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Monin–Obukhov similarity theory is used in large-eddy simulation (LES) models as a surface boundary condition to predict the surface shear stress and scalar fluxes based on the gradients between the surface and the first grid level above the surface. We outline deficiencies of this methodology, such as the systematical underestimation of the surface shear stress, and propose a modified boundary condition to correct for this issue. The proposed boundary condition is applied to a set of LES for both neutral and stable boundary layers with successively decreasing grid spacing. The results indicate that the proposed boundary condition reliably corrects the surface shear stress and the sensible heat flux, and improves grid convergence of these quantities. The LES data indicate improved grid convergence for the surface shear stress, more so than for the surface heat flux. This is either due to a limited performance of the Monin–Obukhov similarity functions or due to problems in the LES model in representing stable conditions. Furthermore, we find that the correction achieved using the proposed boundary condition does not lead to improved grid convergence of the wind-speed and temperature profiles. From this we conclude that the sensitivity of the wind-speed and temperature profiles in the LES model to the grid spacing is more likely related to under-resolved near-surface gradients and turbulent mixing at the boundary-layer top, to the SGS model formulation, and/or to numerical issues, and not to deficiencies due to the use of improper surface boundary conditions.

In this work, we investigate the effect of areawide building retrofitting on summertime, street-level outdoor temperatures in an urban district in Berlin, Germany. We perform two building-resolving, weeklong large-eddy simulations: one with nonretrofitted buildings and the other with retrofitted buildings in the entire domain to meet today’s energy efficiency standards. The comparison of the two simulations reveals that the mean outdoor temperatures are higher with retrofitted buildings during daytime conditions. This behavior is caused by the much smaller inertia of the outermost roof/wall layer in the retrofitting case, which is thermally decoupled from the inner roof/wall layers by an insulation layer. As a result, the outermost layer heats up more rigorously during the daytime, leading to increased sensible heat fluxes into the atmosphere. During the nighttime, the outermost layer’s temperature drops down faster, resulting in cooling of the atmosphere. However, as the simulation progresses, the cooling effect becomes smaller and the warming effect becomes larger. After 1 week, we find the mean temperatures to be 4 K higher during the daytime while the cooling effects become negligible.

In this paper the land surface model embedded in the PALM model system is described and evaluated against in situ measurements at Cabauw, Netherlands. A total of 2 consecutive clear-sky days are simulated, and the components of surface energy balance, potential temperature, humidity, and horizontal wind speed are compared to observations. For the simulated period, components of the energy balance are consistent with daytime and nighttime observations, and the daytime Bowen ratio also agrees fairly well with observations. The model simulates a more stably stratified nocturnal boundary layer than the observations, and near-surface potential temperature and humidity agree fairly well during the day. Moreover, a sensitivity analysis is performed to investigate dependence of the model on land surface and soil specifications, as well as atmospheric initial conditions, because they represent a major source of uncertainty in the simulation setup. It is found that an inaccurate estimation of leaf area index, albedo, or initial humidity causes a significant misrepresentation of the daytime turbulent sensible and latent heat fluxes. During the night, the boundary-layer characteristics are primarily affected by surface roughness and the applied radiation schemes.

Large-eddy simulations (LES) are conducted to study the transport of momentum and passive scalar within and over a real urban canopy in the City of Boston, USA. This urban canopy is characterized by complex building layouts, densities and orientations with high-rise buildings. Special attention is given to the magnitude, variability and structure of dispersive momentum and scalar fluxes and their relative importance to turbulent momentum and scalar fluxes. We first evaluate the LES model by comparing the simulated flow statistics over an urban-like canopy to data reported in previous studies. In simulations over the considered real urban canopy, we observe that the dispersive momentum and scalar fluxes can be important beyond 2–5 times the mean building height, which is a commonly used definition for the urban roughness sublayer height. Above the mean building height where the dispersive fluxes become weakly dependent on the grid spacing, the dispersive momentum flux contributes about 10–15% to the sum of turbulent and dispersive momentum fluxes and does not decrease monotonically with increasing height. The dispersive momentum and scalar fluxes are sensitive to the time and spatial averaging. We further find that the constituents of dispersive fluxes are spatially heterogeneous and enhanced by the presence of high-rise buildings. This work suggests the need to parameterize both turbulent and dispersive fluxes over real urban canopies in mesoscale and large-scale models.

