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Large Eddy Simulations (LES) of neutral flow over regular. arrays of cuboids are conducted to explore connections between momentum (z0m) and scalar (z0s) roughness lengths in urban environments, and how they are influenced by surface geometry. As LES resolves the obstacles but not the micro-scale boundary layers attached to them, the aforementioned roughness lengths are analyzed at two distinct spatial scales. At the micro-scale (roughness of individual facets, e.g. roofs), it is assumed that both momentum and scalar transfer are governed by accepted arguments for smooth walls that form the basis for the LES wall model. At the macro-scale, the roughness lengths are representative of the aggregate effects of momentum and scalar transfer over the resolved roughness elements of the whole surface, and hence they are directly computed from the LES. The results indicate that morphologically-based parameterizations for macro-scale z0m are adequate overall. The relation between the momentum and scalar macro-roughness values, as conventionally represented by log(z0m/z0s) and assumed to scale with Re n (where Re is a roughness Reynolds number), is then interpreted using surface renewal theory (SRT). SRT predicts n = 1/4 when only Kolmogorov-scale eddies dominate the scalar exchange, whereas n =1/2 is predicted when large eddies limit the renewal dynamics. The latter is found to better capture the LES results. However, both scaling relations indicate that z0s decreases when z0m increases for typical urban geometries and scales. This is opposite to how their relation is usually modeled for urban canopies (i.e. z0s/z0m is a fixed value smaller than unity).

Atmospheric boundary-layer dynamics over heterogeneous surfaces is significant to a wide array of geophysical and engineering applications. Yet, despite over five decades of intense efforts by the research community, numerous open research questions remain. This underlines the complexity of the physical processes that are excited by heterogeneity, the multitude of patterns and manifestations that it can display, and the importance of the implications to research in the atmospheric sciences and beyond. Here, existing knowledge is reviewed and a path forward for research is proposed, starting with the smaller scales near a surface transition and proceeding to the influence on large-scale dynamics and their forecasting.

The literature includes a wide variety of definitions or perceptions of non-stationarity. Non-stationarity can be expressed in terms of turbulence statistics or variability of the forcing of the turbulence such as time changes of the wind vector, the horizontal pressure gradient, or the surface heat flux. Our survey emphasizes the development of non-equilibrium turbulence caused by non-stationary forcing. The degree of non-equilibrium of the turbulence is most reliably evaluated following the local flow rather than using the more available fixed-point measurements. We survey methods to eliminate non-stationary records or partially filter out the non-stationarity. We also summarize issues with parametrization of the non-stationarity. Non-stationarity over the sea can be complex due to time-dependent wave state and surface roughness. The impact of non-stationarity is generally less understood in the stable boundary layer compared to the unstable boundary layer.

Mobile laboratory measurements provide information on the distribution of CH4 emissions from point sources such as oil and gas wells, but uncertainties are poorly constrained or justified. Sources of uncertainty and bias in ground-based Gaussian-derived emissions estimates from a mobile platform were analyzed in a combined field and modeling study. In a field campaign where 1009 natural gas sites in Pennsylvania were sampled, a hierarchical measurement strategy was implemented with increasing complexity. Of these sites, ∼ 93 % were sampled with an average of 2 transects in 4 concentrations in a turbulent environment. The LES output and LES-derived emission estimates were used to compare with the results of a standard Gaussian approach. The LES and Gaussian-derived emission rates agreed within a factor of 2 in all except one case; the average difference was 25 %. A controlled release was also used to investigate sources of bias in either technique. The Gaussian method agreed with the release rate more closely than the LES, underlining the importance of inputs as sources of uncertainty for the LES. The LES was also used as a virtual experiment to determine an optimum number of repeat transects and spacing needed to produce representative statistics. Approximately 10 repeat transects spaced at least 1 min apart are required to produce statistics similar to the observed variability over the entire LES simulation period of 30 min. Sources of uncertainty from source location, wind speed, background concentration and atmospheric stability were also analyzed. The largest contribution to the total uncertainty was from atmospheric variability; this is caused by insufficient averaging of turbulent variables in the atmosphere (also known as random errors). Atmospheric variability was quantified by repeat measurements at individual sites under relatively constant conditions. Accurate quantification of atmospheric variability provides a reasonable estimate of the lower bound for emission uncertainty. The uncertainty bounds calculated for this work for sites with > 50 ppb enhancements were 0.05–6.5q (where q is the emission rate) for single-transect sites and 0.5–2.7q for sites with 10+ transects. More transects allow a mean emission rate to be calculated with better precision. It is recommended that future mobile monitoring schemes quantify atmospheric variability, and attempt to minimize it, under representative conditions to accurately estimate emission uncertainty. These recommendations are general to mobile-laboratory-derived emissions from other sources that can be treated as point sources.

This paper investigates the effects of baroclinic pressure gradients on mean flow and turbulence in the diabatic atmospheric boundary layer (ABL). Large-eddy simulations are conducted where the direction of the baroclinicity, its strength, and the surface buoyancy flux are systematically varied to examine their interacting effects. The thermal wind vector, which represents the vertical change in the geostrophic wind vector resulting from horizontal temperature gradients, significantly influences the velocity profiles, the Ekman turning, and the strength and location of the low-level jet (LLJ). For instance, cold advection and positive (negative) geostrophic shear increased (decreased) friction velocity and changed the LLJ elevation. Given the baroclinicity strength and direction under neutral conditions, a simple reduced model is proposed and validated here to predict the general trends of baroclinic mean winds. The baroclinic effects on turbulence intensity and structure are even more intricate, with turbulent kinetic energy (TKE) profiles displaying an increase of TKE magnitude with height for some cases. When a fixed destabilizing surface heat flux is added, a positive geostrophic shear favors streamwise aligned roll-type structures, which are typical of neutral ABLs. Conversely, a negative geostrophic shear promotes cell-type structures, which are typical of strongly unstable ABLs. Furthermore, baroclinicity increases shear in the outer ABL and tends to make the outer flow more neutral by decreasing the Richardson flux number. These findings are consequential for meteorological measurements and the wind-energy industry, among others: baroclinicity alters the mean wind profiles, the TKE, coherent structures, and the stability of the ABL, and its effects need to be considered.

