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July 13, 2026Open Access

Climate Change and Global Warming: A Machine Learning Study Forecasting Global Land Temperature to 2050

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BBINYAMEEN

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Overview

Machine learning models forecast global land temperature changes by 2050, indicating significant warming trends.

Key Points

  • The study aims to develop a reliable model for forecasting global land temperatures based on historical temperature and CO2 emissions data.
  • Utilized two datasets: Berkeley Earth Surface Temperature and Our World in Data CO2 Emissions.
  • Engineered features from 1,992 monthly records and tested five models.
  • Kept Ridge Regression model which achieved high accuracy metrics.
  • Forecasted global land temperature of 10.18 degrees Celsius for 2050, indicating a rise of 2.28 degrees since 1850.
  • Ridge Regression yielded a test R2 of 0.9927 and mean absolute error of 0.2805 degrees Celsius.
  • Identified Mongolia as the fastest-warming area at +1.836 degrees Celsius.

Cite This Study

BINYAMEEN (2026) studied this question.

synapsesocial.com/papers/6a5482a4475c38bf615a5d93https://doi.org/10.5281/zenodo.21305983
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