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Good representation of turbulence in urban canopy models is necessary for accurate prediction of momentum and scalar distribution in and above urban canopies. To develop and improve turbulence closure schemes for one-dimensional multi-layer urban canopy models, turbulence characteristics are investigated here by analyzing existing large-eddy simulation and direct numerical simulation data. A range of geometries and flow regimes are analyzed that span packing densities of 0.0625 to 0.44, different building array configurations (cubes and cuboids, aligned and staggered arrays, and variable building height), and different incident wind directions (0∘ and 45∘ with regards to the building face). Momentum mixing-length profiles share similar characteristics across the range of geometries, making a first-order momentum mixing-length turbulence closure a promising approach. In vegetation canopies turbulence is dominated by mixing-layer eddies of a scale determined by the canopy-top shear length scale. No relationship was found between the depth-averaged momentum mixing length within the canopy and the canopy-top shear length scale in the present study. By careful specification of the intrinsic averaging operator in the canopy, an often-overlooked term that accounts for changes in plan area density with height is included in a first-order momentum mixing-length turbulence closure model. For an array of variable-height buildings, its omission leads to velocity overestimation of up to 17%. Additionally, we observe that the von Kármán coefficient varies between 0.20 and 0.51 across simulations, which is the first time such a range of values has been documented. When driving flow is oblique to the building faces, the ratio of dispersive to turbulent momentum flux is larger than unity in the lower half of the canopy, and wake production becomes significant compared to shear production of turbulent momentum flux. It is probable that dispersive momentum fluxes are more significant than previously thought in real urban settings, where the wind direction is almost always oblique.

Further to our previous large-eddy simulation (LES) of flow over a staggered array of uniform cubes, a simulation of flow over random urban-like obstacles is presented. To gain a deeper insight into the effects of randomness in the obstacle topology, the current results, e.g. spatially-averaged mean velocity, Reynolds stresses, turbulence kinetic energy and dispersive stresses, are compared with our previous LES data and direct numerical simulation data of flow over uniform cubes. Significantly different features in the turbulence statistics are observed within and immediately above the canopy, although there are some similarities in the spatially-averaged statistics. It is also found that the relatively high pressures on the tallest buildings generate contributions to the total surface drag that are far in excess of their proportionate frontal area within the array. Details of the turbulence characteristics (like the stress anisotropy) are compared with those in regular roughness arrays and attempts to find some generality in the turbulence statistics within the canopy region are discussed.

Large-eddy simulations are performed using the U.K. Met Office Large Eddy Model to study the effects of resolution on turbulent structures in a convective boundary layer. A standard Smagorinsky subgrid scheme is used. As the grid length is increased, the diagnosed height of the boundary layer increases, and the horizontally- and temporally-averaged temperature near the surface and in the inversion layer increase. At the highest resolution, quadrant analysis shows that the majority of events in the lower boundary layer are associated with cold descending air, followed by warm ascending air. The largest contribution to the total heat flux is made by warm ascending air, with associated strong thermals. At lower resolutions, the contribution to the heat flux from cold descending air is increased, and that from cold ascending air is reduced in the lower boundary layer; around the inversion layer, however, the contribution from cold ascending air is increased. Calculations of the heating rate show that the differences in cold ascending air are responsible for the warm bias below the boundary layer top in the low resolution simulations. Correlation length and time scales for coherent resolved structures increase with increasing grid coarseness. The results overall suggest that differences in the simulations are due to weaker mixing between thermals and their environment at lower resolutions. Some simple numerical experiments are performed to increase the mixing in the lower resolution simulations and to investigate backscatter. Such simulations are successful at reducing the contribution of cold ascending air to the heat flux just below the inversion, although the effects in the lower boundary layer are weaker.

Turbulence statistics obtained by direct numerical simulations are analysed to investigate spatial heterogeneity within regular arrays of building-like cubical obstacles. Two different array layouts are studied, staggered and square, both at a packing density of [Formula: see text] . The flow statistics analysed are mean streamwise velocity ([Formula: see text]), shear stress ([Formula: see text]), turbulent kinetic energy (k) and dispersive stress fraction ([Formula: see text]). The spatial flow patterns and spatial distribution of these statistics in the two arrays are found to be very different. Local regions of high spatial variability are identified. The overall spatial variances of the statistics are shown to be generally very significant in comparison with their spatial averages within the arrays. Above the arrays the spatial variances as well as dispersive stresses decay rapidly to zero. The heterogeneity is explored further by separately considering six different flow regimes identified within the arrays, described here as: channelling region, constricted region, intersection region, building wake region, canyon region and front-recirculation region. It is found that the flow in the first three regions is relatively homogeneous, but that spatial variances in the latter three regions are large, especially in the building wake and canyon regions. The implication is that, in general, the flow immediately behind (and, to a lesser extent, in front of) a building is much more heterogeneous than elsewhere, even in the relatively dense arrays considered here. Most of the dispersive stress is concentrated in these regions. Considering the experimental difficulties of obtaining enough point measurements to form a representative spatial average, the error incurred by degrading the sampling resolution is investigated. It is found that a good estimate for both area and line averages can be obtained using a relatively small number of strategically located sampling points.