Vertical-axis wind turbines (VAWTs) are being reconsidered as a complementary technology to the more widely used horizontal-axis wind turbines (HAWTs) due to their unique suitability for offshore deployments. In addition, field experiments have confirmed that vertical-axis wind turbines can interact synergistically to enhance the total power production when placed in close proximity. Here, we use an actuator line model in a large-eddy simulation to test novel VAWT farm configurations that exploit these synergistic interactions. We first design clusters with three turbines each that preserve the omni-directionality of vertical-axis wind turbines, and optimize the distance between the clustered turbines. We then configure farms based on clusters, rather than individual turbines. The simulations confirm that vertical-axis wind turbines have a positive influence on each other when packed in well-designed clusters: such configurations increase the power generation of a single turbine by about 10 percent. In addition, the cluster designs allow for closer turbine spacing resulting in about three times the number of turbines for a given land area compared to conventional configurations. Therefore, both the turbine and wind-farm efficiencies are improved, leading to a significant increase in the density of power production per unit land area.

The higher temperature in cities relative to their rural surroundings, known as the urban heat island (UHI), is one of the most well documented and severe anthropogenic modifications of the environment. Heat islands are hazardous to residents and the sustainability of cities during summertime and heat waves; on the other hand, they provide considerable benefits in wintertime. Yet, the evolution of UHIs during cold waves has not yet been explored. In this study, ground-based observations from 12 U.S. cities and high-resolution weather simulations show that UHIs not only warm urban areas in the winter but also further intensify during cold waves by up to 1.32° ± 0.78°C (mean ± standard deviation) at night relative to precedent and subsequent periods. Anthropogenic heat released from building heating is found to contribute more than 30% of the UHI intensification. UHIs thus serve as shelters against extreme-cold events and provide benefits that include mitigating cold hazard and reducing heating demand. More important, simulations indicate that standard UHI mitigation measures such as green or cool roofs reduce these cold-wave benefits to different extents. Cities, particularly in cool and cold temperate climates, should hence revisit their policies to favor (existing) mitigation approaches that are effective only during hot periods.

This study presents results from the Weather Research and Forecasting (WRF) model applied for climatological downscaling simulations over highly complex terrain along the Eastern Mediterranean. We sequentially downscale general circulation model results, for a mild and wet year (2003) and a hot and dry year (2010), to three local horizontal resolutions of 9, 3 and 1 km. Simulated near-surface hydrometeorological variables are compared at different time scales against data from an observational network over the study area comprising rain gauges, anemometers, and thermometers. The overall performance of WRF at 1 and 3 km horizontal resolution was satisfactory, with significant improvement over the 9 km downscaling simulation. The total yearly precipitation from WRF's 1 km and 3 km domains exhibited

The low-wavenumber regime of the spectrum of turbulence commensurate with Townsend’s “attached” eddies is investigated here for the near-neutral atmospheric surface layer (ASL) and the roughness sublayer (RSL) above vegetation canopies. The central thesis corroborates the significance of the imbalance between local production and dissipation of turbulence kinetic energy (TKE) and canopy shear in challenging the classical distance-from-the-wall scaling of canonical turbulent boundary layers. Using five experimental datasets (two vegetation canopy RSL flows, two ASL flows, and one open-channel experiment), this paper explores (i) the existence of a low-wavenumber k−1 scaling law in the (wind) velocity spectra or, equivalently, a logarithmic scaling ln(r) in the velocity structure functions; (ii) phenomenological aspects of these anisotropic scales as a departure from homogeneous and isotropic scales; and (iii) the collapse of experimental data when plotted with different similarity coordinates. The results show that the extent of the k−1 and/or ln(r) scaling for the longitudinal velocity is shorter in the RSL above canopies than in the ASL because of smaller scale separation in the former. Conversely, these scaling laws are absent in the vertical velocity spectra except at large distances from the wall. The analysis reveals that the statistics of the velocity differences Δu and Δw approach a Gaussian-like behavior at large scales and that these eddies are responsible for momentum/energy production corroborated by large positive (negative) excursions in Δu accompanied by negative (positive) ones in Δw. A length scale based on TKE dissipation collapses the velocity structure functions at different heights better than the inertial length scale.

The air–water exchange of momentum and scalars (temperature and water vapour) is investigated using the Lake-Atmosphere Turbulent EXchange (LATEX) dataset. The wind waves and swell are found to affect the coupling between the water surface and the air differently. The surface-stress vector aligns with the wind velocity in the presence of wind waves, but a wide range of stress–wind misalignment angles is observed during swell. The momentum transport efficiency decreases when significant stress–wind misalignment is present, suggesting a strong influence of surface wave properties on surface drag. Based on this improved understanding of the role of wave–wind misalignment, a new relative wind speed for surface-layer similarity formulations is proposed and tested using the data. The new expression yields a value of the von Karman constant ( $$\kappa $$ ) of 0.38, compared to 0.36 when using the absolute wind speed, as well as reduced data fitting errors. Finally, the ratios of aerodynamic to scalar roughness lengths are computed and various existing models in the literature are tested using least-square fitting to the observed ratios. The tests are able to discriminate between the performance of various models; however, they also indicate that more investigations are required to understand the physics of scalar exchanges over waves.

To improve simulation of atmospheric-hydrological processes with shallow groundwater in urban areas, a new fully-coupled model was developed. The Weather Research and Forecasting (WRF) atmospheric model in the large-eddy-simulation (LES) mode, the Princeton Urban Canopy Model (PUCM), and the subsurface hydrological model ParFlow (PF) were linked (WRF-PUCM-PF). To evaluate the impact of coupling, model intercomparison was performed by application to a small watershed in suburban Baltimore, Maryland, USA, for scenarios of both homogeneous and heterogeneous geologic properties, using WRF-PUCM with and without the ParFlow component. Homogeneous scenarios isolated the impact of including terrestrial hydrological processes through ParFlow. In response to rain events, the homogeneous WRF-PUCM model output gained and retained a 40% greater amount of soil moisture (area-averaged) compared to the homogeneous WRF-PUCM-PF case. In heterogeneous scenarios, the WRF-PUCM model generated a 10-fold greater area-averaged soil moisture increase over the simulation period compared to the WRF-PUCM-PF case. The WRF-PUCM-PF model output, influenced by lateral hydrology and impervious surfaces, generated lower latent heat flux, resulting in half of the domain having higher land surface temperatures (2–10 °C), compared to the WRF-PUCM model. Overall, the WRF-PUCM-PF model provides a new tool to simulate urban physics and resolve finer urban microclimatic heterogeneity.

