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Scaling, Anisotropy, and Complexity in Near-Surface Atmospheric Turbulence
Ivana Stiperski1, Marc Calaf2, Mathias W Rotach1
1Department of Atmospheric and Cryospheric Sciences University of Innsbruck Innsbruck Austria.
Separating turbulence data by anisotropy states improves near-surface scaling over complex terrain. This finding suggests a unified framework for turbulence scaling is possible, even over varied landscapes.
Area of Science:
- Atmospheric science
- Fluid dynamics
- Geophysics
Background:
- Unified similarity scaling has been unsuccessful over complex surfaces.
- Previous studies showed improved scaling for flat terrain by separating data based on turbulence anisotropy states.
Purpose of the Study:
- To investigate if separating turbulence data by anisotropy states improves near-surface scaling over complex terrain.
- To explore the possibility of a unified framework for turbulence scaling across diverse terrains.
Main Methods:
- Examined near-surface scaling using 12 diverse datasets from flat to mountainous terrain.
- Separated data according to limiting states of turbulence anisotropy (isotropic, two-component axisymmetric, one-component).
Main Results:
- Separating data by anisotropy states significantly improved data collapse onto common scaling relations.
- Identified a measure of turbulence complexity and its relation to scaling breakdown.
Conclusions:
- The separation by anisotropy states enhances turbulence scaling over complex terrain.
- Findings indicate potential for a unified framework for turbulence scaling, considering anisotropy and terrain complexity.
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