1. Page 1© Crown copyright Modelling the stable boundary layer and the role of land surface heterogeneity Anne McCabe, Bob Beare, Andy Brown EMS 2005

2. Page 2© Crown copyright Outline  the stable boundary layer in numerical weather prediction (NWP) models  parametrization of turbulent fluxes in the Met Office Unified Model  implications of large eddy model and single column model for idealised case  preliminary investigation into the role of surface heterogeneity in generating increased mixing in NWP models

3. Page 3© Crown copyright Stable Boundary Layer Characteristics:  turbulence generated by shear and suppressed by buoyancy forces  boundary layer is shallow, eddies small  typically occurs at night  nocturnal jet Accurate representation of the stable boundary layer in numerical weather prediction (NWP) models is important for many reasons. For example,  forecasting surface temperatures  predicting the timing and extent of fog formation  assessing impact of dispersion

4. Page 4© Crown copyright Parametrization Techniques Parametrization of turbulent fluxes: Choice of stability functions: Long tails Sharpest

5. Page 5© Crown copyright LEM results (GABLS intercomparison) LEM simulations from GABLS intercomparison give closest match to SHARP scheme

6. Page 6© Crown copyright SCM results – 38 levels Long tails shows too much mixing in the boundary layer, relative to LEM results Sharp tails gives a better match for the potential temperature profile, but underestimates height and strength of the nocturnal jet

7. Page 7© Crown copyright SCM results – 70 levels At higher resolution the sharp function matches the LEM profiles more closely Little improvement for long-tails

8. Page 8© Crown copyright Long tails vs Sharp tails  long tails known to overestimate mixing in the stable boundary layer relative to large eddy simulations  sharp tails gives closer match to LEM – so why is sharp tails not used in NWP models?  Met Office and ECMWF models show a reduction in NWP skill scores when sharp function used  why is more mixing needed in NWP models?  could effects of surface heterogeneity be important?

9. Page 9© Crown copyright Heterogeneity – Case Study Night of 16 Feb 2005 cold night, min -1.5C, max 5.0C clear skies low winds Limited area model run over Southern England 200km × 144km domain 1km horizontal resolution 76 vertical levels heterogeneous surface consisting of towns and countryside, gentle hills with orography ranging from sea level to max of 300m

10. Page 10© Crown copyright Richardson Number Variability

11. Page 11© Crown copyright Area Averaging 1km simulation is divided into 8km grid boxes average values of shear and buoyancy gradient in each grid box are used to compute average buoyancy flux for each 8km box actual buoyancy flux is computed at each 1km grid point and then averaged over 8km box comparison of these gives adjusted stability function

12. Page 12© Crown copyright Adjusted stability function

13. Page 13© Crown copyright Summary  NWP skill scores require more mixing in the stable boundary layer than indicated by LES  NWP models typically run with horizontal grid lengths of 12km and above  variations at the surface occur over much shorter length scales and may contribute to more mixing in the stable boundary layer  high resolution run of Met Office Unified Model captures more surface heterogeneity  averaging up to a coarser grid indicates that sharp function may be underestimating mixing in the lower layers

14. Page 14© Crown copyright Future Work  run with increased vertical resolution - to what height does the effect of surface heterogeneity extend? - is this in accord with blending height theory?  alternative case studies - are the results case specific, or can they be applied generally? - how much surface variability is needed for the effects to be extended throughout the boundary layer?  LEM simulations - can the effects of surface heterogeneity be further understood in more idealised cases?

15. Page 15© Crown copyright Questions & Answers