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We tried to reproduce results measured in the wind tunnel experiment with a CFD simulation provided by numerical model PALM. A realistic buildings layout from the Prague-Dejvice quarter has been chosen as a testing domain because solid validation campaign for PALM simulation of Atmospheric Boundary Layer (ABL) over this quarter was documented in the past. The question of input data needed for such simulation and capability of the model to capture correctly the inlet profile and its turbulence structure provided by the wind-tunnel is discussed in the study. The PALM dynamical core contains a solver for the Navier-Stokes equations. By default, the model uses the Large Eddy Simulation (LES) approach in which the bulk of the turbulent motions is explicitly resolved. It is well validated tool for simulations of the complex air-flow within the real urban canopy and also within its reduced scale provided by wind tunnel experiments. However the computed flow field between the testing buildings did not correspond well to the measured wind velocity in some points. Different setting of the inlet boundary condition was tested but none of them gave completely developed turbulent flow generated by vortex generators and castellated barrier wall place at the entrance of the aerodynamic section of the wind tunnel.

In this paper, we present a newly developed mesoscale nesting interface for the PALM model system 6.0, which enables PALM to simulate the atmospheric boundary layer under spatially heterogeneous and non-stationary synoptic conditions. The implemented nesting interface, which is currently tailored to the mesoscale model COSMO, consists of two major parts: (i) the preprocessor INIFOR (initialization and forcing), which provides initial and time-dependent boundary conditions from mesoscale model output, and (ii) PALM's internal routines for reading the provided forcing data and superimposing synthetic turbulence to accelerate the transition to a fully developed turbulent atmospheric boundary layer. We describe in detail the conversion between the sets of prognostic variables, transformations between model coordinate systems, as well as data interpolation onto PALM's grid, which are carried out by INIFOR. Furthermore, we describe PALM's internal usage of the provided forcing data, which, besides the temporal interpolation of boundary conditions and removal of any residual divergence, includes the generation of stability-dependent synthetic turbulence at the inflow boundaries in order to accelerate the transition from the turbulence-free mesoscale solution to a resolved turbulent flow. We demonstrate and evaluate the nesting interface by means of a semi-idealized benchmark case. We carried out a large-eddy simulation (LES) of an evolving convective boundary layer on a clear-sky spring day. Besides verifying that changes in the inflow conditions enter into and successively propagate through the PALM domain, we focus our analysis on the effectiveness of the synthetic turbulence generation. By analysing various turbulence statistics, we show that the inflow in the present case is fully adjusted after having propagated for about two to three eddy-turnover times downstream, which corresponds well to other state-of-the-art methods for turbulence generation. Furthermore, we observe that numerical artefacts in the form of grid-scale convective structures in the mesoscale model enter the PALM domain, biasing the location of the turbulent up- and downdrafts in the LES. With these findings presented, we aim to verify the mesoscale nesting approach implemented in PALM, point out specific shortcomings, and build a baseline for future improvements and developments.

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.

Landoberflächenmodelle (engl. land surface model, LSM) werden heutzutage nicht nur in numerischen Wetter- und Klimavorhersagemodellen eingesetzt, sondern finden auch zunehmend in Modellen für mikroskalige atmosphärische Phänomene Anwendung. Das LSM übernimmt dabei die wichtige Kopplung zwischen Atmosphäre und Boden und ermöglicht es, dass viele unterschiedliche Land- und Bodentypen abgebildet werden. Das Simulationsmodell PALM wird seit mehr als zwanzig Jahren für atmosphärische Grenzschichtprozesse eingesetzt und seit einigen Jahren immer häufiger für komplexe Anwendungen, beispielsweise in Städten, mit integriertem LSM eingesetzt. In der aktuellen Studie wird das LSM in PALM beschrieben und mit in-situ Beobachtungsdaten aus Cabauw (Niederlande) evaluiert. Dazu werden zwei aufeinander folgende Strahlungstage simuliert und Temperatur, spezifische Feuchte, Horizontalwind sowie Komponenten der Energiebilanz mit Beobachtungsdaten verglichen. Dabei zeigen wir, dass die modellierten Komponenten der Energiebilanz im Analysezeitraum konsistent mit den Beobachtungen sind. Allerdings wird die stabile Schichtung der nächtlichen Grenzschicht von dem Modell überschätzt. Am Tag sind keine signifikanten Unterschiede in der bodennahen Temperatur und Feuchte zu beobachten. In einer Sensitivitätsanalyse wird der Einfluss verschiedener Parameter des LSMs auf den Simulationsverlauf getestet, da die Wahl dieser durch den Nutzer eine erhebliche Unsicherheit des Modellsetups darstellt. Insbesondere eine ungenaue Abschätzung des Blattflächenindexes, der Albedo oder des initialen Feuchtegehalts der Grenzschicht führen zu einem signifikanten Fehler in der Simulation der turbulenten fühlbaren und latenten Wärmeströme am Tag. Die nächtliche Grenzschicht wird hingegen hauptsächlich durch die Rauigkeitslänge und das gewählte Strahlungsmodell beeinflusst.

