1. Page 1© Crown copyright 2005 Stratocumulus Adrian Lock

2. Page 2© Crown copyright 2005 Overview  Stratocumulus climatology and recent changes in its representation in the Met Office climate model  Summary of ‘important’ aspects of the boundary layer parametrization  Other issues  Cloud scheme complexity  Resolution  GCM dynamics and grid staggering

3. Page 3© Crown copyright 2005 Inversion Cloud base Tropopause Sub-tropics tropics Inversion Subsidence F q,T Entrainment Increasing SST Borrowed from Pier Siebesma

4. Page 4© Crown copyright 2005 Stratocumulus climatology  Extensive cloud cover in the subtropics  Significant SW radiative impact (cooling the planet)  Errors lead to  SST errors in coupled climate models  surface temperature errors over land  Latest IPCC round includes an almost completely new Met Office model, HadGEM1

5. Page 5© Crown copyright 2005 Climate model JJA total cloud amount HadGAM1(Released 2004) HadGAM1 - HadAM3(Released 1996) HadGAM1 - ISCCPISCCP

6. Page 6© Crown copyright 2005 Climate model improvement in low level cloud amount ISSCP HADAM3 (~1996) HadGAM1(~2004) Thick (scale 0-20%) Intermediate (scale 0-40%)  HadAM3 had excessive thick low cloud and too little thin  HadGAM1 very much better

7. Page 7© Crown copyright 2005 GCM cross-section intercomparison (Siebesma et al 2004 and now GCSS)  GCMs, data from JJA 1998  Cross-section from California to central Pacific  General underestimate of stratocumulus?  HadGAM1 not too bad  HadAM3 wouldn’t look too bad either HadGAM1 x x x x x x x x California Central Pacific HadGAM1 total cloud cover California SSMI (all clouds) HadGAM1 (low clouds)

8. Page 8© Crown copyright 2005 Met Office GCM cloud fractions EUROCS cross-section – 1998 JJA mean Layer cloud fraction Convective cloud fraction California ITCZ HadGAM1 (Released 2004) HadAM3 (Released 1996) ITCZ California  HadGAM1 has more realistic boundary layer structure

9. Page 9© Crown copyright 2005 GPCI: SW radiation  More spread between models in radiation fluxes than in the clouds themselves  HadGAM1 has too much cloud in the Sc-Cu transition region HadGAM1

10. Page 10© Crown copyright 2005 LWP Diurnal cycle validation against satellite  Wood et al (2002) analysed mean LWP diurnal cycle from satellite microwave measurements ( )  Lock (2004) compared with HadGAM1 for the data from the EUROCS intercomparison (JJA in NE Pacific) HadGAM1: JJA mean LWP (kgm -2 ) Wood et al area x x x x x X EUROCS points LWP kgm -2

11. Page 11© Crown copyright 2005 Validation against EPIC profiles  Comparison of HadGAM1 October mean profiles with mean profiles from EPIC for 16-21 October 2001 at (85W, 20S)  But HadGAM1 monthly mean LWP ~ 70gm -2 compared to the observed 150gm -2 HadGAM EPIC

12. Page 12© Crown copyright 2005 Why the improvement from HadCM3 to HadGEM1?  Virtually everything is changed!  Doubled resolution (vertical and horizontal)  New dynamics  New Physics:  Microphysics  Cloud scheme (Smith + parametrized RHcrit)  Convection scheme (revised closure, triggering, CMT)  Radiation ~ the same?!  Plus new boundary layer scheme…

13. Page 13© Crown copyright 2005 The new boundary layer parametrization in HadGEM1  Old scheme (HadAM3)  Local Ri-dependent scheme  Kept for stable boundary layers in HadGEM1  Non-local parametrization for unstable boundary layers  Specified (robust) profiles of turbulent diffusivities, for turbulence driven from the surface and/or cloud-top  Explicit BL top entrainment parametrization  Mass-flux convection scheme trigger based on boundary layer structure rather than local instability  BL mixes in subcloud layer, mass-flux in cloud layer  PBL scheme ~ a mixed layer model on a finite-difference grid

