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The CFMIP-GCSS SCM/LES Case Study: Overview and Preliminary Results

The CFMIP-GCSS SCM/LES Case Study: Overview and Preliminary Results. Minghua Zhang (Stony Brook University)

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The CFMIP-GCSS SCM/LES Case Study: Overview and Preliminary Results

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  1. The CFMIP-GCSS SCM/LES Case Study: Overview and Preliminary Results Minghua Zhang (Stony Brook University) Julio Bacmeister, Sandrine Bony, Chris Bretherton, Florent Brient, Anning Cheng, Charmaine Franklin, Chris Golaz, In-Sik Kang, Martin Koehler Adrian Lock, Ulrike Lohman, Marat Khairoutdinov, Martin Koehler, Roel Neggers, Sing-Bin Park, Pier Siebesma, Colombe Siegenthaler-Le Drian, Kuan-man Xu, Mark Webb, Ming Zhao

  2. The ISSUE

  3. (Cess et al. 1990)

  4. The Idea

  5. RH Fixed (moist adiabat) T(z) T(z) Warm Pool Cold Tongue (Zhang and Bretherton, 2008)

  6. GPCI

  7. The objectives: • To understand the models • To understand the climate feedbacks in the models. • To compare SCM with LES/CRM simulations

  8. Yet to Submit CCCMeteo-France GISSUUtah*UW*UWiscousin * Denotes LES/CRM Models WITH Results SubmittedCAM3.1 (CAM3)CAM3.5 (CAM4)CSIROECHAM1ECHAM2ECMWFGFDLGSFCKNMILaRC/UCLA*LMDSAM*SNUUKMO*UKMO-L38UKMO-L63

  9. Some Philosophical Questions

  10. Question #1Can the idealized setup represent the large-scale atmospheric conditions at the selected locations?Question #2Can the conditions represent those in the GCMs?

  11. Question #3Will the variation of clouds in the SCM be the same as that in the GCM at the same location?Question #4How representative are the cloud responses at the selected locations to the GCM cloud feedback?

  12. CAM-SP DLWP DSWCF DCRF

  13. CAM3.5 DLWP DSWCF DCRF

  14. Question #5How do we know the simulated cloud feedbacks are correct or wrong? Can LES be used to answer this)?Question #6What do we learn from it?

  15. Control GCM Output at S9 DSST=2K GCM Output at S9 DSST=2K SCM Output at S9 Under idealized forcing Control SCM Output at S9 Under idealized forcing Cloud Amount from CAM3.5

  16. Forcing Data

  17. T(p) at two latitudes. Stars are from ECMWF analysis

  18. RH Fixed (moist adiabat) T(z) T(z) Warm Pool Cold Tongue T Rh Rh_ec

  19. w (control) u w (p2k) v

  20. s12 S11 S6 GPCI

  21. S11 S6 http://atmgcm.msrc.sunysb.edu/cfmips

  22. Preliminary Results

  23. Sample of Simulated Cloud Amount from Control Case at s6 (top row), s11 (middle row), and s12 (bottom row) CAM3.5 (1st column), GFDL (2nd Column),UKMO L38 (3rd Column) LaRC/UCLA LES (4th Column) In all 2-D plots that follow, the ordinate is pressure, the abscissa is time in days

  24. CAM3.5 – s6 LaRC/UCLA – s6 UKMOL38 – s6 GFDL – s6 CAM3.5 – s11 LaRC/UCLA– s11 UKMOL38 – s11 GFDL – s11 CAM3.5 – s12 LaRC/UCLA – s12 UKMOL38 – s12 GFDL– s12 Cloud Amount in Control Simulation

  25. Sample of Simulated Cloud Liquid Water from Control Case at s6 (top row), s11 (middle row), and s12 (bottom row) CAM3.5 (1st column), GFDL (2nd Column),UKMO L38 (3rd Column) LaRC/UCLA LES (4th Column)

  26. CAM3.5 – s6 LaRC/UCLA – s6 UKMOL38 – s6 GFDL – s6 CAM3.5 – s11 LaRC/UCLA– s11 UKMOL38 – s11 GFDL – s11 CAM3.5 – s12 LaRC/UCLA – s12 UKMOL38 – s12 GFDL– s12 Cloud Liquid Water in Control Simulation

  27. Next: Only Results from S11 Are Presented Cloud Amount at S11 from the Control Simulation in Different Models

  28. ECMWF CAM3.5 CSIRO ECHAM GFDL GSFC KNMI SNU LaRC/UCLA-LES SAM-LES UKMO-LES UKMOL38 Cloud Amount in Control Simulation at s11

  29. Vertical Profiles of Cloud Amount at S11 from Control Simulation in Different Models

  30. Vertical Profiles of Cloud Liquid Water Content at S11 from Control Simulation in Different Models

  31. Comparison of Vertical Profiles of Cloud Amount at S11 Between Control (ctl, solid) and Perturbed (p2k, dashed)

  32. Comparison of Vertical Profiles of Cloud Liquid Water at S11 Between Control (ctl, solid) and Perturbed (p2k, dashed)

  33. Change of Net Cloud Radiative Forcing (p2k minus ctl) at s11

  34. Cloud Change for Some Selected Models with Large Negative and Positive Feedbacks

  35. Negative Feedback in CAM4 p2k ctl

  36. Negative Feedback in CSIRO p2k ctl

  37. Positive Feedback in GFDL p2k ctl

  38. Positive Feedback in UKMO L38 p2k ctl

  39. Positive Feedback in UKMO L63 p2k ctl

  40. Summary • All models simulated stratocumulus clouds in the idealized case at s11. (The models also simulated shallow cumulus at s6.) • Cloud amount, cloud height, and liquid water content differ greatly in the models. • Both positive and negative cloud feedbacks are obtained in the set of models. • In-depth analyses are needed to understand each model at process levels. These will follow.

  41. The interactions among PBL mixing, convection (shallow and deep), and cloud scheme lead to the unique cloud behaviors in each model

  42. 800mb 900mb 950mb 1000mb 1010mb

  43. (Albrecht 1996)

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