Large eddy simulation of stable boundary layers with a prognostic subgrid tke equation
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Large Eddy Simulation of Stable Boundary Layers with a prognostic subgrid TKE equation. Stephan R. de Roode and Vincent Perrin Clouds, Climate and Air Quality, Dept. of Applied Sciences , Delft University of Technology, Delft, Netherlands. 8 th Annual Meeting of the EMS, Amsterdam, 2008.

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Large eddy simulation of stable boundary layers with a prognostic subgrid tke equation

Large Eddy Simulation of Stable Boundary Layers with a prognostic subgrid TKE equation

Stephan R. de Roode and Vincent Perrin

Clouds, Climate and Air Quality, Dept. of Applied Sciences,

Delft University of Technology, Delft, Netherlands

8th Annual Meeting of the EMS, Amsterdam, 2008


Contents

Contents prognostic subgrid TKE equation

Problem/question

- Dutch LES model: Stable boundary layer simulation dominated by subgrid contributions

Strategy

- Analysis of subgrid prognostic TKE model

LES results

- subgrid vs resolved

- similarity relations

- high resolution results

Conclusions

8th Annual Meeting of the EMS, Amsterdam, 2008


Prognostic subgrid tke equation deardorff 1980

Prognostic subgrid TKE equation (Deardorff 1980) prognostic subgrid TKE equation

 subgrid fluxes ,

 eddy diffusivity

 length scale

 subgrid TKE

8th Annual Meeting of the EMS, Amsterdam, 2008


Gabls sbl intercomparison case

GABLS SBL intercomparison case prognostic subgrid TKE equation

 Neutral layer becomes stable due to a prescribed surface cooling (-0.25 K/h)

 Original set up according to Beare et al. (2003): Dx=Dy=Dz=6.25 m

 Length scale correction turned off: l=D=(Dx Dy Dz)1/3

 ch=cm(ch,1+ch,2,l/D) = cm(ch,1+ch,2)

 cm=0.12, ch,1=1, ch,2=2

8th Annual Meeting of the EMS, Amsterdam, 2008


Les results examples taken from the 5th hour

LES results: Examples taken from the 5th hour prognostic subgrid TKE equation

Turbulent fluxes dominated

by subgrid contribution


Solution close to smagorinsky model s solution

prognostic subgrid TKE equationSmagorinsky subgrid TKE solution:

 LES subgrid constants: cf=2.5  cm=0.12, ce=0.76

corresponding Smagorinsky constant: cs=0.22

Solution close to Smagorinsky model's solution


Changing the filter constant c f 2 5 2

Changing the filter constant c prognostic subgrid TKE equationf=2.52

Less filtering  more resolved motions


Subgrid constants c m and c h

Subgrid constants c prognostic subgrid TKE equationm and ch

lowerRig,

more resolved

ch more mixing of pot. temp.

cm more mixing of hor. winds


Similarity relations

Solution if solution is 100% subgrid prognostic subgrid TKE equation

(Baas et al., 2008)

Similarity relations


Similarity relations c f 2 c m 0 096

DNS Van der Wiel et al. (2008) prognostic subgrid TKE equation

Similarity relations: cf=2 (cm=0.096)


High resolution d x d y d z 1 5626m

High resolution: prognostic subgrid TKE equationDx=Dy=Dz=1.5626m


Conclusions

Conclusions prognostic subgrid TKE equation

1. D=6.25 m resolution not enough

- Solution dictated by Smagorinsky subgrid TKE solution

- too much dependency on subgrid constants: bad simulation

- recommendation: refine grid resolution (smaller D)

2. High resolution simulation

- smaller gradient for fm and fh compared to observations and DNS