Abstract
Understanding near-surface wind variations in urban environments is essential for a wide range of applications, including urban weather forecasting and wind impact assessment. In this study, we introduced a novel model for mean wind speed profiles within the urban roughness sublayer based on theoretical analysis. To calibrate the model's coefficients, we conducted large-eddy simulations of airflow over a variety of idealized urban configurations. The resulting expression effectively captures wind speed variations across different urban morphologies. Subsequently, a regression modeling was employed to identify the relationships between building morphological parameters and these coefficients. This highlights the pivotal role of using building morphology to predict near-surface velocity profiles. The proposed model also yields significantly more accurate wind speed predictions within the urban canopy layer than traditional exponential profiles. The findings in the present study lay a more robust foundation for assessing urban wind conditions and improving urban-scale weather forecasts.
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More From: Journal of Wind Engineering & Industrial Aerodynamics
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