Parallelized Large-eddy Simulation Model Research Articles

An attention-based CNN model integrating observational and simulation data for high-resolution spatial estimation of urban air quality

Machine learning, especially deep learning, can outperform traditional atmospheric models in air quality assessment, offering enhanced efficiency and accuracy without relying on detailed emission inventories and atmospheric chemical mechanisms. Despite their predictive power, deep learning models often grapple with the perception of being “black boxes” due to their intricate architectures. Here, we develop an attention-based convolutional neural network (CNN-attention) model that incorporates observational data, the parallelized large-eddy-simulation model (PALM), and urban morphology data for high-resolution spatial estimation of urban air quality. Our findings indicate that the CNN-attention model outperforms traditional CNN with higher accuracy and efficiency, achieving R2 = 0.987 and root mean square error (RMSE) = 0.15 mg/m3, while significantly reducing training time and memory usage. Compared to traditional machine learning models, the CNN exhibits higher R2 values and lower RMSE, showcasing its adeptness at capturing complex nonlinear patterns. The inclusion of attention layer further improves the model's performance by dynamically assigning attention scores to key features, enabling the model to focus on areas of critical emissions and distinctive urban features such as highways, arterial roads, intersections, and dense building clusters. This approach also reveals fluid dynamical principles, highlighting the significant disparities in pollutant concentration across roadways caused by atmospheric turbulence, and the distinct plume formations influenced by land use and topography. When applied to various urban settings, the CNN-attention model exhibits superior generalizability and transferability. This study provides valuable scientific insights and technical support for urban planning, air quality management, and exposure risk evaluation.

Investigating the influence of stepped roofs on wind dynamics using large eddy simulation

This study investigates airflow and turbulence within varying roof configurations in urban boundary layers by using the parallelized large-eddy simulation model (PALM). Key findings reveal stark contrasts in airflow between stepped and flat roof arrangements, with the former presenting dual counter-rotating vortices and enhanced vertical motion in one street, while the latter exhibited a primary vortex and several secondary vortices. Additionally, normalized turbulence kinetic energy (TKE) was markedly lower in flat roof configurations, with stepped roofs fostering more significant turbulence and small-scale turbulent motion. This variability intensified with decreasing step height and quantity. Vertical profiles further disclosed considerable velocity disturbances and larger Reynolds numbers in one street of stepped roofs, affirming the roof’s influence on turbulence generation and transport. Dispersive stress also displayed differing characteristics in various canyons. Turbulent momentum transport through eddies significantly differs between the windward and leeward streets of flat and stepped roofs. Further exploration into density stratification effects and scalar transport in stepped roofs would enhance practical implications.

Implementation of a Simple Actuator Disk for Large-Eddy Simulation in the Weather Research and Forecasting Model (WRF-SADLES v1.2) for wind turbine wake simulation

Abstract. In this study, we present the development of a Simple Actuator Disk model for Large-Eddy Simulation (SADLES), implemented within the Weather Research and Forecasting (WRF) model, which is widely used in atmospheric research. The WRF-SADLES model supports both idealized studies and realistic applications through downscaling from realistic data, with a focus on resolutions of tens of meters. Through comparative analysis with the Parallelized Large-eddy Simulation Model (PALM) at resolutions of 10 and 30 m, we validate the effectiveness of WRF-SADLES in simulating the wake characteristics of a 5 MW wind turbine. Results indicate good agreement between WRF-SADLES at 30 m resolution and 10 m resolution and the PALM model. Additionally, we demonstrate a practical case study of WRF-SADLES by downscaling ERA5 reanalysis data using a nesting method to simulate turbine wakes at the Alpha Ventus wind farm in the south of the North Sea. The meso-to-micro downscaling simulation reveals that the wake effect simulated by WRF-SADLES at the FINO1 offshore meteorological mast station aligns well with the cup anemometer and lidar measurements. Furthermore, we investigate an event of farm-to-farm interaction, observing a 16 % reduction in ambient wind speed and a 38 % decrease in average turbine power at Alpha Ventus due to the presence of a wind farm to the southwest. WRF-SADLES offers a promising balance between computational efficiency and accuracy for wind turbine wake simulations, making it valuable for wind energy assessments and wind farm planning.

