1. Stephan de Roode The art of modeling stratocumulus clouds

2. Cloud regimes – The Hadley circulation

3. ISCCP stratocumulus cloud climatology & ECMWF net shortwave radiation error

4. Stratocumulus-Topped Boundary Layer - Vertical structure Entrainment: mixing of relatively warm and dry air from above the inversion into the cloud layer

5. Stratocumulus-Topped Boundary Layer - Vertical structure

6. The representation of clouds in most GCMs K-diffusion : Massflux : K-diffusion: Mass flux:

7. Eddy diffusivity coefficient K ECMWFRACMO 2 K-profileprescribed K(z) = TKE(z) 1/2 (z) [1] stabilitycontrols K-profiles controls TKE and entrainment K = w e  z w e from parameterization by Eq. [1]

8. Strategy: Adapt TKE scheme for moist convection Develop moist TKE scheme for RACMO2 + no need for explicit entrainment parameterization + dry TKE scheme (Lenderink/Holtslag) is already present in RACMO2

9. Outline of the talk Introduction stratocumulus presence model representation of stratocumulus Moist TKE scheme some details Evaluation - GCSS cases - entrainment rates - vertical mixing & cloud liquid water path - problems Conclusions & outlook

10. TKE scheme turbulent transport pressure transport buoyancy production mechanical shear dissipation (liquid water static energy) (total specific humidity) The difference between the dry and moist TKE scheme is incorporated in the prefactors A and B diffusion on conserved variables s l and q t

11. Buoyancy flux & moist thermodynamics c f = cloud fraction,, for c f > 0, latent heat release effects

12. Length scale Length scale depends on Richardson number: buoyancy gradient in cloud computed as in TKE scheme

13. Call tree

14. suphec1c.F90: RVTMP2 = 0

15. Outline of the talk Introduction stratocumulus presence model representation of stratocumulus Moist TKE scheme some details Evaluation - GCSS cases EUROCS FIRE I (diurnal cycle) ASTEX A209 (entrainment) - vertical mixing & cloud liquid water path - problems Conclusions & outlook

16. Stratocumulus cases based on observations Prescribe in SCM version of RACMO2 - initial state - large-scale horizontal advection - large-scale subsidence rate - surface fluxes or SST Today focus on - EUROCS FIRE I diurnal cycle case - ASTEX A209 GCSS intercomparison cases

17. 1D results from General Circulation Models - Cloud liquid water path (LWP) for EUROCS FIRE I Single Column Model liquid water path results very sensitive to drizzle parameterization convection scheme (erroneous triggering of cumulus clouds) vertical resolution

18. 3D results from Large-Eddy Simulation results - The cloud liquid water path

19. FIRE I: 1D and Large-Eddy Simulation results vertical levels = 60 time step = 900 s precipitation = on/off convection= off TKE scheme: thicker cloud for FIRE I

20. Outline of the talk Introduction stratocumulus presence model representation of stratocumulus Moist TKE scheme some details Evaluation - GCSS cases EUROCS FIRE I (diurnal cycle) ASTEX A209 (entrainment) - vertical mixing & cloud liquid water path - problems Conclusions & outlook

21. ASTEX A209 _________________________________ cloud base height = 240 m cloud top height = 755 m sensible heat flux = 10 W/m 2 latent heat flux = 30 W/m 2 longwave flux jump= 70 W/m 2 max liq. water content= 0.5 g/kg LWP = 100 g/m 2  l = 5.5 K  q t = -1.1 g/kg

22. Buoyancy flux for ASTEX A209 cloud top "locked" for 60 level run and less entrainment realistic buoyancy flux profile for high-resolution run

23. Entrainment parameterizations proposed in the literature Nicholls and Turton (1986) Stage and Businger (1981), Lewellen and Lewellen (1998) VanZanten et al. (1999) Lock (1998) Lilly (2002)