The Weather Research and Forecasting (WRF) model was applied as a downscaling tool over an orographically complex terrain along the Eastern Mediterranean. It was forced with the National Centers for Environment Prediction (NCEP) Final Analysis (FNL) (resolution 1°) for the years 2003 (a cold and wet year) and 2010 (a hot and dry year) and nested at sequential horizontal resolutions of 9 and 3 km. This study focuses on the assessment of simulated temperature and precipitation against data from an observational network over the study area. The observations comprise rain gauges and temperature stations with records of both daily average and/or maximum and minimum temperatures. The yearly precipitation validation shows that the WRF simulation has good agreement with the observed data, with a percentage bias of 3.80% in 2010. The errors in various extreme indices (such as minimum and maximum temperatures, number of hot or frost days, and rainfall intensity) were reduced by the downscaling, marking a large improvement over FNL analysis data in the description of temperature variability and extremes. These improvements support the benefits of dynamic downscaling over complex terrain, which can reduce the errors associated with mesoscales that are not resolved by the coarser driving model, and establish the skill of WRF for such downscaling.

In polar regions, where the boundary layer is often stably stratified, atmospheric models produce large biases depending on the boundary-layer parametrizations and the parametrization of the exchange of energy at the surface. This model intercomparison focuses on the very stable stratification encountered over the Antarctic Plateau in 2009. Here, we analyze results from 10 large-eddy-simulation (LES) codes for different spatial resolutions over 24 consecutive hours, and compare them with observations acquired at the Concordia Research Station during summer. This is a challenging exercise for such simulations since they need to reproduce both the 300-m-deep convective boundary layer and the very thin stable boundary layer characterized by a strong vertical temperature gradient (10 K difference over the lowest 20 m) when the sun is low over the horizon. A large variability in surface fluxes among the different models is highlighted. The LES models correctly reproduce the convective boundary layer in terms of mean profiles and turbulent characteristics but display more spread during stable conditions, which is largely reduced by increasing the horizontal and vertical resolutions in additional simulations focusing only on the stable period. This highlights the fact that very fine resolution is needed to represent such conditions. Complementary sensitivity studies are conducted regarding the roughness length, the subgrid-scale turbulence closure as well as the resolution and domain size. While we find little dependence on the surface-flux parametrization, the results indicate a pronounced sensitivity to both the roughness length and the turbulence closure.

The Urban Climate and Resiliency-Science Working Group (i.e., The WG) was convened in the summer of 2018 to explore the scientific grand challenges related to climate resiliency of cities. The WG leveraged the presentations at the 10th International Conference on Urban Climate (ICUC10) held in New York City (NYC) on 6–10 August 2018 as input forum. ICUC10 was a collaboration between the International Association of Urban Climate, American Meteorological Society, and World Meteorological Organization. It attracted more than 600 participants from more than 50 countries, resulting in close to 700 oral and poster presentations under the common theme of “Sustainable & Resilient Urban Environments”. ICUC10 covered topics related to urban climate and weather processes with far-reaching implications to weather forecasting, climate change adaptation, air quality, health, energy, urban planning, and governance. This article provides a synthesis of the analysis of the current state of the art and of the recommendations of the WG for future research along each of the four Grand Challenges in the context of urban climate and weather resiliency; Modeling, Observations, Cyber-Informatics, and Knowledge Transfer & Applications.

A set of ten downscaling simulations at high spatial resolution (3 km horizontally) were performed using the Weather Research and Forecasting (WRF) model to generate future climate projections of annual and seasonal temperature and precipitation changes over the Eastern Mediterranean (with a focus on Lebanon). The model was driven with the High Resolution Atmospheric Model (HiRAM), running over the whole globe at a resolution of 25 km, under the conditions of two Representative Concentration Pathways (RCP) (4.5 and 8.5). Each downscaling simulation spanned one year. Two past years (2003 and 2008), also forced by HiRAM without data assimilation, were simulated to evaluate the model’s ability to capture the cold and wet (2003) and hot and dry (2008) extremes. The downscaled data were in the range of recent observed climatic variability, and therefore corrected for the cold bias of HiRAM. Eight future years were then selected based on an anomaly score that relies on the mean annual temperature and accumulated precipitation to identify the worst year per decade from a water resources perspective. One hot and dry year per decade, from 2011 to 2050, and per scenario was simulated and compared to the historic 2008 reference. The results indicate that hot and dry future extreme years will be exacerbated and the study area might be exposed to a significant decrease in annual precipitation (rain and snow), reaching up to 30% relative to the current extreme conditions.

The recent International Panel on Climate Change report predicts the highly urbanized Northeastern U.S. to be at high risk to heat waves. Since urban residents and infrastructure are known to be highly vulnerable to extreme heat, the goal of this paper is to understand the interaction between the synoptic-scale heat wave and the city-scale urban heat island (UHI) effects. The study also qualitatively analyzes the primary factors that contribute to UHIs by comparing their intensities in different cities with distinct geo-physical characteristics. Our results, generated by using the Weather Research and Forecasting model augmented with advanced urban surface parameterizations, confirm that the amplitude of UHI is related to the physical size of the city. However, the results suggest that cities of comparabale sizes might interact differently with heat waves: in New York City; Washington, DC; and Baltimore (but not in Philadelphia) the regular UHI was amplified more strongly during heat waves compared to smaller cities. The results also establish that the pattern of UHI in different cities, its variability, and its interaction with heat waves are inherently linked to dynamic factors.

Both observational and numerical studies of the convective boundary layer (CBL) have demonstrated that when surface heat fluxes are small and mean wind shear is strong, convective updrafts tend to organize into horizontal rolls aligned within 10–20 $$^\circ $$ of the geostrophic wind direction. However, under large surface heat fluxes and weak to negligible shear, convection tends to organize into open cells, similar to turbulent Rayleigh-Benard convection. Using a suite of 14 large-eddy simulations (LES) spanning a range of $$-z_i/L$$ between zero (neutral) and 1041 (highly convective), where $$z_i$$ is the CBL depth and L is the Obukhov length, the transition between roll- and cellular-type convection is investigated systematically for the first time using LES. Mean vertical profiles including velocity variances and turbulent transport efficiencies, as well the “roll factor,” which characterizes the rotational symmetry of the vertical velocity field, indicate the transition occurs gradually over a range of $$-z_i/L$$ ; however, the most significant changes in vertical profiles and CBL organization occur from near-neutral conditions up to about $$-z_i/L \approx $$ 15–20. Turbulent transport efficiencies and quadrant analysis are used to characterize the turbulent transport of momentum and heat with increasing $$-z_i/L$$ . It is found that turbulence transports heat efficiently from weakly to highly convective conditions; however, turbulent momentum transport becomes increasingly inefficient as $$-z_i/L$$ increases.

