JOURNAL ARTICLE
Study of the relationships between flares and coronal mass ejections in high-energy solar particle events during the early stages of Solar Cycle 25.
Published In: International Journal of Modern Physics A: Particles & Fields; Gravitation; Cosmology; Nuclear Physics, 2025, v. 40, n. 21. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Abdulameer, Nour Jalal; Allawi, Habeeb; Ujvari, Balazs 3 of 3
Abstract
This research examined the complex relationships between high-energy solar energetic particle (SEP) events, solar flares, and Coronal Mass Ejections (CMEs) during Solar Cycle 25's initial phase. We study the sources and characteristics of high-energy solar particles, including solar flares and CMEs, throughout the solar cycle. Although SEPs often accompany CMEs, neither is guaranteed to take place because the surrounding variability in magnetic fields and propagation conditions is large. A better understanding of this variability has obvious implications for improvements in predictive capabilities for space weather events. Advanced observational methods have been used to investigate CMEs and determine their relationship to solar cycle activity. The investigations focus on the relationship between CMEs and solar cycle activity during Solar Cycle 25, utilizing advanced observational and analytical techniques. The analysis incorporates data from space-based observatories, including SOHO (LASCO), SDO and the Parker Solar Probe, as well as ground-based facilities like the National Solar Observatory (NSO). Observations focused on events occurring between 2021 and 2024, emphasizing CMEs with linear velocities exceeding 500 km/s and angular widths reaching 3 6 0 ∘ , indicative of high-energy halo events. The CDAW CME catalog and LASCO data were utilized to extract key parameters such as speed, angular width and timing. Statistical techniques, including principal component analysis (PCA) and regression modeling, were employed to analyze CME and flare associations, their propagation conditions, and the variability in magnetic field interactions. Results indicate that CMEs and associated SEP events are influenced by both magnetic field dynamics and solar cycle phases, with significant variability observed across events. These findings contribute to improved predictive models for space weather impacts, particularly on satellite operations and Earth's technological systems. We also discuss how these solar phenomena may affect Earth'Wes space weather and technology. Comparisons with previous cycles of solar activity are provided. We conclude with a discussion of the state of predictive modeling and forecasting and highlight the necessity of further advances in predictive models in space weather. We find that correlations between the SEP peak intensity and the CME speed are much weaker than those for lower SEP energies. The correlations with flare intensity are broadly similar or weaker. Strong correlations are seen around > 3 0 0 MeV data and Ground Level Enhancement (GLE) properties from Neutron Monitors (NM). The results of our work can be utilized in future forecasting models for both high energy SEP and GLE events. In general, this study shall contribute to the solar physics and space weather knowledge, particularly in the realm of high-energy SPE dynamics in relation to the interrelationships with flares and CMEs in the early stages of Solar Cycle 25. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Modern Physics A: Particles & Fields; Gravitation; Cosmology; Nuclear Physics. 2025/07, Vol. 40, Issue 21, p1
- Document Type:Article
- Subject Area:Physics
- Publication Date:2025
- ISSN:0217-751X
- DOI:10.1142/S0217751X25420072
- Accession Number:186254862
- Copyright Statement:Copyright of International Journal of Modern Physics A: Particles & Fields; Gravitation; Cosmology; Nuclear Physics is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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