We present an algorithm for detecting sea breezes based on fuzzy logic, using changes in variables commonly measured at meteorological stations. The method is applied to 1 year's worth of UK Met Office data (2012) measured at several stations around London, UK. Results indicate about a dozen potential events over the year, when matched against corresponding detections at a coastal reference site (Gravesend). In some cases the time lags between corresponding events detected at different stations can be used to characterize the average propagation speed of the sea‐breeze front. Advantages and disadvantages of the method are discussed. We present an objective algorithm for detecting sea breezes based on fuzzy logic, using changes in variables commonly measured at meteorological stations. The method is applied to 1 year's worth of UK Met Office data (2012) measured at several stations around London, UK. Results indicate about a dozen potential events over the year, when matched against corresponding detections at a coastal reference site (Gravesend).

The need to balance computational speed and simulation accuracy is a key challenge in designing atmospheric dispersion models that can be used in scenarios where near real-time hazard predictions are needed. This challenge is aggravated in cities, where models need to have some degree of building-awareness, alongside the ability to capture effects of dominant urban flow processes. We use a combination of high-resolution large-eddy simulation (LES) and wind-tunnel data of flow and dispersion in an idealised, equal-height urban canopy to highlight important dispersion processes and evaluate how these are reproduced by representatives of the most prevalent modelling approaches: (1) a Gaussian plume model, (2) a Lagrangian stochastic model and (3) street-network dispersion models. Concentration data from the LES, validated against the wind-tunnel data, were averaged over the volumes of streets in order to provide a high-fidelity reference suitable for evaluating the different models on the same footing. For the particular combination of forcing wind direction and source location studied here, the strongest deviations from the LES reference were associated with mean over-predictions of concentrations by approximately a factor of 2 and with a relative scatter larger than a factor of 4 of the mean, corresponding to cases where the mean plume centreline also deviated significantly from the LES. This was linked to low accuracy of the underlying flow models/parameters that resulted in a misrepresentation of pollutant channelling along streets and of the uneven plume branching observed in intersections. The agreement of model predictions with the LES (which explicitly resolves the turbulent flow and dispersion processes) greatly improved by increasing the accuracy of building-induced modifications of the driving flow field. When provided with a limited set of representative velocity parameters, the comparatively simple street-network models performed equally well or better compared to the Lagrangian model run on full 3D wind fields. The study showed that street-network models capture the dominant building-induced dispersion processes in the canopy layer through parametrisations of horizontal advection and vertical exchange processes at scales of practical interest. At the same time, computational costs and computing times associated with the network approach are ideally suited for emergency-response applications.

Dynamic subgrid models are increasingly being used in simulations of the atmospheric boundary layer. We have implemented several variant forms of dynamic models in the UK Met Office Large Eddy Model (MetLEM), including a state‐of‐the‐art Lagrangian‐Averaged‐Scale‐Dependent (LASD) model. The implementation includes optional use of stability functions in the specification of the eddy viscosity and diffusivity, as well as optional use within the dynamic calculation of the Smagorinsky parameter. This paper reports on the behaviour of the LASD model with different choices for the inclusion and treatment of stability functions in convective boundary layer simulations at different resolutions. Results are compared against a high‐resolution Large‐Eddy simulation (LES) and against simulations employing the Smagorinsky–Lilly subgrid model. We conclude that the use of stability functions improves the behaviour of the LASD model in the grey zone regime. Moreover, a careful treatment of the stability functions in the calculation of the dynamic parameters, while attractive theoretically, is found to be unnecessary in practical terms. We implement a number of variants of the dynamic model in the UK Met Office Large Eddy Model (MetLEM), including a state of the art Lagrangian‐Averaged‐Scale‐Dependent (LASD) model. The implementation includes optional use of stability functions for convective simulations. Compared against a high‐resolution Large‐Eddy simulation (LES), the use of stability functions improves the behaviour of the LASD model in the grey zone regime.

This paper presents a review of recent experimental and numerical studies which deal with the analysis of form-induced stress in rough wall turbulent boundary layers. The aim of the paper is to assess the importance of this stress for various rough wall geometries and flow conditions. Analysis of the significance of form-induced stress is first performed by comparing its magnitude with the magnitude of Reynolds stress for each data set available in literature. Then, by selecting a special set of data, we analyze the comparison between the gradients of both stresses. We point out that the comparison of stress gradients gives a different perspective on the role of form-induced stress in rough wall boundary layers.