Advances in Science and Research
Advances in Science and Research
ASR
Articles | Volume 20
Articles | Volume 20
https://doi.org/10.5194/asr-20-55-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/asr-20-55-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 20
05 Jul 2023
 | 05 Jul 2023

Capturing features of turbulent Ekman–Stokes boundary layers with a stochastic modeling approach

Marten Klein and Heiko Schmidt

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Latest update: 13 Dec 2024
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Short summary
Atmospheric boundary layers are inherently unsteady and exhibit processes on multiple scales. A stochastic one-dimensional turbulence model is applied here to periodically forced Ekman flows. These flows are hard to model due to competing laminar and turbulent response mechanisms. It is shown that the model is able to capture parametric dependencies of the near-surface turbulence. The results consolidate improvements seen in a subgrid-scale application of the model within large-eddy simulations.
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