overview of the uk / european program on i&a clare goodess climatic research unit university of...
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Overview of theOverview of theUK / European programUK / European program
on I&Aon I&A
Clare GoodessClare GoodessClimatic Research UnitClimatic Research Unit
University of East AngliaUniversity of East Angliahttp://www.cru.uea.ac.ukhttp://www.cru.uea.ac.uk
A ‘selective’ view from Norwich
MICE / PRUDENCE / STARDEXENSEMBLES
This co-operative cluster of projects brings together European expertise in the fields of climate modelling, regional downscaling, statistics, and impacts analysis to explore future changes in extreme events in response to global warming.•PRUDENCE will provide high-resolution climate change scenarios for 2071-2100 for Europe using regional climate models. PRUDENCE project summary•STARDEX will provide improved downscaling methodologies for the construction of scenarios of changes in the frequency and intensity of extreme events. STARDEX project summary•MICE uses information from climate models to explore future changes in extreme events across Europe in response to global warming. MICE project summary Last modified:16 August 2002 MICE STARDEX PRUDENCEProject Web Sites:
Contact InformationCopyright information: the above photo montage was created in XaraX using copyright pictures from: © Collier County Florida Emergency Management and © Environment Agency.The three projects are supported by the European Commission under the Framework V Thematic Programme ”Energy, Environment and Sustainable Development” (EESD), 2002-2005.
Scroll down for Project Summaries: follow the links above to Project Web Sites.
Hit CounterWeb Site designed and implemented by Tom Holt, © 2002
Comments and suggestions welcome: [email protected]
PRUDENCE
STARDEX
MICE
http://www.cru.uea.ac.uk/projects/mps/
Observed changes in extremes
1958-2000 trend in frost days1958-2000 trend in frost days
Scale is days per year. Red is decreasing
Malcolm Haylock, UEA/STARDEX
1958-2000 trend in frost days1958-2000 trend in frost days
Scale is days per year. Red is decreasing.
Malcolm Haylock, UEA/STARDEX
AthensAthensFebruary 2004February 2004
1958-2000 trend in hot summer (JJA) days1958-2000 trend in hot summer (JJA) days
Scale is days per year. Red is increasing
Malcolm Haylock, UEA/STARDEX
Scale is days per year. Red is increasing
Malcolm Haylock, UEA/STARDEX
Western EuropeWestern EuropeAugust 2003August 2003
Property damage: US$ 13 bnProperty damage: US$ 13 bnFatalities: 27,000 (14,800 in France)Fatalities: 27,000 (14,800 in France)
1958-2000 trend in hot summer (JJA) days1958-2000 trend in hot summer (JJA) days
1958-2000 trend in 1958-2000 trend in heavy summer (JJA) rain eventsheavy summer (JJA) rain events
Scale is days per year. Blue is increasing
Malcolm Haylock, UEA/STARDEX
1958-2000 trend in 1958-2000 trend in heavy summer rain eventsheavy summer rain events
Scale is days per year. Blue is increasing
Malcolm Haylock, UEA/STARDEX
Central and Eastern EuropeCentral and Eastern EuropeAugust 2002August 2002
Fatalities: > 100Fatalities: > 100Economic losses: > US$18 bnEconomic losses: > US$18 bnInsured losses: > US$3 bnInsured losses: > US$3 bn
Are extremes well simulated byclimate models?
90% precipitation quantile, Autumn (SON)90% precipitation quantile, Autumn (SON)
OBS (79-93)
HadRM (CTR1) HIRHAM (CTR1)
Figure provided by Christoph Frei, ETH and STARDEX/PRUDENCE
How are extremes projected to change?
GC
Column 1: HadAM3. Columns 2-7: six European RCMs
Top row: temperature. Bottom row: rainfall
JJA changes: 2071-2100 minus 1961-1990JJA changes: 2071-2100 minus 1961-1990
DJF, Relative Change, Central Europe
Frequency
Intensity 90% Quantile
5-, 10-, 20-year ExtremesMean
JJA, Relative Change, Central Europe
Frequency
Intensity 90% Quantile
5-, 10-, 20-year ExtremesMean
Change in the length of the summer drought between 1961-90 and 2070-2100, based on the HadRM3 (A2a) simulation. Over the Mediterranean region of Europe, especially S. Italy and S. Spain, this number is predicted to increase by more than 30 days.
RAINFALL: Summer Drought
Are the predicted future changes Are the predicted future changes consistent with the observed consistent with the observed
changes in extremes?changes in extremes?