24. Buoyancy flux decomposition

25. Stability jumps

26. Examples of entrainment rates [cm/s] from parameterizations Parameterization  Case  ObservedMoengLock UKMO, new ECMWF LillyNicholls- Turton MM5 Lewellen / van Zanten North Sea NT620 0.550.500.130.30 0.33 North Sea NT624 0.560.760.280.550.660.61 ASTEX A209 0.9 ± 0.31.230.420.861.060.97 ASTEX RF06 1.0 ± 0.61.240.481.041.311.33 DYCOMSII RF01 0.38 ± 0.100.720.690.620.600.64 FIRE I0.58 ± 0.08 (mean LES) 0.570.160.370.350.50  high low TKE H_Res: w e = 1.27 cm/s

27. Examples of entrainment rates [cm/s] from parameterizations Parameterization  Case  ObservedMoengLock UKMO, new ECMWF LillyNicholls- Turton MM5 Lewellen / van Zanten North Sea NT620 0.550.500.130.30 0.33 North Sea NT624 0.560.760.280.550.660.61 ASTEX A209 0.9 ± 0.31.230.420.861.060.97 ASTEX RF06 1.0 ± 0.61.240.481.041.311.33 DYCOMSII RF01 0.38 ± 0.100.720.690.620.600.64 FIRE I0.58 ± 0.08 (mean LES) 0.570.160.370.350.50  high low

28. Entrainment sensitivity: vary inversion jumps for ASTEX A209

29. Entrainment sensitivity to inversion jumps Entrainment rate depends on moisture jump with TKE scheme buoyancy reversal criterion ASTEX A209

30. Outline of the talk Introduction stratocumulus presence model representation of stratocumulus Moist TKE scheme some details Evaluation - GCSS cases EUROCS FIRE I (diurnal cycle) GCSS ASTEX A209 (entrainment) - vertical mixing & cloud liquid water path - problems Conclusions & outlook

31. Quotes from Zhu et al. (2005) on the DYCOMS II RF01 intercomparison case "The large spread in LWP in part reflects the sensitivity of liquid water content to small changes in total humidity and temperature induced by the different turbulent transport and microphysics scheme employed in the SCMs." "For two models using the same microphysics scheme, the different turbulent transport realized in models is a more important factor than microphysics for causing large LWP spread..."

32. K-coefficients from FIRE I LES

33. K-coefficient from TKE scheme compared to LES for FIRE I

34. The role of the K-coefficient on the vertical cloud structure - Test different K-profiles 3. Compute vertical profiles from integration same change 1. Play with magnitude K profiles 2. Use fixed flux profiles 4. Diagnose cloud liquid water content

35. Total water content as a function of magnitude K

36. Liquid water content as a function of magnitude K K factorLWP [g/m 2 ] 0.22 0.552 1.079 2.094 5.0103  109 Magnitude K-coefficient in interior BL important for cloud liquid water content!

37. Outline of the talk Introduction stratocumulus presence model representation of stratocumulus Moist TKE scheme some details Evaluation - GCSS cases EUROCS FIRE I (diurnal cycle) GCSS ASTEX A209 (entrainment) - vertical mixing & cloud liquid water path - problems Conclusions & outlook

38. Two-layer structure for K-profile - Example for ASTEX A209

39. Fluxes of conserved variables - Example for ASTEX A209 TKE scheme: fluxes of  l and q t not linear Effect standard (coarse) 60 level vertical resolution is obvious

40. Evaluation of TKE scheme: Conclusions GCSS cases Diurnal cycle of EUROCS FIRE I is represented reasonably well Entrainment rate depends on moisture jump (as like some parametrizations) Eddy diffusivity K-profile K-profile controls cloud liquid water path - Eddy diffusivities for q t and  l usually differ Potential problem for K-profile below cloud base (two-layer structure) Further remarks Coarse vertical resolution can be problematic Fluxes appear not to be linear in the boundary layer Cloud scheme seems to maintain clouds for relatively low relative humidities (not shown)

41. Outlook Next step(s) Combine TKE scheme with mass-flux approach (Eddy-Diffusivity Mass-Flux => EDMF) Does this solve the two-layer eddy-diffusivity structure? but also Snow Janneke Ettema Stable boundary layerPeter Baas Cabauw Reinder Ronda Climate Geert Lenderink, Erik van Meijgaard, Willem-Jan van de Berg Radiation Dave Donovan and Gerd-Jan van Zadelhoff Cloud effective radius Gabriella de Martino Precipitation Margreet van Zanten Cumulus convectionPier Siebesma => meeting dedicated to RACMO?