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  • Impact of topography and land cover on air temperature space-time variability in an urban environment with contrasted topography (Dijon, France, 2014-2021)

Authors Contributions:

Julien Crétat, Yves Richard, Benjamin Pohl, Julita Dudek, Julien Pergaud, Mario Rega and Mélissa Poupelin – Centre de Recherches de Climatologie, UMR 6282 Biogéosciences, CNRS/Université de Bourgogne, Dijon, France

Justin Emery, Damien Roy, Daniel Joly and Thomas Thévenin – ThéMA, UMR 6049, CNRS/Université de Bourgogne et
Université de Franche-Comté, Besançon, France

Eva Marquès and Valéry Masson – Centre National de Recherches Météorologiques, Université de Toulouse, Météo-France, CNRS, Toulouse, France

Abstract:

The influence of topography and land cover on air temperature space-time variability is examined in an urban environment with contrasted topography through simple and multiple linear regression (SLR and MLR) models, ran for each hour of the period 2014–2021, to explain spatial patterns of air temperature measured by a dense network. The SLR models reveal a complementary influence of topography and land cover, with the largest influence during daytime and nighttime, respectively. The MLR significantly improves upon the SLR models despite persistent intensity errors at night and spatial errors in the early morning. Topography influences air temperatures all year round, with temperature decreasing with height during the day and frequent thermal inversions at night (up to 30% of the time). Impervious surfaces are more influential in summer and early fall, especially during the late afternoon for the fraction covered by buildings and during the early night for the distance from the city center. They contribute to increasing air temperature close to the city center and where the fraction covered by buildings is large. By contrast, vegetation contributes to cool air temperatures during the night, especially in spring and early summer for field crops, summer and early fall for forests, and late fall and winter for low vegetation. Our framework proves to be a low-cost and efficient way to assess how strongly and how recurrently the static surface conditions influence air temperature along the annual and diurnal cycles. It is easily transposable to other areas and study fields.

Read the full paper here.