A nested multi-scale system implemented in the large-eddy simulation model PALM model system 6.0

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Hellsten, A.; Ketelsen, K.; Sühring, M.; Auvinen, M.; Maronga, B. et al.: A nested multi-scale system implemented in the large-eddy simulation model PALM model system 6.0. In: Geoscientific Model Development 14 (2021), Nr. 6, S. 3185-3214. DOI: https://doi.org/10.5194/gmd-14-3185-2021

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Zum Zitieren der Version im Repositorium verwenden Sie bitte diesen DOI: https://doi.org/10.15488/12408

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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. © 2021 Antti Hellsten et al.
Lizenzbestimmungen: CC BY 4.0 Unported
Publikationstyp: Article
Publikationsstatus: publishedVersion
Erstveröffentlichung: 2021
Die Publikation erscheint in Sammlung(en):Fakultät für Mathematik und Physik

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