© 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 Workshop Paris, April 2007

© Crown copyright 2006Page 2 Modelling and Prediction of Climate variability and change Outline Tentative CFMIP II / AR5 timelines Current plans for various elements of the CFMIP II strategy How you can contribute…

© Crown copyright 2006Page 3 Modelling and Prediction of Climate variability and change CFMIP II experiments and CMIP4/AR5 experiments CFMIP I ran experiments parallel to those in AR4 with enhanced cloud diagnostics (ISCCP simulator) Our strategy for AR5 is to work to have the best diagnostics in the official AR5 simulations and to minimise the number of experiments that CFMIP II needs to run in parallel Even if this effort is successful CFMIP II will still run sensitivity experiments with the AR5 model versions in parallel with the official AR5 experiments

© Crown copyright 2006Page 4 Tentative CFMIP II and CMIP4/AR5 timelines

© Crown copyright 2006Page 5 Strategy for a better assessment of cloud feedbacks in AR5 1/ Develop diagnostic techniques for evaluating clouds and modelled cloud climate feedbacks using satellite data 2/ Develop process level diagnostics to better understand physical cloud- climate feedback mechanisms in models 3/ Work with modelling groups to encourage use of detailed cloud diagnostics in the AR5 experiments 4/ Develop a lightweight experimental framework for studying cloud feedbacks 5/ Run co-ordinated sensitivity experiments to understand the impact of different model assumptions on cloud climate feedbacks 6/ Work with the GCSS/parametrization community to assess the credibility of models cloud feedback mechanisms

© Crown copyright 2006Page 6 Strategy for a better assessment of cloud feedbacks in AR5 1/ Develop diagnostic techniques for evaluating clouds and modelled cloud climate feedbacks using satellite data 2/ Develop process level diagnostics to better understand physical cloud- climate feedback mechanisms in models 3/ Work with modelling groups to encourage use of detailed cloud diagnostics in the AR5 experiments 4/ Develop a lightweight experimental framework for studying cloud feedbacks 5/ Run co-ordinated sensitivity experiments to understand the impact of different model assumptions on cloud climate feedbacks 6/ Work with the GCSS/parametrization community to assess the credibility of models cloud feedback mechanisms

© Crown copyright 2006Page 7 ISCCP cloud cluster evaluation (Williams and Tselioudis, Climate Dynamics 2007) 1/ Diagnostics for cloud evaluation with satellite data

© Crown copyright 2006Page 8 Modelling and Prediction of Climate variability and change Develop use of lightweight 2D ISCCP simulator diagnostics for use in clustering studies (Williams, Webb) - daily mean optical depth (albedo weighted) - cloud top pressure - ISCCP TCC Alternative to 42 element tau-Pc histograms This will allow cluster statistics to be collected in long integrations periods without saving/exchanging large volumes of daily data Pilot study/upgrade ISCCP simulator vn 3.5 byend 2007 Modellers upgrade/install by mid 2008? 1a/ ISCCP simulator development

© Crown copyright 2006Page 9 Modelling and Prediction of Climate variability and change 1b/ CFMIP CloudSat/CALIPSO simulator development Various modules currently under development Met Office Alejandro Bodas, Mark Webb, Mark Ringer IPSL/LMD Marjolaine Chiriaco, Helene Chepfer, Sandrine Bony LLNL Steve Klein, Yuying Zhang CSUJohn Haynes, Jonny Lyo PNL/UWRoger Marchand Prototype release expected beforeend 2007 Release of official CFMIPII/AR5 version mid 2008 Modellers may start installation from early 2008 We plan to add the ISCCP simulator as an additional module

© Crown copyright 2006Page 10 Strategy for a better assessment of cloud feedbacks in AR5 1/ Develop diagnostic techniques for evaluating clouds and modelled cloud climate feedbacks using satellite data 2/ Develop process level diagnostics to better understand physical cloud- climate feedback mechanisms in models 3/ Work with modelling groups to encourage use of detailed cloud diagnostics in the AR5 experiments 4/ Develop a lightweight experimental framework for studying cloud feedbacks 5/ Run co-ordinated sensitivity experiments to understand the impact of different model assumptions on cloud climate feedbacks 6/ Work with the GCSS/parametrization community to assess the credibility of models cloud feedback mechanisms

© Crown copyright 2006Page 11 2a/ CFMIP Point diagnostics - point locations including - GPCI (Teixeira et al) - ARM/BSRN/Cloudnet sites - locations where models show largest spread? - locations with largest observed inter-annual sensitivity? - 3hrly or timestep sampling of all cloud diagnostics? - present day and climate change years? - pilot study (Met Office and others?) by end 2007 ? - modellers set up in models bymid 2008

© Crown copyright 2006Page 12 2a/ CFMIP Point diagnostics

© Crown copyright 2006Page 13 2a/ CFMIP Point diagnostics

© Crown copyright 2006Page 14 90S 60S 30S EQ 30N 60N 90N sigma ΔCloud water (2xco2 - 1xco2, DJF) cloud decrease increase Correlation coefficient (when positive) contour=3e-6 [kg/kg] - pilot model inter-comparison (NIES,MetOffice,MPI) end modellers set up in models byend b/ Cloud condensate tendency analysis (Ogura et al) Cloud water vs condensation-precip