Das Large-Eddy Simulationsmodell PALM-4U wurde in den letzten Jahren als Stadtklimamodell ausgebaut, mit dem Ziel die für stadtklimatologische Fragestellungen relevanten physikalischen Prozesse auf der Mesoskala sowie Mikroskala zu berücksichtigen. Um die Leistungsfähigkeit von PALM-4U zu demonstrieren, präsentieren wir in diesem Beitrag zwei simulierte Szenarien, ein Winter- und ein Sommerszenario, welche die gesamte Bandbreite der implementierten Stadtklimakomponenten ausnutzen. In beiden Szenarien wird die Stadt Berlin simuliert, deren gesamte Stadtfläche vom Simulationsgebiet abgedeckt wird. Der simulierte Bereich erstreckt sich über ein Gebiet von etwa 50 km x 50 km und umfasst somit das vollständige Stadtgebiet von Berlin und die nähere Umgebung. Die räumliche Auflösung variiert im Simulationsgebiet zwischen 16 m und 2 m. Durch die gewählte Gebietsgröße, Gitterweite und die Anzahl der explizit dargestellten Wechselwirkungen stellen die gezeigten Simulationen nach unserer Kenntnis die bisher weltweit größten und umfangreichsten Stadtklimasimulationen auf LES Basis dar. Momentan dienen die Ergebnisse der Simulationen als Grundlage zur Evaluierung des Modells. Im Beitrag zeigen wir wie die Eingangsdaten in die Simulationen einfließen und sich auf die Modellergebnisse auswirken. Dabei wird das Augenmerk sowohl auf die allgemeine Bodenbeschaffenheit, die explizit aufgelöste Vegetation und die Gebäude gelegt, als auch auf die seitlichen Randbedingungen welche aus dem mesoskaligen Modell COSMO stammen um Änderungen auf der Mesoskala abzubilden. Tagesgänge der meteorologischen Größen wie Lufttemperatur, Feuchte und Wind können sowohl im Stadtzentrum als auch in der ländlichen Umgebung im Außenbereich der Stadt wiedergegeben werden und stimmen mit Messungen überein. Durch die hohe räumliche Auflösung und die explizite Berücksichtigung von Hindernissen können flächendeckend für ganz Berlin aktuelle Fragestellungen der Stadtplanung beantwortet werden. Der thermische Komfort kann beispielsweise mittels der direkt von PALM-4U berechneten Größen UTCI oder PET bestimmt werden. "Hot-Spot" Analysen können durch die gesamt-städtische Betrachtung lückenlos durchgeführt werden. Insbesondere kann bei der Betrachtung eines vollständigen Stadtgebiets der urbane Wärmeinseleffekt abgebildet und dank der feinen räumlichen Auflösung im Detail bewertet werden. Die Möglichkeit auch chemische Stoffe und Feinstaub mit PALM-4U zu betrachten, bietet darüber hinaus auch das Potential PALM-4U für den Bereich der Luftqualität anzuwenden. Für die Evaluierung wurden im Vorfeld intensive Messkampagnen durchgeführt, welche mit Hilfe des in PALM-4U vorhandenen virtuellen Messmoduls in den Simulationen nachgebildet wurden. Erste Eindrücke dieser Messungen werden wir im Vortrag präsentieren. Abschließend geben wir einen Ausblick auf die aktuellen Fortschritte der Evaluierungen und gehen auf noch geplante und aktuell durchgeführte Vorhaben für die Evaluierung ein.

