Verifying urban canopy parameterization effects in a mesoscale model with wind tunnel data

<p>Airflow within and above urban canopy layers are modelled by different approaches in a wind tunnel and in a numerical mesoscale model. For the experimental approaches in the wind tunnel, the combination of spires, roughness elements and a physical model generates a scaled boundary layer flow with velocity and turbulence characteristics that are consistent with microscale urban canopy flows in reality. A wind tunnel is comparable in resolution with an obstacle resolving microscale model, therefore data comparisons are frequently done for this scale. However, for many applications numerical models of 1 km resolution are used, resolving mesoscale atmospheric phenomena but not microscale ones. Parameterizations are then used to represent physical processes and obstacle influences on the atmospheres. Due to the coarse resolution, a direct comparison of mesoscale model results and wind tunnel is difficult.</p> <p>In this study, we use wind tunnel data as validation datasets to evaluate the urban canopy parameterization effects on airflow in a mesoscale model. We have developed a multi-layer urban canopy parameterization using nudging, implemented in the atmospheric model METRAS. The extended model is tested in an idealized case, in which the model domain is designed using realistic topographical data for the Hamburg city center but not resolving buildings. To simplify the city structure, two important canopy morphological parameters are used: building surface fraction and building height. Experiments with a similar model configuration were carried out in parallel in the Blasius wind tunnel facility of the Environmental Wind-Tunnel Laboratory of the University of Hamburg at a model scale of 1:500. Based on the realistic building surface fraction and building height, a pyramid-like model for the urban canopy is placed in the wind tunnel. The set-ups of the numerical model runs and the wind tunnel experiments are designed following two principles: first, keeping the set-up in both approaches as equivalent as possible, in terms of meteorological conditions, roughness lengths, simulation durations, etc.; secondly, taking into account the limitations of the microscale wind tunnel datasets and keeping as many characteristics of atmospheric processes as possible.</p> <p>The METRAS results show a good agreement with the wind tunnel datasets, in terms of representing building effects such as the reduction of mean wind speeds in the building wake, enhanced turbulence intensities and turbulent fluctuation characteristics for a sufficiently fine scale. However, for coarser resolution, the result comparability reduces and the agreement is less. Thus, we conclude that sub-grid scale canopy effects can be parameterized sufficiently well for their impacts on the average flow, but any detailed changes can only be simulated with a sufficiently high resolution.</p>

Resolving urban canopy flows: Scales, turbulence and boundary conditions in obstacle-resolving numerical models

<p>Large-eddy simulations are increasingly used for studying the atmospheric boundary layer. With increasing computational resources even obstacle-resolving Large-eddy simulations became possible and will be used in urban climate studies more frequently. In these applications, grid sizes are in the order of a few meters. Whereas major urban structures can be resolved in general, details like aerodynamically rough surface structures can not be resolved explicitly. Based on the original fields of application, boundary conditions in Large-eddy simulations were initially formulated for surfaces of homogeneous roughness and for wall-distances much larger than the roughness sublayer height (Hultmark et al., 2013). The height of the roughness sublayer depends on the size of small-scale obstacles present on the surface exposed to the flow (Raupach et al., 1991). Typically, boundary conditions are evaluated between the surface and the first grid level. Thus, grid resolution in obstacle-resolved Large-Eddy simulations should also be a question of scales and therefore has to be chosen carefully (Basu and Lacser, 2017; Maronga et al., 2020). <br />In several wind tunnel experiments presented here, we measured the near-wall influence of differently scaled and shaped objects on a flow and its turbulence characteristics. Experimental setups were replicated numerically using the PALM model (Maronga et al. 2019). In a first, more generic experiment, the flow over horizontally homogeneous surfaces of different roughness was investigated. In a second experiment, the spatial separation of the turbulence scales was investigated in a more complex flow case. These experiments lead to considerations on model grid sizes in urban type Large-eddy simulations. The limitations of interpreting simulation results within the urban canopy layer are highlighted. There is an urgent need to reconsider how near-wall results of urban large-eddy simulations are generated and interpreted in the context of practical applications like flow and transport modelling in urban canopies. <br /><br /><em><strong>References</strong></em><br /><em>Basu, S. and Lacser, A. (2017). A Cautionary Note on the Use of Monin–Obukhov Similarity Theory in Very High-Resolution Large-Eddy Simulations. Boundary-Layer Meteorol, 163(2):351–355.</em></p> <p><em>Hultmark, M., Calaf, M., and Parlange, M. B. (2013). A new wall shearstress model for atmospheric boundary layer simulations. J Atmos Sci,70(11):3460–3470.</em></p> <p><em>Maronga, B., et al. (2020). Overview of the PALM model system 6.0. Geosci Model Dev Discussions, 06(June):1–63.</em></p> <p><em>Maronga, B., Knigge, C., and Raasch, S. (2020). An Improved Surface Boundary Condition for Large-Eddy Simulations Based on Monin–Obukhov Similarity Theory: Evaluation and Consequences forGrid Convergence in Neutral and Stable Conditions. Boundary-Layer Meteorol, 174(2):297–325.</em></p> <p><em>Raupach, M. R., Antonia, R. A., and Rajagopalan, S. (1991). Rough-wall turbulent boundary layers. Appl Mech Rev, 44(1):1–25</em></p>

