1. The Cloud Feedback Model Intercomparison Project Plans for CFMIP-2
Mark Webb (Met Office Hadley Centre)
Hadley Centre Seminar, July 2008
© Crown copyright Met Office

2. Acknowledgements Alejandro Bodas-Salcedo, Sandrine Bony,
Chris Bretherton, Helene Chepfer, Steve Klein,
Adrian Lock, Brian Medeiros, Brian Mapes,
Roger Marchand, Tomoo Ogura, Johannes Quaas,
Mark Ringer, Pier Siebesma, Brian Soden,
Karl Taylor, George Tselioudis, Joao Teixeira,
Keith Williams, Minghua Zhang, Yujing Zhang
© Crown copyright Met Office

3. Outline CFMIP-1 and CFMIP-2 Evaluation of clouds in climate models
Understanding cloud feedback mechanisms in models
Assessing their physical credibility
Project timescales
© Crown copyright Met Office

4. CFMIP-1 ( )
Started by WGCM (WCRP Working Group on Coupled Modelling)
Aims were to identify key cloud-climate feedback uncertainties and to link them to observations
ISCCP simulator used to evaluate model clouds quantitatively and expose compensating errors
Slab and +2K experiments were run in parallel with CMIP3 AOGCMs
Results contributed to IPCC 4th Assessment report (AR4)
CFMIP data used in QUMP/UKCIP08 for structural uncertainty estimates
Data are available from PCMDI
See for details including publications
© Crown copyright Met Office

5. Cloud Feedback Model Intercomparison Project Phase 2 (CFMIP-2)
Assessment of
cloud-climate
responses
GCM process/sensitivity
studies
CRMs/LES/SCMs
via GCSS
A-Train/ISCCP & simulators
Understanding
Evaluation
Coordinators: Mark Webb, Sandrine Bony, George Tselioudis, Chris Bretherton
[Full proposal available at: ]
© Crown copyright Met Office

6. ISCCP tropical cloud regimes
Clustering of daily joint cloud-top-pressure – cloud-optical-depth histograms of cloud amount can be a useful way of separating macroscale cloud regimes in GCMs (this was first done by Jakob and Tselioudis, 2003). The plot illustrates the resulting mean histograms for the tropics (20N-20S). It can be used, for example, as a simple method of separating out a handful of different ice cloud types (thin cirrus, thick/anvil cirrus, deep convective clouds, frontal clouds etc.)
Also shown are results from projecting MODIS data onto these clusters (to provide an indication of observational uncertainty), and GCM results using ISCCP simulator diagnostics. This is code which emulates the satellite retrieval so that the model and obs can be directly compared. Hence we can evaluate these large scale cloud regimes in GCMs
Williams and Webb (in press, Climate Dynamics)
© Crown copyright Met Office

7. Cloud regime error metric
© Crown copyright Met Office
Williams and Webb (in press, Climate Dynamics)

8. CloudSat/CALIPSO cloud profiling radar and lidar on the A-train
CloudSat cloud profiling radar (Stephens et al., 2002)
CALIPSO/CALIOP cloud profiling lidar (Winker et al, 2007)
Vertical profiles of reflectivities from clouds and precipitation
© Crown copyright Met Office

9. CFMIP Observational Simulator Package (COSP)
ISCCP, CloudSat Radar and CALIPSO Lidar simulators
Met Office Alejandro Bodas, Mark Webb, Keith Williams
IPSL/LMD Helene Chepfer, Sandrine Bony
LLNL Steve Klein, Yuying Zhang
CSU John Haynes
PNL/UW Roger Marchand
Test release was made Feb 2008 – in testing with 10 models
Plans for MISR, TRMM, RTTOVS and microwave modules
© Crown copyright Met Office

10. CloudSat Radar Simulator in MetUM: North Atlantic NWP case study
Effective Reflectivity Factor (dBZe)
Bodas et al, submitted to JGR
© Crown copyright Met Office

11. LIDAR simulator: CALIOP / LMDz-GCM
GCM + SIMULATOR
CALIOP / GOCCP
HIGH
MID
LOW
CLOUD FRACTION
(H. Chepfer, S. Bony, JL Dufresne, D. Winker, D. Konsta, G. Cesana, G. Sèze)
© Crown copyright Met Office