The regional water cycle is examined with a special focus on water vapor transport in Iowa during the Iowa Flood Studies (IFloodS) campaign period, April–June 2013. The period had exceptionally large rainfall accumulations, and rainfall was distributed over an unusually large number of storm days. Radar-derived rainfall fields covering the 200 000 km2 study region; precipitable water from a network of global positioning system (GPS) measurements; and vertically integrated water vapor flux derived from GPS precipitable water, radar velocity–azimuth display (VAD) wind profiles, and radiosonde humidity profiles are utilized. They show that heavy rainfall is relatively weakly correlated with precipitable water and precipitable water change, with somewhat stronger direct relationships to water vapor flux. Thermodynamic properties tied to the vertical distribution of water vapor play an important role in determining heavy rainfall distribution, especially for periods of strong southerly water vapor flux. The diurnal variation of the water cycle during the IFloodS field campaign is pronounced, especially for rainfall and water vapor flux. To examine the potential effects of relative humidity in the lower atmosphere on heavy rainfall, numerical simulations are performed. It is found that low-level moisture can greatly affect heavy rainfall amount under favorable large-scale environmental conditions.

Low-level convergence induced by land surface heterogeneities can have substantial influence on atmospheric convection and rainfall. Analyses of heavy convective rainfall in the Baltimore–Washington metropolitan area are performed using the Weather Research and Forecasting (WRF) Model, coupled with the Princeton Urban Canopy Model (PUCM) that resolves urban subfacet heterogeneity. Analyses center on storms that produced heavy rainfall and record urban flooding in Baltimore on 1 June 2012. The control simulation using PUCM shows a better performance in reproducing the surface energy balance and rainfall than the simulation using a traditional slab model for the urban area. Sensitivity experiments are carried out to identify the role of the land surface heterogeneities, arising from land–water and urban–nonurban contrasts in the Baltimore–Washington metropolitan area, on heavy rainfall from organized thunderstorm systems. The intersection of low-level convergence zones from thunderstorm downdrafts and from the bay breeze from the Chesapeake Bay enhances the upward motion of preexisting convective storms. The larger sensible heating from the urban area modifies the low-level temperature and wind fields, which in turn modifies the bay breeze. The enhanced moisture supply in the deepened bay-breeze inflow layer due to urban heating promotes intense convection and heavy rainfall in conjunction with the enhanced upward motion at intersecting convergence zones. This study suggests that better representations of surface heat and moisture fluxes in urban areas along major water bodies are required to better capture the timing and location of severe thunderstorms and heavy rainfall.

A single-layer urban canopy model that captures sub-facet heterogeneity and various hydrological processes is further developed to explicitly incorporate trees within the urban canyon. The physical processes associated with trees are shortwave/longwave radiation exchange, including mutual interception and shading by trees and buildings and multiple reflections, sensible heat and latent heat (through transpiration) exchange, and root water uptake. A computationally-efficient geometric approach is applied to the radiation exchanges, requiring a priori knowledge of view factors. These view factors are first obtained from independent Monte Carlo ray-tracing simulations, and subsequently simple relations, which are functions of canyon aspect ratio and tree-crown ratio, are proposed to estimate them. The developed model is evaluated against field observations at two urban sites and one suburban site, showing improved performance for latent heat flux compared to the previous version that only includes ground vegetation. The trees in the urban canopy act to considerably decrease sensible heat flux and increase latent heat flux, and these effects are found to be more significant in the more dense urban site. Sensitivity tests are then performed to examine the effects of tree geometry relative to canyon geometry. The results indicate that the tree-crown size relative to canyon width is the most influential parameter to decrease sensible heat flux and increase latent heat flux, resulting in cooling of the urban area.

Heatwave intensity and frequency are predicted to increase in the coming years, and this will bear adverse consequences to the environmental well-being and the socio-economic fabric in urbanized areas. The hazardous combination of increased heat storage and reduced water retention capacities of the land surface make the urban areas warmer than the surrounding rural areas in what is commonly known as the urban heat island (UHI) effect. The primary motives of this study are to quantify the interaction of this city-scale UHI with synoptic-scale heatwave episodes and to analyze the factors that mediate this interaction. A modified version of the Weather Research and Forecasting model (WRF) is utilized to simulate two heatwave episodes in New York City. The land surface scheme in the default WRF model is modified to better represent the surface to atmosphere exchanges over urban areas. Our results indicate that during the heatwave episodes, the daily-averaged UHI in NYC increased by 1.5 K. Furthermore, most of this amplification occurs in the mid-afternoon period when the temperatures peak. Wind direction and urban-rural contrasts in available energy and moisture availability are found to have significant and systematic effects on the UHI, but wind speed plays a secondary role.

The Ekman boundary layer (EBL) is a central problem in geophysical fluid dynamics that emerges when the pressure gradient force, the Coriolis force, and the frictional force interact in a flow. The unsteady version of the problem, which occurs when these forces are not in equilibrium, is solvable analytically only for a limited set of forcing variability regimes, and the resulting solutions are intricate and not always easy to interpret. In this paper, large-eddy simulations (LESs) of neutral atmospheric EBLs are conducted under various unsteady forcings to reveal the range of physical characteristics of the flow. Subsequently, it is demonstrated that the dynamics of the unsteady EBL can be reduced to a second-order ordinary differential equation that is very similar to the dynamical equation of a damped oscillator, such as a mass–spring–damper system. The validation of the proposed reduced model is performed by comparing its analytical solutions to LES results, revealing very good agreement. The reduced model can be solved for a wide range of variable forcing conditions, and this feature is exploited in the paper to elucidate the physical origin of the inertia (mass), energy storage (spring), and energy dissipation (damper) attributes of Ekman flows.

The turbulent energy spectra and cospectra of momentum and sensible heat fluxes are examined theoretically and experimentally with increasing flux Richardson number (Rf) inthestableatmosphericsurfacelayer.Acospectralbudgetmodel,previouslyusedtoexplain the bulk relation between the turbulent Prandtl number (Prt) and the gradient Richardson number (Ri) as well as the relation between Rf and Ri, is employed to interpret field measure- ments over a lake and a glacier. The shapes of the vertical velocity and temperature spectra, needed for closing the cospectral budget model, are first examined with increasing Rf .I n addition, the wavenumber-dependent relaxation time scales for momentum and heat fluxes are inferred from the cospectral budgets and investigated. Using experimental data and pro- posedextensionstothecospectralbudgetmodel,theexistenceofa'−1'power-lawscalingin the temperature spectra but its absence from the vertical velocity spectra is shown to reduce the magnitude of the maximum flux Richardson number (Rfm), which is commonly inferred from the Rf-Ri relation when Ri becomes very large (idealized with Ri →∞ ). Moreover, dissimilarity in relaxation time scales between momentum and heat fluxes, also affected by the existence of the '−1' power-law scaling in the temperature spectra, leads to Prt � 1 under near-neutral conditions. It is further shown that the production rate of turbulent kinetic energy decreases more rapidly than that of turbulent potential energy as Rf → Rfm ,w hich explains the observed disappearance of the inertial subrange in the vertical velocity spectra at a smaller Rf as compared to its counterpart in the temperature spectra. These results further demonstrate novel linkages between the scale-wise turbulent kinetic energy and potential energy distributions and macroscopic relations such as stability correction functions to the mean flow and the Prt-Ri relation.

