Understanding the intricate relationship between solar activity and cosmic rays is crucial for advancing our knowledge in space weather and its impacts on Earth’s environment. This study investigates the relationship between cosmic rays and solar activity,as measured by the sunspot number, using advanced time series analysis techniques. Data represented by the sunspot number and cosmic ray intensity from 1980 to 2024. SARIMA modeling, spectral analysis, seasonal decomposition, and cross-correlation methodswere used to look into the complex dynamics that control how cosmic rays and sunspot number interact with each other. Our findings reveal a strong inverse correlation between these two variables, with a significant lag effect indicating that changes in solar activity influence cosmic ray flux with a delay of approximately 10 months. The findings from this study underscore the importance of selecting appropriate machine learning models when investigating the dynamic and non-linear relationships inherent in space weather phenomena. This research contributes to the ongoing efforts to better understand the Cosmic Rays-Sun-Earth connection and provides a comparative analysis that could inform future modeling approaches in solar-terrestrial physics.
Primary Language | English |
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Subjects | Nanoelectromechanical Systems |
Journal Section | Research Articles |
Authors | |
Publication Date | December 15, 2024 |
Submission Date | October 2, 2024 |
Acceptance Date | November 16, 2024 |
Published in Issue | Year 2024 Volume: 8 Issue: 2 |