Implementation and evaluation of mean radiant temperature schemes in the microclimate model ENVI-met

Mean radiant temperature is a key element in evaluating human thermal comfort. It is generally assessed by measurements or microclimate models. Among microclimate models, ENVI-met features the most applications in human thermal comfort research. However, recent evaluation studies revealed shortcomings in mean radiant temperature modeling. The common six-directional radiative flux calculation approach as well as three established shortwave radiation projection factors have thus been implemented into ENVI-met to improve its modeling accuracy. To investigate the accuracy gains, an evaluation study is performed using six-directional flux measurements at six different sites in Hong Kong. Comparisons using statistical metrics of R-2, d, RMSE, and MBE demonstrated that newly modeled mean radiant temperature values performed better than previously used approaches, e.g. by an improvement of RMSE from 8 K to 3.5 K. In general, simulation results with the new configurations showed very high agreements with measurements (R-2 similar to 0.9, d similar to 0.95) as well as low error magnitudes (RMSE similar to 3 K, MBE similar to 1.2 K) on average for five of six sites. An improved mean radiant temperature estimation yields performance gains for future urban climate investigations providing higher accuracy in heat mitigation strategy research and resilient urban planning.

Automated summary

Mean radiant temperature is a crucial factor in assessing human thermal comfort, and ENVI-met is widely used in this field. However, recent evaluations have identified shortcomings in mean radiant temperature modeling. To improve accuracy, a six-directional radiative flux calculation approach and three established shortwave radiation projection factors have been implemented into ENVI-met. A study in Hong Kong showed that the new modeling approach outperformed previous methods, with a significant improvement in the root mean square error. This improved estimation of mean radiant temperature will contribute to more accurate heat mitigation strategies and resilient urban planning in future climate investigations.