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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 for Climate Change Submitted to J. Climate ENSEMBLES/CFMIP workshop, Paris, 12/04/07
Page 2© Crown copyright 2007 Why look at cloud regimes in short range forecasts? Differences in the simulation of present-day cloud regimes amongst GCMs has been shown to contribute to a significant proportion of the spread in climate sensitivity (Williams and Tselioudis 2007). However, it may not be easy to identify the cause of errors in a particular regime from the model climatology. The Met Office has the unique asset of using the same physical model for its operational data assimilation, NWP forecasts and climate change projection (HadGEM1). Evaluation of cloud regimes in short range forecasts provides a framework in which the initial meteorological conditions are constrained by observations. Thus the evolution of the errors may provide information on the cause of systematic model bias.
Page 3© Crown copyright 2007 Principle questions to be addressed Are the properties of the simulated cloud regimes (e.g. frequency of occurrence; radiative effect) similar in a short simulation (a few days) as in the model climatology? Does the increased resolution in the NWP model improve the simulation of the cloud regimes? Are the cloud regime properties any closer to observations immediately after the model is initialised from operational analyses? Can initial tendencies in the state variables be associated with particular cloud regimes?
Page 4© Crown copyright 2007 Principal tropical cloud regimes
Page 5© Crown copyright 2007 Principal extra-tropical cloud regimes
Page 6© Crown copyright 2007 Initial tendencies in cloud regime properties
Page 7© Crown copyright 2007 Initial temperature tendency in cloud regimes
Page 8© Crown copyright 2007 Conclusions The simulated cloud regimes are essentially the same in a short run as for the model climatology, hence improvements (which will be relevant to both NWP and climate) can be tested in short runs (although it would be good to address a few initialisation issues). Increased resolution generally has little effect on the cloud regimes, although the simulation of tropical shallow cumulus is improved, whereas tropical deep convection is too infrequent when compared with ISCCP. The errors in the simulated cloud regimes are generally no smaller at T+0, which suggests weaknesses in the local processes (boundary layer/cloud/convection). Some of the initial tendencies in the state variables appear to be associated with particular regimes, which may help with identifying a cause.
Page 9© Crown copyright 2007
Page 1© Crown copyright 2007 Constraining the range of climate sensitivity through the diagnosis of cloud regimes Keith Williams 1 and George Tselioudis.
© Crown copyright Met Office Evaluation of cloud regimes in climate models Keith Williams and Mark Webb (A quantitative performance assessment of cloud.
© Crown copyright 2006Page 1 CFMIP II sensitivity experiments Mark Webb (Met Office Hadley Centre) Johannes Quaas (MPI) Tomoo Ogura (NIES) With thanks.
© Crown copyright Met Office Towards understanding the mechanisms responsible for different cloud-climate responses in GCMs. Mark Webb, Adrian Lock (Met.
© Crown copyright Met Office Southern Ocean surface flux biases in GCMs Keith Williams, Alejandro Bodas-Salcedo & Patrick Hyder SOCRATES workshop 18/03/14.
© Crown copyright Met Office CFMIP-2 techniques for understanding cloud feedbacks in climate models. Mark Webb (Met Office Hadley Centre) CFMIP/GCSS BLWG.
© Crown copyright Met Office Using stability composites to analyse cloud feedbacks in the CMIP3/CFMIP-1 slab models. Mark Webb (Met Office) CFMIP-GCSS.
Yuying Zhang, Jim Boyle, and Steve Klein Program for Climate Model Diagnosis and Intercomparison Lawrence Livermore National Laboratory Jay Mace University.
1 Hadley Centre Using Earth radiation budget data for climate model evaluation Mark Ringer Hadley Centre, Met Office, UK GIST 19: Aug 27-29, 2003.
© Crown copyright Met Office Predictability and systematic error growth in Met Office MJO predictions Ann Shelly, Nick Savage & Sean Milton, UK Met Office.
© Crown copyright Met Office Climate Projections for West Africa Andrew Hartley, Met Office: PARCC national workshop on climate information and species.
Met Office Hadley Centre, FitzRoy Road, Exeter, Devon, EX1 3PB United Kingdom Tel: +44 (0) Fax: +44 (0)
1 Evaluating climate model using observations of tropical radiation and water budgets Richard P. Allan, Mark A. Ringer Met Office, Hadley Centre for Climate.
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.
Laura Davies, University of Reading, UK. Supervisors: Bob Plant, Steve Derbyshire (Met Office)
© Crown copyright Met Office Met Office SCM and CRM results Adrian Lock, Met Office, UK.
Cloud, radiation, and precipitation changes with dynamic regime: An observational analysis and model evaluation study PI: George Tselioudis Co-PI: Chris.