Change in mean JJArainfall from 1961-90to 2071-2100 (%)
Change in exceedence of99th percentile of JJA rainfall from 1961-90 to 2071-2100
Christensen & Christensen, Christensen & Christensen, NatureNature, 2003, 2003
Schaer et al., Schaer et al., NatureNature, 2004, 2004
Beniston, Beniston, GRLGRL, 2004, 2004
Statistical downscaling – STARDEXStatistical downscaling – STARDEX
http://www.cru.uea.ac.uk/projects/stardex/
Heavy winter rainfall and links with Heavy winter rainfall and links with North Atlantic Oscillation/SLPNorth Atlantic Oscillation/SLP
-3
-2
-1
0
1
2
3
4
1955 1965 1975 1985 1995
NAO -R90N PC2
CC1: Heavy rainfall (R90N) CC1: mean sea level pressure
Malcolm Haylock, UEA/STARDEX
0
0.1
0.2
0.3
0.4
0.50.6
0.7
0.8
0.9
1
pav pint pq90 px5d pxcdd pfl90 pnl90
Indices/season
Co
rrel
atio
nNW UK (averages of 15 stations)
RBF - yellow, MLP – red, SDSM - green
0
0.1
0.20.3
0.4
0.5
0.6
0.70.8
0.9
1
pav pint pq90 px5d pxcdd pfl90 pnl90
Indices/season
Co
rrel
atio
n
SE UK(averages of 28 stations)
Colin Harpham and Rob Wilby, KCL/STARDEX
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
pav pint pq90 px5d pxcdd pfl90 pnl90
Indices/season
Co
rrel
atio
n
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
pav pint pq90 px5d pxcdd pfl90 pnl90
Indices/season
Co
rrel
atio
n
Murcia
Alicante
RBF (single-site) - blue, RBF - yellow, GA-RBF – red, SDSM - green
Colin Harpham and Rob Wilby, KCL/STARDEX
STARDEX Study Regions
UK: 6 stations
Iberia: 16 stationsGreece: 8 stations
Italy: 7 stations
Alps: 10 stations
Germany: 10 stations
The ‘FIC dataset’
Method provides: Y/N Comments/Notes Station-scale information Grid-box information European-wide information Daily time series Seasonal indices of extremes Temporally consistent temperature and precipitation
Spatially consistent multi-site information Temporally consistent multi-site information Method requirements : Relatively
high/low Comments/Notes
Computing resources Volume of data inputs Availability of input data
Draft methodological criteria forstatistical and dynamical downscaling
Relative Performance Confidence High Medium Low Temperature
Indices Seasons Regions
Precipitation Indices
Seasons Regions
Overall performance: Mean temperature
Temperature extremes Mean precipitation
Precipitation extremes
Good/average/poor/NA Good/average/poor/NA Good/average/poor/NA Good/average/poor/NA
Optimal spatial scale: Recommended impact applications:
Draft performance criteria forstatistical and dynamical downscaling
What are the potential impacts of the projected changes?
MICEMICEModelling the Impact of Climate ExtremesModelling the Impact of Climate Extremes
• 2 objectives– To select/develop models to predict the
impact of changing extremes on activity sectors
• Energy use• Insurance losses• Forestry (wind throw – N Europe)• Forestry (fire – Mediterranean)• Agriculture
– Assess spatial changes in these impacts
Work Package 4 – impact modelling
• The impact of changes in climate extremes on Mediterranean Agriculture – GIS-based model of fire risk, Tuscany, Italy.
• Environmental Database– Climate– Morphology– Land use and vegetation cover– Forest fire data– Agricultural crops
• FWI and CROPSYST• Interpolation strategies were tested
Work Package 4 – impact modelling
10.731.7>1000 m
17.217.3600-1000m
14.210.60-600 m
B2a-AA2a-AAltitude
10.731.7>1000 m
17.217.3600-1000m
14.210.60-600 m
B2a-AA2a-AAltitude
60 00 00 65 00 00 70 0000 75 00 00
4 7 0 0 0 0 0
4 7 5 0 0 0 0
4 8 0 0 0 0 0
4 8 5 0 0 0 0
4 9 0 0 0 0 0
0
5
10
15
20
25
30
35
40
60 00 00 65 00 00 70 0000 75 00 00
4 7 0 0 0 0 0
4 7 5 0 0 0 0
4 8 0 0 0 0 0
4 8 5 0 0 0 0
4 9 0 0 0 0 0
0
5
10
15
20
25
30
35
40
A2a-A B2a-A
-3%7%>1000 m
17%30%600-1000m
20%23%0-600 m
B2a-AA2a-AAltitude
-3%7%>1000 m
17%30%600-1000m
20%23%0-600 m
B2a-AA2a-AAltitude6 000 00 6 500 00 70 000 0 75 000 0
4 700 000
4 750 000
4 800 000
4 850 000
4 900 000
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
6 000 00 6 500 00 70 000 0 75 000 0
4 700 000
4 750 000
4 800 000
4 850 000
4 900 000
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
X 100X 100
A2a-A B2a-A
95th percentile values of the FWI for August expressed as the difference between future scenarios (A2a, B2a) and the present scenario (A).
