WP2: Megacity environments: features, processes and effects

Overview and background

Megacities are localized, heterogeneous and variable sources of the anthropogenic impact on air quality and ultimately on climate. The major difficulty in megacity forcing in simulations arises from the sub-grid scale features. They are typically unresolved in climate models and barely resolved in regional scale models. Thus, models rely on parameterizations of megacity features aggregated within the model grid cell. Aggregation is not straightforward given surface heterogeneity and strong non-linearity of the turbulent transport in the urban atmospheric boundary layer (UABL). The latter prohibits the application of direct averaging to obtain the large-scale forcing. Albeit known since Schmidt (1921), the aggregation problems are still largely ignored in existing urban parameterizations. A more sophisticated approach which accounts for emission at different levels and for the surface thermal and drag heterogeneity is needed. Recent progress in street- and urban-scale turbulence-resolving simulations has opened the way for the development of a new generation of effective urban parameterizations. The models require databases of emissions and surface characteristics as initial and boundary conditions. Feature analysis helps assessment of the megacity climate. It also relaxes the stability constraints on the megacity forcing in large-scale models. Challenging sub-grid features in the WP tasks include: spatial and temporal distribution of emission source activities; flow modification by the urban canopy structure; flow modification by the urban surface heat balance; enhancement/damping of turbulent fluxes in the urban boundary layer due to surface and emission heterogeneity; chemical modification of pollutants in the dispersion process.

Methodology and advancement beyond the state-of-the-art

A state-of-the-art assessment will be provided of the megacity climate, dispersion of anthropogenic pollutants, fine-scale simulations with the state-of-the-art turbulence-resolving models and improved parameterizations in regional- and global-scale models. The urban models will be evaluated using WPs 1 and 3 data. Resulting parameterizations will be used in WPs 4-7. To advance current understanding of megacity features as climate forming factors, process studies will be conducted; for example, impact of surface morphology on flow near and in the urban sub-layer, which impacts the surface energy balance. Knowledge of these processes will allow computation of turbulence statistics, chemical transformation and dispersion mechanisms in the UABL. Using the 3D data, the universal assumptions for evolution equations for integral turbulence measures, e.g. UABL thickness will be verified and a set of prognostic equations to parameterize those processes will be formulated. To accomplish this, the work will be divided into five tasks, with tasks 1-3 providing boundary conditions for tasks 4-5:

1) Surface morphology: classification and database: Databases will be compiled, which include parameters for urban morphology, land-use and surface structure. These characteristics will be derived from satellite, aerial and in situ data collection (Grimmond and Souch, 1994). The database will allow quick generation of boundary conditions for different types of models. Starting the work with existing relevant databases, it will focus on London, Paris and other major megacities in the project. The height of structures will be determined using satellite images, stereography, laser scanning and SAR-interferometry. The obtained database will be passed to other tasks of WP2 and WPs 3-6.

2) Flow deformation by urban canopy in the urban sub-layer: Parameterizations of flow deformation and inter-canopy transport processes will be improved through systematic study of small-scale features of urban canopy effects on air flow. Aggregation of urban canopy properties to form a hierarchy of approaches relevant to different urban and meteorological scales will be the focus. Single or multi-layer canopy approaches will be pursued at different scales: Roughness and porosity approach (Baklanov et al., 2005; Zilitinkevich et al., 2007); Building Effect Parameterisation (BEP) (Martilli et al., 2002); Obstacle-resolved and dispersive stress approach (Martilli and Santiago, 2007). To overcome the challenges, CFD codes will be extensively is used in the development.

3) Urban energy balance: For accurate physical description of the atmosphere it is necessary to model the surface-atmosphere energy exchanges. Currently available urban land surface schemes will be assessed for their suitability for different air quality modelling applications. The constraint of improving modelling performance over data requirements and computational time will be considered. The models will be evaluated against surface flux data (Martilli et al., 2002; Masson et al. 2002; von Salzen et al., 1996). The methods best to parameterize the spatial and temporal dynamics of the key physical processes of the urban energy balance that need to be resolved for air quality applications will be analysed.

4) Urban atmospheric boundary layer (UABL): Turbulence-resolving simulations (LES) of UABL are necessary to account for strong non-linearity of the turbulence aggregation over surface heterogeneities. Turbulence parameterizations derived from homogeneous turbulence studies may not represent the UABL adequately (Esau, 2007). LES provide 3-d evolving fields of meteo-parameters fluctuations. A procedure to aggregate this information into a single-column profile will be developed. The approach links UABL integral measures, less sensitive to the heterogeneity, to UABL mixing properties and ultimately to the large-scale meteorological fields (Zilitinkevich and Esau, 2005; Esau and Zilitinkevich, 2006). The new parameterization encoded into climate models will improve their accounting for heterogeneity of anthropogenic heat fluxes etc, i.e. features neglected for simplicity in earlier approaches.

5) “Megacity dispersion features”: Sub-grid variability of emissions and pollutant dispersions need to be accounted for in large-scale models. Turbulence in the UABL mixes chemically reactive compounds so that their composition may change rapidly with distance from an emission source (Galmarini et al., 1997a, b; Molemaker et al., 1998; Krol et al., 2000). LES and CFD models are powerful tools to study the relevant dispersion processes and to develop parameterizations for meteorological, air quality and dispersion models. Two approaches tackle different levels of complexity: LES will assess chemical efficiency of non-homogenous mixing of emissions with urban scale turbulence; CFD will quantify dispersion of passive tracers accounting for specific effects in mixing caused by rapid changes of urban geometry. The results will facilitate scientific integration of reactive chemistry and effective emissions into urban sub-grid parameterizations.

FP7 EC MEGAPOLI, 2008-2011