Microclimate simulations are critical for assessing urban heat mitigation strategies, yet they face ongoing challenges regarding computational cost and physical parameterization. This study evaluates the performance of the three-dimensional microclimate model ENVI-met, comparing air temperature prediction of the legacy Version 5.6 against the updated Version 5.9. The updated kernel introduces a revised formulation for surface-to-air sensible heat exchange alongside code optimizations. The validation utilizes a high-resolution air temperature dataset collected around a standalone office building in Aalborg, Denmark, covering a 7-day period with varying meteorological conditions. Detailed statistical analysis, including daytime and nighttime stratification, reveals that both model versions reproduce diurnal temperature cycles with a coefficient of determination (R 2 ) exceeding 0.94. The updated Version 5.9 demonstrated a reduction in the aggregated Root Mean Square Error (RMSE) from 0.89 K to 0.78 K and successfully reduced systemic Mean Bias Error (MBE) across the domain, with the most distinct improvements observed in the immediate boundary layer of sun-exposed façades. Additionally, the simulation runtime for the observed period decreased by a factor of approximately three. These findings indicate that the algorithmic updates improve physical consistency in resolving near-surface temperature gradients while significantly lowering the computational resources required for microclimate modeling.
Sinsel et al. (Mon,) studied this question.
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