hierarchical Agglomerative Clustering to analyze sources on the Sun and the impacts of the intense geomagnetic storms in the first half of Solar Cycle 24. The conducted analyzes underline the importance of solar-wind proton temperature and point out other solar-wind and geomagnetic parameters independently indicated by all the methods used in this study.

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A treatment of the all-clear problem for solar energetic particle events and subsequent decision making

Georgoulis

2024

Acta Astronautica

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Comparing the Heliospheric Cataloging, Analysis, and Techniques Service (HELCATS) Manual and Automatic Catalogues of Coronal Mass Ejections Using Solar Terrestrial Relations Observatory/Heliospheric Imager (STEREO/HI) Data

Cited by 4 publications

References 49 publications

Quantifying errors in 3D CME parameters derived from synthetic data using white-light reconstruction techniques

Quantifying errors in 3D CME parameters derived from synthetic data using white-light reconstruction techniques

Analysis of Geoeffective Impulsive Events on the Sun During the First Half of Solar Cycle 24

A treatment of the all-clear problem for solar energetic particle events and subsequent decision making

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