Predicting high-resolution air quality using machine learning: Integration of large eddy simulation and urban morphology data

Accurately predicting air pollutants, especially in urban areas with well-defined spatial structures, is crucial. Over the past decade, machine learning techniques have been widely used to forecast urban air quality. However, traditional machine learning approaches have limitations in accuracy and interpretability for predicting pollutants. In this study, we propose a convolutional neural network (CNN) model to predict the spatial distribution of CO concentration in Nanjing urban area at 10 m resolution. Our model incorporates various factors as input, such as building height, topography, emissions, and is trained against the outputs simulated by the parallelized large-eddy simulation model (PALM). The PALM model has 48 different scenarios that varied in emissions, wind speeds, and wind directions. The results display a strong consistency between the two models. Furthermore, we evaluate the performance of our model using a 10-fold cross-validation and out-of-sample cross-validation approach. This yields a robust correlation (with both R2 > 0.8) and a low RMSE between the CO predicted by the PALM and CNN models, which demonstrates the generalization capability of our CNN model. The CNN can extract crucial features from the resulted weight contribution map. This map indicates that the CO concentration at a location is more influenced by nearby buildings and emissions than distant ones. The interpretable patterns uncovered by our model are related to neighborhood effects, wind speeds, directions, and the impact of orientation on urban CO distribution. The model also shows high prediction accuracy (R > 0.8) when applied to another city. Overall, the integration of our CNN framework with the PALM model enhances the accuracy of air quality predictions, while enabling a fluid dynamic laws interpretation, providing effective tools for air quality management.

Evaluation and Validation of Microscale Atmospheric Modeling With Offline Weather Research and Forecasting Model to Parallelized Large-Eddy Simulation Model Forcing Conditions

Abstract As the rate of urbanization increases, local vegetation is being replaced with man-made materials, causing increasingly adverse impacts on the surface-atmosphere energy balance. These negative effects can be simulated by modeling the urban landscapes in question; however, the main challenges of modeling urban thermal environments are the scale and resolution at which to perform such tasks. Current modeling of urban thermal environments is typically limited to either mesoscale (1 –2000 km) or microscale (<1 km) phenomena. In the present work, an open-source framework for one-way upstream coupled multiscale urban thermal environment simulations is examined and validated. This coupled simulation can provide valuable insights into the flow behavior and energy transport between mesoscale and microscale interactions. The mesoscale to microscale boundary conditions are coupled together using simulated data from the advanced research weather research and forecasting model (WRF-ARW), a mesoscale numerical weather prediction software, and assimilating it into parallelized large-eddy simulation model (PALM), a computational fluid dynamics style (CFD-style) software designed for microscale atmospheric and oceanic flows. The multiscale urban thermal environment simulations are tested for grid sensitivity to variations in model input and control parameters, and then experimentally validated against distributed sensor measurements at the Georgia Institute of Technology (Georgia Tech) campus in Atlanta, GA. Validated microscale atmospheric models with heterogeneous domains can be used to project the thermal benefits of urban heat mitigation strategies (increase use of high-albedo surfaces, tree and vegetation cover, and smart growth practices) and advise building energy usage modeling and policies.

Multiscale Simulation of Offshore Wind Variability During Frontal Passage: Brief Implication on Turbines’ Wakes and Load

Enhancing the performance of offshore wind park power production requires, to a large extent, a better understanding of the interactions of wind farms and individual wind turbines with the atmospheric boundary layer over a wide range of spatiotemporal scales. In this study, we use a multiscale atmospheric model chain coupled offline with the aeroelastic Fatigue, Aerodynamics, Structures, and Turbulence (FAST) code. The multiscale model contains two different components in which the nested mesoscale Weather and Research Forecast (WRF) model is coupled offline with the Parallelized Large-eddy Simulation Model (PALM). Such a multiscale framework enables to study in detail the turbine behaviour under various atmospheric forcing conditions, particularly during transient atmospheric events.

Evaluation of the Street Canyon Level Air Pollution Distribution Pattern in a Typical City Block in Baoding, China.

