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

Hellsten, Antti; Ketelsen, Klaus; Sühring, Matthias; Auvinen, Mikko; Maronga, Björn; Knigge, Christoph; Barmpas, Fotios; Tsegas, Georgios; Moussiopoulos, Nicolas; Raasch, Siegfried

doi:https://doi.org/10.5194/gmd-14-3185-2021

Articles | Volume 14, issue 6

https://doi.org/10.5194/gmd-14-3185-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

The PALM model system 6.0 for atmospheric and oceanic boundary-layer...

https://doi.org/10.5194/gmd-14-3185-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 6

Development and technical paper

|

03 Jun 2021

Development and technical paper |

| 03 Jun 2021

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

Antti Hellsten, Klaus Ketelsen, Matthias Sühring, Mikko Auvinen, Björn Maronga, Christoph Knigge, Fotios Barmpas, Georgios Tsegas, Nicolas Moussiopoulos, and Siegfried Raasch

Data sets

A Nested Multi-Scale System Implemented in the Large-Eddy Simulation Model PALM model system 6.0 [Draft] Antti Hellsten, Klaus Ketelsen, Matthias Sühring, Mikko Auvinen, Björn Maronga, Christoph Knigge, Fotios Barmpas, Georgios Tsegas, Nicolas Moussiopoulos, and Siegfried Raasch https://doi.org/10.25835/0090593

Model code and software

A Nested Multi-Scale System Implemented in the Large-Eddy Simulation Model PALM model system 6.0 [Draft] Antti Hellsten, Klaus Ketelsen, Matthias Sühring, Mikko Auvinen, Björn Maronga, Christoph Knigge, Fotios Barmpas, Georgios Tsegas, Nicolas Moussiopoulos, and Siegfried Raasch https://doi.org/10.25835/0090593

Short summary

Large-eddy simulation (LES) of the urban atmospheric boundary layer involves a large separation of turbulent scales, leading to prohibitive computational costs. An online LES–LES nesting scheme is implemented into the PALM model system 6.0 to overcome this problem. Test results show that the accuracy within the high-resolution nest domains approach the non-nested high-resolution reference results. The nesting can reduce the CPU by time up to 80 % compared to the fine-resolution reference runs.