Abstract
Fidelity in simulating urban boundary‐layer (UBL) physics is recognized to prescribe the prognostic skill of subsequent regional air pollutant transport modeling. Conventional mesoscale meteorological models (MMM) deployed over the South China coast among urban locales have often yielded positive bias in surface wind speed. This bias has been hypothetically attributed to model parameterizations that yield inaccurate meteorological predictions due to underrepresentation of urban aerodynamic roughness. Chemical transport model (CTM) simulations that are forced by the overestimated UBL wind field may undergo excessive advection which results in negative bias in predicted pollutant concentration. This study aimed to corroborate the proposed causality between parameterized urban morphometry and UBL meteorology. Focus was placed on the urban meteorological adjustments induced by urban morphometry modifications rather than prediction improvements attributable to urban canopy parameterization (UCP). Case studies were devised to assess the sensitivity of an urban‐meteorology model to a pervasive, region‐wide urban morphometry modification. Performance of a UCP scheme was evaluated for the Pearl River Delta (PRD) region, a meso‐ β‐scale subtropical coastal megalopolis. To benchmark the limits of UBL adjustments that were predominantly attributable to urban morphometric transformation, numerical experiments were conducted against two urban fabrics of vastly dissimilar morphometric compositions, each occupying identical topographic tracts. Differences in the diurnal evolution of UBL structure and in the mean and turbulent flow characteristics were analyzed. This UCP sensitivity study suggests that improved urban morphological realism is able to reduce positive wind speed bias observed in conventional mesoscale meteorological models when applied to the PRD region.
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