Urban traffic pollution, which is strongly influenced by the complex urban morphology, has posed a great threat to human health. In this study, we performed a high-resolution simulation of traffic pollution in a typical city block in Baoding, China, based on the Parallelized Large-eddy simulation Model (PALM), to examine the distribution patterns of traffic-related pollutants and explore their relationship with urban morphology. Based on the model results, we conducted a multi-linear regression (MLR) analysis and found that the distribution of air pollutants inside the city block was dominated by both traffic emissions and urban morphology, which explained about 70% of the total variance in spatial distribution of air pollutants. Excluding the contribution of emissions, over 50% of the total variance can still be explained by the urban morphology. Among these urban morphological factors, the key factors determining the spatial distribution of air pollution are “Distance from the road” (DR), “Building Coverage Ratio” (BCR) and “Aspect Ratio” (H/W) of the street canyon. Specifically, urban areas with lower Aspect Ratio, lower BCR and larger DR are less affected by traffic pollution. Compiling these individual factors, we developed a complex Urban Morphology Pollution Index (UMPI). Each unit increase in UMPI is associated with a one percent increase of nearby traffic pollution contribution. This index can help urban planners to semi-quantitatively evaluate building groups which tend to trap or ventilate traffic pollution and thus help to reduce human exposure to street canyon level pollution through either traffic emission control or urban morphology amelioration.

Tall-building effects on pedestrian-level flow and pollutant dispersion: Large-eddy simulations

The urban environmental impact of tall buildings has increasingly become an important topic of investigation, with the rapid pace of tall-building constructions around the world. In this study, the effects of a tall building on pedestrian-level flow and pollutant dispersion are investigated using the parallelized large-eddy simulation model (PALM). Numerical simulations are conducted by changing the tall-building height in the configuration of a tall building surrounded by low-rise cubical buildings. As the tall-building height increases, the time- and area-averaged pedestrian-level wind speed and pollutant concentration increases and decreases, respectively. Both the rates of changes in the average wind speed and pollutant concentration decrease with increasing tall-building height. The trend of the average wind speed is attributable to an increasing tendency of oncoming flows to pass by the sides of the tall building rather than going down as the tall-building height increases. The trend of the average pollutant concentration is associated with that of the average wind speed. Instantaneous flow and pollutant dispersion are also analyzed. In the upstream region of the tall building, bulks of polluted air are repeatedly transported from further upstream regions and enter the canyon right in front of the tall building, temporarily increasing the pedestrian-level pollutant concentration near the windward wall of the tall building. In the downstream region of the tall building, at the pedestrian level, two counter-rotating vortices appear in the canyon just behind the tall building. Each of these vortices repeatedly develops at one of the two leeward corners of the tall building, moves downstream while changing its size, and disappears after reaching the windward wall of the neighboring low-rise building. These coherent vortices considerably affect the spatiotemporal variation of pedestrian-level pollutant concentration in the canyon just behind the tall building.

Importance of radiative transfer processes in urban climate models: a study based on the PALM 6.0 model system

Abstract. 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 parameterize radiative transfer in microscale building-resolving UCMs. To that end, we introduce a stepwise parameterization method to the Parallelized Large-eddy Simulation Model (PALM) 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 major and the minor effects of radiative transfer processes on the radiation budget. The study shows that processes such as surface and vegetation interaction with shortwave and longwave radiation will have major effects, while a process such as multiple reflections will have minor effects. 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 identified those processes which are essentially needed to assure acceptable quality of the flow field. These processes are receiving radiation from atmosphere based on the sky-view factors, interaction of urban vegetation with radiation, radiative transfer among urban surfaces, and considering at least single reflection of radiation. Omitting any of these processes may lead to high uncertainties in the model results.

Simulation of the Scalar Transport above and within the Amazon Forest Canopy

The parallelized large-eddy simulation model (PALM) was used to understand better the turbulent exchanges of a passive scalar above and within a forested region located in the central Amazon. Weak (2 ms−1) and strong (6 ms−1) wind conditions were simulated. A passive scalar source was introduced to the forest floor for both simulations. The simulations reproduced the main characteristics of the turbulent flow and of the passive scalar transport between the forest and the atmosphere. Noteworthily, strong and weak wind conditions presented different turbulence structures that drove different patterns of scalar exchange both within and above the forest. These results show how passive scalar concentration is influenced by the wind speed at the canopy top. Additionally, higher wind speeds are related to stronger sweep and ejection regimes, generating more intense plumes that are able to reduce the passive scalar concentration inside the forest canopy. This work was the first that used PALM to investigate scalar transport between the Amazon rainforest and the atmosphere.

