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GMES - ENSEMBLES 2008

ENSEMBLES


The ENSEMBLES Project

Began 4 years ago, will end in December 2009

Supported by €15M of European Commission funding, coordinated by Met Office Hadley Centre

67 partners from across EU, Switzerland, Australia, US we welcome requests from new groups to participate (unfunded)

Collaborates with other international projects

Brings together a wide range of climate change-related research communities

Who, where, when


Output / products:

Multi-model RCM projections for Europe at 25kmSignificant contribution to IPCC AR4 Investigating probabilistic methods for “s2d2c” timescales

for range of models to explore impactsEarth system model simulations, will use a mitigation

emissions scenario developed within ENSEMBLESProviding information relevant to IPCC planningWeb-based statistical tools for finer scale informationDaily gridded dataset for Europe, + uncertainty estimates


Project output 2004-2007

150 publications20 book contributionsApprox 500 conference presentations

These numbers do not include the planned project output (conferences, workshops etc)


ENSEMBLES Strategic Objectives

Project Goal:Overall goal is to maintain and extend European pre-eminence in the provision of policy relevant information on climate and climate change and its interactions with society

Develop an ensemble prediction system based on global and regional climate models, validated against observations and analyses, to work towards a probabilistic 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

Exploit the results by linking the outputs to a range of applications, including agriculture, forestry, health, energy, water resources, insuranceWe are aiming to increase availability of scientific knowledge and provision of relevant information related to the impacts of climate change

How


Comparison of calculated storm loss based on ERA-40 with insurance data for

Germany. Correlations between calculated loss and insurance date rate between 0.85-0.9


1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

123456789

101112131415161718192021222324252627282930

Tro

pic

al S

torm

Nu

mb

er

MULTIMODEL: ECMWF LODYC UKMO CNRM CERFACS MPI SCNR

Forecast starting on 1st MayTropical Storm Frequency over the Eastern North Pacific (JJASO)

RMS Error= 3.82( 4.56)Correlation=0.59( 0.98)

FORECAST Observations 2 Standard Deviations

1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

123456789

1011121314151617181920212223

Tro

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al S

torm

Nu

mb

er


Forecast starting on 1st NovemberTropical Storm Frequency over the South Pacific (DJFMA)



1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

23456789

1011121314151617181920212223242526

Tro

pic

al S

torm

Nu

mb

er


Forecast starting on 1st MayTropical Storm Frequency over the North Atlantic (JJASO)



North Atlantic Eastern North Pacific

South Pacific

Seasonal prediction of tropical cyclones

1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

89

101112131415161718192021222324252627282930313233343536373839

Tro

pic

al S

torm

Nu

mb

er


Forecast starting on 1st MayTropical Storm Frequency over the western North Pacific (JJASO)



Western North Pacific

F. Vitart (ECMWF)


Seasonal crop forecast using an ensemble crop yield model

63 ensemble members

0

5

10

15

20

25

200 300 400 500 600 700 800 900 1000 1100 1200

Yield (kg ha-1)

Fre

qu

ency

Multi-model ensemble for predicting seasonal groundnut yield in Gujarat, India, 1998, from Challinor et al. (2005).

Observed775 kg ha-1

713 kg ha-1

Model average


ENSEMBLES mitigation emissions scenario

Uses proposed IPCC “AR5” design Earth system models will be driven by GHG concentrations, rather than emissions. Carbon fluxes give implied emissions

Will inform details of AR5 design and how to scientifically exploit the runs

New emissions scenario developed IPCC SRES A1B baseline, stabilise

towards 450ppmv CO2eq

provides information towards EU goal of limiting warming to less than 2°C above pre-industrial levels


T2m response E1 scenario

Taken from E. Roeckner, RT2A presentation ENSEMBLES GA 2008, Santander, Spain


Observations, 1864-2003

Projected temperature extremes


Precipitation changes to 2090-2099


ECHAM HIRHAM

Change in mean precipitation (%)

July August September


Mean

Changes in precipitation frequency (%)

July-August-September> 99% percentile


Projected change in summer-average precipitation over Europe

- an ensemble of model simulations.

-15 0 15

% change in 2050s


Response surface modelling of projected risk of climate change impact

0 1 2 3 4272

353

434

515

596

Temperature change (°C)

CO2 c

on

cen

tratio

n (

pp

mv

)

100

8060

110

90

70

120

Present dayPresent day

0 1 2 3 4272

353

434

515

596

Temperature change (°C)

CO2 c

on

cen

tratio

n (

pp

mv

)

100

8060

110

90

70

120

Present dayPresent day

80 70

60 50

(a) Response surface (b) Risk of impact, 2050


Likelihood of low water levels in Lake Mälaren, Sweden (perturbed physics exp.)

Use of aresponse surfaceApproach – regionalscale


Risk probability of low crop productivity - Durum wheat, perturbed physics experiment

Delta Risk< -20 % -10 % 0 % 10 % 20 % 30 % 40 % 50 % > 60 %

**

** Delta Risk was calculated as differences between the percentage of yields that do not exceed yield threshold (20 percentile) in present and A1b scenarios


Projections of bark beetle infestation in northern European forests

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