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The Cloud Feedback Model Intercomparison Project Plans for CFMIP-2Mark 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 modelsUnderstanding cloud feedback mechanisms in models Assessing their physical credibility Project timescales © Crown copyright Met Office
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
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
ISCCP tropical cloud regimesClustering 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-trainCloudSat 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 studyEffective Reflectivity Factor (dBZe) Bodas et al, submitted to JGR © Crown copyright Met Office
LIDAR simulator: CALIOP / LMDz-GCMGCM + 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 modelsShort 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 experimentZhang 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 UniversitySAM 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 outputCRM 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 continueWGCM 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
CFMIP-2 plans: summary Evaluation of clouds in climate modelscontinuing 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
Met Office Hadley Centre, FitzRoy Road, Exeter, Devon, EX1 3PB United Kingdom Tel: +44 (0) Fax: +44 (0)
© Crown copyright 2006Page 1 CFMIP II sensitivity experiments Mark Webb (Met Office Hadley Centre) Johannes Quaas (MPI) Tomoo Ogura (NIES) With thanks.
Page 1© Crown copyright 2007 CFMIP2: Options for SST-forced and slab experiments Mark Ringer, Brian Soden Hadley Centre,UK & RSMA/MPO, US CFMIP/ENSEMBLES.
Page 1© Crown copyright 2007 Initial tendencies of cloud regimes in the Met Office Unified Model Keith Williams and Malcolm Brooks Met Office, Hadley Centre.
© Crown copyright Met Office Towards understanding the mechanisms responsible for different cloud-climate responses in GCMs. Mark Webb, Adrian Lock (Met.
© Crown copyright 2006Page 1 The Cloud Feedback Model Intercomparison Project (CFMIP) Progress and future plans Mark Webb, Keith Williams, Mark Ringer,
© Crown copyright 2006Page 1 CFMIP II Plans Mark Webb (Met Office Hadley Centre) Sandrine Bony (IPSL) Rob Colman (BMRC) with help from many others… CFMIP/ENSEMBLES.
Page 1© Crown copyright 2007 Constraining the range of climate sensitivity through the diagnosis of cloud regimes Keith Williams 1 and George Tselioudis.
R. Forbes, 17 Nov 09 ECMWF Clouds and Radiation University of Reading ECMWF Cloud and Radiation Parametrization: Recent Activities Richard Forbes, Maike.
Robin Hogan, Andrew Barrett
© University of Reading Richard Allan Department of Meteorology, University of Reading Thanks to: Jim Haywood and Malcolm.
University of Reading 2007www.nerc-essc.ac.uk/~rpa Monitoring satellite observations and model simulations of changes in the atmospheric.
IRS2004, Busan, August 2004 Using Satellite Observations and Reanalyses to Evaluate Climate and Weather Models Richard Allan Environmental Systems Science.
© University of Reading 2009 EUMETSAT Monitoring changes in precipitation and radiative energy using satellite data and.
Clouds processes and climate
© University of Reading Monitoring and understanding current changes in the global energy & water cycles Richard Allan.
1 Evaluating climate model using observations of tropical radiation and water budgets Richard P. Allan, Mark A. Ringer Met Office, Hadley Centre for Climate.
Robin Hogan (with input from Anthony Illingworth, Keith Shine, Tony Slingo and Richard Allan) Clouds and climate.
© University of Reading Radiative effects of persistent aircraft contrails: a case study Richard Allan Environmental Systems.
1 03/0045a © Crown copyright Evaluating water vapour in HadAM3 with 20 years of satellite data Richard P. Allan Mark A. Ringer Met Office, Hadley Centre.
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