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According to the Intergovernmental Panel on Climate Change (IPCC), global temperatures have risen at an alarming pace since the early 20th century and this warming has been more pronounced since the 1970s. Temperature variations are significant because of their relation with thermal comfort and public health. In this study, we characterize the impacts of increasing maximum air temperatures in Sonora, Mexico. Heat days (HDs) and heat waves (HWs) were used as indicators to investigate historical trends in extreme heat. Furthermore, HDs were represented using a generalized linear regression model during the observed period (1966–2015) to generate future scenarios related to extreme heat and subsequently compared with six downscaled general circulation models (CNRM‐CM5, CSIRO Mk3.6.0, HadGEM2‐CC, HadGEM2‐ES, IPSL‐CM5A‐LR and IPSL‐CM5A‐MR) under low and high radiative scenarios (RCP4.5 and RCP8.5). Results of this work indicate that climate stations in Sonora have exhibited increases in the number of HDs and HWs in the historical record that can be associated to physical factors such as elevation, urban land cover and the percent of annual rainfall during the summer. Statistical and model‐based projections indicate that these trends will continue in the future up to 2060, with less moderate increases and high uncertainty noted for the difference scenarios of the downscaled models. These observed and projected trends in extreme heat are important for identifying adaptation strategies in the public and environmental health sectors in Sonora.

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The case of an arid Northwest city of Mexico is studied with the general objective of assessing the influence of the percentage of vegetation cover (VC) in Land Surface Temperature (LST) and mapping its spatial distribution, through a geographic information system using remote sensing data. Results showed: 1) on average, 12% (min. 0 to max. 59%) of a city block is covered with vegetation, 38% of the blocks had % VC ≤ 10; 2) the LST regression model estimated temperatures range from 37 to 45°C, the main explanatory variable was % VC, increasing % VC in 10 is associated with cooling effect of 1.1 °C. The spatial heterogeneity in the distribution of LST can be interpreted as the human effect modifying the climate on a small scale; this creates internal diurnal oasis.