A scheme to represent the impact of urban buildings on airflow in mesoscale atmospheric models is presented. In the scheme, the buildings are not explicitly resolved, but their effects on the grid-averaged variables are parameterised. An urban quarter is characterised by a horizontal building size, a street canyon width and a building density as a function of height. The module computes the impact of the horizontal (roof and canyon floor) and vertical (walls) surfaces on the wind speed, temperature and turbulent kinetic energy. The computation of the shortwave and longwave radiation, needed to compute the temperature of the urban surfaces, takes into account the shadowing and radiation trapping effects induced by the urban canyons. The computation of the turbulent length scales in the TKE equation is also modified to take into account the presence of the buildings. The parameterisation is introduced into a mesoscale model and tested in a bidimensional case of a city over flat terrain. The new parameterisation is shown to be able to reproduce the most important features observed in urban areas better than the traditional approach which is based only on the modification of the roughness length, thereby retaining the Monin-Obukhov similarity theory. The new surface exchange parameterisation is furthermore shown to have a strong impact on the dispersion characteristics of air pollutants in urban areas.

ABSTRACT:To bridge the gaps between traditional mesoscale modelling and microscale modelling, the National Center for Atmospheric Research, in collaboration with other agencies and research groups, has developed an integrated urban modelling system coupled to the weather research and forecasting (WRF) model as a community tool to address urban environmental issues. The core of this WRF/urban modelling system consists of the following: (1) three methods with different degrees of freedom to parameterize urban surface processes, ranging from a simple bulk parameterization to a sophisticated multi-layer urban canopy model with an indoor-outdoor exchange sub-model that directly interacts with the atmospheric boundary layer, (2) coupling to fine-scale computational fluid dynamic Reynolds-averaged Navier-Stokes and Large-Eddy simulation models for transport and dispersion (T&D) applications, (3) procedures to incorporate highresolution urban land use, building morphology, and anthropogenic heating data using the National Urban Database and Access Portal Tool (NUDAPT), and (4) an urbanized high-resolution land data assimilation system. This paper provides an overview of this modelling system; addresses the daunting challenges of initializing the coupled WRF/urban model and of specifying the potentially vast number of parameters required to execute the WRF/urban model; explores the model sensitivity to these urban parameters; and evaluates the ability of WRF/urban to capture urban heat islands, complex boundary-layer structures aloft, and urban plume T&D for several major metropolitan regions. Recent applications of this modelling system illustrate its promising utility, as a regional climate-modelling tool, to investigate impacts of future urbanization on regional meteorological conditions and on air quality under future climate change scenarios.

A large number of urban surface energy balance models now exist with different assumptions about the important features of the surface and exchange processes that need to be incorporated. To date, no comparison of these models has been conducted; in

Urban land surface schemes have been developed to model the distinct features of the urban surface and the associated energy exchange processes. These models have been developed for a range of purposes and make different assumptions related to the inclusion and representation of the relevant processes. Here, the first results of Phase 2 from an international comparison project to evaluate 32 urban land surface schemes are presented. This is the first large-scale systematic evaluation of these models. In four stages, participants were given increasingly detailed information about an urban site for which urban fluxes were directly observed. At each stage, each group returned their models' calculated surface energy balance fluxes. Wide variations are evident in the performance of the models for individual fluxes. No individual model performs best for all fluxes. Providing additional information about the surface generally results in better performance. However, there is clear evidence that poor choice of parameter values can cause a large drop in performance for models that otherwise perform well. As many models do not perform well across all fluxes, there is need for caution in their application, and users should be aware of the implications for applications and decision making.