In recent years, the the Large-eddy simulation (LES) model PALM has been rapidly developed its capability to simulate physical processes within urban environments. For example, this includes 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, as well as nesting capabilities that enable “hot-spot” analysis, to name a few. This contribution provides an evaluation of modeled meteorological as well as ground and wall-surface quantities against dedicated in-situ measurements taken in an urban environment in Dejvice, Prague. Measurements included monitoring of surface temperature and wall heat fluxes. Simulations were performed for multiple days during several summer and winter episodes, characterized by different atmospheric conditions. To consider time-evolving synoptic conditions, boundary conditions were obtained from mesoscale WRF simulations. For the simulated episodes, the resulting temperature and wind speed 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 in some scenarios. 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 multi-layer wall structure, the heat transfer through the walls is not well captured in some cases, leading to discrepancies between the modeled and observed wall-surface temperature. Moreover, we also show that the model performance with respect to the observations strongly depends on the accuracy of the input data. To name a few, this includes e.g. the prescribed initial soil moisture, the given leaf-area densities to account for correct shading, or if a facade is insulated or not. Additionally, we will point out current model limitations, particularly implications accompanied by the step-like topography on the Cartesian grid, or wide glass facades that are not fully represented in terms of radiative processes. With our findings we are able to evaluate the representation of physical processes in PALM, while also pointing out specific shortcomings.

High-resolution large-eddy simulation (LES) is exploited to study indoor air turbulence and its effect on the dispersion of respiratory virus-laden aerosols and subsequent transmission risks. The methodology is applied to assess two dissimilar approaches to reduce transmission risks: a strategy to augment the indoor ventilation capacity with portable air purifiers and a strategy to utilize partitioning by exploiting portable space dividers. To substantiate the physical relevance of the LES model, a set of experimental aerosol concentration measurements are carried out, and their results are used for validating the LES model results. The obtained LES dispersion results are subjected to pathogen exposure and infection probability analysis. Wells-Riley probability model is extended to rely on realistic time- and space-dependent concentration fields to yield time- and space-dependent infection probability fields. The use of air purifiers leads to greater reduction in absolute risks compared to the analytical Wells-Riley model, which fails to predict the original risk level. However, the two models do agree on the relative risk reduction. The spatial partitioning strategy is demonstrated to have an undesirable effect when employed without other measures. The partitioning approach may yield positive results when employed together with targeted air purifier units. The LES-based results are examined in juxtaposition with the classical Wells-Riley model, which is shown to significantly underestimate the infection probability, highlighting the importance of employing accurate indoor turbulence modeling when evaluating different risk-reduction strategies., Preprint, 24 pages, 20 figures

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 PM2.5 dispersion, which generally shows opposite behaviour to that of thermal indicators; i.e. improved thermal comfort brings deterioration of PM2.5 concentrations.

Large-eddy simulations are useful tools to study transport processes by mesoscale structures in the atmospheric boundary layer, since in contrast to single-tower eddy covariance measurements, they provide not only temporally but also spatially highly resolved information. Therefore, they are well suited to study the energy balance closure problem, for which the mesoscale transport of latent and sensible heat, triggered by heterogeneous ecosystems, is suspected to be a major cause. However, this requires simulations that are as realistic as possible and thus allow a comparison of real measurements in the field and virtual measurements in the simulation.During the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors (CHEESEHEAD) experiment in the summer of 2019, a heterogeneous 10x10 square km domain was intensively sampled across scales. This data offers a unique possibility to set up large-eddy simulations with realistic surface heterogeneity. We use PALM to simulate two days and an area of 40 by 40 square kilometers incorporating the CHEESEHEAD site. The large scale atmospheric forcings to inform the boundary conditions are determined from the NCEP HRRR product. As the lower boundary condition, we use a soil and land-surface model coupled with a plant-canopy model, which we adapt to the CHEESEHEAD area based on ground-based and airborne measurements of plant physiological data.In this study, we investigate how well the simulations match with real measurements by comparing simulated profiles and virtual tower measurements with field measurements from radiosonde ascents, lidar measurements of three-dimensional wind and water vapor, eddy-covariance measurements from the 400 meter tower in the center of the study domain, as well as from typical eddy-covariance stations distributed through the study area. This way, we investigate how realistic the simulations actually are and to what extent the knowledge gained from them concerning the energy balance closure problem can be transferred to field measurements.

The observing system design of multi-disciplinary field measurements involves a variety of considerations on logistics, safety, and science objectives. Typically, this is done based on investigator...

