1. Craig Smith Fernando Porte-Agel WIRE, EPFL, Switzerland craig.smith@epfl.ch Craig Smith WIRE, EPFL Subgrid models in LES of drainage flows

2. Craig Smith WIRE, EPFL Why study drainage flows? Source: Whiteman 2008 z jet = 5-10m – requires very fine resolution, or highly anisotropic grids

3. Craig Smith WIRE, EPFL Science questions Predictability of drainage flows Predictability of drainage flows Subgrid model performance Subgrid model performance Monin Obukov similarity (MOS) Monin Obukov similarity (MOS) Rattlesnake Ridge – SE WA, USA Horan and Dorst, 1983

4. Craig Smith WIRE, EPFL Observations Rattlesnake Ridge – SE WA, USA Horan and Dorst, 1983  x = 7m,  y = 10m

5. Craig Smith WIRE, EPFL AB A BC Numerical setup  x = 20m,  z = 2.5-3.8m 500x20x400  x = 13.3m,  z = 1.6-2.4m 900x30x620 WIRE LES code – spectral difference in horizontal, center difference in vertical, 2 nd order Adams Bashforth in time, z 0 = 0.1 m, q sfc = -15-40 Wm -2 (not at peak) Subgrid models – Smagorinsky (wall corrected), Dynamic, Lagrangian scale dependent dynamic

6. Craig Smith WIRE, EPFL SGS models

7. Smagorinsky (wall corrected) – model coefficients are constant (isotropic homogenous TKE) Smagorinsky (wall corrected) – model coefficients are constant (isotropic homogenous TKE) Dynamic – uses a 2 nd test filter to dynamically optimize model coefficients Dynamic – uses a 2 nd test filter to dynamically optimize model coefficients Scale dependent dynamic – allows model coefficients to vary with filter size Scale dependent dynamic – allows model coefficients to vary with filter size Oregon State University College of Oceanic and Atmospheric Sciences log(E k ) log(k) k c =  InertialsubrangeresolvedscalesDissipation subrange subrange unresolvedscales SGS models

8. Craig Smith WIRE, EPFL Scale dependent Lagrangian dynamic after 45 minutes of integration Velocity Results Potential temperature

9. Craig Smith WIRE, EPFL U  TKE Scale dependent Lagrangian dynamic after 45 minutes of integration Results

10. Craig Smith WIRE, EPFL Rattlesnake ridge observations comparison Results

11. Craig Smith WIRE, EPFL U  TKE Smagorinsky ->low near surface temperature -> 10-20% more cold air flux

12. Craig Smith WIRE, EPFL Smagorinsky ->low near surface temperature -> 10-20% more cold air flux U  TKE

13. Craig Smith WIRE, EPFL Results Smagorinksy Dynamic Scale dependent dynamic Assumption of constant model coefficients in Smagorinsky

14. Craig Smith WIRE, EPFL Results Dynamic Scale dependent dynamic Assumption of scale invariance in dynamic model

15. Craig Smith WIRE, EPFL In context Observations suggest z j = 5-10m Author  bc Burkholder et al 2010-very smallperiodicmany Axelsen 2009glacial2.6x2.6x0.4periodic??? Skyllingstad 2003SE WA0.75x0.75x0.75slopeFSF Smith and Skyllingstad 2005VTMX3x3x3slopeFSF 100x100x5valley1.5 TKE (ARPS) Chow et al 2006MAP150x150x20valley1.5 TKE and DRM (ARPS) Catalano and Cenedese 2010-50x50x2valleyWRF in LES mode Zhong and Whiteman 2008VTMX250x250x2.1valley2.5 TKE (RAMS) locationsgs

16. Craig Smith WIRE, EPFL Future work Numerical setup Numerical setup Grid aspect ratio Grid aspect ratio Spanwise heterogeneity Spanwise heterogeneity Smagorinsky model for katabatic winds – constant Pr sgs

17. Craig Smith Fernando Porte-Agel WIRE, EPFL, Switzerland craig.smith@epfl.ch Craig Smith WIRE, EPFL Subgrid models in LES of drainage flows

18. Craig Smith WIRE, EPFL Smagorinsky – original vs wall corrected Results