Meteorological and Air Quality Models for Urban Areas

Abstract

Urban features essentially influence atmospheric flow and microclimate, strongly enhance atmospheric turbulence, and modify turbulent transport, dispersion, and deposition of atmospheric pollutants (e.g., Piringer et al., 2007). Increased resolution in numerical weather prediction (NWP) models allows for a more realistic reproduction of urban air flows and air pollution processes, however most of the operational models still do not consider, or consider very poorly, the urban effects. This has triggered new interest in model development and investigation of processes specific to urban areas. Recent developments performed as part of the European project FUMAPEX on integrated systems for forecasting urban meteorology and air pollution (Baklanov et al., 2002(Baklanov et al., , 2005, the US EPA and NCAR communities for MM5 Bornstein et al., 2006;Taha 2008), WRF models , and other relevant studies (see e.g. Baklanov and Grisogono, 2007) have shown many opportunities in the "urbanization" of weather forecasting and atmospheric pollution dispersion models.Atmospheric models for urban areas have different requirements (e.g. relative importance of the urban boundary layer (UBL) and urban surface sublayer (USL) structure) depending on: (i) the scale of the models (global, regional, city, local, micro, etc.); (ii) the functional type of the model, e.g.:• Forecasting or assessment type of models, • Urban or regional climate models, • Research meso-meteorological models, • Numerical weather prediction models, • Atmospheric pollution models (city-scale), • Emergency preparedness models, • Meteo-preprocessors (or post-processors).A wide range of approaches have been taken to incorporating urban characteristics. In addition there are a wide range of processes which includes: characteristics of the urban canopy sublayer, components of urban surface energy balance (net radiation, sensible and latent heat fluxes, storage heat flux, etc.), and water v vi Introduction to the Problem and Aims transport. This results in a wide range of models (e.g., Brown and Williams, 1998;Oke et al., 1999;Grimmond and Oke, 1999;Kusaka et al., 2001; Masson, 2000;Dupont, 2001;Martilli et al., 2002). Most urban NWP or meso-meteorological models modify the existing non-urban approaches (e.g., the Monin-Obukhov similarity theory, MOST) for urban areas by parameterisation or finding proper values for the effective roughness lengths, displacement height, and heat fluxes, including the anthropogenic heat flux, heat storage capacity, albedo and emissivity change, etc. The main limitation is when there is a need to resolve meteorological profiles within the urban canopy, where the MOST assumption of a constant flux surface layer is invalid. This is obviously important as it is a layer into which pollutants are emitted and in which people live. The sophistication of urbanization within research mesoscale models has increased during the last 10 years, starting with the work of Brown and Williams (1998), which included urban effects in their TKE scheme. Masson ...

UDINEE: Evaluation of Multiple Models with Data from the JU2003 Puff Releases in Oklahoma City. Part I: Comparison of Observed and Predicted Concentrations

“…Urban features (e.g., sizes of buildings and overall morphology, distribution of streets, total dimension of urban area) affect low-level atmospheric flow and hence influence turbulence and the dispersion of airborne pollutants and their deposition (Baklanov et al 2009). The simulation of airflow distribution constitutes a challenge whenever ADMs are used to better understand and/or predict the pollutant dispersion in an urban environment (e.g.…”

UDINEE: Evaluation of Multiple Models with Data from the JU2003 Puff Releases in Oklahoma City. Part II: Simulation of Puff Parameters

“…Because of this progress, a wide range of ADMs can now simulate air pollution dispersion in cities (e.g. Baklanov et al 2009;Lateb et al 2016;Wingstedt et al 2017).…”

Sensitivity analysis and optimization of a mesoscale atmospheric model

“…The single-layer urban canopy models (SLUCMs) simulate the urban energy fluxes at one atmospheric layer representing the city below the roof level. The multilayer models, on the other hand, simulate the energy fluxes at several atmospheric layers that interact with the buildings within the UCL (Grimmond et al, 2009;Masson, 2006).…”

“…Air temperature and humidity are assumed to be uniform in the UCL. For the wind, the logarithmic law is applied down to just under the top of the canyon and the exponential law is used below (Grimmond et al, 2009;Masson, 2006). Despite the simplification approaches, the SLUCMs that primarily developed for applications in mesoscale modeling (Kusaka et al, 2001;Masson, 2000) have shown a good performance in simulating the sensible heat fluxes and the surface and air temperatures over built-up areas (Masson et al, 2002;Kusaka and Kimura, 2004).…”

“…The latter set of variables includes temperature, wind, humidity, radiation and soil characteristics to force the UCM simulations. When a UCM is coupled to a mesoscale NWP model, these forcing data are provided by the NWP model and therefore are updated at each integration time step (Grimmond et al, 2010(Grimmond et al, , 2009. This interaction is two-way in the sense that the UCM also supply the NWP model with the lower boundary conditions.…”