ENSEMBLES Overview, progress, plans EMS 2007, El Escorial, October 2007 Chris Hewitt, Met Office Hadley Centre Project Office can be contacted on ensemblesfp6@metoffice.gov.uk Web site is http://www.ensembles-eu.org Outline Overview of the Ensembles project Progress Plans © Crown copyright 2007 Page 2 Motivation Predictions of natural climate variability on seasonal to decadal to centennial timescales, and the human impact on climate are inherently probabilistic due to uncertainties in: initial conditions representation of key processes within models climatic forcing factors Reliable seasonal to decadal forecasts, and estimates of climatic risk can only be made through ensemble integrations of Earth-System Models in which these uncertainties are explicitly incorporated. The ENSEMBLES project will provide these probabilistic estimates. © Crown copyright 2007 Page 3 Motivation: Recent Status of Climate Change Prediction We can produce a small number of different predictions with little idea of how reliable they might be © Crown copyright 2007 Page 4 Probabilistic Climate Predictions required position current position Probability Probability 100% 0% 20% 40% 60% 2080s SE England winter rainfall © Crown copyright 2007 0% 20% 40% 60% 2080s SE England winter rainfall Page 5 Sources of uncertainty Effects of natural variability Future emission scenarios Modelling of Earth system processes © Crown copyright 2007 Page 6 Climate Prediction Modelling From Murphy et al, Nature 2004 © Crown copyright 2007 Page 7 Motivation (continued) Seasonal forecast case study: Winter 1997 El-Niño, Precipitation DEMETER multi-model Flooding: East Africa Uruguay / Argentina Verification Rainforest fires: Amazonia, Indonesia Storm damage: California Tornados: Florida courtesy Francisco Doblas-Reyes: verification of a multi-model system ©Slide Crown copyrightof2007 Page 8 Better performance of multi-model for seasonal fc Test of individual and multi-model probabilistic skill (area-averaged ROC) over 8 regions, 4 seasons, 4 events, 2 lead times ECMWF DEMETER multi-model 16% UKMO MPI CNRM 13% 56% 9% courtesy Francisco Doblas-Reyes ©Slide Crown copyrightof2007 6% Page 9 Impact of ensemble size on seasonal fc Ranked probability skill score for tropical (region in blue in the inset) precipitation as a function of the ensemble size for a multi-model (red) and a single-model (blue) with the same ensemble size. The multi-model has superior performance than the single model for every ensemble size. courtesy Francisco Doblas-Reyes ©Slide Crown copyrightof2007 Page 10 Motivation: Ensemble Climate Prediction Run ensembles of different climate models to sample uncertainties Measure variations in reliability between models using hindcasts Produce probabilistic predictions of climate change Do this for seasonal to decadal and longer timescales, and global, regional and local spatial scales, for use in a wide range of applications ENSEMBLES © Crown copyright 2007 Page 11 The ENSEMBLES Project 5-year Integrated Project supported by EC FP6 funding coordinated by Met Office Hadley Centre 67 partners: EU, Switzerland, Australia, US we welcome requests from new groups to participate on an unfunded basis – currently 19 such groups worldwide affiliated to the project Builds upon EC FP5 projects e.g. DEMETER, MICE, PRUDENCE, STARDEX Integrates a wide range of research communities Work carried out in Ten Research Themes © Crown copyright 2007 Page 12 Strategic Objectives 1. Develop an ensemble prediction system based on global and regional Earth System models, validated against observations and analyses, to produce for the first time, a probabalistic estimate of uncertainty in future climate at the seasonal, decadal and longer timescales 2. Quantify and reduce uncertainty in the representation of physical, chemical, biological and human-related feedbacks in the Earth System 3. Exploit the results by linking the outputs to a range of applications, including agriculture, health, food security, energy, water resources, insurance We are aiming to increase availability of scientific knowledge and provision of relevant information related to the impacts of climate change © Crown copyright 2007 Page 13 Research Themes (RTs) summary System development and assembly © Crown copyright 2007 Model ‘engine’: hindcasts, climate integrations Understanding, evaluation Impacts, Scenarios and policy Page 14 Progress: GCM seasonal to decadal 3 different s2d forecast systems to estimate model uncertainty: Multi-model (9) system, installed at ECMWF built from EUROSIP operational activities and DEMETER experience Perturbed parameter system, built from the decadal prediction system at the Met Office Stochastic physics system, from the CASBS system developed for medium-range forecasting at ECMWF Design of a set of common experiments to determine the benefits of each approach Ensemble of ocean analyses available for initialisation Improved ocean data assimilation systems for s2d prediction Publications demonstrating additional skill in annual-decadal projections by initialising the ocean component of CGMS © Crown copyright 2007 Page 15 Progress: GCM centennial Multi-model ACC simulations (contributed to IPCC 4AR) Conducted historical runs (1860-2000) and scenario runs (IPCC A1B, A2, B1) including Hadley Centre perturbed