In this article we describe the implementation of an online-coupled gas-phase chemistry model in the turbulence-resolving PALM model system 6.0 (formerly an abbreviation for Parallelized Large-eddy Simulation Model and now an independent name). The new chemistry model is implemented in the PALM model as part of the PALM-4U (PALM for urban applications) components, which are designed for application of the PALM model in the urban environment (Maronga et al., 2020). The latest version of the Kinetic PreProcessor (KPP, 2.2.3) has been utilized for the numerical integration of gas-phase chemical reactions. A number of tropospheric gas-phase chemistry mechanisms of different complexity have been implemented ranging from the photostationary state (PHSTAT) to mechanisms with a strongly simplified volatile organic compound (VOC) chemistry (e.g. the SMOG mechanism from KPP) and the Carbon Bond Mechanism 4 (CBM4; Gery et al., 1989), which includes a more comprehensive, but still simplified VOC chemistry. Further mechanisms can also be easily added by the user. In this work, we provide a detailed description of the chemistry model, its structure and input requirements along with its various features and limitations. A case study is presented to demonstrate the application of the new chemistry model in the urban environment. The computation domain of the case study comprises part of Berlin, Germany. Emissions are considered using street-type-dependent emission factors from traffic sources. Three chemical mechanisms of varying complexity and one no-reaction (passive) case have been applied, and results are compared with observations from two permanent air quality stations in Berlin that fall within the computation domain. Even though the feedback of the model's aerosol concentrations on meteorology is not yet considered in the current version of the model, the results show the importance of online photochemistry and dispersion of air pollutants in the urban boundary layer for high spatial and temporal resolutions. The simulated NOx and O3 species show reasonable agreement with observations. The agreement is better during midday and poorest during the evening transition hours and at night. The CBM4 and SMOG mechanisms show better agreement with observations than the steady-state PHSTAT mechanism. © 2021 Copernicus GmbH. All rights reserved.

The Chequamegon Heterogeneous Ecosystem Energy-Balance Study Enabled by a High-Density Extensive Array of Detectors 2019 (CHEESEHEAD19) is an ongoing National Science Foundation project based on an intensive field campaign that occurred from June to October 2019. The purpose of the study is to examine how the atmospheric boundary layer (ABL) responds to spatial heterogeneity in surface energy fluxes. One of the main objectives is to test whether lack of energy balance closure measured by eddy covariance (EC) towers is related to mesoscale atmospheric processes. Finally, the project evaluates data-driven methods for scaling surface energy fluxes, with the aim to improve model–data comparison and integration. To address these questions, an extensive suite of ground, tower, profiling, and airborne instrumentation was deployed over a 10 km × 10 km domain of a heterogeneous forest ecosystem in the Chequamegon–Nicolet National Forest in northern Wisconsin, United States, centered on an existing 447-m tower that anchors an AmeriFlux/NOAA supersite (US-PFa/WLEF). The project deployed one of the world’s highest-density networks of above-canopy EC measurements of surface energy fluxes. This tower EC network was coupled with spatial measurements of EC fluxes from aircraft; maps of leaf and canopy properties derived from airborne spectroscopy, ground-based measurements of plant productivity, phenology, and physiology; and atmospheric profiles of wind, water vapor, and temperature using radar, sodar, lidar, microwave radiometers, infrared interferometers, and radiosondes. These observations are being used with large-eddy simulation and scaling experiments to better understand submesoscale processes and improve formulations of subgrid-scale processes in numerical weather and climate models.

Large-eddy simulation (LES) provides a physically sound approach to study complex turbulent processes within the atmospheric boundary layer including urban boundary layer flows. However, such flow problems often involve a large separation of turbulent scales, requiring a large computational domain and very high grid resolution near the surface features, leading to prohibitive computational costs. To overcome this problem, an online LES–LES nesting scheme is implemented into the PALM model system 6.0. The hereby documented and evaluated nesting method is capable of supporting multiple child domains, which can be nested within their parent domain either in a parallel or recursively cascading configuration. The nesting system is evaluated by first simulating a purely convective boundary layer flow system and then three different neutrally stratified flow scenarios with increasing order of topographic complexity. The results of the nested runs are compared with corresponding non-nested high- and low-resolution results. The results reveal that the solution accuracy within the high-resolution nest domain is clearly improved as the solutions approach the non-nested high-resolution reference results. In obstacle-resolving LES, the two-way coupling becomes problematic as anterpolation introduces a regional discrepancy within the obstacle canopy of the parent domain. This is remedied by introducing canopy-restricted anterpolation where the operation is only performed above the obstacle canopy. The test simulations make evident that this approach is the most suitable coupling strategy for obstacle-resolving LES. The performed simulations testify that nesting can reduce the CPU time up to 80 % compared to the fine-resolution reference runs, while the computational overhead from the nesting operations remained below 16 % for the two-way coupling approach and significantly less for the one-way alternative.

