Outdoor microclimate modelling is getting popular for estimating comfort conditions in urban environments. Current calibration approaches usually rely on measurements of air temperature for a limited number of points in the study domain, in spite of the fact that it is the Mean Radiant Temperature (Tmrt) the parameter mostly affecting comfort. However, the direct measurement of Tmrt outdoors via the globe thermometer or using the six direction radiation method is prone to errors. To overcome these issues, the present paper proposes a novel method to indirectly improve its estimate based on the use of infrared thermal pictures gathered by drone flights to measure surface temperatures, and then use these values for calibrating numerical models. This novel approach has been demonstrated for a 400 × 400 m2 wide area in the city of Medicina (Italy) and showed a good agreement with ENVI-met simulations, with average and standard deviation values difference between measured and simulated surface temperatures of 1.53 °C and 2.22 °C respectively. The highest differences (up to 19 °C) are found for areas densely covered by vegetation. Further studies are planned to evaluate the goodness of the calibration pixel wise and to propose calibration thresholds based on Tmrt sensitivity.