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Surface temperature analysis: variability and trends

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Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2025, Tutora: Yolanda Sola Salvatierra

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This work analyses global surface temperature anomalies from 1880 to 2024 using the GISS database. ARIMA and Bayesian Structural Time Series models are employed to make predictions. Both approaches reveal a strong warming trend predicting, respectively, an average annual increase of 0.021 K and 0.031 K until 2060. Higher warming over land and, especially in the Bayesian model, Arctic amplification are forecasted. These findings align with IPCC projections and underscore the urgency of climate mitigation strategies

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Surface temperature analysis: variability and trends