Large-Eddy Simulations on the Effects of Two Wind Passage Types between Buildings on the Airflow and Drag Characteristics

Passages between buildings comprise the airflow path through the buildings, and the wind passage is often studied in terms of two buildings located parallel or at a certain angle. From the perspective of urban areas, the wind passage can be considered the series connection of all local wind passages between each row of buildings. Whether the central axis of each local wind passage is collinear or not, the wind passages of the building array can be summarized as distorted and streamlined types. Large-eddy simulations (LESs) are employed to assess the impacts of the above two wind passage types on the airflow and drag characteristics. The mean, unsteady flow fields and the drag distributions are discussed to assess the effects of wind passages types. Span-wise airflow was found in the wake region in the case of distorted wind passages (DWP), whereas the recirculating vortices dominated the wake region for the case of streamlined wind passages (SWP). Span-wise airflow enhanced the mean stream-wise velocity U and span-wise velocity U in the wake region, decreased U in the wind passage region, and increased dispersive stress 〈V˜2〉 and 〈U˜2〉 within the urban canopy and the peak Reynolds stress above the urban canopy. Further, it strengthened the individual drag forces of buildings and the fluctuations of span-wise and stream-wise individual drag forces. The air of DWP penetrated deeper than SWP. These findings provide theory and data support for better design of wind passages between buildings and may serve as a foundation for urban design and planning.

Seasonal variation of dry and wet islands in Beijing considering urban artificial water dissipation

Urbanization has resulted in dry/wet island effects in built-up areas. Compared to the limited number of observational datasets, simulations can provide data with richer spatial distribution, thereby proving to be more helpful for revealing the spatial distribution of dry/wet islands. This study simulated dry/wet island effects during typical summer and winter conditions in Beijing by coupling the Artificial Water Dissipation Urban Canopy Model with the Weather Research and Forecasting model. Observations of relative humidity, absolute humidity, and temperature from weather stations in Beijing were used to verify the model. The results showed that in 2020, Beijing was prone to be a dry island during summer, with the relative humidity approximately 5–10% lower than the surrounding suburbs. The dry island effect was not obvious in winter, and Beijing tended to be a wet island. The influence of artificial water dissipation on dry/wet islands is higher in winter than in summer. By considering the water vapor from artificial water dissipation, humidity in urban areas can be simulated more accurately.

Influence of the local urban environment on the thermo-radiative and hydrological behaviour of a garden lawn

Several urban canopy models now incorporate urban vegetation to represent local urban cooling related to natural soils and plants evapotranspiration. Nevertheless, little is known about the realism of simulating these processes and turbulent exchanges within the urban canopy. Here, the coupled modelling of thermal and hydrological exchanges was investigated for a lawn located in an urban environment, and for which soil temperature and water content measurements were available. The ISBA-DF surface-vegetation-atmosphere transfer model is inline coupled to the TEB urban canopy model to model mixed urban environments. For the present case study, ISBA-DF was applied to the lawn and first evaluated in its default configuration. Particular attention was then paid to the parameterization of turbulent exchanges above the lawn, and to the description of soil characteristics. The results highlighted the importance of taking into account local roughness related to surrounding obstacles for computing the turbulent exchanges over the lawn, and simulating realistic surface and soil temperatures. The soil nature and texture vertical heterogeneity are also key properties for simulating the soil water content evolution and water exchanges.