We revisit the longstanding problem of grid sensitivity, i.e., the lack of grid convergence in large-eddy simulations (LES) of the stable boundary layer. We use a comprehensive set of LES of the well-known Global Energy and Water Cycle Experiment Atmospheric Boundary Layer Study 1 (GABLS1) case with varying grid spacings between 12.5 m and 1 m to investigate several physical processes and numerical features that are possible causes of grid sensitivity. Our results demonstrate that there are two resolution regimes in which grid sensitivity manifests differently. We find that changing the numerical advection schemes and the subgrid-scale models alters the simulation results, but the options tested do not fully address the grid-sensitivity issue. Moreover, sensitivity runs suggest that the surface boundary condition and the interaction of the surface with the near-surface flow, as well as the mixing with the free atmosphere, are unlikely to be the causes of the observed grid sensitivity. One interesting finding is that the grid sensitivity in the fine grid-spacing regime (grid spacings ≤2m) is closely related to the reduction in the energy content of large-scale turbulence, leading to less turbulence kinetic energy and hence lower boundary-layer heights. The present work demonstrates that there is still an urgent need to address this grid-sensitivity issue in order to perform reliable LES of the stable boundary layer.

The development of radiation fog is influenced by multiple physical processes such as radiative cooling and heating, turbulent mixing, and microphysics, which interact on different spatial and temporal scales with one another. Once a fog layer has formed, the number of fog droplets and their size distribution have a particularly large impact on the development of the fog layer due to their feedback on gravitational settling and radiative cooling at the fog top, which are key processes for fog. However, most models do not represent microphysical processes explicitly, or parameterize them rather crudely. In this study we simulate a deep radiation fog case with a coupled large-eddy simulation (LES)–Lagrangian cloud model (LCM) approach for the first time. By simulating several hundred million fog droplets as Lagrangian particles explicitly (using the so-called superdroplet approach), we include a size-resolved diffusional growth including Köhler theory and gravitational sedimentation representation. The results are compared against simulations using a state of the art bulk microphysics model (BCM). We simulate two different aerosol backgrounds (pristine and polluted) with each microphysics scheme. The simulations show that both schemes generally capture the key features of the deep fog event, but also that there are significant differences: the drop size distribution produced by the LCM is broader during the formation and dissipation phase than in the BCM. The LCM simulations suggest that its spectral shape, which is fixed in BCMs, exhibits distinct changes during the fog life cycle, which cannot be taken into account in BCMs. The picture of the overall fog droplet number concentration is twofold: For both aerosol environments, the LCM shows lower concentrations of larger fog droplets, while we observe a higher number of small droplets and swollen aerosols reducing the visibility earlier than in the BCM. As a result of the different model formulation we observe higher sedimentation rates and lower liquid water paths for the LCM. The present work demonstrates that it is possible to simulate fog with the computational demanding approach of LCMs to assess the advantages of high-resolution cloud models and further to estimate errors of traditional parameterizations.

This study analyses the departure of the velocity-variances profiles from their quasi-steady state described by the mixed-layer similarity, using large-eddy simulations with different prescribed shapes and time scales of the surface kinematic heat flux decay. Within the descriptive frames where the time is tracked solely by the forcing time scale (either constant or time-dependent) describing the surface heat flux decay, we find that the normalized velocity-variances profiles from different runs do not collapse while they depart from mixed-layer similarity. As the mixed-layer similarity relies on the assumption that the free-convective boundary layer is in a quasi-equilibrium, we consider the ratios of the forcing time scales to the convective eddy-turnover time scale. We find that the normalized velocity-variances profiles collapse in the only case where the ratio (r~) of the time-dependent forcing time scale to the convective eddy-turnover time scale is used for tracking the time, supporting the independence of the departure from the characteristics of the surface heat flux decay. As a consequence of this result, the knowledge of r~ is sufficient to predict the departure of the velocity variances from their quasi-steady state, irrespective of the shape of the surface heat flux decay. This study highlights the importance of considering both the time-dependent forcing time scale and the convective eddy-turnover time scale for evaluating the response of the free-convective boundary layer to the surface heat flux decay.

