In this paper, we describe the PALM model system 6.0. PALM (formerly an abbreviation for Parallelized Large-eddy Simulation Model and now an independent name) is a Fortran-based code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. This is a follow-up paper to the PALM 4.0 model description in Maronga et al. (2015). During the last years, PALM has been significantly improved and now offers a variety of new components. In particular, much effort was made to enhance the model with components needed for applications in urban environments, like fully interactive land surface and radiation schemes, chemistry, and an indoor model. This paper serves as an overview paper of the PALM 6.0 model system and we describe its current model core. The individual components for urban applications, case studies, validation runs, and issues with suitable input data are presented and discussed in a series of companion papers in this special issue.

We investigate the impact of observed surface heterogeneities during the LITFASS-2003 experiment on the convective boundary layer (CBL). Large-eddy simulations (LES), driven by observed near-surface sensible and latent heat fluxes, were performed for the diurnal cycle and compare well with observations. As in former studies of idealized one- and two-dimensional heterogeneities, secondary circulations developed that are superimposed on the turbulent field and that partly take over the vertical transport of heat and moisture. The secondary circulation patterns vary between local and roll-like structures, depending on the background wind conditions. For higher background wind speeds, the flow feels an effective surface heat-flux pattern that derives from the original pattern by streamwise averaging. This effective pattern generates a roll-like secondary circulation with roll axes along the mean boundary-layer wind direction. Mainly the upstream surface conditions control the secondary circulation pattern, where the fetch increases with increasing background wind speed. Unlike the entrainment flux that appears to be slightly decreased compared to the homogeneously-heated CBL, the vertical flux of sensible heat appears not to be modified in the mixed layer, while the vertical flux of latent heat shows different responses to secondary circulations. The study illustrates that sufficient time averaging and ensemble averaging is required to separate the heterogeneity-induced signals from the raw LES turbulence data. This might be an important reason why experiments over heterogeneous terrain in the past did not give any clear evidence of heterogeneity-induced effects.

The aim of the research project “Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer (ISOBAR)” is to substantially increase the understanding of the stable atmospheric boundary layer (SBL) through a combination of well-established and innovative observation methods as well as by models of different complexity. During three weeks in February 2017, a first field campaign was carried out over the sea ice of the Bothnian Bay in the vicinity of the Finnish island of Hailuoto. Observations were based on ground-based eddy-covariance (EC), automatic weather stations (AWS) and remote-sensing instrumentation as well as more than 150 flight missions by several different Unmanned Aerial Vehicles (UAVs) during mostly stable and very stable boundary layer conditions. The structure of the atmospheric boundary layer (ABL) and above could be resolved at a very high vertical resolution, especially close to the ground, by combining surface-based measurements with UAV observations, i.e., multicopter and fixed-wing profiles up to 200 m agl and 1800 $\mathrm{m}$ agl, respectively. Repeated multicopter profiles provided detailed information on the evolution of the SBL, in addition to the continuous SODAR and LIDAR wind measurements. The paper describes the campaign and the potential of the collected data set for future SBL research and focuses on both the UAV operations and the benefits of complementing established measurement methods by UAV measurements to enable SBL observations at an unprecedented spatial and temporal resolution.

Surface-layer-resolving large-eddy simulations (LESs) of free-convective to near-neutral boundary layers are used to study Monin–Obukhov similarity theory (MOST) functions. The LES dataset, previously used for the analysis of MOST relationships for structure parameters, is extended for the mean vertical gradients and standard deviations of potential temperature, specific humidity, and wind. Also, local-free-convection (LFC) similarity is studied. The LES data suggest that the MOST functions for mean gradients are universal and unique. The data for the mean gradient of the horizontal wind display significant scatter, while the gradients of temperature and humidity vary considerably less. The LES results suggest that this scatter is mostly related to a transition from MOST to LFC scaling when approaching free-convective conditions and that it is associated with a change of the slope of the similarity functions toward the expected value from LFC scaling. Overall, the data show slightly, but consistent, steeper slopes of the similarity functions than suggested in literature. The MOST functions for standard deviations appear to be unique and universal when the entrainment from the free atmosphere into the boundary layer is sufficiently small. If entrainment becomes significant, however, we find that the standard deviation of humidity no longer follows MOST. Under free-convective conditions, the similarity functions should reduce to universal constants (LFC scaling). This is supported by the LES data, showing only little scatter, but displaying a systematic height dependence of these constants. Like for MOST, the LFC similarity constant for the standard deviation of specific humidity becomes nonuniversal when the entrainment of dry air reaches significant levels.

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.