The seasonal and diurnal climatologies of precipitable water and water vapor flux in the mid-Atlantic region of the United States are examined. A new method of computing water vapor flux at high temporal resolution in an atmospheric column using global positioning system (GPS) precipitable water, radiosonde data, and velocity–azimuth display (VAD) wind profiles is presented. It is shown that water vapor flux exhibits striking seasonal and diurnal cycles and that the diurnal cycles exhibit rapid transitions over the course of the year. A particularly large change in the diurnal cycle of meridional water vapor flux between spring and summer seasons is found. These features of the water cycle cannot be resolved by twice-a-day radiosonde observations. It is also shown that precipitable water exhibits a pronounced seasonal cycle and a less pronounced diurnal cycle. There are large contrasts in the climatology of water vapor flux between precipitation and nonprecipitation conditions in the mid-Atlantic region. It is hypothesized that the seasonal transition of large-scale flow environments and the change in the degree of differential heating in the mountainous and coastal areas are responsible for the contrasting diurnal cycle between spring and summer seasons.

The atmospheric transport and ground deposition of radioactive isotopes 131I and 137Cs during and after the Fukushima Dai-ichi Nuclear Power Plant (FDNPP) accident (March 2011) are investigated using the Weather Research and Forecasting-Chemistry (WRF-Chem) model. The aim is to assess the skill of WRF in simulating these processes and the sensitivity of the model's performance to various parameterizations of unresolved physics. The WRF-Chem model is first upgraded by implementing a radioactive decay term into the advection–diffusion solver and adding three parameterizations for dry deposition and two parameterizations for wet deposition. Different microphysics and horizontal turbulent diffusion schemes are then tested for their ability to reproduce observed meteorological conditions. Subsequently, the influence of emission characteristics (including the emission rate, the gas partitioning of 131I and the size distribution of 137Cs) on the simulated transport and deposition is examined. The results show that the model can predict the wind fields and rainfall realistically and that the ground deposition of the radionuclides can also be captured reasonably well. The modeled precipitation is largely influenced by the microphysics schemes, while the influence of the horizontal diffusion schemes on the wind fields is subtle. However, the ground deposition of radionuclides is sensitive to both horizontal diffusion schemes and microphysical schemes. Wet deposition dominated over dry deposition at most of the observation stations, but not at all locations in the simulated domain. To assess the sensitivity of the total daily deposition to all of the model physics and inputs, the averaged absolute value of the difference (AAD) is proposed. Based on AAD, the total deposition is mainly influenced by the emission rate for both 131I and 137Cs; while it is not sensitive to the dry deposition parameterizations since the dry deposition is just a minor fraction of the total deposition. Moreover, for 131I, the deposition is moderately sensitive (AAD between 10 and 40% between different runs) to the microphysics schemes, the horizontal diffusion schemes, gas-partitioning and wet deposition parameterizations. For 137Cs, the deposition is very sensitive (AAD exceeding 40% between different runs) to the microphysics schemes and wet deposition parameterizations, but moderately sensitive to the horizontal diffusion schemes and the size distribution.

Urban facets—the walls, roofs, and ground in built-up terrain—are often conceptualized as homogeneous surfaces, despite the obvious variability in the composition and material properties of the urban fabric at the subfacet scale. This study focuses on understanding the influence of this subfacet heterogeneity, and the associated influence of different material properties, on the urban surface energy budget. The Princeton Urban Canopy Model, which was developed with the ability to capture subfacet variability, is evaluated at sites of various building densities and then applied to simulate the energy exchanges of each subfacet with the atmosphere over a densely built site. The analyses show that, although all impervious built surfaces convert most of the incoming energy into sensible heat rather than latent heat, sensible heat fluxes from asphalt pavements and dark rooftops are 2 times as high as those from concrete surfaces and light-colored roofs. Another important characteristic of urban areas—the shift in the peak time of sensible heat flux in comparison with rural areas—is here shown to be mainly linked to concrete’s high heat storage capacity as well as to radiative trapping in the urban canyon. The results also illustrate that the vegetated pervious soil surfaces that dot the urban landscape play a dual role: during wet periods they redistribute much of the available energy into evaporative fluxes but when moisture stressed they behave more like an impervious surface. This role reversal, along with the direct evaporation of water stored over impervious surfaces, significantly reduces the overall Bowen ratio of the urban site after rain events.

Large-eddy simulations of the atmospheric boundary layer (ABL) under a wide range of stabilities are conducted to educe very-large-scale motions and then to study their dynamics and how they are influenced by buoyancy. Preliminary flow visualizations suggest that smaller-scale motions that resemble hairpins are embedded in much larger scale streamwise meandering rolls. Using simulations that represent more than 150 h of physical time, many snapshots in the $$xy$$ -, $$yz$$ - and $$xz$$ -planes are then collected to perform snapshot proper orthogonal decomposition and further investigate the large structures. These analyses confirm that large streamwise rolls that share several features with the very-large-scale motions observed in laboratory studies arise as the dominant modes under most stabilities, but the effect of the surface kinematic buoyancy flux on the energy content of these dominant modes is very significant. The first two modes in the $$yz$$ -plane in the neutral case contain up to 3 % of the total turbulent kinetic energy; they also have a vertical tilt angle in the $$yz$$ -plane of about 0 to 30 $$^\circ $$ due to the turning effect associated with the Coriolis force. Unstable cases also feature streamwise rolls, but in the convective ABL they are strengthened by rising plumes in between them, with two to four rolls spanning the whole domain in the first few modes; the Coriolis effect is much weaker in the unstable ABL. These rolls are no longer the dominant modes under stable conditions where the first mode is observed to contain sheet-like motions with high turbulent kinetic energy. Using these proper orthogonal decomposition modes, we are also able to extract the vertical velocity fields corresponding to individual modes and then to correlate them with the horizontal velocity or temperature fields to obtain the momentum and heat flux carried by individual modes. Structurally, the fluxes are explained by the topology of their corresponding modes. However, the fraction of the fluxes produced by the modes is invariably smaller than the fraction of energy they contain, particularly under stable conditions where the first modes are found to perform weak counter-gradient fluxes.