12. Hierarchy of CFMIP-2 experiments to better understand cloud feedback mechanisms in climate models
Short SST forced experiments
Realistic control SSTs (20 years)
Aquaplanet experiments (36 months)
Single column model experiments (1-2 months)
Additional diagnostics to understand response mechanisms
High frequency output at selected locations
T,q and cloud tendency diagnostics
Sensitivity experiments to understand impact of model assumptions on cloud response mechanisms
© Crown copyright Met Office

13. © Crown copyright Met Office

14. Do aquaplanets predict climate sensitivity?
Brian Medeiros, CSU
© Crown copyright Met Office

15. Do aquaplanets predict climate sensitivity?
Total Feedback λ }
Brian Medeiros, CSU
© Crown copyright Met Office

16. Single column low cloud feedback experiment
Zhang and Bretherton, J. Climate, 2008
© Crown copyright Met Office

17. NCAR CAM3 – negative SW cloud feedback
Cloud amount, convective mass flux,
cloud liquid all increase
Solid: control
Dashed: +2k
GFDL AM2 – positive SW cloud feedback
Small cloud amount change,
convective mass flux increases and
cloud liquid decreases
Cloud Amount
Cloud Liquid
Mass Flux
control
+2k
control
+2k
control
+2k
Minghua Zhang, Stony Brook University
© Crown copyright Met Office

18. Minghua Zhang, Stony Brook University
SAM LES: Negative SW cloud feedback
Cloud Amount
Mass Flux
control
+2k
control
+2k
Cloud Liquid
control
+2k
Cloud Amount
Cloud Liquid
control
+2k
control
+2k
UCLA LES
Negative SW
cloud feedback
Minghua Zhang, Stony Brook University
© Crown copyright Met Office

19. Locations for 3 hourly CFMIP-2 output (85)
GCSS Pacific and South East Tropical Pacific sections
ARM sites/GCSS field studies/locations with feedback spread
© Crown copyright Met Office

20. Diurnal cycle in GCM low cloud cover along GCSS-Pacific cross section (GPCI)
Joao Teixeira, JPL
© Crown copyright Met Office

21. Composite analysis of 3 hourly point output
CRM forced by observations
NCAR CAM3
GFDL AM2
NASA NSIPP2 model
Brian Mapes, University of Miami
© Crown copyright Met Office

22. South East Tropical Pacific Section
(Mark Webb, Tomoo Ogura and Adrian Lock)
© Crown copyright Met Office

23. (Mark Webb, Tomoo Ogura and Adrian Lock)
cloud water
(mg/kg)
Cloud
water
convective
detrainment (mg/kg/s)
condensation from
LW cooling (mg/kg/s)
control
+2K SST
response
(Mark Webb, Tomoo Ogura and Adrian Lock)
© Crown copyright Met Office

24. (Mark Webb, Tomoo Ogura and Adrian Lock)
cloud water
(mg/kg)
Cloud
water
no convective
detrainment (mg/kg)
no condensation from
LW cooling (mg/kg)
control
+2K SST
response
(Mark Webb, Tomoo Ogura and Adrian Lock)
© Crown copyright Met Office

25. CFMIP-2 timeline 2008 Pilot studies continue
WGCM meeting finalises CMIP plans
Production releases of simulators
Data hosting arrangements in place
Modelling groups adopt simulators
Joint CFMIP/GCSS meeting on SCM/LES study
CMIP and CFMIP-2 experiments run by groups
Data submitted to PCMDI
Scientific studies submitted for publication
Publication of AR5
© Crown copyright Met Office

26. CFMIP-2 plans: summary Evaluation of clouds in climate models
continuing use of the ISCCP simulator in CMIP/CFMIP (metrics)
development of new radar/lidar simulators for CMIP/CFMIP
Understanding cloud feedback mechanisms in models
Hierarchy of lightweight climate change experiments
High frequency model outputs
Analysis of tendency terms
Sensitivity tests
Assessing physical credibility of cloud feedback mechanisms
Idealised cloud feedback studies with CRM/LES/SCMs
© Crown copyright Met Office