Effects of spatial heterogeneity of leaf density and crown spacing of canopy patches on dry deposition rates

Trees have a large role in improving urban air quality, among other mechanisms, through dry deposition of scalars and aerosols on leaf surfaces. We tested the role of leaf density and canopy structure in modulating the rate of dry deposition. We simulated the interactions between a virtual forest patch and deposition rate of an arbitrary scalar using the Parallelized Large Eddy Simulation Model (PALM). Two canopy structures were considered: a homogenous canopy and canopy stripes. For each canopy stripe scenario, we considered thin, intermediate, and wide stripes, while the space between stripes equals the stripes’ width. Four leaf area densities were considered for each case (LAI = 0.5, 1, 1.5, and 2). The results showed that denser canopies and canopy stripes experienced more total deposition, noting that stripes had a larger per leaf area deposition than homogeneous canopies. Our results can be explained by canopy-induced turbulence structures that couple the air within and above the canopy and lead to more effective leaf area where this coupling is stronger. We aggregate our results to the whole-patch scale and suggest a canopy-structure and leaf-area dependent correction to the canopy resistance parameter so to be used in coarse models that resolve dry deposition.

Towards multiscale modeling of ocean surface turbulent mixing using coupled MPAS-Ocean v6.3 and PALM v5.0

Abstract. A multiscale modeling approach for studying the ocean surface turbulent mixing is explored by coupling an ocean general circulation model (GCM) MPAS-Ocean with the Parallelized Large Eddy Simulation Model (PALM). The coupling approach is similar to the superparameterization approach that has been used to represent the effects of deep convection in atmospheric GCMs. However, the focus of this multiscale modeling approach is on the small-scale turbulent mixing and their interactions with the larger-scale processes in the ocean, so that a more flexible coupling strategy is used. To reduce the computational cost, a customized version of PALM is ported on the general-purpose graphics processing unit (GPU) with OpenACC, achieving 10–16 times overall speedup as compared to running on a single CPU. Even with the GPU-acceleration technique, a superparameterization-like approach to represent the ocean surface turbulent mixing in GCMs using embedded high fidelity and three-dimensional large eddy simulations (LESs) over the global ocean is still computationally intensive and infeasible for long simulations. However, running PALM regionally on selected MPAS-Ocean grid cells is shown to be a promising approach moving forward. The flexible coupling between MPAS-Ocean and PALM allows further exploration of the interactions between the ocean surface turbulent mixing and larger-scale processes, as well as future development and improvement of ocean surface turbulent mixing parameterizations for GCMs.

Evaluation of Gaussian wake models under different atmospheric stability conditions: Comparison with large eddy simulation results

The calculation of the velocity deficit in the wake of individual wind turbines is a fundamental part of the wind farm analysis. A good approximation of the wake deficit behind a single wind turbine will improve the power estimation for downwind turbines. Large-eddy simulation (LES) is a research tool widely used in studying the velocity deficit and turbulence intensity in the wake. However, the computational cost of the LES prevents its application in wind farm performance analysis and control. Existing analytical wake models provide a fast estimation of the velocity deficit and the wake expansion rate downstream from the rotor. The Gaussian wake models use a Gaussian distribution to improve the prediction of the wake velocity deficit. With the number of analytical models available, an extensive evaluation of their performance under different flow parameters is needed. In this work, we simulate a wake of a single wind turbine using the LES code PALM (Parallelized LES Model) combined with an actuator disc model with rotation. We compare the computed flow field with the predictions made by Gaussian models and fit their parameters to obtain the best possible fit for the wake field data as computed by LES.

Calculating human thermal comfort and thermal stress in the PALM model system 6.0

Abstract. In the frame of the project “MOSAIK – Model-based city planning and application in climate change”, a German-wide research project within the call “Urban Climate Under Change” ([UC]2) funded by the German Federal Ministry of Education and Research (BMBF), a biometeorology module was implemented into the Parallelized Large-Eddy Simulation Model (PALM) system. The new biometeorology module is comprised of methods for the calculation of UV-exposure quantities, a human–biometeorologically weighted mean radiant temperature (Tmrt), as well as for the estimation of human thermal comfort or stress. The latter is achieved through the implementation of the three widely used thermal indices: perceived temperature (PT), Universal Thermal Climate Index (UTCI), as well as physiologically equivalent temperature (PET). Comparison calculations were performed for the PT, UTCI and PET indices based on the SkyHelios model and showing PALM calculates higher values in general. This is mostly due to a higher radiational gain leading to higher values of mean radiant temperature. For a more direct comparison, the PT, PET and UTCI indices were calculated by the biometeorology module, as well as the programs provided by the attachment to Verein Deutscher Ingenieure (VDI) guideline 3787, as well as by the RayMan model based on the very same input dataset. Results show deviations below the relevant precision of 0.1 K for PET and UTCI and some deviations of up to 2.683 K for PT caused by repeated unfavorable rounding in very rare cases (0.027 %).