Energetics of Urban Canopies: A Meteorological Perspective

The urban climatology consists not only of the urban canopy temperature but also of wind regime and boundary layer evolution among other secondary variables. The energetic input and response of urbanized areas is rather different to rural or forest areas. In this paper, we outline the physical characteristics of the urban canopy that make its energy balance depart from that of vegetated areas and change local climatology. Among the several canopy characteristics, we focus on the aspect ratio h/d and its effects. The literature and methods of retrieving meteorological quantities in urban areas are reviewed and a number of physical analyzes from conceptual or numerical models are presented. In particular, the existence of a maximum value for the urban heat island intensity is discussed comprehensively. Changes in the local flow and boundary layer evolution due to urbanization are also discussed. The presence of vegetation and water bodies in urban areas are reviewed. The main conclusions are as follows: for increasing h/d, the urban heat island intensity is likely to attain a peak around h/d≈4 and decrease for h/d>4; the temperature at the pedestrian level follows similar behavior; the urban boundary layer grows slowly, which in combination with low wind, can worsen pollution dispersion.

Impact of 3D radiative transfer on airborne NO₂ imaging remote sensing over cities with buildings

Airborne imaging remote sensing is increasingly used to map the spatial distribution of nitrogen dioxide (NO2) in cities. Despite the small ground-pixel size of the sensors, the measured NO2 distributions are much smoother than one would expect from high-resolution model simulations of NO2 over cities. This could partly be caused by 3D radiative transfer effects due to observation geometry, adjacency effects and effects of buildings. Here, we present a case study of imaging a synthetic NO2 distribution for a district of Zurich using the 3D MYSTIC (Monte carlo code for the phYSically correct Tracing of photons In Cloudy atmospheres) solver of the libRadtran radiative transfer library. We computed NO2 slant column densities (SCDs) using the recently implemented 3D-box air mass factors (3D-box AMFs) and a new urban canopy module to account for the effects of buildings. We found that for a single ground pixel (50 m × 50 m) more than 50 % of the sensitivity is located outside of the pixel, primarily in the direction of the main optical path between sun, ground pixel, and instrument. Consequently, NO2 SCDs are spatially smoothed, which results in an increase over roads when they are parallel to the optical path and a decrease otherwise. When buildings are included, NO2 SCDs are reduced on average by 5 % due to the reduced sensitivity to NO2 in the shadows of the buildings. The effects of buildings also introduce a complex pattern of variability in SCDs that would show up in airborne observations as an additional noise component (about 12 µmol m−2) similar to the magnitude of typical measurement uncertainties. The smearing of the SCDs cannot be corrected using 1D-layer AMFs that assume horizontal homogeneity and thus remains in the final NO2 map. The 3D radiative transfer effects by including buildings need to be considered to compute more accurate AMFs and to reduce biases in NO2 vertical columns obtained from high-resolution city-scale NO2 remote sensing.

Intra–Community Scale Variability of Air Quality in the Center of a Megacity in South Korea: A High-Density Cost-Effective Sensor Network

To investigate the spatial and temporal variability of air quality (CO, NO2, O3, and PM2.5) with a high spatial resolution in various adjacent micro-environments, 30 sets of sensor-nodes were deployed within an 800 × 800 m monitoring domain in the center of the largest megacity (Seoul) in South Korea. The sensor network was operated in summer and winter. The daily variation in air pollutant concentrations revealed a similar trend, with discernible concentration differences among monitoring sub-sites and a government-operated air quality monitoring station. These differences in pollutant levels (except PM2.5) among the sub-sites were pronounced in the daytime with high volumes of traffic. The coefficient of divergence and Pearson correlation coefficient showed that spatial and temporal variability was more significant in summer than winter. Ozone displayed the greatest spatial variability, with little temporal variability among the sub-sites and a negative correlation with NO2, implying that ozone concentrations were primarily determined by vehicular NOX emissions due to NO titration effects under the urban canopy. The PM2.5 concentration displayed homogeneous spatial and temporal distributions over the entire monitoring period, implying that PM2.5 monitoring with at least a 1 × 1 km resolution is sufficient to examine the spatial and temporal heterogeneity in urban areas.