Mathematical Modeling for Climate Change Prediction and Its Role in Science and Education

Abstract

Climate change is a global issue that generates extensive impacts on the environment, economy, health, agriculture, and socio-cultural dimensions. Understanding and predicting its consequences are essential for formulating effective public policies, mitigation strategies, and adaptation measures. Mathematical modeling plays a central role in quantifying, simulating, and forecasting climate phenomena. Various models are employed, including the sophisticated Global Climate Models (GCMs), which capture complex interactions within the climate system, and the more straightforward Energy Balance Models (EBMs), which explain fundamental energy equilibrium principles. Both approaches provide complementary insights, from comprehensive projections to conceptual understanding. Beyond scientific applications, mathematical modeling also functions as an educational strategy that enhances students’ critical thinking, problem-solving abilities, and scientific literacy. Nonetheless, challenges persist in implementing innovative model-based learning in schools, particularly due to limitations in resources, teacher preparedness, and curricular support. This study aims to explore the dual contribution of mathematical modeling, both in predicting