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

Abstract

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 2014–202 to explain air temperature spatial patterns observed by a dense in-situ network. The SLR models reveal a complementary influence of topography and land cover, with 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 an adiabatic gradient 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 distance from the city centre. They contribute to warm air temperature close to the city centre and where the fraction covered by buildings increases. On the other hand, vegetation contributes to cool air temperature during the night, especially in spring and early summer for field crops, summer and early fall for forests and water, and late fall and winter for low vegetation. Our framework proves to be a low-cost and efficient way to understand the static drivers of air temperature along the annual and diurnal cycles, and is easily transposable to other areas and study fields, such as viticultural environments to further understand spring frost events.