Flow and turbulence above urban terrain is more complex than above rural terrain, due to the different momentum and heat transfer characteristics that are affected by the presence of buildings (e.g. pressure variations around buildings). The applicability of similarity theory (as developed over rural terrain) is tested using observations of flow from a sonic anemometer located at 190.3 m height in London, U.K. using about 6500 h of data. Turbulence statistics-dimensionless wind speed and temperature, standard deviations and correlation coefficients for momentum and heat transfer-were analysed in three ways. First, turbulence statistics were plotted as a function only of a local stability parameter z/ (where is the local Obukhov length and z is the height above ground); the σ i /u * values (i = u, v, w) for neutral conditions are 2.3, 1.85 and 1.35 respectively, similar to canonical values. Second, analysis of urban mixed-layer formulations during daytime convective conditions over London was undertaken, showing that atmospheric turbulence at high altitude over large cities might not behave dissimilarly from that over rural terrain. Third, correlation coefficients for heat and momentum were analyzed with respect to local stability. The results give confidence in using the framework of local similarity for turbulence measured over London, and perhaps other cities. However, the following caveats for our data are worth noting: (i) the terrain is reasonably flat, (ii) building heights vary little over a large area, and (iii) the sensor height is above the mean roughness sublayer depth.

An urban canopy parameterization (UCP) is implemented into the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5) to improve meteorological fields in the urban boundary layer for finescale (ϳ1-km horizontal grid spacing) simulations. The UCP uses the dragforce approach for dynamics and a simple treatment of the urban thermodynamics to account for the effects of the urban environment. The UCP is evaluated using a real-data application for Philadelphia, Pennsylvania. The simulations show that the UCP produces profiles of wind speed, friction velocity, turbulent kinetic energy, and potential temperature that are more consistent with the observations taken in urban areas and data from idealized wind tunnel studies of urban areas than do simulations that use the roughness approach. In addition, comparisons with meteorological measurements show that the UCP simulations are superior to those that use the roughness approach. This improvement of the treatment of the urban areas in the meteorological model could have implications for simulating air chemistry processes at this scale.

In several recent large-eddy simulation studies, the lowest grid level was located well within the roughness sublayer. Monin-Obukhov similarity-based boundary conditions cannot be used under this scenario, and in this note we elaborate on this fundamental problem and suggest potential solutions.Keywords Inertial sublayer · Large-eddy simulation · Monin-Obukhov similarity theory · Roughness sublayer · Surface layerIn the era of petascale computing, very high-resolution (the grid size, Δ = O(1) m or finer) large-eddy simulation (LES) of atmospheric boundary-layer (ABL) flows is gradually becoming a norm. For example, in a recent study (Sullivan et al. 2016), Δ = 0.39m was utilized in the idealized simulation of the stable boundary layer. It is a well-known fact that all the contemporary LES codes utilize the conventional Monin-Obukhov similarity theory (MOST) as lower boundary conditions (e.g., Heus et al. 2010;Maronga et al. 2015). It is also common knowledge (e.g., Lumley and Panofsky 1964;Monin and Yaglom 1971;Wyngaard 2010) that MOST is only valid for heights z z • , where z • is the aerodynamic roughness length. MOST is not applicable for z < αh, where h denotes the height of the roughness elements. Typically, α is assumed to be between 2 and 5 based on laboratory studies (see Raupach et al. 1991, and references therein). Unfortunately, a number of recent LES studies (e.g., Beare et al. 2006;Basu et al. 2011; Maronga 2014;Sullivan et al. 2016;Udina et al.