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1. Next The evening boundary layer: turbulence or no turbulence? Bas van de Wiel, Ivo van Hooijdonk & Judith Donda in collaboration with: Fred Bosveld, Peter Baas, Arnold Moene, Harm Jonker, Jielun Sun, Herman Clercx, e.a.

2. A fruitful symbiosis ~ 1 paper / year

3. Scope The very stable boundary layer: ‘cold’ How much wind needed to keep turbulence going? The weakly stable boundary layer: ‘warm’

4. Need for reliable process parameterizations

5. The collapse of turbulence:Practical track -----Formal track

6. Concept: collapse driven by SEB Idealistic case: Fresh snow (low heat capacity & conductance) Surface Energy Balance: Here: Qn denoted as H0 Regime 1 H=H0 Regime 2 H<H0

7. Non-linear diffusion K decreases with increasing dT/dz

8. Surface flux defines velocity scale

9. “Weather lab”: ensembles • Clear nights: similar radiative forcing • “Wind strength decides on regime” • Classes 40m wind: • -0.5-1.0 m/s • -1.0-1.5 m/s • -2.0-... etc.

10. Temperature inversion:T(z)-T(1.0 m) Can we predict critical wind ?

11. Turbulence ‘hockey stick’ 10m 20m 40m 80m Can we predict critical wind ?

12. Predicting minimum wind speed

13. -for given wind a flux maximum is found vice versa -for given demand (Qn-G) characteristic speed is found: Umin

14. After some calculations…… Correction for soil heat Radiative Loss parameters The minimum wind speed for sustainable turbulence

15. Height-independent regime-classification

16. Height-independent regime-classification

17. Comparison with classical parameters

18. Stability indicators Scaling based on fluxes: Scaling based on gradients: Combined scaling: Or formally: “Shear Capacity” Also combines knowledge flow AND boundary condition

19. Problem with classical stability parameters

20. Comparison with classical parameters

21. Formal track • Step 1: Direct Numerical Simulation of regime transition

22. Formal track • Step 2: Analogy with local similarity closure

23. Formal track • Step 3: analysis, prediction • -local scaling, gradient form • -model independent scaling: • -derivation from TKE-equation

24. prediction ‘normalized hockey stick’ Step 4: validation laminar turbulent

25. Conclusion • Shear Capacity (U/Umin) compares transport capacity flow to flux demand at surface • Prediction idealized configurations & observed reality Details: Van Hooijdonk et al. (2014; J.A.S. Submitted) Donda et al. (submission June 2014)

26. Outlook • Parameterisation Forecast models • DNS/LES/RANS simulations • Other climatologies: Fluxnet – data

27. Thank you for your attention

28. What’s the use?? Physically preferable In practice (Louis 1979) -Non-physical curve aimed to enhance mixing in the very stable regime only -But..... -it causes too much mixing in the well-behaved, weakly stable case as well....!

29. regime based enhanced mixing Very stable Continuous turbulent

30. Extra: relation to tke budget Note: SC=shear capacity ~ U/Umin

31. Strong wind: steady balance In the following: blue/green points

32. Weak wind: no balance initially In the following: red points

33. Maximum found in observations Here: z=40 m

34. Tendency for regeneration

35. Sensibelewarmteflux

36. Instortenturbulentietgvsterkekoeling

37. Concept