We investigate the scaling for decaying turbulence kinetic energy (TKE) in the free-convective boundary layer, from the time the surface heat flux starts decaying, until a few hours after it has vanished. We conduct a set of large-eddy simulation experiments, consider various initial convective situations, and prescribe realistic decays of the surface heat flux over a wide range of time scales. We find that the TKE time evolution is dictated by the decaying magnitude of the surface heat flux up to \\[0.7 \\tau \\] approximately, where \\[\\tau \\] is the prescribed duration from maximum to zero surface heat flux. During the time period starting at zero surface heat flux, we search for potential power-law scaling by examining the log–log presentation of TKE as a function of time. First, we find that the description of the decay highly depends on whether the time origin is defined as the time when the surface heat flux starts decaying (traditional scaling framework), or the time when it vanishes (proposed new scaling framework). Second, when varying \\[\\tau \\], the results plotted in the traditional scaling framework indicate variations in the power-law decay rates over several orders of magnitude. In the new scaling framework, however, we find a unique decay exponent in the order of 1, independent of the initial convective condition, and independent of \\[\\tau \\], giving support for the proposed scaling framework.

In this paper we study the influence of the cloud microphysical parameterization, namely the effect of different methods for calculating the supersaturation and aerosol activation, on the structure and life cycle of radiation fog in large-eddy simulations. For this purpose we investigate a well-documented deep fog case as observed at Cabauw (the Netherlands) using high-resolution large-eddy simulations with a comprehensive bulk cloud microphysics scheme. By comparing saturation adjustment with a diagnostic and a prognostic method for calculating supersaturation (while neglecting the activation process), we find that, even though assumptions for saturation adjustment are violated, the expected overestimation of the liquid water mixing ratio is negligible. By additionally considering activation, however, our results indicate that saturation adjustment, due to approximating the underlying supersaturation, leads to a higher droplet concentration and hence significantly higher liquid water content in the fog layer, while diagnostic and prognostic methods yield comparable results. Furthermore, the effect of different droplet number concentrations is investigated, induced by using different common activation schemes. We find, in line with previous studies, a positive feedback between the droplet number concentration (as a consequence of the applied activation schemes) and strength of the fog layer (defined by its vertical extent and amount of liquid water). Furthermore, we perform an explicit analysis of the budgets of condensation, evaporation, sedimentation and advection in order to assess the height-dependent contribution of the individual processes on the development phases.

The Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer Program (ISOBAR) is a research project investigating stable atmospheric boundary layer (SBL) processes, whose representation still poses significant challenges in state-of-the-art numerical weather prediction (NWP) models. In ISOBAR ground-based flux and profile observations are combined with boundary layer remote sensing methods and the extensive usage of different unmanned aircraft systems (UAS). During February 2017 and 2018 we carried out two major field campaigns over the sea ice of the northern Baltic Sea, close to the Finnish island of Hailuoto at 65°N. In total 14 intensive observational periods (IOPs) resulted in extensive SBL datasets with unprecedented spatiotemporal resolution, which will form the basis for various numerical modeling experiments. First results from the campaigns indicate numerous very stable boundary layer (VSBL) cases, characterized by strong stratification, weak winds, and clear skies, and give detailed insight in the temporal evolution and vertical structure of the entire SBL. The SBL is subject to rapid changes in its vertical structure, responding to a variety of different processes. In particular, we study cases involving a shear instability associated with a low-level jet, a rapid strong cooling event observed a few meters above ground, and a strong wave-breaking event that triggers intensive near-surface turbulence. Furthermore, we use observations from one IOP to validate three different atmospheric models. The unique finescale observations resulting from the ISOBAR observational approach will aid future research activities, focusing on a better understanding of the SBL and its implementation in numerical models.