There is a strong interaction between the urban atmospheric canopy layer and the building energy balance. The urban atmospheric conditions affect the heat transfer through exterior walls, the long-wave heat transfer between the building surfaces and the surroundings, the short-wave solar heat gains, and the heat transport by ventilation. Considering also the internal heat gains and the heat capacity of the building structure, the energy demand for heating and cooling and the indoor thermal environment can be calculated based on the urban microclimatic conditions. According to the building energy concept, the energy demand results in an (anthropogenic) waste heat; this is directly transferred to the urban environment. Furthermore, the indoor temperature is re-coupled via the building envelope to the urban environment and affects indirectly the urban microclimate with a temporally lagged and damped temperature fluctuation. We developed a holistic building model for the combined calculation of indoor climate and energy demand based on an analytic solution of Fourier's equation and implemented this model into the PALM model.

The observing system design of multidisciplinary field measurements involves a variety of considerations on logistics, safety, and science objectives. Typically, this is done based on investigator intuition and designs of prior field measurements. However, there is potential for considerable increases in efficiency, safety, and scientific success by integrating numerical simulations in the design process. Here, we present a novel numerical simulation–environmental response function (NS–ERF) approach to observing system simulation experiments that aids surface–atmosphere synthesis at the interface of mesoscale and microscale meteorology. In a case study we demonstrate application of the NS–ERF approach to optimize the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19). During CHEESEHEAD19 pre-field simulation experiments, we considered the placement of 20 eddy covariance flux towers, operations for 72 h of low-altitude flux aircraft measurements, and integration of various remote sensing data products. A 2 h high-resolution large eddy simulation created a cloud-free virtual atmosphere for surface and meteorological conditions characteristic of the field campaign domain and period. To explore two specific design hypotheses we super-sampled this virtual atmosphere as observed by 13 different yet simultaneous observing system designs consisting of virtual ground, airborne, and satellite observations. We then analyzed these virtual observations through ERFs to yield an optimal aircraft flight strategy for augmenting a stratified random flux tower network in combination with satellite retrievals. We demonstrate how the novel NS–ERF approach doubled CHEESEHEAD19's potential to explore energy balance closure and spatial patterning science objectives while substantially simplifying logistics. Owing to its modular extensibility, NS–ERF lends itself to optimizing observing system designs also for natural climate solutions, emission inventory validation, urban air quality, industry leak detection, and multi-species applications, among other use cases.

Large-eddy simulations (LES) are an important tool for investigating the longstanding energy-balance-closure problem, as they provide continuous, spatially-distributed information about turbulent flow at a high temporal resolution. Former LES studies reproduced an energy-balance gap similar to the observations in the field typically amounting to 10–30% for heights on the order of 100 m in convective boundary layers even above homogeneous surfaces. The underestimation is caused by dispersive fluxes associated with large-scale turbulent organized structures that are not captured by single-tower measurements. However, the gap typically vanishes near the surface, i.e. at typical eddy-covariance measurement heights below 20 m, contrary to the findings from field measurements. In this study, we aim to find a LES set-up that can represent the correct magnitude of the energy-balance gap close to the surface. Therefore, we use a nested two-way coupled LES, with a fine grid that allows us to resolve fluxes and atmospheric structures at typical eddy-covariance measurement heights of 20 m. Under different stability regimes we compare three different options for lower boundary conditions featuring grassland and forest surfaces, i.e. (1) prescribed surface fluxes, (2) a land-surface model, and (3) a land-surface model in combination with a resolved canopy. We show that the use of prescribed surface fluxes and a land-surface model yields similar dispersive heat fluxes that are very small near the vegetation top for both grassland and forest surfaces. However, with the resolved forest canopy, dispersive heat fluxes are clearly larger, which we explain by a clear impact of the resolved canopy on the relationship between variance and flux–variance similarity functions.

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. © 2021 Pavel Krč et al.

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.

