Simulation of an evolving convective boundary layer using a scale-dependent dynamic Smagorinsky model at near grey-zone resolutions
Efstathiou, G; Plant, R; Bopape, M-J
Date: 14 September 2018
Article
Journal
Journal of Applied Meteorology and Climatology
Publisher
American Meteorological Society
Publisher DOI
Abstract
A scale-dependent Lagrangian-averaged Dynamic Smagorinsky sub-grid
scheme with stratification effects is used to simulate the evolving convective
boundary layer of the Wangara case study in the grey-zone regime (specifically,
for grid lengths from 25 to 400 m). The dynamic Smagorinsky and standard
Smagorinsky approaches are assessed ...
A scale-dependent Lagrangian-averaged Dynamic Smagorinsky sub-grid
scheme with stratification effects is used to simulate the evolving convective
boundary layer of the Wangara case study in the grey-zone regime (specifically,
for grid lengths from 25 to 400 m). The dynamic Smagorinsky and standard
Smagorinsky approaches are assessed for first and second order quantities
in comparison with results derived from coarse-grained LES fields. In
the LES regime the sub-grid schemes produce very similar results, albeit with
some modest differences near the surface. At coarser resolutions, the use
of the standard Smagorinsky significantly delays the onset of resolved turbulence,
the delay increasing with coarsening resolution. In contrast, the dynamic
Smagorinsky scheme much improves the spin-up and so is also able
to maintain consistency with the LES temperature profiles at the coarser resolutions.
Moreover, the resolved part of the turbulence reproduces well the
turbulence profiles obtained from the coarse-grained fields, especially in the
near grey-zone. The dynamic scheme does become somewhat over-energetic
with further coarsening of the resolution, especially near the surface. The dynamic
scheme reaches its limit in our current configuration when the test filter
starts to sample at the unresolved scales returning very small Smagorinsky coefficients.
Sensitivity tests reveal that the dynamic model can adapt to changes
in the imposed numerical or sub-grid diffusion by adjusting the Smagorinsky
constant to the changing flow field and minimising the dissipation effects on
the resolved turbulence structures
Mathematics and Statistics
Faculty of Environment, Science and Economy
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