D E S C R I P T I O N O F W O R K - MEGAPOLI - Dmi

MEGAPOLI 212520
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
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