The PALM model system 6.0 is designed to simulate micro- and mesoscale flow dynamics in realistic urban environments. The simulation results can be very valuable for various urban applications, for example to develop and improve mitigation strategies related to heat stress or air pollution. For the accurate modelling of urban environments, realistic boundary conditions need to be considered for the atmosphere, the local environment, and the soil. The local environment with its geospatial components is described in the static driver of the model and follows a standardized, hereafter called PALM input data standard. The main input parameters describe surface type, buildings and vegetation. Depending on the desired simulation scenario and the available data, the local environment can be described at different levels of detail. To compile a complete static driver describing a whole city, various data sources are used, including remote sensing, municipal data collections and open data such as OpenStreetMap. This manuscript shows how input data sets for three German cities can be derived. Based on these data sets, the static driver for PALM can be generated. As the collection and preparation of input data sets is tedious, prospective research aims at the development of a semi-automated processing chain to support users in formatting their geospatial data.

There is a strong interaction between the urban and the building energy balance. The urban climate affects the heat transfer through exterior walls, the longwave heat transfer between the building surfaces and the surroundings, the shortwave solar heat gains and the heat transport by ventilation. Considering also the internal heat gains and the heat capacity of the building structure, the energy demand for heating and cooling and the indoor thermal environment can be calculated based on the urban climate. According to the building energy concept, the energy demand results in an (anthropogenic) waste heat, this is directly transferred to the urban environment. Furthermore, the indoor temperature is re-coupled via the building envelope to the urban environment and affects indirectly the urban climate with a time shifted and damped temperature fluctuation. We developed and implemented a holistic building model for the combined calculation of indoor climate and energy demand based on an analytic solution of Fourier’s equation. The building model is integrated via an urban surface model into the urban climate model.

The PALM 6.0 model system has been rapidly developed in the recent years with respect to its capability to simulate physical processes within urban environments. In this regard, it includes e.g. energy-balance solvers for building and land surfaces, a radiative transfer model to account for multiple reflections and shading, as well as a plant-canopy model to consider the effects of plants on the (thermo)dynamics of the flow. This study provides a thorough evaluation of modelled meteorological, air chemistry and wall-surface quantities against dedicated in-situ measurements taken in an urban environment in Prague, Dejvice, Czech Republic. Measurements included e.g. monitoring of air quality and meteorology in street canyons, surface temperature scanning with infrared camera and monitoring of wall heat fluxes. Large-eddy simulations (LES) for multiple days within two summer and three winter episodes that are characterized by different atmospheric conditions were performed with the PALM model driven by boundary conditions obtained from a mesoscale model. For the simulated episodes, the resulting temperature, wind speed and concentrations of chemical compounds within street canyons agreed well with the observations, except the LES did not adequately capture nighttime cooling near the surface at certain meteorological conditions. In some situations, less turbulent mixing was modelled resulting in higher near-surface concentrations. At most of the surface evaluation points the simulated wall-surface temperature agreed fairly well with the observed one regarding its absolute value as well as daily amplitude. However, especially for the winter episodes and for modern buildings with multi-layer walls, the heat transfer through the wall is partly not well captured leading to discrepancies between the modelled and observed wall-surface temperature. Furthermore, we show that model results depend on the accuracy of the input data, particularly 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, or wall-surface temperatures depend on the correct prescription of wall material parameters, though these parameters are often not available with sufficient accuracy. Moreover, we also point out current model limitations, here we particularly focus on implications with respect to the discrete representation of topography on a Cartesian grid, complex heterogeneous facades, as well as glass facades that are not well represented in terms of radiative processes. With these findings presented, we aim to validate the representation of physical processes in PALM as well as to point out specific shortcomings. This will help to build a baseline for future developments of the model and for improvements of simulations of physical processes in an urban environment.

Including radiative transfer processes within the urban canopy layer into microscale urban climate models (UCMs) is essential to obtain realistic model results. These processes include the interaction of buildings and vegetation with shortwave and longwave radiation, thermal emission, and radiation reflections. They contribute differently to the radiation budget of urban surfaces. Each process requires different computational resources and physical data for the urban elements. This study investigates how much detail modellers should include to parameterise radiative transfer in microscale building resolving UCMs. To that end, we introduce a stepwise parameterization method to the the PALM model system 6.0 to quantify individually the effects of the main radiative transfer processes on the radiation budget and on the flow field. We quantify numerical simulations of both simple and realistic urban configurations to identify the radiative transfer processes which have major effects on the radiation budget, such as surface and vegetation interaction with short wave and long wave radiation, and those which have minor effects, such as multiple reflections. The study also shows that radiative transfer processes within the canopy layer implicitly affect the incoming radiation since the radiative transfer model is coupled to the radiation model. The flow field changes considerably in response to the radiative transfer processes included in the model. The study highlights those processes which are essentially needed to assure acceptable quality of the flow field. Omitting any of these processes may lead to high uncertainties in the model results.

