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

© Crown copyright Met Office

The Cloud Feedback Model Intercomparison Project Plans for CFMIP-2Mark Webb (Met Office Hadley Centre)

Hadley Centre Seminar, July 2008


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


Outline

• CFMIP-1 and CFMIP-2

• Evaluation of clouds in climate models

• Understanding cloud feedback mechanisms in models

• Assessing their physical credibility

• Project timescales


CFMIP-1 (2003-2007)

• 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 www.cfmip.net for details including publications


Cloud Feedback Model Intercomparison Project Phase 2 (CFMIP-2)

Understanding

GCM

process/sensitivity

studies

CRMs/LES/SCMs

via GCSS

A-Train/ISCCP

& simulators

Assessment of

cloud-climate

responses

[Full proposal available at: http://www.cfmip.net ]

Coordinators: Mark Webb, Sandrine Bony, George Tselioudis, Chris Bretherton

Evaluation


ISCCP tropical cloud regimes

Williams and Webb (in press, Climate Dynamics)


Cloud regime error metric

Williams and Webb (in press, Climate Dynamics)


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


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


CloudSat Radar Simulator in MetUM: North Atlantic NWP case study

Effective Reflectivity Factor (dBZe)

Bodas et al, submitted to JGR


LIDAR simulator: CALIOP / LMDz-GCM

GCM GCM + SIMULATOR CALIOP / GOCCP

CLOUD FRACTION

LOW

MID

HIGH

(H. Chepfer, S. Bony, JL Dufresne, D. Winker, D. Konsta, G. Cesana, G. Sèze)


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



Do aquaplanets predict climate sensitivity?

Brian Medeiros, CSU


Climate sensitivity

}

Brian Medeiros, CSU

Do aquaplanets predict climate sensitivity?

Total Feedback λ


Zhang and Bretherton, J. Climate, 2008

Single column low cloud feedback experiment


Cloud Amount Cloud LiquidMass Flux

NCAR CAM3 – negative SW cloud feedbackCloud amount, convective mass flux,cloud liquid all increase

GFDL AM2 – positive SW cloud feedbackSmall cloud amount change, convective mass flux increases andcloud liquid decreases

Minghua Zhang, Stony Brook University

Solid: controlDashed: +2k

control +2k

control +2k

control +2k


UCLA LES Negative SW

cloud feedback

SAM LES: Negative SW cloud feedback

Cloud Liquid

Mass FluxCloud Amount

Cloud Amount Cloud Liquid

Minghua Zhang, Stony Brook University

control +2k

control +2k

control +2k

control +2k

control +2k


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


Joao Teixeira, JPL

Diurnal cycle in GCM low cloud cover along GCSS-Pacific cross section (GPCI)


Composite analysis of 3 hourly point output

Brian Mapes, University of Miami

CRM forced by observations NCAR CAM3

GFDL AM2 NASA NSIPP2 model

© Crown copyright Met Office (Mark Webb, Tomoo Ogura and Adrian Lock)

South East Tropical Pacific Section


control

+2K SSTresponse

Cloud water

convective detrainment (mg/kg/s)

cloud water (mg/kg)

condensation from LW cooling (mg/kg/s)


control

+2K SSTresponse

Cloud water

no convective detrainment (mg/kg)

cloud water (mg/kg)

no condensation from LW cooling (mg/kg)


CFMIP-2 timeline

2008 Pilot studies continue WGCM meeting finalises CMIP plans Production releases of simulators Data hosting arrangements in place

2009-10 Modelling groups adopt simulators Joint CFMIP/GCSS meeting on SCM/LES study CMIP and CFMIP-2 experiments run by groups Data submitted to PCMDI

2010-11 Scientific studies submitted for publication

2013 Publication of AR5


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 The Cloud Feedback Model Intercomparison Project Plans for CFMIP-2 Mark Webb (Met Office Hadley Centre) Hadley Centre Seminar,

Documents

cloud feedback mechanisms

csu slide

total feedback slide

sze slide

jgr slide

climate dynamics slide

cloud response mechanisms

cloud liquid minghua