This paper discusses the performance of the temperature perturbation-type ADMS-Temperature and Humidity Model (ADMS-TH) and the Computational Fluid Dynamics (CFD)-based model ENVI-met for the prediction of urban air temperature using measurements collected in the city of Lecce (IT) in summer 2012. The goal is to identify the most important factors influencing numerical predictions. Direct comparisons with measured data and statistical indices show that modelled results are within the range of acceptance. Daily trends are well captured although an underestimation of maximum temperature is observed. In ADMS-TH this is due to an underestimation of sensible heat fluxes during daytime, while in ENVI-met it can be attributed to an underestimation of turbulent momentum and thermal diffusivity. Overall, ADMS-TH did predict the temperature cycle with higher accuracy than ENVI-met and its performance was particularly good during the night. ENVI-met required an ad-hoc tuning of surface boundary conditions to predict nocturnal cooling, satisfactorily.
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