Abstract
The spatial range of near-surface air temperature average and trends for Southeast Brazil in recent decades motivated us to investigate the causality of local vegetation and other geophysical controls at the regional scale to explain the spatial variability of the average maximum and minimum temperature (Tmax and Tmin). We used measurements from 52 weather stations between 1985 and 2010. Using linear regression, NDVI and cloud cover were significant to explain spatial variability of Tmax and Tmin. With the Generalized Additive Model (GAM), we improved temperature-dependent relationships with regional geophysical controls, and local scale NDVI. The modeling of Tmax and Tmin showed non-linear and combined relationships with geographical position (lat,lon) jointly expressing the effects of zonality and continentality, and NDVI at distances of 300 m and 3000 m. For Tmin, geographical position and altitude responded with an amplitude of ≃5 °C each, and NDVI with ≃3 °C. Similarly, the geographical position and altitude were significant for Tmax, with an amplitude of ≃5 °C each, and cloud cover with ≃3.5 °C. Our findings help to clarify the local scale controls of near-surface air temperature and stress the need to increase resilience against adversities of global climate change and increasing urbanization, by providing metrics to predict the effects of nature-based solutions within the urban space.
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