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Mathematical Modeling of Climate Change and Global Warming
Subject area: Science,Engineering and Technology · Area of research: Mathematics
DOI: https://doi.org/10.64388/IREV9I11-1718654
Abstract
Climate change and global warming represent some of the most pressing environmental issues affecting humanity today. These phenomena are driven by both natural processes and anthropogenic activities, particularly the emission of greenhouse gases such as carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O). Mathematical modeling has emerged as a fundamental tool for analyzing, understanding, and predicting climate behavior over time. This paper provides a comprehensive discussion of mathematical approaches used in climate science, including differential equations, statistical modeling, and computational simulations. It further examines various climate models such as Energy Balance Models, General Circulation Models, and Earth System Models. The study also highlights the importance of feedback mechanisms, uncertainty analysis, and modern advancements like machine learning integration. By expanding the theoretical and applied aspects, this paper demonstrates how mathematical modeling supports climate policy, environmental planning, and global sustainability efforts.
How to cite this paper
@article{1718654,
author = {Lavkush Pandey},
title = {Mathematical Modeling of Climate Change and Global Warming},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {11},
pages = {5162-5165},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1718654.pdf},
abstract = {Climate change and global warming represent some of the most pressing environmental issues affecting humanity today. These phenomena are driven by both natural processes and anthropogenic activities, particularly the emission of greenhouse gases such as carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O). Mathematical modeling has emerged as a fundamental tool for analyzing, understanding, and predicting climate behavior over time. This paper provides a comprehensive discussion of mathematical approaches used in climate science, including differential equations, statistical modeling, and computational simulations. It further examines various climate models such as Energy Balance Models, General Circulation Models, and Earth System Models. The study also highlights the importance of feedback mechanisms, uncertainty analysis, and modern advancements like machine learning integration. By expanding the theoretical and applied aspects, this paper demonstrates how mathematical modeling supports climate policy, environmental planning, and global sustainability efforts.},
month = {May},
doi = {https://doi.org/10.64388/IREV9I11-1718654}
}