On the Convergence and Capability of the Large-Eddy Simulation of Concentration Fluctuations in Passive Plumes for a Neutral Boundary Layer at Infinite Reynolds Number

Large-eddy simulation (LES) experiments have been performed using the Parallelized LES Model (PALM). A methodology for validating and understanding LES results for plume dispersion and concentration fluctuations in an atmospheric-like flow is presented. A wide range of grid resolutions is shown to be necessary for investigating the convergence of statistical characteristics of velocity and scalar fields. For the scalar, the statistical moments up to the fourth order and the shape of the concentration probability density function (p.d.f.) are examined. The mean concentration is influenced by grid resolution, with the highest resolution simulation showing a lower mean concentration, linked to larger turbulent structures. However, a clear tendency to convergence of the concentration variance is observed at the two higher resolutions. This behaviour is explained by showing that the mechanisms driving the mean and the variance are differently influenced by the grid resolution. The analysis of skewness and kurtosis allows also the obtaining of general results on plume concentration fluctuations. Irrespective of grid resolution, a family of Gamma p.d.f.s well represents the shape of the concentration p.d.f. but only beyond the peak of the concentration fluctuation intensity. In the early plume dispersion phases, the moments of the p.d.f. are in good agreement with those generated by a fluctuating plume model. To the best of our knowledge, our study demonstrates for the first time that, if resolution and averaging time are adequate, atmospheric LES provides a trustworthy representation of the high order moments of the concentration field, up to the fourth order, for a dispersing plume.

Overview of the PALM model system 6.0

Abstract. 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.

Grid-Resolution Requirements for Large-Eddy Simulations of the Atmospheric Boundary Layer

Large-eddy simulations are widely used to study flows in the atmospheric boundary layer. As atmospheric boundary-layer flows of different atmospheric stratification have very different flow characteristics on different length scales, well-resolved simulations of these flows require very different meshes. The Parallelized Large-Eddy Simulation Model combined with a realizable dynamic subgrid model is used to identify the best method for evaluating the resolution requirements for boundary-layer flows simulated by large-eddy simulations. In particular, we consider three atmospheric boundary-layer set-ups with different stratifications (stable, neutral, convective) to investigate how the quality of the simulation changes with the grid resolution. By following the work of Davidson (Int J Heat Fluid Flow 30(5):1016–1025, 2009), the results are examined using criteria such as the convergence of mean profiles, the ratio of modelled and resolved turbulence kinetic energy, and the two-point correlation. We conclude that the two-point correlation is the best measure to evaluate whether the resolution demands for a specific flow are fulfilled.

A one-dimensional model of turbulent flow through “urban” canopies (MLUCM v2.0): updates based on large-eddy simulation

Abstract. In mesoscale climate models, urban canopy flow is typically parameterized in terms of the horizontally averaged (1-D) flow and scalar transport, and these parameterizations can be informed by computational fluid dynamics (CFD) simulations of the urban climate at the microscale. Reynolds averaged Navier–Stokes simulation (RANS) models have previously been employed to derive vertical profiles of turbulent length scale and drag coefficient for such parameterization. However, there is substantial evidence that RANS models fall short in accurately representing turbulent flow fields in the urban roughness sublayer. When compared with more accurate flow modeling such as large-eddy simulations (LES), we observed that vertical profiles of turbulent kinetic energy and associated turbulent length scales obtained from RANS models are substantially smaller specifically in the urban canopy. Accordingly, using LES results, we revisited the urban canopy parameterizations employed in the one-dimensional model of turbulent flow through urban areas and updated the parameterization of turbulent length scale and drag coefficient. Additionally, we included the parameterization of the dispersive stress, previously neglected in the 1-D column model. For this objective, the PArallelized Large-Eddy Simulation Model (PALM) is used and a series of simulations in an idealized urban configuration with aligned and staggered arrays are considered. The plan area density (λp) is varied from 0.0625 to 0.44 to span a wide range of urban density (from sparsely developed to compact midrise neighborhoods, respectively). In order to ensure the accuracy of the simulation results, we rigorously evaluated the PALM results by comparing the vertical profiles of turbulent kinetic energy and Reynolds stresses with wind tunnel measurements, as well as other available LES and direct numerical simulation (DNS) studies. After implementing the updated drag coefficients and turbulent length scales in the 1-D model of urban canopy flow, we evaluated the results by (a) testing the 1-D model against the original LES results and demonstrating the differences in predictions between new (derived from LES) and old (derived from RANS) versions of the 1-D model, and (b) testing the 1-D model against LES results for a test case with realistic geometries. Results suggest a more accurate prediction of vertical turbulent exchange in urban canopies, which can consequently lead to an improved prediction of urban heat and pollutant dispersion at the mesoscale.

