Overview of the PALM model system 6.0

Maronga, Björn; Banzhaf, Sabine; Burmeister, Cornelia; Esch, T.; Forkel, R.; Fröhlich, Dominik; Fuka, Vladimír; Gehrke, Katrin Frieda; Geletič, Jan; Giersch, Sebastian; Gronemeier, Tobias; Groß, Günter; Heldens, Wieke; Hellsten, Antti; Hoffmann, Franziska; Inagaki, Atsushi; Kadasch, Eckhard; Kanani-Sühring, Farah; Ketelsen, Klaus; Khan, Basit; Knigge, Christoph; Knoop, Helge; Krč, Pavel; Kurppa, Mona; Maamari, Halim; Matzarakis, Andreas; Mauder, Matthias; Pallasch, Matthias; Pavlik, Dirk; Pfafferott, Jens; Resler, Jaroslav; Rißmann, Sascha; Russo, Emmanuele; Salim, Mohamed; Schrempf, Michael; Schwenkel, Johannes; Seckmeyer, Günther; Schubert, Sebastian; Sühring, Matthias; Tils, Robert von; Vollmer, Lukas; Ward, Simon; Witha, Björn; Wurps, Hauke; Zeidler, Julian; Raasch, Siegfried

doi:10.5194/gmd-13-1335-2020

Cited by 191 publications

(144 citation statements)

References 124 publications

(160 reference statements)

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“…However, Oceananigans.jl features a more efficient non-hydrostatic pressure solver than MITgcm (and MOM6 is strictly hydrostatic). PALM (Maronga et al, 2020) is Fortran software for large eddy simulation of atmospheric and oceanic boundary layers with complex boundaries on parallel CPU and GPU architectures. Oceananigans.jl is distinguished by its use of Julia which allows for a scriptbased interface as opposed to a configuration-file-based interface used by MITgcm, MOM6, and PALM.…”

Section: Fig 1: (Left)mentioning

confidence: 99%

Oceananigans.jl: Fast and friendly geophysical fluid dynamics on GPUs

Ramadhan¹,

Wagner²,

Hill³

et al. 2020

JOSS

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Oceananigans.jl is a fast and friendly software package for the numerical simulation of incompressible, stratified, rotating fluid flows on CPUs and GPUs. Oceananigans.jl is fast and flexible enough for research yet simple enough for students and first-time programmers. Oceananigans.jl is being developed as part of the Climate Modeling Alliance project for the simulation of small-scale ocean physics at high-resolution that affect the evolution of Earth's climate.

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Section: Fig 1: (Left)mentioning

confidence: 99%

Oceananigans.jl: Fast and friendly geophysical fluid dynamics on GPUs

Ramadhan¹,

Wagner²,

Hill³

et al. 2020

JOSS

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“…The PALM model system is freely available from http://palm-model.org and distributed under the GNU General Public License v3 (http://www.gnu.org/copyleft/gpl.html). The code version used and all input files are permanently available under https://doi.org/10.25835/0005529 (Gehrke et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…The radiation components are defined positive according to their direction (SW ↓ and LW ↓ positive downwards; SW ↑ and LW ↑ positive upwards). The radiative fluxes are provided by one of the available radiation schemes in PALM (for details, see Maronga et al, 2020).…”

Section: Energy Balance Solvermentioning

confidence: 99%

“…Note that for water surfaces, a Charnock parameterization can be switched on for taking into account the effect of subgrid-scale wave motions through the roughness lengths. For details on the particular implementation of MOST and the Charnock parameterization in PALM, see Maronga et al (2020). Note that r a is calculated based on u * and θ * values from the current time step to calculate H at the prognostic time step.…”

Section: Parameterization Of Fluxesmentioning

confidence: 99%

“…Accordingly, the degree of freedom is reduced and we can focus on parameters of the LSM rather than additional uncertainties of a radiation model. Nonetheless, we performed sensitivity tests using the Rapid Radiation Transfer Model for Global Models (RRTMG, Clough et al, 2005) as well as a clear-sky radiation parameterization, which are described in detail in Maronga et al (2020). The longwave outgoing radiation of the surface is calculated from the skin-layer temperature using Stefan-Boltzmann law.…”

Section: Simulation Setupmentioning

confidence: 99%

See 2 more Smart Citations

Modeling of land-surface interactions in the PALM model system 6.0: Land surface model description, first evaluation, and sensitivity to model parameters

Gehrke¹,

Sühring²,

Maronga³

2020

Preprint

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Abstract. In this paper the land-surface model embedded in the PALM model system is described and evaluated against in-situ measurement data in Cabauw. For this, two consecutive clear-sky days are simulated and the components of surface energy balance, as well as near-surface potential temperature, humidity and horizontal wind speed are compared against observation data. For the simulated period, components of the energy balance agree well during day- and nighttime, and also the daytime Bowen ratio agrees fairly well compared to the observations. Although the model simulates a significantly more stably-stratified nocturnal boundary layer compared to the observation, near-surface potential temperature and humidity agree fairly well during day. Moreover, we performed a sensitivity study in order to investigate how much the model results depend on land-surface and soil specifications, as well as atmospheric initial conditions. By this, we find that a false estimation of the leaf area index, the albedo, or the initial humidity causes a serious misrepresentation of the daytime turbulent sensible and latent heat fluxes. During night, the boundary-layer characteristics are mostly affected by grid size, surface roughness, and the applied radiation schemes.

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Evaluating modelled winds over an urban area using ground‐based Doppler lidar observations

Filioglou

Preißler²,

Troiville³

et al. 2022

Meteorological Applications

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Wind information in urban areas is essential for many applications related to air pollution, urban climate and planning, safety of drone-related operations, and assessment of urban wind energy potential. These applications require accurate wind forecasts, and obtaining this information in an urban environment is challenging as the morphology of a city varies from street to street, altering the wind flow. Remote sensing techniques such as Doppler lidars (light detection and ranging) provide a unique opportunity for wind forecast verification as they can provide both the vertical profile of the horizontal wind and the spatial variation in the horizontal domain at high resolution. In this study, the performance of numerical weather prediction (NWP) models, analysis systems, and large-eddy simulation (LES) models have been analysed by comparing the modelled winds against Doppler lidar observations under various atmospheric conditions and from season to season, in the coastal environment of Helsinki, Finland. The long-term mean vertical profile of the modelled horizontal wind shows good agreement with observations; the NWP model and the analysis systems selected here exhibit different strengths and weaknesses depending on the atmospheric conditions but no significant diurnal variation in performance. However, both the model and analysis systems show differences in their spatially-averaged bias when investigating different wind directions. LES verification shows that these models can potentially provide winds down to Associated post doc with Vaisala through PoDoCo program.

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Overview of the PALM model system 6.0

Cited by 191 publications

References 124 publications

Oceananigans.jl: Fast and friendly geophysical fluid dynamics on GPUs

Oceananigans.jl: Fast and friendly geophysical fluid dynamics on GPUs

Modeling of land-surface interactions in the PALM model system 6.0: Land surface model description, first evaluation, and sensitivity to model parameters

Evaluating modelled winds over an urban area using ground‐based Doppler lidar observations

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