parameter runs © Crown copyright 2007 Page 16 Progress: regional scenarios Defined RCM domain Central model data archive available at DMI Contains 14 RCM hindcasts (1961-2000 driven by ERA40) at 50km and 25km Matrix of driving GCMs/RCMs devised Transient scenario runs underway 25km RCMs, 1950-2050/2100 driven by GCMs, A1B scenario from 2001 Regional scenario web portal launched in June 2007 DRAFT – TO BE FINALISED RCM’s GCM’s METOMPIMET CNRM HC DMI METO- 1950HC 2100 MPIME 1950T 2100 ETH KNMI ICTP 19502050 19502100 19502050 19502050 SMHI UCLM 19502050 19502050 19502050 C4I GKSS MetNo CHMI 19502050 19502050 FUB IPSL CNRM NERSC © Crown copyright 2007 0.22º (25km) grid mesh (courtesy of Burkhardt Rockel) 19502050 19502050 19502050 19502050 19502050 19502050 Page 17 Progress (continued) Scientific analyses (e.g. cloud feedbacks, carbon, sea-ice, …) Coordinated experiments (web), especially for land-sea warming contrasts Linking impact models to probabilistic projections Publicly available Climate Explorer http://climexp.knmi.nl/ further developed as integrated diagnostic tool Producing daily gridded datasets for Europe with uncertainty estimates. Particularly of use for evaluating extremes OLD (ECA daily dataset) © Crown copyright 2007 NEW Page 18 Progress (continued) New emissions scenario developed A1B baseline, stabilise towards 475ppmv CO2eq provides information towards EU goal of limiting warming to less than 2°C above pre-industrial levels Uses proposed IPCC “AR5” design ESMs including the carbon cycle will be driven by GHG concentrations, rather than emissions. Carbon fluxes give implied emissions Will inform details of AR5 design and how to exploit the runs © Crown copyright 2007 Page 19 Pre AR4 used forward approach AR5 likely to use reverse approach Forward approach: start with socio-economic variables Socio-economic variables Emissions Concentrations Surface temperature Reverse approach: start with stabilization scenario concentrations Socio-economic variables mitigation costs Emissions implied emissions Concentrations Surface temperature concentrations sensitivity impacts Requires interpolating and scaling © Crown copyright 2007 Page 20 Progress (continued) West Africa to be the non-European RCM domain Publications of ENSEMBLES results appearing in journals. ENSEMBLES Technical Reports series created Expanding the “affiliated partners” (19 currently) FAO, Rene Gommes, RT5&6 Univ. Zurich, Nadine Salzmann, RT6 Nat. Univ. of Ireland, Kieran Hickey, RT5 FRGCG, Michio Kawamiya, RT1&2A Nat. Inst. Earth Sciences, Seita Emori, RT2A University of Copenhagen, Eigil Kaas, RT2A Nat.Acad.Sci. Ukraine, Alexander Palonski, RT6 OURANOS group, Daniel Caya, RT2B Climate Analysis Group, Philippe Gachon, RT2B IBIMET Institute, Massimiliano Pasqui, RT1, RT2A © Crown copyright 2007 WHO, Bettine Menne, RT5 ESSC, John Christy, RT5 NCAR, Guy Brasseur, Jerry Meehl, Linda Mearns, RT2A&2B CCSR (Uni Tokyo), Masahide Kimoto, RT4 SINTEF Energy Research, Atle Harby, RT6 University of Exeter, David Stephenson, RT4 University of Newcastle, Hayley Fowler Canadian Reg. Clim. Modelling and Diag. Network (CRCMD), Colin Jones Proudman Oceanographic Laboratory, Roger Proctor, RT6 Page 21 Plans for year 4 of the project (starts Sep 07) Start “Stream 2” simulations: s2d hindcasts 1960 onwards (previously 1991-2001) 1860-2000 simulations using updated models 21st Century scenarios using updated models and E1 (previously A1B, A2, B1) RCM A1B Europe@25km 1950-2050/2100 Plan RCM simulations for West African domain Develop databases s2d @ ECMWF building on DEMETER database RCM @ DMI building on PRUDENCE database GCM @ MPIMET building on IPCC WCDC activities © Crown copyright 2007 Page 22 Plans for year 4 of the project (starts Sep 07) Develop impacts models (e.g. crops, water resources, energy) Develop statistical downscaling tools Improved estimates for changes in extreme events Workshops General Assembly, Prague, 12-16Nov07 Socio-Economic Drivers of Climatic Change, Paris, Dec07 Climate Change, Impacts and Adaptation in the Mediterranean, Greece, late 2008 others to be announced © Crown copyright 2007 Page 23 Concluding remarks – innovative work Brings together largely separate communities and integrates worldleading European research: s2d, anthropogenic climate change, global modellers, regional modellers (dynamical and statistical downscaling), scientific understanding, evaluation with observations, training programmes, application modellers to deliver climate impacts, emission scenario developers, Multi-disciplinary approach allows exchange of knowledge, ideas and techniques, e.g. extensive work on extremes Multi-model ensemble-based probability approach will quantify uncertainty, increase understanding, influence the development of the next generation of models, leading to uncertainty reduction in the future Examples of new products: multi-model RCM system at 25km resolution probabilistic methods for use for GCMs, RCMs, impact models probabilistic predictions from s2d2c timescales to explore impacts gridded observations for Europe with estimate of uncertainty public availability of large datasets developments to the publicly available Climate Explorer on-line tools for users to downscale Ensembles simulations © Crown copyright 2007 Page 24 Questions © Crown copyright 2007 Page 25