14. Page 14© Crown copyright 2005 Mixed layer framework - motivation  Marine stratocumulus is often an equilibrium state arising from complicated interactions between many processes that are parametrized in GCMs  Need to replicate this balance within GCM parametrizations, often using schemes that currently operate independently  Simple conceptual framework: mixed layer model  turbulent mixing generally ensures that variables conserved under moist adiabatic ascent are close to uniform in the vertical. For example:

15. Page 15© Crown copyright 2005 Observed profiles from stratocumulus Price (QJ, 1999) Stevens et al (QJ,2003)

16. Page 16© Crown copyright 2005 Mixed layer model  Integrating over the boundary layer and assuming a discontinuous inversion gives the mixed layer model equations: where is the jump across the inversion and is the entrainment rate.  Mixed layer model is simple but effective  highlights the importance of entrainment

17. Page 17© Crown copyright 2005 Entrainment efficiency (Stevens, 2002)  Cloud-top radiative cooling both cools the ML but also drives entrainment and so warms (and dries) it  Net effect of radiative cooling on ML evolution is therefore a strong function of the entrainment efficiency  Eg. for ‘minimal’ model:  Uncertain – parametrizations in the literature give widely different entrainment efficiencies (Stevens, 2002):

18. Page 18© Crown copyright 2005 Entrainment efficiencies (Stevens, 2002)  Differences in variability of entrainment efficiency as well as its magnitude  AL is noticeably weaker 0.4 0.7 0.9 0.7 0.8 0.5

19. Page 19© Crown copyright 2005 LES Cloud free:  = surface heated Smoke clouds: = radiatively cooled = surf heat + rad cool Water clouds: X = rad cool (no b.r.) + = rad cool + buoy rev = buoyancy reversal only Observations = Nicholls & Leighton,1986; Price, 1999; Stevens et al 2003 Verification of entrainment parametrization against LES and observations Parametrized entrainment rate (m/s) Actual entrainment rate (m/s)

20. Page 20© Crown copyright 2005 Entrainment parametrization in GCMs  Hard to parametrize on (coarse) GCM grids using traditional down-gradient diffusion because gradients at inversions are large and  K(Ri): local stability dependence is not relevant  K(z/z i ): very sensitive to the definition of z i  K(TKE): accurate TKE evolution hard to resolve  Explicit parametrization requires a formulation for w e  Uncertain  But you know what you are (or should be) getting

21. Page 21© Crown copyright 2005 Numerical handling of inversions  All model processes (turbulence, radiation, LS advection) should be coupled to preserve mixed layer budgets  i.e., no spurious numerical transport across inversion (Stevens et al 1999, Lenderink and Holtslag 2000, Lock 2001, Grenier and Bretherton 2001, Chlond et al 2004)  Explicit BL top entrainment parametrization with flux-coupling  A subgrid inversion diagnosis takes tendencies from subsidence, radiation and turbulence and realistically distributes them between the mixed layer and the inversion grid-level – ‘inversion flux-coupling’ x x x x x Entrainment Subsidence Mixed layer GCM inversion grid-level (cools/warms) Real inversion (rises/falls)  l profile (idealised mixed layer) Free atmosphere

22. Page 22© Crown copyright 2005 Diagnosis of subgrid mixed-layer model profile X X X X X Inversion grid-level GCM cell-averages Subgrid profile Parcel ascent  vl =  l ( 1+r m q t ) Flux grid-levels  Identify ‘inversion grid-level’  Extrapolate GCM profiles into the inversion grid-level  Assume a discontinous subgrid inversion  Calculate subgrid inversion height and strength

23. Page 23© Crown copyright 2005 Example calculation of grid-level entrainment fluxes (ignoring subsidence) Radiative flux X X = GCM fluxes Heat Fluxes X X X X X X Inversion grid-level Flux grid-levels = mixed layer model fluxes  Subsidence fluxes across the inversion must be coupled similarly X X X X

24. Page 24© Crown copyright 2005 Impact of inversion treatment  SCM: Time-height contour plots of liquid water from simulations with subsidence > entrainment but ML budget (so cloud depth) stationary With inversion flux-coupling Without inversion flux-coupling  GCM: JJA mean liquid water path With inversion flux-coupling: Impact of removing inversion flux-coupling: Inversion height  Errors from not coupling fluxes amount to spurious additional entrainment

