An Integrated Project under the 6 th Framework Programme of the EU Project Overview Project Office can be contacted on [email protected] Web

An Integrated Project under the 6th Framework Programme of the EU

Project Overview

Project Office can be contacted on [email protected] site is http://www.ensembles-eu.org

ENSEMBLES

© Crown copyright 2004 Page 2

Outline

Motivation for the project

What is the project

What will the project do


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.


We can produce a small number of different predictions with no idea of how reliable they might be

Current Status of Climate Change Prediction


Probabilistic Climate Predictions

2080s SE England winter rainfall

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0% 20% 40% 60% 2080s SE England winter rainfall

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current position required position


Future emission scenariosEffects of natural variability

Modelling of Earth system processes

Sources of uncertainty


Climate Prediction Modelling

From Murphy et al, Nature 2004


Ensemble Climate Prediction

Run ensembles of different climate models to sample uncertainties

Measure variations in reliability between models

Produce probabalistic predictions of climate change


The ENSEMBLES Project

A five year project supported by funding under FP6Started 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)


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


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


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.


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.



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.



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.


Research Themes


RT0 Management

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


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 multi-model 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


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

Concluding remarks II


Documents

An Integrated Project under the 6 th Framework Programme of the EU Project Overview Project Office can be contacted on [email protected] Web