Investigating the Relationship between Climate Variables and Solar Activity: A Regression Analysis Approach

Abstract

This study employs regression analysis to investigate the relationships between carbon dioxide levels, sunspot occurrences, and global temperatures, encompassing both land and sea. By uncovering these connections, the study contributes to our understanding of climate change and solar phenomena interactions. The primary objective is to reveal the intricate associations between these elements, potentially influencing climate change and solar activity. The study's outcomes have significant implications for climate change research and solar activity monitoring. The positive correlation between carbon dioxide concentration and ocean temperatures emphasizes the impact of atmospheric carbon dioxide on sea temperature fluctuations. Conversely, the inverse correlation between sunspot numbers and land/global temperatures suggests solar activity's potential role in shaping Earth's temperature oscillations. This research introduces novelty by concurrently investigating the interconnectedness of these factors. The study establishes substantial connections between carbon dioxide concentration, sunspot numbers, and global temperatures. While the models shed light on some variability, the complexity of climate change and solar activity calls for further exploration of additional factors. This underscores the need to consider multiple variables for a comprehensive understanding. Further research is recommended to enhance the precision of these models.

Keywords

• regression analysis
• carbon dioxide
• sunspot numbers
• global temperatures
• climate change interactions