In this study, observational and numerical modeling analyses based on the Weather Research and Forecasting Model (WRF) are used to investigate the impact of urbanization on heavy rainfall over the Milwaukee–Lake Michigan region. The authors examine urban modification of rainfall for a storm system with continental-scale moisture transport, strong large-scale forcing, and extreme rainfall over a large area of the upper Midwest of the United States. WRF simulations were carried out to examine the sensitivity of the rainfall distribution in and around the urban area to different urban land surface model representations and urban land-use scenarios. Simulation results suggest that urbanization plays an important role in precipitation distribution, even in settings characterized by strong large-scale forcing. For the Milwaukee–Lake Michigan region, the thermodynamic perturbations produced by urbanization on the temperature and surface pressure fields enhance the intrusion of the lake breeze and facilitate the formation of a convergence zone, which create favorable conditions for deep convection over the city. Analyses of model and observed vertical profiles of reflectivity using contoured frequency by altitude displays (CFADs) suggest that cloud dynamics over the city do not change significantly with urbanization. Simulation results also suggest that the large-scale rainfall pattern is not sensitive to different urban representations in the model. Both urban representations, the Noah land surface model with urban land categories and the single-layer urban canopy model, adequately capture the dominant features of this storm over the urban region.

Numerical weather and climate prediction systems necessitate accurate land surface–atmosphere fluxes, whose determination typically replies on a suite of parameterization schemes. The authors present a field investigation over tall grass in a Beijing suburb, where the aerodynamic roughness length (z0) and zero-plane displacement height (d) are found to be 0.02 and 0.44 m, respectively (the value of d is close to two-thirds the average grass height during this field experiment). Both z0 and d values are then used as input parameters of an analytic model of flux footprint; the footprint model reveals that eddy-covariance flux measurements are mainly representative of the tall grass surface concerned herein, potential influences from anthropogenic sources in this suburban area notwithstanding. Based on the “fair weather” data (with an energy balance ratio of 0.89), the authors evaluate four parameterizations of turbulent surface fluxes, namely, a total of three traditional “iterative” schemes and one “noniterative” scheme developed recently to reduce computational time. Their performances are intercompared in terms of the estimations of the sensible heat flux and two turbulence components (the friction velocity and temperature scale). In weakly stable to unstable conditions, two schemes are recommended here for their good performance overall; the first scheme stems jointly from the work of Högström and Beljaars and Holtslag, and the second stems from that of Li et al.. For this tall grass surface, the choice of z0/z0h = 100 (z0h is the thermal roughness length) is more appropriate than another choice of 10, because the former produces comparatively accurate sensible heat flux estimations.

Cities are well known to be hotter than the rural areas that surround them; this phenomenon is called the urban heat island. Heat waves are excessively hot periods during which the air temperatures of both urban and rural areas increase significantly. However, whether urban and rural temperatures respond in the same way to heat waves remains a critical unanswered question. In this study, a combination of observational and modeling analyses indicates synergies between urban heat islands and heat waves. That is, not only do heat waves increase the ambient temperatures, but they also intensify the difference between urban and rural temperatures. As a result, the added heat stress in cities will be even higher than the sum of the background urban heat island effect and the heat wave effect. Results presented here also attribute this added impact of heat waves on urban areas to the lack of surface moisture in urban areas and the low wind speed associated with heat waves. Given that heat waves are projected to become more frequent and that urban populations are substantially increasing, these findings underline the serious heat-related health risks facing urban residents in the twenty-first century. Adaptation and mitigation strategies will require joint efforts to reinvent the city, allowing for more green spaces and lesser disruption of the natural water cycle.

High-resolution simulations with the Weather Research and Forecasting Model (WRF) are used in conjunction with observational analyses to investigate land surface processes and heavy rainfall over the Baltimore–Washington metropolitan area. Analyses focus on a 6-day period, 21–26 July 2008, which includes a major convective rain event (23–24 July), a prestorm period (21–22 July), and a dry-down period (25–26 July). The performance of WRF in capturing land–atmosphere interactions, the bulk structure of the atmospheric boundary layer, and the rainfall pattern in urban environments is explored. Results indicate that WRF captures the incoming radiative fluxes and surface meteorological conditions. Mean profiles of potential temperature and humidity in the atmosphere are also relatively well reproduced, both preceding and following the heavy rainfall period. However, wind features in the lower atmosphere, including low-level jets, are not accurately reproduced by WRF. The biases in the wind fields play a central role in determining errors in WRF-simulated rainfall fields. The study also investigates the sensitivity of WRF simulations to different urban surface representations. It is found that urban surface representations have a significant impact on the surface energy balance and the rainfall distribution. As the impervious fraction increases, the sensible heat flux and the ground heat flux increase, while the latent heat flux decreases. The impact of urban surface representations on precipitation is as significant as that of microphysical parameterizations. The fact that changing urban surface representations can significantly alter the rainfall field suggests that urbanization plays an important role in modifying the regional precipitation pattern.

This is the second part of a study about turbulence and vertical fluxes in the stable atmospheric boundary layer. Based on a suite of large-eddy simulations in Part I where the effects of stability on the turbulent structures and kinetic energy are investigated, first-order parameterization schemes are assessed and tested in the Geophysical Fluid Dynamics Laboratory (GFDL)’s single-column model. The applicability of the gradient-flux hypothesis is first examined and it is found that stable conditions are favorable for that hypothesis. However, the concept of introducing a stability correction function fm as a multiplicative factor into the mixing length used under neutral conditions lN is shown to be problematic because fm computed a priori from large-eddy simulations tends not to be a universal function of stability. With this observation, a novel mixing-length model is proposed, which conforms to large-eddy simulation results much better under stable conditions and converges to the classic model under neutral conditions. Test cases imposing steady as well as unsteady forcings are developed to evaluate the performance of the new model. It is found that the new model exhibits robust performance as the stability strength is changed, while other models are sensitive to changes in stability. For cases with unsteady forcings, which are very rarely simulated or tested, the results of the single-column model and large-eddy simulations are also closer when the new model is used, compared to the other models. However, unsteady cases are much more challenging for the turbulence closure formulations than cases with steady surface forcing.

