Abstract
AbstractA recently developed, height‐distributed urban drag parametrization is tested with the London Model, a sub‐kilometre resolution version of the Met Office Unified Model over Greater London. The distributed‐drag parametrization requires vertical morphology profiles in the form of height‐distributed frontal‐area functions, which capture the full extent and variability of building heights. London's morphology profiles are calculated and parametrized by an exponential distribution with the ratio of maximum to mean building height as the parameter. A case study evaluates the differences between the new distributed‐drag scheme and the current London Model setup using the MORUSES urban land‐surface model. The new drag parametrization shows increased horizontal spatial variability in total surface stress, identifying densely built‐up areas, high‐rise building clusters, parks, and the river. Effects on the wind speed in the lower levels include a lesser gradient and more heterogeneous wind profiles, extended wakes downwind of the city centre, and vertically growing perturbations that suggest the formation of internal boundary layers. The surface sensible heat fluxes are underpredicted, which is attributed to difficulties coupling the distributed momentum exchange with the surface‐based heat exchange.
Highlights
Urban environments alter aerodynamic, radiative, thermal, and hydrological processes, which can intensify heat waves, flash floods, and air pollution
This study describes a step towards developing a new multilayer scheme: at this point we only consider momentum exchanges, with a focus on the representation and effects of heterogeneous subgrid morphology
The spatial variability of surface stresses is largest with the distributed-drag model, highlighting various local features, such that the spatial patterns of τ0 reflect the heterogeneity of the urban area
Summary
Radiative, thermal, and hydrological processes, which can intensify heat waves, flash floods, and air pollution. Parametrizations for urban environments in numerical weather prediction (NWP) or climate models aim to represent the effects of the built-up system without resolving it explicitly. The schemes are commonly based on Monin–Obukhov similarity theory to calculate exchange fluxes between the atmosphere and the surface, where urban environments are represented by an increased roughness length that modifies surface friction and heat exchange. The urban morphology is represented in these schemes by a simple street-canyon geometry with variable height-to-width ratios, which parametrizes most physical processes in the urban canopy such as different flow regimes, shadowing, and radiation trapping (e.g., Porson et al, 2010a). The urban environment is effectively seen as a “bulk surface”, which interacts with the atmosphere close to the canopy top, at the level of the displacement height
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