Land surface heterogeneity influences patterns of sensible and latent heat flux, which in turn affect processes in the atmospheric boundary layer. However, gridded atmospheric models often fail to incorporate the influence of land surface heterogeneity due to differences between the temporal and spatial scales of models compared to the local, sub-grid processes. Improving models requires the scaling of surface flux measurements; a process made difficult by the fact that surface measurements usually find an imbalance in the energy budget.The Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors (CHEESEHEAD19) was an observational experiment designed to investigate how the atmospheric boundary layer responds to scales of spatial heterogeneity in surface-atmosphere heat and water exchanges. The campaign was conducted from June – October 2019, measuring surface energy fluxes over a heterogeneous forest ecosystem as fluxes transitioned from latent heat-dominated summer through sensible heat-dominated fall. Observations were made by ground, airborne, and satellite platforms within the 10 x 10 km study region, which was chosen to match the scale of a typical model grid cell. The spatial distribution of energy fluxes was observed by an array of 20 eddy covariance towers and a low-flying aircraft. Mesoscale atmospheric properties were measured by a suite of LiDAR and sounding instruments, measuring winds, water vapor, temperature, and boundary layer development. Plant phenology was measured in-situ and mapped remotely using hyperspectral imaging.The dense set of multi-scale observations of land-atmosphere exchange collected during the CHEESEHEAD field campaign permits combining the spatial and temporal distribution of energy fluxes with mesoscale surface and atmospheric properties. This provides an unprecedented data foundation to evaluate theoretical explanations of energy balance non-closure, as well as to evaluate methods for scaling surface energy fluxes for improved model-data comparison. Here we show how fluxes calculated using a spatial eddy covariance technique across the 20-tower network compare to those of standard temporal eddy covariance fluxes in order to characterize of the spatial representativeness of single tower eddy covariance measurements. Additionally, we show how spatial EC fluxes can be used to better understand the energy balance over heterogeneous ecosystems.

Leads are Chanel-like openings in the sea-ice through which heat of several 100 Watt/m2 is transferred from the ocean into the atmosphere. Even though leads account only for a view percent to the total ice coverage in polar regions, they modify the polar boundary layer significantly. Therefore, leads need to be considered in numerical weather and climate models. Since, generally leads are not explicitly resolved in these models it is important to understand the overall effect of leads of different sizes onto the boundary layer for different meteorological conditions.With numerous Large-Eddy Simulations we investigated the dependency of the lead averaged surface heat flux on the lead width in a range between 50 m and 25 000 m for different meteorological conditions. Generally, we found under same temperature differences between ice and water and same meteorological conditions an increase of the the lead averaged heat flux with increasing lead width by more then 200% for some situations. We like to give some brief explanations of the possible causes for this behavior as well as to oppose these results to other former studies in this field, which might disagree to them in some points.

Large-Eddy Simulation (LES) allow to simulate pollutant dispersion at a fine-scale turbulence-resolving scale with explicitly resolved turbulent transport around building structures and in street canyons. The microscale urban climate model with atmospheric chemistry PALM-4U (i.e. PALM for Urban applications; Maronga et al., 2019, Met. Z., https://doi.org/10.1127/metz/2019/0909) has been developed within the collaborative project MOSAIK (Model-based city planning and application in climate change). With such a large-eddy simulation (LES) model, pollutant dispersion around buildings and within street canyons can be simulated, with explicitly resolving the turbulent transport in urban environments.Cyclic boundaries are frequently applied in LES in order to obtain lateral boundary conditions for the turbulent quantities. In addition to the default cyclic boundary conditions, PALM-4U allows also time-dependent boundary conditions from regional models to account for variable weather conditions and regional scale pollutant transport. Turbulent fluctuations, which are not included in the boundary conditions from the regional simulation but are needed as additional boundary conditions for the LES model are produced by a turbulence generator (Maronga et al, 2019, GMDD, https://doi.org/10.5194/gmd-2019-103).PALM-4U simulations with and without time dependent boundary conditions from regional simulations with WRF-Chem are performed for different setups in order to test the impact of the domain configuration. The simulations indicate that cyclic boundary conditions can lead to unrealistic accumulation of pollutants over urban areas with strong sources, which is not the case when time-dependent boundary conditions are applied. However, even though a turbulence generator is applied, explicit setting of time-dependent boundary conditions requires large model domains, in order to obtain fully developed turbulence within the domain of interest, increasing the computational demand of the simulation.