This study seeks to quantitatively and qualitatively understand how stability affects transport in the continuously turbulent stably stratified atmospheric boundary layer, based on a suite of large-eddy simulations. The test cases are based on the one adopted by the Global Energy and Water Cycle Experiment (GEWEX) Atmospheric Boundary Layer Study (GABLS) project, but with a largely expanded stability range where the gradient Richardson number (Rig) reaches up to around 1. The analysis is mainly focused on understanding the modification of turbulent structures and dynamics with increasing stability in order to improve the modeling of the stable atmospheric boundary layer in weather and climate models, a topic addressed in Part II of this work. It is found that at quasi equilibrium, an increase in stability results in stronger vertical gradients of the mean temperature, a lowered low-level jet, a decrease in vertical momentum transport, an increase in vertical buoyancy flux, and a shallower boundary layer. Analysis of coherent turbulent structures using two-point autocorrelation reveals that the autocorrelation of the streamwise velocity is horizontally anisotropic while the autocorrelation of the vertical velocity is relatively isotropic in the horizontal plane and its integral length scale decreases as stability increases. The effects of stability on the overall turbulent kinetic energy (TKE) and its budget terms are also investigated, and it is shown that the authors' large-eddy simulation results are in good agreement with previous experimental findings across varied stabilities. Finally, Nieuwstadt's local-scaling theory is reexamined and it is concluded that the height z is not a relevant scaling parameter and should be replaced by a constant length scale away from the surface, indicating that the z-less range starts lower than previously assumed.

The Weather Research and Forecasting Model permits finescale large-eddy simulations (LES) to be nested within coarser simulations, an approach that can generate more accurate turbulence statistics and improve other aspects of simulated flows. However, errors are introduced into the finer domain from the nesting methodology. Comparing nested domain, flat-terrain simulations of the neutral atmospheric boundary layer with single-domain simulations using the same mesh, but instead using periodic lateral boundary conditions, reveals the errors contributed to the nested solution from the parent domain and nest interfaces. Comparison of velocity spectra shows good agreement among higher frequencies, but greater power predicted on the nested domain at lower frequencies. Profiles of mean wind speed show significant near-surface deficits near the inflow boundaries, but equilibrate to improved values with distance. Profiles of the vertical flux of x momentum show significant underprediction by the nested domain close to the surface and near the inlet boundaries. While these underpredictions of the stresses, which cause the near-surface velocity deficits, attenuate with distance within the nested domains, significant errors remain throughout. Profiles of the resolved turbulence kinetic energy show considerable deviations from their single-domain values throughout the nested domains. The authors examine the accuracy of these parameters and their sensitivities to the turbulence subfilter stress model, mesh resolution, and grid aspect ratio, and provide guidance to practitioners of nested LES.

We propose a new surface exchange scheme coupling the transport of energy and water in urban canopies. The new model resolves the subfacet heterogeneity of urban surfaces, which is particularly useful for capturing surface exchange processes from vegetated urban surfaces, such as lawns or green roofs. We develop detailed urban hydrological models for surfaces consisting of either natural (soil and vegetation) or engineered materials with water-holding capacity. The coupling of energy and water transport enables us to parametrize surface evaporation from different urban facets including soils, vegetation and water-holding engineered surfaces. The new coupled model is evaluated using field measurement data obtained through a wireless sensor network deployed over the Princeton University campus. Comparison of model prediction and measured results shows that the proposed surface exchange scheme is able to predict widely varying surface temperatures for each subfacet with good accuracy. Different weather conditions and seasonal variability are found to have insignificant effect on the model performance. The new model is also able to capture the subsurface hydrological processes with reasonable accuracy, particularly for urban lawns. The proposed model is then applied to assess different mitigation strategies of the urban heat island effect.

This paper assesses the performance of the Weather Research and Forecasting Model (WRF) as a tool for multiscale atmospheric simulations. Tests are performed in real and idealized cases with multiple configurations and with resolutions ranging from the mesoscale (gridcell size ~10 km) for the real cases to local scales (gridcell size ~50 m) for both real and idealized cases. All idealized simulations and the finest real-case simulations use the turbulence-resolving large-eddy simulation mode of WRF (WRF-LES). Tests in neutral conditions and with idealized forcing are first performed to assess the model’s sensitivity to grid resolutions and subgrid-scale parameterizations and to optimize the setup of the real cases. An increase in horizontal model resolution is found to be more beneficial than an increase in vertical resolution. WRF-LES is then tested, using extensive observational data, in real-world cases over complex terrain through nested simulations in which the mesoscale domains drive the LES domains. Analysis of the mesoscale simulations indicates that the data needed to force the largest simulated domain and to initialize surface parameters have the strongest influence on the results. Similarly, LES model fields are primarily influenced by their mesoscale meteorological forcing. As a result, the nesting of LES models down to a 50-m resolution does not improve all aspects of hydrometeorological predictions. Advantages of using fine-resolution LES are noted at nighttime (under stable conditions) and over heterogeneous surfaces when local properties are required or when resolving small-scale surface features is desirable.

Most conventional numerical schemes for soil ground heat flux estimation rely on the knowledge of the temporal evolution of soil temperature. Here we propose and test a novel scheme, which requires no information on soil temperatures to supplement the flux plate measurement. The proposed method is based on the fundamental solution of the one-dimensional heat equation and Duhamel's principle for the incorporation of inhomogeneous boundary conditions. Being completely independent of the soil temperature, the new scheme therefore avoids a potential source of error in measurements and in heat storage calculation. The only thermal property involved in the new scheme is the thermal diffusivity of the soil, which is a weak function of soil water content and can be approximated as constant with reasonable accuracy. For validation, the proposed method is compared to the conventional approach using a canonical one-dimensional heat conduction problem, as well as real field measurements. Results of the comparison highlight that the new model is robust and capable of preserving the good accuracy of the conventional approach with reduced input information. In addition, the effect of inclusion of the heat storage term in the ground heat flux is evaluated in the context of surface energy balance closure for field measurements.

The performance of a range of simple to moderately-complex subfilter-scale (SFS) stress models implemented in the Weather Research and Forecasting (WRF) model is evaluated in large-eddy simulations of neutral atmospheric boundary layer flow over both a flat terrain and a two-dimensional symmetrical transverse ridge. Two recently developed dynamic SFS stress models, the Lagrangian-averaged scale-dependent (LASD) dynamic model and the dynamic reconstruction model (DRM), are compared with the WRF model’s existing constant-coefficient linear eddy-viscosity and (as of version 3.2) nonlinear SFS stress models to evaluate the benefits of more sophisticated and accurate, but also more computationally expensive approaches. Simulation results using the different SFS stress models are compared among each other, as well as against the Monin–Obukhov similarity theory. For the flat terrain case, vertical profiles of mean wind speed from the newly implemented dynamic models show the best agreement with the similarity solution, improving even upon the nonlinear model, which likewise yields a significant improvement compared to the Smagorinsky model. The more sophisticated SFS stress models more successfully predict the expected production and inertial range scaling of power spectra, especially near the surface, with the dynamic models achieving the best scaling overall. For the transverse ridge case, the nonlinear model predicts the greatest amount of reverse flow in the lee of the ridge, and also demonstrates the greatest ability to duplicate qualitative features of the highest-resolution simulations at coarser resolutions. The dynamic models’ flow distributions in the lee of the ridge did not differ significantly from the constant-coefficient Smagorinsky model.

