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.

In recent years, the PALM 6.0 modelling system has been rapidly developing its capability to simulate physical processes within urban environments. Some examples in this regard are energy-balance solvers for building and land surfaces, a radiative transfer model to account for multiple reflections and shading, a plant-canopy model to consider the effects of plants on flow (thermo)dynamics, and a chemistry transport model to enable simulation of air quality. This study provides a thorough evaluation of modelled meteorological, air chemistry, and ground and wall-surface quantities against dedicated in situ measurements taken in an urban environment in Dejvice, Prague, the Czech Republic. Measurements included monitoring of air quality and meteorology in street canyons, surface temperature scanning with infrared cameras, and monitoring of wall heat fluxes. Large-eddy simulations (LES) using the PALM model driven by boundary conditions obtained from a mesoscale model were performed for multiple days within two summer and three winter episodes characterized by different atmospheric conditions. For the simulated episodes, the resulting temperature, wind speed, and chemical compound concentrations within street canyons show a realistic representation of the observed state, except that the LES did not adequately capture night-time cooling near the surface for certain meteorological conditions. In some situations, insufficient turbulent mixing was modelled, resulting in higher near-surface concentrations. At most of the evaluation points, the simulated surface temperature reproduces the observed surface temperature reasonably well for both absolute and daily amplitude values. However, especially for the winter episodes and for modern buildings with multilayer walls, the heat transfer through walls is not well captured in some cases, leading to discrepancies between the modelled and observed wall-surface temperature. Furthermore, the study corroborates model dependency on the accuracy of the input data. In particular, the temperatures of surfaces affected by nearby trees strongly depend on the spatial distribution of the leaf area density, land surface temperatures at grass surfaces strongly depend on the initial soil moisture, wall-surface temperatures depend on the correct setting of wall material parameters, and concentrations depend on detailed information on spatial distribution of emissions, all of which are often unavailable at sufficient accuracy. The study also points out some current model limitations, particularly the implications of representing topography and complex heterogeneous facades on a discrete Cartesian grid, and glass facades that are not fully represented in terms of radiative processes. Our findings are able to validate the representation of physical processes in PALM while also pointing out specific shortcomings. This will help to build a baseline for future developments of the model and improvements of simulations of physical processes in an urban environment.

The Radiative Transfer Model (RTM) is an explicitly resolved three-dimensional multi-reflection radiation model integrated into the PALM modelling system. It is responsible for modelling complex radiative interactions within the urban canopy. It represents a key component in modelling energy transfer inside the urban layer and consequently PALM's ability to provide explicit simulations of the urban canopy at metre-scale resolution. This paper presents RTM version 3.0, which is integrated into the PALM modelling system version 6.0. This version of RTM has been substantially improved over previous versions. A more realistic representation is enabled by the newly simulated processes, e.g. the interaction of longwave radiation with the plant canopy, evapotranspiration and latent heat flux, calculation of mean radiant temperature, and bidirectional interaction with the radiation forcing model. The new version also features novel discretization schemes and algorithms, namely the angular discretization and the azimuthal ray tracing, which offer significantly improved scalability and computational efficiency, enabling larger parallel simulations. It has been successfully tested on a realistic urban scenario with a horizontal size of over 6 million grid points using 8192 parallel processes.

Scalar dispersion from ground-level sources in arrays of buildings is investigated using wind-tunnel measurements and large-eddy simulation (LES). An array of uniform-height buildings of equal dimensions and an array with an additional single tall building (wind tunnel) or a periodically repeated tall building (LES) are considered. The buildings in the array are aligned and form long streets. The sensitivity of the dispersion pattern to small changes in wind direction is demonstrated. Vertical scalar fluxes are decomposed into the advective and turbulent parts and the influences of wind direction and of the presence of the tall building on the scalar flux components are evaluated. In the uniform-height array turbulent scalar fluxes are dominant, whereas the tall building produces an increase of the magnitude of advective scalar fluxes that yields the largest component. The presence of the tall building causes either an increase or a decrease to the total vertical scalar flux depending on the position of the source with respect to the tall building. The results of the simulations can be used to develop parametrizations for street-canyon dispersion models and enhance their capabilities in areas with tall buildings.

Sensitivity of the PALM model 6.0 with respect to land-surface and building properties is tested in a real urban environment in the vicinity of a typical crossroads in a densely built-up residential area in Prague, Czech Republic. The turbulence-resolving PALM is able to simulate the urban boundary layer flow for realistic setups. Besides an accurate representation of the relevant physical processes, the model performance also depends on the input data describing the urban setup, namely the building and land-surface properties. Two types of scenario are employed. The first one is the synthetic scenarios altering mainly surface and material parameters such as albedo, emissivity or wall conductivity, testing sensitivity of the model simulations to potentially erroneous input data. Second, urbanistic-type scenarios are analysed, in which commonly considered urban heat island mitigation measures such as greening of the streets or changing surface materials are applied in order to assess the limits of the effects of a particular type of scenario. For the synthetic scenarios, surface parameters used in radiation balance equations are found to be the most sensitive overall followed by the volumetric heat capacity and thermal conductivity of walls. Other parameters show a limited average effect; however, some can still be significant during some parts of the day, such as surface roughness in the morning hours. The second type, the urbanistic scenarios, shows urban vegetation to be the most effective measure, especially when considering both physical and biophysical temperature indicators. The influence of both types of scenario was also tested for air quality, specifically PM_2.5 dispersion, which generally shows opposite behaviour to that of thermal indicators; i.e. improved thermal comfort brings deterioration of PM_2.5 concentrations.