A very high-resolution assessment and modelling of urban air quality

Abstract. Urban air quality is one of the most prominent environmental concerns for modern city residents and authorities. Accurate monitoring of air quality is difficult due to intrinsic urban landscape heterogeneity and superposition of multiple polluting sources. Existing approaches often do not provide the necessary spatial details and peak concentrations of pollutants, especially at larger distances from monitoring stations. A more advanced integrated approach is needed. This study presents a very high-resolution air quality assessment with the Parallelized Large-Eddy Simulation Model (PALM), capitalising on local measurements. This fully three-dimensional primitive-equation hydrodynamical model resolves both structural details of the complex urban surface and turbulent eddies larger than 10 m in size. We ran a set of 27 meteorological weather scenarios in order to assess the dispersion of pollutants in Bergen, a middle-sized Norwegian city embedded in a coastal valley. This set of scenarios represents typically observed weather conditions with high air pollution from nitrogen dioxide (NO2) and particulate matter (PM2.5). The modelling methodology helped to identify pathways and patterns of air pollution caused by the three main local air pollution sources in the city. These are road vehicle traffic, domestic house heating with wood-burning fireplaces and ships docked in the harbour area next to the city centre. The study produced vulnerability maps, highlighting the most impacted districts for each weather and emission scenario. Overall, the largest contribution to air pollution over inhabited areas in Bergen was caused by road traffic emissions for NO2 and wood-burning fireplaces for PM2.5 pollution. The effect of emission from ships in the port was mostly restricted to the areas close to the harbour and moderate in comparison. However, the results have contributed to implementation of measures to reduce emissions from ships in Bergen harbour, including provision of shore power.

Vertically nested LES for high-resolution simulation of the surface layer in PALM (version 5.0)

Abstract. Large-eddy simulation (LES) has become a well-established tool in the atmospheric boundary layer research community to study turbulence. It allows three-dimensional realizations of the turbulent fields, which large-scale models and most experimental studies cannot yield. To resolve the largest eddies in the mixed layer, a moderate grid resolution in the range of 10 to 100 m is often sufficient, and these simulations can be run on a computing cluster with a few hundred processors or even on a workstation for simple configurations. The desired resolution is usually limited by the computational resources. However, to compare with tower measurements of turbulence and exchange fluxes in the surface layer, a much higher resolution is required. In spite of the growth in computational power, a high-resolution LES of the surface layer is often not feasible: to fully resolve the energy-containing eddies near the surface, a grid spacing of O(1 m) is required. One way to tackle this problem is to employ a vertical grid nesting technique, in which the surface is simulated at the necessary fine grid resolution, and it is coupled with a standard, coarse, LES that resolves the turbulence in the whole boundary layer. We modified the LES model PALM (Parallelized Large-eddy simulation Model) and implemented a two-way nesting technique, with coupling in both directions between the coarse and the fine grid. The coupling algorithm has to ensure correct boundary conditions for the fine grid. Our nesting algorithm is realized by modifying the standard third-order Runge–Kutta time stepping to allow communication of data between the two grids. The two grids are concurrently advanced in time while ensuring that the sum of resolved and sub-grid-scale kinetic energy is conserved. We design a validation test and show that the temporally averaged profiles from the fine grid agree well compared to the reference simulation with high resolution in the entire domain. The overall performance and scalability of the nesting algorithm is found to be satisfactory. Our nesting results in more than 80 % savings in computational power for 5 times higher resolution in each direction in the surface layer.