© Crown copyright 2006Page 15 Strategy for a better assessment of cloud feedbacks in AR5 1/ Develop diagnostic techniques for evaluating clouds and modelled cloud climate feedbacks using satellite data 2/ Develop process level diagnostics to better understand physical cloud- climate feedback mechanisms in models 3/ Work with modelling groups to encourage use of detailed cloud diagnostics in the AR5 experiments 4/ Develop a lightweight experimental framework for studying cloud feedbacks 5/ Run co-ordinated sensitivity experiments to understand the impact of different model assumptions on cloud climate feedbacks 6/ Work with the GCSS/parametrization community to assess the credibility of models cloud feedback mechanisms

© Crown copyright 2006Page 16 Proposed diagnostics for AR5/CFMIPII experiments

© Crown copyright 2006Page 17 Modelling and Prediction of Climate variability and change 3/ Working with modellers to include these in AR5/CMIP4 The ISCCP simulator is already in most climate models and will be part of standard IPCC diagnostic requirement for AR5 (agreed by WGCM Sep 06) Cloud tendencies are already diagnosed in many models Most groups have submitted data to the WGNE-GCSS GPCI C3S is relatively new, but many groups are interested in making good use of CloudSat/CALIPSO data. Please start to make the case to the relevant people in your organisation for setting up these diagnostics for CFMIP and AR5! If AR5 integrations start in late 2008, then this work will need to be done in the next 18 months.

© Crown copyright 2006Page 18 Strategy for a better assessment of cloud feedbacks in AR5 1/ Develop diagnostic techniques for evaluating clouds and modelled cloud climate feedbacks using satellite data 2/ Develop process level diagnostics to better understand physical cloud- climate feedback mechanisms in models 3/ Work with modelling groups to encourage use of detailed cloud diagnostics in the AR5 experiments 4/ Develop a lightweight experimental framework for studying cloud feedbacks 5/ Run co-ordinated sensitivity experiments to understand the impact of different model assumptions on cloud climate feedbacks 6/ Work with the GCSS/parametrization community to assess the credibility of models cloud feedback mechanisms

© Crown copyright 2006Page 19 Modelling and Prediction of Climate variability and change Current proposal: - AMIP like present day (June 1984 – Dec 2007 ) - AMIP + CO2 doubling forcing experiment (Hansen) - AMIP + 1% CMIP2 composite SST pattern (Soden) If significant variations on this are proposed then a pilot study will be necessary Proposed timetable: - Pilot study (volunteers?) end CFMIP-2 experiments with AR5 versions / Lightweight idealised experimental framework

© Crown copyright 2006Page 20 Strategy for a better assessment of cloud feedbacks in AR5 1/ Develop diagnostic techniques for evaluating clouds and modelled cloud climate feedbacks using satellite data 2/ Develop process level diagnostics to better understand physical cloud- climate feedback mechanisms in models 3/ Work with modelling groups to encourage use of detailed cloud diagnostics in the AR5 experiments 4/ Develop a lightweight experimental framework for studying cloud feedbacks 5/ Run co-ordinated sensitivity experiments to understand the impact of different model assumptions on cloud climate feedbacks 6/ Work with the GCSS/parametrization community to assess the credibility of models cloud feedback mechanisms

© Crown copyright 2006Page 21 Modelling and Prediction of Climate variability and change Examples: - Does suppressing cloud liquid water content feedback increase climate sensitivity? - Does using a stability based cloud fraction reduce climate sensitivity? Proposed timetable: - Pilot study (Met Office, MPI, NIES) end CFMIP-2 experiments with AR5 versions / Sensitivity tests to assess impact of model assumptions

© Crown copyright 2006Page 22 Strategy for a better assessment of cloud feedbacks in AR5 1/ Develop diagnostic techniques for evaluating clouds and modelled cloud climate feedbacks using satellite data 2/ Develop process level diagnostics to better understand physical cloud- climate feedback mechanisms in models 3/ Work with modelling groups to encourage use of detailed cloud diagnostics in the AR5 experiments 4/ Develop a lightweight experimental framework for studying cloud feedbacks 5/ Run co-ordinated sensitivity experiments to understand the impact of different model assumptions on cloud climate feedbacks 6/ Work with the GCSS/parametrization community to assess the credibility of models cloud feedback mechanisms

© Crown copyright 2006Page 23 Modelling and Prediction of Climate variability and change Proposals in this area are very much under discussion as part of the GEWEX/GCSS-CFMIP collaboration arrangements, and are less tied to the CMIP4 timetable. Having high frequency point/process diagnostics in AR5/CFMIP-2 will help climate modelling and GCSS/process communities to understand cloud feedbacks mechanisms in models and the reasons for their differences. We need to find ways to bridge the gap between global models and single column/case studies for climate feedback experiments as well as present day. Doing this should allow us to use CRM/LES/SCM studies to assess our relative confidence in the cloud feedbacks shown by different models. 6/ Assess credibility of cloud feedback mechanisms

© Crown copyright 2006Page 24 Modelling and Prediction of Climate variability and change Please give us your feedback…. Please take part in our project working groups today – everyone is welcome! We plan to write a concrete project proposal this summer, based on the recommendations from this meeting. The aim is to publish this and send out a call for participation from modelling groups at the end of this year. This will include recommendations for diagnostics to be included in the AR5 experiments, which are expected to be finalised in 2008.

© Crown copyright 2006Page 25 Cloud system composites from Lau & Crane (1995) and Klein and Jakob (1999) TWP