Author:
Morlini Isabella,Orlandini Stefano
Abstract
Abstract
Global mean surface air temperature is a key metric in climatology, but understanding its relationship with local temperatures is crucial for projecting climate impacts at regional and local scales. This study analyzes air temperature data from Modena, Italy, in comparison with NASA GISTEMP global mean annual air temperature for the period 1881–2021 to identify local deviations from global patterns and assess the interplay of local and global factors influencing urban temperatures. Since linear relationships are found to be spurious, nonlinear methods such as cubic splines and regression trees are employed. Cubic splines effectively capture asymmetric bivariate relationships between local temperature deviations and influencing factors without overfitting, while regression trees highlight the most influential predictors in multivariate analysis. The analysis shows that both local and global temperatures are strongly correlated with global CO2 concentrations. However, deviations arise due to local factors such as urban expansion and variations in precipitation. Since 1986, the increasing number of registered vehicles appears to contribute significantly to these deviations, likely through traffic congestion and resulting anthropogenic heat. Although further research is needed for reliable validation, an order-of-magnitude analysis supports the plausibility of this hypothesis. The findings suggest that urban areas may experience a ‘fever’ from anthropogenic heat effects. Targeted mitigation strategies, such as reducing traffic congestion, could help address these localized impacts.
Funder
Università degli Studi di Modena e Reggio Emilia
Publisher
Springer Science and Business Media LLC