Monin–Obukhov similarity functions for the structure parameters of temperature and humidity are needed to derive surface heat and water vapour fluxes from scintillometer measurements and it is often assumed that the two functions are identical in the atmospheric surface layer. Nevertheless, this assumption has not yet been verified experimentally. This study investigates the dissimilarity between the turbulent transport of sensible heat and water vapour, with a specific focus on the difference between the Monin–Obukhov similarity functions for the structure parameters. Using two datasets collected over homogeneous surfaces where the surface sources of sensible heat and water vapour are well correlated, we observe that under stable and very unstable conditions, the two functions are similar. This similarity however breaks down under weakly unstable conditions; in that regime, the absolute values of the correlations between temperature and humidity are also observed to be low, most likely due to large-scale eddies that transport unsteadiness, advection or entrainment effects from the outer layer. We analyze and demonstrate how this reduction in the correlation leads to dissimilarity between the turbulent transport of these two scalars and the corresponding Monin–Obukhov similarity functions for their structure parameters. A model to derive sensible and latent heat fluxes from structure parameters without measuring the friction velocity is tested and found to work very well under moderately to strongly unstable conditions (−z/L > 0.5). Finally, we discuss the modelling of the cross-structure parameter over wet surfaces, which is crucial for correcting water vapour effects on optical scintillometer measurements and also for obtaining surface sensible and latent heat fluxes from the two-wavelength scintillometry.

Single-layer physically based urban canopy models (UCM) have gained popularity for modeling urban–atmosphere interactions, especially the energy transport component. For a UCM to capture the physics of conductive, radiative, and turbulent advective transport of energy, it is important to provide it with an accurate parameter space, including both mesoscale meteorological forcing and microscale surface inputs. While field measurement of all input parameters to a UCM is rarely possible, understanding the model sensitivity to individual parameters is essential to determine the relative importance of parameter uncertainty for model performance. In this paper, an advanced Monte Carlo approach—namely, subset simulation—is used to quantify the impact of the uncertainty of surface input parameters on the output of an offline modified version of the Weather Research and Forecasting (WRF)-UCM. On the basis of the conditional sampling technique, the importance of surface parameters is determined in terms of their impact on critical model responses. It is found that model outputs (both critical energy fluxes and surface temperatures) are highly sensitive to uncertainties in urban geometry, whereas variations in emissivities and building interior temperatures are relatively insignificant. In addition, the sensitivity of the model to input surface parameters is also shown to be very weakly dependent on meteorological parameters. The statistical quantification of the model’s sensitivity to input parameters has practical implications, such as surface parameter calibrations in UCM and guidance for urban heat island mitigation strategies.

Atmospheric stability effects on the dissimilarity between the turbulent transport of momentum and scalars (water vapour and temperature) are investigated in the neutral and unstable atmospheric surface layers over a lake and a vineyard. A decorrelation of the momentum and scalar fluxes is observed with increasing instability. Moreover, different measures of transport efficiency (correlation coefficients, efficiencies based on quadrant analysis and bulk transfer coefficients) indicate that, under close to neutral conditions, momentum and scalars are transported similarly whereas, as the instability of the atmosphere increases, scalars are transported increasingly more efficiently than momentum. This dissimilarity between the turbulent transport of momentum and scalars under unstable conditions concurs with, and is likely caused by, a change in the topology of turbulent coherent structures. Previous laboratory and field studies report that under neutral conditions hairpin vortices and hairpin packets are present and dominate the vertical fluxes, while under free-convection conditions thermal plumes are expected. Our results (cross-stream vorticity variation, quadrant analysis and time series analysis) are in very good agreement with this picture and confirm a change in the structure of the coherent turbulent motions under increasing instability, although the exact structure of these motions and how they are modified by stability requires further investigation based on three-dimensional flow data.

In the urban environment, surface temperatures and conductive heat fluxes through solid media (roofs, walls, roads and vegetated surfaces) are of paramount importance for the comfort of residents (indoors) and for microclimatic conditions (outdoors). Fully discrete numerical methods are currently used to model heat transfer in these solid media in parametrisations of built surfaces commonly used in weather prediction models. These discrete methods usually use finite difference schemes in both space and time. We propose a spatially-analytical scheme where the temperature field and conductive heat fluxes are solved analytically in space. Spurious numerical oscillations due to temperature discontinuities at the sublayer interfaces can be avoided since the method does not involve spatial discretisation. The proposed method is compared to the fully discrete method for a test case of one-dimensional heat conduction with sinusoidal forcing. Subsequently, the analytical scheme is incorporated into the offline version of the current urban canopy model (UCM) used in the Weather Research and Forecasting model and the new UCM is validated against field measurements using a wireless sensor network and other supporting measurements over a suburban area under real-world conditions. Results of the comparison clearly show the advantage of the proposed scheme over the fully discrete model, particularly for more complicated cases.

We perform large-eddy simulations of neutral atmospheric boundary-layer flow over a cluster of buildings surrounded by relatively flat terrain. The first investigated question is the effect of the level of building detail that can be included in the numerical model, a topic not yet addressed by any previous study. The simplest representation is found to give similar results to more refined representations for the mean flow, but not for turbulence. The wind direction on the other hand is found to be important for both mean and turbulent parameters. As many suburban areas are characterised by the clustering of buildings and homes into small areas separated by surfaces of lower roughness, we look at the adjustment of the atmospheric surface layer as it flows from the smoother terrain to the built-up area. This transition has unexpected impacts on the flow; mainly, a zone of global backscatter (energy transfer from the turbulent eddies to the mean flow) is found at the upstream edge of the built-up area.

We examine the dynamics of turbulence subgrid (or sub-filter) scales over a lake surface and the implications for large-eddy simulations (LES) of the atmospheric boundary layer. The analysis is based on measurements obtained during the Lake-Atmosphere Turbulent EXchange (LATEX) field campaign (August–October, 2006) over Lake Geneva, Switzerland. Wind velocity, temperature and humidity profiles were measured at 20 Hz using a vertical array of four sonic anemometers and open-path gas analyzers. The results indicate that the observed subgrid-scale statistics are very similar to those observed over land surfaces, suggesting that the effect of the lake waves on surface-layer turbulence during LATEX is small. The measurements allowed, for the first time, the study of subgrid-scale turbulent transport of water vapour, which is found to be well correlated with the transport of heat, suggesting that the subgrid-scale modelling of the two scalars may be coupled to save computational resources during LES.