25. Page 25© Crown copyright 2005 Equilibrium mixed layers – Stevens 2002  Minimal model with entrainment efficiency of 0.5  For this fixed entrainment efficiency, heading towards California (increasing divergence, reducing SST):  Strong response: z i decreases, wT surf increases (contours)  Weaker response: LWP decreases, wq surf decreases (grey-scales)  Minimal model not too far from reality Towards California

26. Page 26© Crown copyright 2005 Mixed layer model sensitivity to entrainment efficiency  Minimal model with entrainment efficiency of 0.5  Efficiency of 1: lower LWP, much reduced wT surf Towards California

27. Page 27© Crown copyright 2005 GCM cloud sensitivity to entrainment Std Met Office 2 x w e No flux coupling  Test GCM sensitivity to cloud-top entrainment  More active entrainment (either explicit or numerical) gives an equilibrium state with smaller surface heat fluxes and less stratocumulus (as in Stevens, 2002)  Removing inversion flux-coupling is more severe than doubling w e

28. Page 28© Crown copyright 2005 Surface heat flux sensitivity to entrainment Standard Met Office 2 x w e No flux coupling Expect spurious numerical entrainment to be so increases as you approach the coast Implies wT surf would reduce towards the coast As it does if flux-coupling removed in Met Office GCM As it does in other GCMs from EUROCS Spurious or deliberate increase in parametrized entrainment efficiency?

29. Page 29© Crown copyright 2005 Entrainment efficiencies (Stevens, 2002)  None of these proposed parametrizations show entrainment efficiency increasing ‘towards California’ 0.4 0.7 0.9 0.7 0.8 0.5 0.81.0 0.8

30. Page 30© Crown copyright 2005 What about precipitation?  But AL is still a ‘weak’ entrainment parametrization  Is this being compensated for in HadGAM1 by a spuriously high drizzle rate?  Requires a drizzle climatology – satellite borne radar? HadGAM1 No obs!

31. Page 31© Crown copyright 2005 Other issues  Cloud scheme  Prognostic vs diagnostic – does it matter?  Vertical resolution  Decoupling – structure within ‘mixed’ layers  New Dynamics

32. Page 32© Crown copyright 2005 Other issues – cloud scheme complexity  Cloud-top height dependence on cloud scheme: HadGAM1 (Smith) PC2 (prognostic q l and C F )

33. Page 33© Crown copyright 2005 Other issues – partial cloud cover Near Hawaii C F ~0.1 Convection scheme Somewhere in between! C F ~0.5 ? Near LA C F ~1 BL scheme

34. Page 34© Crown copyright 2005 Other issues – cloud scheme number of events (%) all clouds low clouds (>700hPa) all clouds low clouds (>700hPa) AM2p12b ARPEGE CAM 3.0 GSM 0412 HadGAM RACMO2 all clouds low clouds (>700hPa) Histograms of Cloud Cover JJA 1998 JJA 2003 Cloud cover PDFs from GPCI  Medium cloud cover  Relatively low occurrence in HadGAM1  Mixed layer model would break down  Possible cause of excessive cloud problems in Sc-Cu transition? HadGAM1: Latitude 0 Low cloud cover 1

35. Page 35© Crown copyright 2005 Other issues  Cloud scheme  Vertical resolution  How much is sufficient?  Currently 38 levels ~280m at 1km ~ cloud thickness  Decoupling – structure within ‘mixed’ layers  New Dynamics

36. Page 36© Crown copyright 2005 Namibian Stratocumulus region 31 st March 2004 Model Level Lock (2001) Striping in cloud fields not observed in albedo from GERB instrument (not shown)

37. Page 37© Crown copyright 2005 Other issues  Cloud scheme  Vertical resolution  Decoupling – structure within ‘mixed’ layers  New Dynamics