Airborne flux measurements allow us to quantify the surface–atmosphere exchange over heterogeneous land surfaces. While often applied to regional-scale fluxes, it is also possible to infer component fluxes emanating from different surface patches from the measurement via disaggregation strategies. Here, we emulate flux disaggregation strategies by conducting an ensemble of virtual flight measurements within a set of large-eddy simulations over idealized surface heterogeneities and under different flow regimes. The resulting patch surface fluxes are compared with the prescribed patch surface fluxes in the simulation. To calculate fluxes along the flight legs, we apply traditional eddy-covariance and space–frequency (wavelet) methods. We show that the patch fluxes are captured best with the space–frequency method, where the disaggregation error is almost invariant of the segment length. For the eddy-covariance method, however, the error strongly depends on the segment length, with largest random and systematic errors for shorter segments. Furthermore, we determine a trade-off between a permissible disaggregation error and a sufficient resolution of the heterogeneous surface signals. Among our set-ups, an optimal segment length is determined to be 3–4 km for the eddy-covariance method, while with the space–frequency method even shorter segment lengths of a few hundreds of metres can be chosen, which enables sufficient isolation of signals from surface patches and the resolution of small-scale surface heterogeneity.

In this paper we present the current version of the Parallelized Large-Eddy Simulation Model (PALM) whose core has been developed at the Institute of Meteorology and Climatology at Leibniz Universität Hannover (Germany). PALM is a Fortran 95-based 5 code with some Fortran 2003 extensions and has been applied for the simulation of a variety of atmospheric and oceanic boundary layers for more than 15 years. PALM is optimized for use on massively parallel computer architectures and was recently ported to general-purpose graphics processing units. In the present paper we give a detailed description of the current version of the model and its features, such as an embedded 10 Lagrangian cloud model and the possibility to use Cartesian topography. Moreover, we discuss recent model developments and future perspectives for LES applications. DFG/RA/617/3 DFG/RA/617/6 DFG/RA/617/16 DFG/RA/617/27-1

The computational power and availability of graphics processing units (GPUs) and many integrated core (MIC) processors on high performance computing (HPC) systems is rapidly evolving. However, HPC applications need to be ported to take advantage of such hardware. This paper is a report on our experience of porting the MPI+OpenMP parallelised large-eddy simulation model (PALM) to multi-GPU as well as to MIC processor environments using OpenACC and OpenMP. PALM is written in Fortran, entails 140 kLOC and runs on HPC farms of up to 43,200 cores. The main porting challenges are the size and complexity of PALM, its inconsistent modularisation and no unit-tests. We report the methods used to identify performance issues as well as our experiences with state-of-the-art profiling tools. Moreover, we outline the required porting steps, describe the problems and bottlenecks we encountered and present separate performance tests for both architectures. We however, do not provide benchmark information.

An understanding of how the convective boundary layer (CBL) is mixed under heterogeneous surface forcing is crucial for the interpretation of area-averaged turbulence measurements. To determine the height and degree to which a complex heterogeneous surface affects the CBL, large-eddy simulations (LES) for two days of the LITFASS-2003 experiment representing two different wind regimes were undertaken. Spatially-lagged correlation analysis revealed the turbulent heat fluxes to be dependent on the prescribed surface flux pattern throughout the entire CBL including the entrainment layer. These findings prompted the question of whether signals induced by surface heterogeneity can be measured by airborne systems. To examine this question, an ensemble of virtual flights was conducted using LES, according to Helipod flight measurements made during LITFASS-2003. The resulting ensemble-averaged heat fluxes indicated a clear dependence on the underlying surface up to the top of the CBL. However, a large scatter between the flux measurements in different ensemble runs was observed, which was the result of insufficient sampling of the largest turbulent eddies. The random and systematic errors based on the integral length scale did not indicate such a large scatter. For the given flight leg lengths, at least 10-15 statistically independent flight measurements were necessary to give a significant estimate of heterogeneity-induced signals in the CBL. The need for ensemble averaging suggests that the observed blending of heterogeneity-induced signals in the CBL can be partly attributed to insufficient averaging. DFG/RA 617/21-1