This dataset consists of hourly gridded 3.5x3.5 km air temperature data for entire South Africa.The data set was created using a Random Forest approach: MSG SEVIRI data from 2010 to 2014 were used and related to air temperature measured by 78 weather stations. An external validation on new climate stations and years that were not used for model training indicated the ability of the model to predict air temperature with a RMSE of 2.61°C and a R² of 0.89.The data set hence allows for spatio-temporal pattern analysis as well as for the detection of trends which is relevant in the context of climate change.The data are available as one geotif per day in geos projection (proj4String: +proj=geos +lon_0=0 +h=35785831 +x_0=0 +y_0=0 +ellps=WGS84 +units=m +no_defs ). Note that the unit of the data is °C*10. Supplement to: Meyer, Hanna; Schmidt, Johannes Peter; Detsch, Florian; Nauss, Thomas (2019): Hourly gridded air temperatures of South Africa derived from MSG SEVIRI. International Journal of Applied Earth Observation and Geoinformation, 78, 261-267