Transcript Overview - Ensembles

ENSEMBLES
An Integrated Project under the 6th
Framework Programme of the EU
Project Overview
Project Office can be contacted on [email protected]
Web site is http://www.ensembles-eu.org
Outline
 Motivation for the project
 What is the project
 What will the project do
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Motivation
Predictions of natural climate variability 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 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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Current Status of Climate Change Prediction
We can produce a small number of different predictions with no idea of
how reliable they might be
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Probabilistic Climate Predictions
required position
current position
Probability
Probability
100%
0%
20%
40%
60%
2080s SE England winter rainfall
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0%
20%
40%
60%
2080s SE England winter rainfall
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Sources of uncertainty
Effects of natural variability
Future emission scenarios
Modelling of
Earth system
processes
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Climate Prediction Modelling
From Murphy et al, Nature 2004
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Ensemble Climate Prediction
 Run ensembles of different climate models to sample
uncertainties
 Measure variations in reliability between models
 Produce probabalistic predictions of climate change
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The ENSEMBLES Project
 A five year project supported by funding under FP6
Started 1 September 2004
 Funding from EC of 15 million Euros
 About 66 partners from across EU, Switzerland,
Australia, US
 Ten Research Themes (~300 page DoW)
 Project will be managed by a Management Board
under the terms of a Consortium Agreement
 Follows on from/builds upon FP5 project (e.g. DEMETER,
MICE, PRUDENCE, STARDEX)
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Strategic Objectives
 Develop an ensemble prediction system based on the
principal state-of-the-art high resolution, 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
 Quantify and reduce uncertainty in the representation of
physical, chemical, biological and human-related
feedbacks in the Earth System
 Maximise the exploitation of the results by linking the
outputs to a range of applications, including agriculture,
health, food security, energy, water resources, insurance
and risk management
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Scientific Objectives
1. Produce probabilistic predictions from seasonal to decadal and
longer timescales and use these to explore the related impacts
2. Integrate additional processes in climate models
3. Develop high resolution regional climate models along with
high quality gridded climate datasets for Europe
4. Reduce uncertainty in climate predictions and impact
estimates
5. Increased application of climate predictions
6. Increased availability of scientific knowledge and provision of
relevant information related to the impacts of climate change
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Overview of Research Themes
RT1 James Murphy, Tim Palmer
 To build and test an ensemble prediction system based on
global Earth System Models for use in the generation of
multi-model simulations of future climate in RT2A.
RT2A Jean-Francois Royer, Guy Brasseur
 To produce sets of climate simulations and provide the
multi-model results needed in other RTs: validation RT5,
understanding processes RT4, as well as providing
boundary conditions and forcing fields for regional model
simulations RT2B.
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Overview of Research Themes (continued)
RT3 Jens Christensen, Markku Rummukainen
 To provide improved climate model tools developed in the
context of regional models, first at 50 km, later at 25 km
resolution for specified sub-regions, including provision of a
multi-model based ensemble system for regional climate
prediction for use in RT2B.
RT2B Clare Goodess, Daniela Jacob
 To provide ensemble based regional climate scenarios and
seasonal to decadal hindcasts for use in other RTs:
understanding processes RT4, validation RT5, and impacts
studies RT6.
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Overview of Research Themes (continued)
RT4 Julia Slingo, Herve le Treut
 To advance the understanding of the basic science at the
heart of the ENSEMBLES project, exploiting integrations
performed in RT2A, linking with RT5 on the evaluation of
the ensemble prediction system and feeding back results
to RT1.
RT5 Antonio Navarra, Albert Klein Tank
 To perform a comprehensive and independent evaluation
of the performance of the ensemble prediction system,
including the production of high resolution observational
dataset, and using integrations from RT1, RT2A, RT2B
and RT3.
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Overview of Research Themes (continued)
RT6 Andy Morse, Colin Prentice
 To carry out climate impact assessments, including linking
impact models to ENSEMBLES probabalistic scenarios
produced in RT2A and RT2B, in order 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 with and without greenhouse
gas reduction policies, and test the sensitivity of these
scenarios to climate change.
RT8 Martin Beniston, Christos Giannakopolous
 Represents the interface between the ENSEMBLES scientific
consortium and a wider audience that includes scientists,
stakeholders, policymakers and the general public.
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Research Themes
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RT0 Management
The Project Office:
ENSEMBLES
Co-ordinator
Dave
Griggs
ENSEMBLES
Director
Chris
Hewitt
ENSEMBLES
Secretary
Pip
Gilbert
Assisted by:
ENSEMBLES EC
Project Officer
Met Office EU
Manager
ENSEMBLES
Management Board
RT Steering Groups
All participants
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Georgios Amanatidis
Adrian Broad
2 RT co-ordinators
per RT
Work Package
leaders
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Concluding remarks I
Integrates world-leading European research
 Participation by main European modelling centres to provide earth
system model (ESM) and regional model components
 Exploits PRISM infrastructure to explore uncertainty using multimodel approach
 Strengthened collaboration between physical climate modellers
and experts in the carbon cycle and atmospheric chemistry
 Participation by applications modellers to deliver climate impacts
predictions of societal relevance
 Uses techniques and knowledge gained at seasonal timescales
and applies them to decadal and longer timescales
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Concluding remarks II
Quantifies and reduces uncertainty in representation of Earth system
 Carbon cycle, atmospheric chemistry, and climate to be considered
together in a rigorous and interactive way
 Combination of global and regional models enables resolution of
adequate geographic detail, capturing both regional effects/impacts
but including global teleconnections
 Economic and social dimensions of uncertainty to be considered
 Multi-model ensemble-based probability approach will quantify
uncertainty, lead to increased understanding, and influence the
development of the next generation of models, thereby leading to
uncertainty reduction in the future
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