1. Parameterization of atmospheric stratification
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Parameterization of atmospheric stratification
and issues in connection with canopy flow
Sogachev Andrey
Wind Energy Division, Risø National Laboratory for Sustainable Energy , DTU, Building 118, Box 49, DK-4000, Roskilde, Denmark,

2. SCADIS (scalar distribution) model: overview
Basic equations:
momentum,
heat,
moisture,
scalars (CO2, SO2, O3),
turbulent kinetic energy (E)
One-and-a-half-order turbulence closure
based on equations of E and ε (dissipation rate) : ( E-l, E-ε.)
E-ω closure based on ω (ε/E) equation
Terrain-following coordinate system
Horizontal and vertical resolutions
(depending on a specific problem)
(Sogachev et al., 2002, 2004; Sogachev and Panferov, 2006; Sogachev et al., 2008, Sogachev 2009)

3. l o w e r b o u n d a r y c o n d i t i o n s
SCADIS model: domain
q(t),
T(t),
C(t),
V(t),
U(t)
Clouds ( t ) T
soil ), q F
CO2
V = 0 ,
U = 0 Q
t),
l o w e r b o u n d a r y c o n d i t i o n s
3 - 5 km km
Upper boundary conditions
(Sogachev et al., 2002, 2004; Sogachev and Panferov, 2006; Sogachev et al., 2008, Sogachev 2009)

4. SCADIS model: physical processes in the model grid-cellF
CO2 E R H G y f x , m
advection
(Sogachev et al., 2002, 2004; Sogachev and Panferov, 2006; Sogachev et al., 2008, Sogachev 2009)

5. Turbulence model: governing equations
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Turbulence model: governing equations
with
with

6. Accounting for plant drag and buoyancy: the traditional way
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Accounting for plant drag and buoyancy: the traditional way ?
( Raupach and Shaw, 1982 )
( Apsley and Castro, 1997)
(Blackadar, 1962)

7. Modelling of Askervein flow
Askervein Hill topographic map (brawn isolines) and dimensionless speed-up, ΔS estimated by SCADIS at z = 10 m above the ground (colored field). Figure 1 also shows the reference site (RS) (with ΔS = 0 ), the 210o wind direction in our simulations and the lines A, AA and B along which the measurements were made. Background of Figure 1 is taken from Castro et al., 2003.

8. Modelling of Askervein flow
(b)
Dimensionless speed-up, ΔS at z = 10 m above the ground along lines A (a) and AA (b). During measurements along line AA two different sets of instruments were used.

9. Uncertainties: buoyancy
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Uncertainties: buoyancy
(Baumert and Peters, 2000)

10. Uncertainties: dissipation
( Ayotte et al., 1999 )
(Sogachev and Panferov., 2006)

11. Accounting for plant drag and buoyancy: the revised way
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Accounting for plant drag and buoyancy: the revised way
(Seginer et al., 1976)
( Raupach and Shaw, 1982 )
( Apsley and Castro, 1997)
(Blackadar, 1962)
(Sogachev and Panferov, 2006 )
(Sogachev 2009 )

12. Accounting for plant drag and buoyancy: the revised way
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Accounting for plant drag and buoyancy: the revised way

13. Treatment of the plant drag
►The Elora corn
canopy
(Wilson et al., 1982;
Wilson, 1988)
▲The Pine forest canopy
(Katul and Chang, 1999)
◄Furry hill
wind-tunnel experiment
(Finnigan and Brunet, 1995)
(after Sogachev and Panferov, 2006)

14. Treatment of the plant drag
The basic requirement of K-theory – that the length scale of the mixing process be substantially smaller than that of the inhomogeneity in the mean scalar or momentum gradient (Corrsin 1974) – is not violated for disturbed flow and for slow spatial variation of cdA (Finnigan and Belcher, 2004).
SCADIS reproduces the experimental variation in length scales
(Sogachev and
Panferov, 2006)

15. Verification: low-roughness surface
Wind speed ( m s-1 )
Fig. 1 (a) ABL wind evolution and (b) surface characteristics: u* and Monin-Obukhov length, L, during fair weather over low-roughness land derived by E-ω model.
Converse Prandtl number
(Businger et al. 1971, Sogachev et al. 2002)

16. Uncertainties: Turbulent Prandtl number, Pr versus Ri
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Uncertainties: Turbulent Prandtl number, Pr versus Ri

17. Verification: low-roughness surface
Fig. 2 (a) Wind evolutions and (b) wind profiles for different hours in the atmospheric surface layer during fair weather over low-roughness land derived by E-ω and analytical models.
(Paulson, 1970)

18. Verification: forested surface
(Laakso et al., 2007)

19. Uncertainties: buoyancy inside canopy
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Uncertainties: buoyancy inside canopy

20. Uncertainties: buoyancy inside canopy
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Uncertainties: buoyancy inside canopy
(Sogachev and Panferov, 2006 ) ?

21. Uncertainties: buoyancy inside canopy
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Uncertainties: buoyancy inside canopy

22. Uncertainties: buoyancy inside canopy
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Uncertainties: buoyancy inside canopy
H =16 m, LAI = 1.38
(Christen and Novak, 2008)

23. slide
ABL evolution

24. Energy budget above canopy layer
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Energy budget above canopy layer

25. slide
Ri in ABL

26. slide
Low-level jet

27. Low-level jet effects on wind energy related variables
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Low-level jet effects on wind energy related variables

28. slide
Summary
Much work remains to be done…