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

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

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

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 © Crown copyright Met Office

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: http://www.cfmip.net ] © Crown copyright Met Office

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

Cloud regime error metric © Crown copyright Met Office 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 © Crown copyright Met Office

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

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

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

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

© Crown copyright Met Office

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

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

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

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

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

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

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

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

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

(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

(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

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 © Crown copyright Met Office

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