Workshop on Tropical Biases, 28 May 2003 CCSM CAM2 Tropical Simulation James J. Hack National Center for Atmospheric Research Boulder, Colorado USA Collaborators:
Robin Hogan (with input from Anthony Illingworth, Keith Shine, Tony Slingo and Richard Allan) Clouds and climate.
Systematic Errors in the ECMWF Forecasting System ECMWF Thomas Jung.
An Examination Of Interesting Properties Regarding A Physics Ensemble 2012 WRF Users’ Workshop Nick P. Bassill June 28 th, 2012.
© Crown copyright Met Office Working with climate model ensembles PRECIS workshop, MMD, KL, November 2012.
© Crown copyright Met Office Climate change and variability - Current capabilities - a synthesis of IPCC AR4 (WG1) Pete Falloon, Manager – Impacts Model.
National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California 1 J. Teixeira(1), C. A.
Page 1© Crown copyright 2004 SRNWP Lead Centre Report on Data Assimilation 2005 for EWGLAM/SRNWP Annual Meeting October 2005, Ljubljana, Slovenia.
© Crown copyright Met Office An Introduction to PRECIS PRECIS Workshop, University of Reading, 13 th -17 th May, 2013.
Sensitivity to the PBL and convective schemes in forecasts with CAM along the Pacific Cross-section Cécile Hannay, Jeff Kiehl, Dave Williamson, Jerry Olson,
© Crown copyright Met Office Vertical structure and diabatic processess of MJO: Initial results from the 2-day hindcasts Prince Xavier, Jon Petch N. Klingaman.
© Crown copyright Met Office Radiation developments Latest work on the radiation code in the Unified Model James Manners, Reading collaboration meeting.
© Crown copyright Met Office WGNE activities and future directions Andy Brown.
CAUSES (Clouds Above the United States and Errors at the Surface) "A new project with an observationally-based focus, which evaluates the role of clouds,
Robin Hogan Ewan OConnor Damian Wilson Malcolm Brooks Evaluation statistics of cloud fraction and water content.
RT5, WP5.2 : Evaluation of processes and phenomena Objectives : Analyse the capability of the models to reproduce and predict the major modes of variations.
© Crown copyright Met Office Providing High-Resolution Regional Climates for Vulnerability Assessment and Adaptation Planning Joseph Intsiful, African.
Page 1© Crown copyright 2004 Data Assimilation at the Met Office Hadley Centre, Met Office, Exeter.CTCD Workshop. 8 th Nov, 2005 Chris Jones.
Trials of a 1km Version of the Unified Model for Short Range Forecasting of Convective Events Humphrey Lean, Susan Ballard, Peter Clark, Mark Dixon, Zhihong.
© Crown copyright Met Office Implementation of a new dynamical core in the Met Office Unified Model Andy Brown, Director of Science.
Page 1© Crown copyright Simulation of radar reflectivities in the UK Met Office model: comparison with CloudSat Data Alejandro Bodas-Salcedo, M.E. Brooks.
Data assimilation for validation of climate modeling systems Pierre Gauthier Department of Earth and Atmospheric Sciences Université du Québec à Montréal.
Operational assimilation of dust optical depth Bruce Ingleby, Yaswant Pradhan and Malcolm Brooks © Crown copyright 08/2013 Met Office and the Met Office.
© Crown copyright Met Office Deep moist convection as a governor of the West African Monsoon 1 UK Met Office, 2 University of Leeds, 3 National Centre.
LEFE type proposal: Impacts of the Andes on the South American (and global?) Climate Systematic errors on precipitation are important in South America:
VOCALS-UK Len Shaffrey and Thomas Toniazzo Walker Institute, University of Reading John Constable ‘Cloud Study’ 1822.
Predictable Chaotic Exhibits memory Equilibrium Towards non-equilibrium Acknowledgements LD is supported by NERC CASE award NER/S/A/2004/ Conclusions.
The NTU-GCM'S AMIP Simulation of the Precipitation over Taiwan Area Wen-Shung Kau 1, Yu-Jen Sue 1 and Chih-Hua Tsou 2 1 Department of Atmospheric Sciences.
© Crown copyright Met Office Assimilating infra-red sounder data over land John Eyre for Ed Pavelin Met Office, UK Acknowledgements: Brett Candy DAOS-WG,
© Crown copyright 2006Page 1 The Cloud Feedback Model Intercomparison Project (CFMIP) Progress and future plans Mark Webb (Hadley Centre) and CFMIP contributors.
Using GERB and CERES data to evaluate NWP and Climate models over the Africa/Atlantic region Richard Allan, Tony Slingo, Ali Bharmal Environmental Systems.
© Crown copyright Met Office Plans for Met Office contribution to SMOS+STORM Evolution James Cotton & Pete Francis, Satellite Applications, Met Office,
Page 1© Crown copyright Modelling the stable boundary layer and the role of land surface heterogeneity Anne McCabe, Bob Beare, Andy Brown EMS 2005.
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