Evaluation of the dynamic core of the PALM model system 6.0 in a neutrally stratified urban environment: Comparison between les and wind-tunnel experiments

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Gronemeier, T.; Surm, K.; Harms, F.; Leitl, B.; Maronga, B. et al.: Evaluation of the dynamic core of the PALM model system 6.0 in a neutrally stratified urban environment: Comparison between les and wind-tunnel experiments. In: Geoscientific Model Development 14 (2021), Nr. 6, S. 3317-3333. DOI: https://doi.org/10.5194/gmd-14-3317-2021

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/12407

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Sum total of downloads: 69




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Abstract: 
We demonstrate the capability of the PALM model system version 6.0 to simulate neutrally stratified urban boundary layers. Our simulation uses the real-world building configuration of the HafenCity area in Hamburg, Germany. Using PALM's virtual measurement module, we compare simulation results to wind-tunnel measurements of a downscaled replica of the study area. Wind-tunnel measurements of mean wind speed agree within 5% on average while the wind direction deviates by approximately 4 °. Turbulence statistics similarly agree. However, larger differences between measurements and simulation arise in the vicinity of surfaces where building geometry is insufficiently resolved. We discuss how to minimize these differences by improving the grid layout and give tips for setup preparation. Also, we discuss how existing and upcoming features of PALM like the grid nesting and immersed boundary condition help improve the simulation results. © 2021 Tobias Gronemeier et al.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2021
Appears in Collections:Fakultät für Mathematik und Physik

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pos. country downloads
total perc.
1 image of flag of United States United States 20 28.99%
2 image of flag of Germany Germany 17 24.64%
3 image of flag of Ireland Ireland 6 8.70%
4 image of flag of Korea, Republic of Korea, Republic of 5 7.25%
5 image of flag of France France 5 7.25%
6 image of flag of China China 5 7.25%
7 image of flag of Switzerland Switzerland 4 5.80%
8 image of flag of Russian Federation Russian Federation 2 2.90%
9 image of flag of United Kingdom United Kingdom 2 2.90%
10 image of flag of Indonesia Indonesia 1 1.45%
    other countries 2 2.90%

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