38. Page 38© Crown copyright 2005 Change in total cloud cover Increasing the susceptibility to decoupling Control Revised scheme Bias RMS speed error  EUROCS diurnal cycle of FIRE1 stratocumulus motivated changes to decoupling diagnosis (include subgrid cloudbase)  Operational testing (10 global forecast case studies) showed:  Reduced cloudiness, as expected  Significant improvement to tropical winds at 850hPa

39. Page 39© Crown copyright 2005 Improved tropical winds hypothesis  Decoupling implies moister near surface implies reduced surface moisture fluxes in subtropical stratocumulus areas  Implies less moisture transported to tropics implies reduced tropical rainfall implies reduction in current model excessive tropical hydrological cycle implies beneficial reduction in trade wind strength  Implies mixed layer structure is important Change in total cloud coverChange in surface moisture flux

40. Page 40© Crown copyright 2005 Other things  Cloud scheme  Vertical resolution  Decoupling – structure within ‘mixed’ layers  New dynamical formulation included:  Semi-implicit, semi-Lagrangian dynamics  Revised timestep (parallel calculation of ‘slow’ physics increments and BL diffusion coefficients)  Revised vertical grid staggering (better handling of normal modes and control of computational modes)  Showed a general improvement in low cloud  But no clean comparison (eg. with the same physics)

41. Page 41© Crown copyright 2005 HadSM3 Cloud Response along GCSS Pacific Cross Section transect  Coupled atmosphere/slab-ocean models  Sc in HadSM4 (old dynamics) very different from HadGSM1 (new dynamics)  HadSM4 includes Lock et al (2000) scheme but not flux-coupling

42. Page 42© Crown copyright 2005 Stratocumulus issues  Met Office model appears to have overcome the 1 st order problem (it has stratocumulus-like clouds in some of the right places) but…  Entrainment  Still large spread in parametrizations (Stevens 2002)  Still large spread in LES (Duynkerke et al 2004 or Stevens et al 2005)  Is a special treatment of fluxes across inversions necessary in GCMs?  Need observed cloud-top height to validate NWP (eg. lidar or radar?)  Drizzle  Large term in mixed layer budget  How well is it represented in GCMs (lack of observed climatology)?  Role and parametrization of aerosols (cf land/sea split in NWP)?  Stabilising feedback on turbulent dynamics (Ackerman et al 2004)?  Mixed layer structure in subtropics is important for downwind deep convection in tropics  Beneficial impact from changes to decoupling  Testing revisions to non-local part of flux parametrization  How well-mixed are the wind profiles?

43. Page 43© Crown copyright 2005 More parametrization issues  What level of cloud scheme complexity is necessary?  Smith scheme couples liquid water and cloud fraction too strongly  Is a prognostic scheme necessary for BL clouds?  Inhomogeneity – important for SW and drizzle  How to model partial cloud cover?  Massflux versus turbulent diffusion  Would unification help?  Communication would be easier (eg. Cu detraining into Sc)  Current massflux schemes seem incompatible with the top-down mixing predominant in stratocumulus  Debate is fuelled by a lack of understanding (limited case studies - need more extensive examination of parameter space)  If we knew (physically) how to parametrize BL clouds in general, wouldn’t the choice be made on numerical stability and accuracy?

44. Page 44© Crown copyright 2005 Questions?

45. Page 45© Crown copyright 2005 Stratocumulus forecasting  Important for forecasting surface temperatures  Case study of widespread low cloud over Europe in December 2004 (eg. 12Z on the 10 th ) Low cloud fraction in global UM T+48 x Budapest x Thanks to Martin Kohler

46. Page 46© Crown copyright 2005 Stratocumulus forecasting  Boundary layer depth evolution mimics the observed  General underestimate of boundary layer depth by ~100m (< grid size)  General cold moist bias  Analysis tends to ‘decouple’ 12Z 10 th December Day of December 2004 Surface mixed layer depth (m)

47. Page 47© Crown copyright 2005 Spin-up of cloud in forecast models  Significant underestimate of cloud cover in the analysis followed by spin-up, at all horizontal resolutions

48. Page 48© Crown copyright 2005 - SW + + LW - CFMIP cloud feedback classes: Low positive class contributes most to uncertainty in sensitivity

49. Page 49© Crown copyright 2005 Lidar versus IR retrieval – Wylie, from Internet!