ENSEMBLES
Progress and PlansPrepared by Chris Hewitt, Project Director
Project Office can be contacted on [email protected] site is http://www.ensembles-eu.org
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Motivation
Predictions of natural climate variability on seasonal 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 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.
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ENSO predictions in seasonal forecasting
Multi-model seasonal (MAM) predictions for Niño3.4 SSTs
Slide courtesy of Francisco Doblas-Reyes
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We can produce a small number of different predictions with little idea of how reliable they might be.
Current Status of Climate Change Prediction
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Probabilistic approach
From Murphy et al, Nature 2004
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End-to-end methodology
0PDF of meteorological variables End-user PDF (eg crop yield)
0
non-linear transformation
Slide courtesy of Francisco Doblas-Reyes
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The ENSEMBLES Project
5-year Integrated Project supported by EC FP6 funding1 September 2004 – 31 August 2009
67 partners from across EU, Switzerland, Australia, US we welcome requests from new groups to participate on an unfunded basis – currently 11 such groups worldwide affiliated to the project
Builds upon FP5 projectse.g. DEMETER, MICE, PRUDENCE, STARDEX, PRISM, ATEAM
Work carried out in 10 Research Themes (RTs)
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ENSEMBLES Strategic Objectives
1. Develop an ensemble prediction system based on global and regional Earth System models, validated against quality controlled, high resolution gridded datasets for Europe, to produce for the first time, an objective 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
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ENSEMBLES Research Themes
RT1 Co-leaders: James Murphy, Tim Palmer To build and test an ensemble prediction system based on
global Earth System Models.
RT2A Jean-Francois Royer, Erich Roeckner To produce sets of multi-model climate simulations.
RT3 Jens Christensen, Markku Rummukainen To provide improved regional models.
RT2B Clare Goodess, Daniela Jacob To provide ensemble based regional climate scenarios and
seasonal to decadal hindcasts.
RT4 Julia Slingo, Jean-Louis Dufresne To advance the understanding of the basic science.
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ENSEMBLES Research Themes (continued)
RT5 Antonio Navarra, Albert Klein Tank To perform a comprehensive and independent evaluation.RT6 Andy Morse, Colin Prentice To develop risk based estimates of impacts.
RT7 Richard Tol, Roberto Roson To provide scenarios of greenhouse gas emissions, land-use
changes and adaptive capacity.
RT8 Martin Beniston, Christos Giannakopolous Represents the interface with a wider audience that includes
scientists, stakeholders, policymakers and the general public.
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ENSEMBLES Management Structure
The Project Office:
ENSEMBLES Co-ordinator
Dave Griggs
ENSEMBLES Director
Chris Hewitt
ENSEMBLES Secretary
Pip Gilbert
Assisted by:
ENSEMBLES EC Project Officer Georgios Amanatidis
Met Office EU Manager Adrian Broad
ENSEMBLES Management Board
2 RT co-ordinators per RT
RT Steering Groups Work Package leaders
All participants
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Progress: seasonal to decadal
Three different seasonal to decadal forecast systems to estimate model uncertainty:
Multi-model system for s2d forecasts installed at ECMWF built from EUROSIP operational activities and DEMETER experience
Perturbed parameter system, built from the decadal prediction system (DePreSys) 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
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Progress: anthropogenic climate change
New set of GCM ACC simulations (for IPCC 4AR) Conducted historical runs (1860-2000) and scenario runs (IPCC A1B, A2, B1)
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Progress (continued)
Defined RCM domain, ERA40 (1961-2000) runs underwayScientific analyses (e.g. cloud feedbacks, carbon, sea-ice, …)Linking impact models to probabilistic scenariosPublicly available Climate Explorer http://climexp.knmi.nl/
further developed as integrated diagnostic toolProducing daily high-resolution gridded datasets for evaluation
0.22º (25km) grid mesh (courtesy of Burkhardt Rockel)
OLD (ECA daily dataset) NEW
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Progress (continued)
Scientific papers published or in prep. Published overview articles, newsletters, brochures
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http://www.ensembles-eu.org
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Plans for 2006-2007
Finish “Stream 1” simulations using existing models: s2d hindcasts 1991-2001 1860-2000 historical simulations 21st Century scenarios (A1B, A2, B1) RCM ERA40@50km 1961-2000 (first multi-model RCM system)
Start “Stream 2” simulations: s2d hindcasts 1960 onwards 1860-2000 simulations using updated models 21st Century scenarios (A1B, A2, B1, ENS1) using updated models RCM ERA40@25km 1961-2000
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Plans for 2006-2007 (continued)
Develop databases S2d @ ECMWF building on DEMETER database RCM @ DMI building on PRUDENCE database GCM @ MPIMET building on IPCC WCDC activities
Develop impacts models (e.g. crops, water resources, energy) Testing the sensitivity of emissions scenarios to climate change Develop new emissions scenario (ENS1) for Stream 2 simulations Develop statistical downscaling tools Improved estimates for changes in extreme events Workshops (Climatic change and impacts in Eastern Europe, Romania 13-15 Sep; Adaptation to the
impacts of climate change in the European Alps, Switzerland 4-6 Oct; Extreme climatic events and
Impacts, Switzerland 2007; 5th Study Conference on BALTEX, Estonia 2007)
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Concluding remark
ENSEMBLES brings together largely separate communities and integrates world-leading European research on the Earth system:
s2d, anthropogenic climate change, global modellers, regional modellers (dynamical and statistical downscaling), climate and chemistry, scientific understanding, evaluation with observations, application modellers to deliver climate impacts, emission scenario developers, training programmes
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Questions