Increase in the risk of heat stress during flowering stages expressed as the difference between future scenarios (A2a, B2a) and the present scenario (A)
• 4 mini workshops:– Climate Change and Winter Tourism 04.11.03,
Lucerne. 34 participants, discussions about the uncertain future of winter tourism in the Alps
– Poznan, impacts on flooding – 25.03.04– Lund, impacts on forests and high latitude
ecosystems – 06.05.04– Crete, impacts on Mediterranean beach
tourism – 05.06.04
Work Package 5
This co-operative cluster of projects brings together European expertise in the fields of climate modelling, regional downscaling, statistics, and impacts analysis to explore future changes in extreme events in response to global warming.•PRUDENCE will provide high-resolution climate change scenarios for 2071-2100 for Europe using regional climate models. PRUDENCE project summary•STARDEX will provide improved downscaling methodologies for the construction of scenarios of changes in the frequency and intensity of extreme events. STARDEX project summary•MICE uses information from climate models to explore future changes in extreme events across Europe in response to global warming. MICE project summary Last modified:16 August 2002 MICE STARDEX PRUDENCEProject Web Sites:
Contact InformationCopyright information: the above photo montage was created in XaraX using copyright pictures from: © Collier County Florida Emergency Management and © Environment Agency.The three projects are supported by the European Commission under the Framework V Thematic Programme ”Energy, Environment and Sustainable Development” (EESD), 2002-2005.
Scroll down for Project Summaries: follow the links above to Project Web Sites.
Hit CounterWeb Site designed and implemented by Tom Holt, © 2002
Comments and suggestions welcome: [email protected]
PRUDENCE
STARDEX
MICE
http://www.cru.uea.ac.uk/projects/mps/
35 00/XXXX © Crown copyrightHadleyCentre
ENSEMBLES
ENSEMBLE-based Predictions of Climate Changes and their Impacts
36 00/XXXX © Crown copyright
Hadley Centre for Climate Prediction & Research HadleyCentre
ENSEMBLES
A five year project under EC Framework Programme VI
Start date 1 September? (concluding negotiations)
Funding from EC of 15 million Euros
72 partners - EU, candidate countries, Switzerland, Australia, US
Ten Research Themes
37 00/XXXX © Crown copyright
Hadley Centre for Climate Prediction & Research HadleyCentre
ENSEMBLES
Project Goals 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
38 00/XXXX © Crown copyright
Hadley Centre for Climate Prediction & Research HadleyCentre
Scientific and Technological Objectives 1-3 Produce probabilistic predictions from seasonal
to decadal & longer timescales through the use of ensembles, and use these to explore the related impacts
Integrate additional processes in climate models to produce true Earth System models
Develop higher resolution climate models to provide more regionally detailed climate predictions and better information on extreme events
ENSEMBLES
39 00/XXXX © Crown copyright
Hadley Centre for Climate Prediction & Research HadleyCentre
Scientific and Technological Objectives 4-6 Reduce uncertainty in climate predictions
through increased understanding of climate processes and feedbacks and through evaluation and validation of models and techniques
Increased application of climate predictions by a growing and increasingly diverse user community
Increased availability of scientific knowledge and provision of relevant information related to the impacts of climate change, within the scientific community, and to stakeholders, policymakers and the public
ENSEMBLES
40 00/XXXX © Crown copyrightHadleyCentre
ENSEMBLES Research Themes
RT Name Co-ordinators
0 Project integration, management and promotion Dave Griggs
1 Development of the Ensemble Prediction System James Murphy, Tim Palmer
2A Production of seasonal to decadal hindcasts and
climate change scenarios (Model Engine Part 1) Guy Brasseur, Jean-François Royer
2B Production of Regional Climate Scenarios for Impact Clare Goodess, Daniela Jacob
Assessments (Model Engine Part 2)
3 Formulation of very high resolution Regional Climate Jens Christensen,
Model Ensembles for Europe Markku Rummukainen
4 Understanding the processes governing climate Julia Slingo, Herve le Treut
variability and change, climate predictability and
the probability of extreme events
5 Independent comprehensive evaluation of the Antonio Navarra, Albert Klein Tank
ENSEMBLES simulation-prediction system against observations/analyses
6 Assessments of impacts of climate change Andy Morse, Colin Prentice
7 Scenarios and Policy Implications Richard Tol, Roberto Roson
8 Dissemination, Education, and Training Martin Beniston,
Christos Giannakopolous