overview of the uk / european program on i&a clare goodess climatic research unit university of...

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: t.holt@uea.ac.uk

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: t.holt@uea.ac.uk

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