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Envi-met is the most-used simulation tool to assess outdoor thermal comfort in urban microclimates. Considering reported disparities between modeled and observed mean radiant temperature (MRT), failing to accurately predict the MRT may have a negative impact on the conclusions drawn by urban designers and policy makers. Therefore, this study aims to validate the Envi-met model’s efficiency for predicting MRT in the hot arid climate of Mecca city. Sensitivity analyses were conducted to investigate the settings and inputs of Envi-met, including two- and six-directional methods for calculating MRT, shortwave radiation projection factors, Indexed View Sphere (IVS), Advanced Canopy Radiation Transfer (ACRT), and the localization of materials and vegetation. Two statistical metrics (RMSE and MAE) were employed to assess Envi-met’s performance for the two evaluation points. Envi-met produced the best results with the 6-directional, ƒp-RayM (in winter) and ƒp-City (in summer), IVS on and ACRT on mode, and localized soil condition, materials, and vegetation inputs. An analysis of the modeled MRT results illustrated that error magnitudes were decreased significantly as a result of sufficient settings and inputs; for example, RMSE was improved by 2.31 and 8.48 K in the winter and summer open site results, respectively, and by 7.30 K in the summer under-tree site. Overall, the results of winter and summer analyses demonstrate average RMSE of 4.99 K and MAE of 4.02 K. The findings illustrate that substantial enhancement of model performance can be achieved through the use of proper settings and inputs.
Alzahrani et al. (Thu,) studied this question.