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Page 1GMES - ENSEMBLES 2008
ENSEMBLES
Page 2GMES - ENSEMBLES 2008
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
Page 3GMES - ENSEMBLES 2008
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
Page 4GMES - ENSEMBLES 2008
Project output 2004-2007
150 publications20 book contributionsApprox 500 conference presentations
These numbers do not include the planned project output (conferences, workshops etc)
Page 5GMES - ENSEMBLES 2008
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
Page 6GMES - ENSEMBLES 2008
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
Page 7GMES - ENSEMBLES 2008
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
pic
al S
torm
Nu
mb
er
MULTIMODEL: ECMWF LODYC UKMO CNRM CERFACS MPI SCNR
Forecast starting on 1st NovemberTropical Storm Frequency over the South Pacific (DJFMA)
RMS Error= 2.50( 3.17)Correlation=0.62( 0.99)
FORECAST Observations 2 Standard Deviations
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
MULTIMODEL: ECMWF LODYC UKMO CNRM CERFACS MPI SCNR
Forecast starting on 1st MayTropical Storm Frequency over the North Atlantic (JJASO)
RMS Error= 2.93( 3.65)Correlation=0.62( 0.99)
FORECAST Observations 2 Standard Deviations
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
MULTIMODEL: ECMWF LODYC UKMO CNRM CERFACS MPI SCNR
Forecast starting on 1st MayTropical Storm Frequency over the western North Pacific (JJASO)
RMS Error= 2.73( 3.93)Correlation=0.72( 1.00)
FORECAST Observations 2 Standard Deviations
Western North Pacific
F. Vitart (ECMWF)
Page 8GMES - ENSEMBLES 2008
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
Page 9GMES - ENSEMBLES 2008
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
Page 10GMES - ENSEMBLES 2008
T2m response E1 scenario
Taken from E. Roeckner, RT2A presentation ENSEMBLES GA 2008, Santander, Spain
Page 11GMES - ENSEMBLES 2008
Observations, 1864-2003
Projected temperature extremes
Page 12GMES - ENSEMBLES 2008
Precipitation changes to 2090-2099
Page 13GMES - ENSEMBLES 2008
ECHAM HIRHAM
Change in mean precipitation (%)
July August September
Page 14GMES - ENSEMBLES 2008
Mean
Changes in precipitation frequency (%)
July-August-September> 99% percentile
Page 15GMES - ENSEMBLES 2008
Projected change in summer-average precipitation over Europe
- an ensemble of model simulations.
-15 0 15
% change in 2050s
Page 16GMES - ENSEMBLES 2008
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
Page 17GMES - ENSEMBLES 2008
Likelihood of low water levels in Lake Mälaren, Sweden (perturbed physics exp.)
Use of aresponse surfaceApproach – regionalscale
Page 18GMES - ENSEMBLES 2008
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
Page 19GMES - ENSEMBLES 2008
Projections of bark beetle infestation in northern European forests
Page 20GMES - ENSEMBLES 2008