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The PRUDENCE project Jens Hesselbjerg Christensen PRUDENCE coordinator COP10, 13 December 2004.

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Presentation on theme: "The PRUDENCE project Jens Hesselbjerg Christensen PRUDENCE coordinator COP10, 13 December 2004."— Presentation transcript:

1 The PRUDENCE project Jens Hesselbjerg Christensen PRUDENCE coordinator COP10, 13 December 2004

2 1.Danish Meteorological Institute, Copenhagen, DK 2.CINECA, Bologna, IT 3.Météo-France/CNRM, Toulouse, FRA 4.Deutsches Zentrum für Luft- und Raumfahrt e.V., Weßling, GER 5.Hadley Centre for Climate Prediction and Research, Met Office, Bracknell, UK 6.Climate Research ETH (Eidsgenössische Technische Hochschule), Zürich, CH 7.GKSS Research Center (Institute for Coastal Research), Geesthacht, GER 8.Max Planck Institut für Meteorologie, Hamburg, GER 9.Swedish Meteorological and Hydrological Institute, Rossby Centre, Norrköping, SWE 10.Universidad Complutense, Madrid, SP 11.Universidad Politecnica, Madrid, SP 12.International Centre for Theoretical Physics, Trieste, IT 13.Danish Institute of Agricultural Sciences, Foulum, DK 14.Risø National Laboratory, System Analysis Dept., DK 15.University of Fribourg, CH 16.Finnish Environmental Institute, Helsinki, FIN 17.University of Reading, UK 18.University of Lund, SWE 19.Centre International de Reserche sur l’Environment et Developpement,SMASH, Paris, FRA 20.Climate Research Unit, University of East Anglia, UK 21.Finnish Meteorological Institute, Associated to FEI (No. 16), FIN A.Norwegian Meteorological Institute, Blindern, NO B.Royal Dutch Meteorological Institute, De Bilt, NL C.UQAM, Montreal, CAN D.CSIRO, Victoria, AUS E.Czech Republic, Israel, Greece, California, USA……………….. F.Munich-Re, Electricité de France, Elforsk, Hamburg Institute of International Economics, Uni-Münster, DG-Research, STARDEX, MICE The PRUDENCE Consortium

3 Overview this presentation The scientific objectives Aims and products Results

4 PRUDENCE objectives provide a series of high resolution (spatially and in time) climate change scenarios for for Europe;provide a series of high resolution (spatially and in time) climate change scenarios for for Europe; assess the uncertainty in European regional climate scenarios resulting from model formulation;assess the uncertainty in European regional climate scenarios resulting from model formulation; in practical terms characterise the level of confidence in these scenarios and the variability in them related to model formulations and climate natural/internal variability;in practical terms characterise the level of confidence in these scenarios and the variability in them related to model formulations and climate natural/internal variability;

5 PRUDENCE objectives quantitatively assess the risks rising from changes in regional weather and climate over all of Europe, and estimate future changes in extreme events such as flooding and wind storms, by providing a robust estimation of the likelihood and magnitude of the changes;quantitatively assess the risks rising from changes in regional weather and climate over all of Europe, and estimate future changes in extreme events such as flooding and wind storms, by providing a robust estimation of the likelihood and magnitude of the changes;

6 PRUDENCE objectives demonstrate the value of the wide-ranging climate change scenarios by applying them to climate impacts models focusing on effects on adaptation and mitigation strategies;demonstrate the value of the wide-ranging climate change scenarios by applying them to climate impacts models focusing on effects on adaptation and mitigation strategies; assess socio-economic and policy related decisions for which such improved scenarios could be beneficial;assess socio-economic and policy related decisions for which such improved scenarios could be beneficial; disseminate the results of PRUDENCE widely and provide a project summary aimed at policy makers and non-technical interested partiesdisseminate the results of PRUDENCE widely and provide a project summary aimed at policy makers and non-technical interested parties

7  Regional aspects of coupled ocean- atmosphere general circulation models Regional information

8 A2 & B2 Temperature change relative to global mean (Giorgi et al. GRL, 2001)

9 A2 & B2 Precipitation change (Giorgi et al. GRL, 2001)

10  Regional aspects of coupled ocean-atmosphere general circulation models Regional information  Time slice experiments utilizing high- and variable- resolution atmospheric GCM’s

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12  Regional aspects of coupled ocean-atmosphere general circulation models Regional information  Limited area (regional climate) models RCM’s  Statistical down scaling (see STARDEX)  Time slice experiments utilizing high- and variable- resolution atmospheric GCM’s

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16 Impact scenarios today scenario GCM today scenario RCM scale globallocal An interface Impactmodel A road to impact scenarios the Delta Change approach

17 UNCERTAINTIES IN CLIMATE CHANGE PROJECTIONS Uncertainty due to observational limitations –use multiple means of validation Uncertainty in future emissions –use a range of SRES emissions scenarios Natural variability –use a number of different initial conditions (ensembles) Uncertainty in the response of the climate system –use a range of climate modelling systems –AND/OR assess confidence in climate projections (better models) Need for a large-scale coordinated effort

18 CO 2 EMISSIONS PROFILES under IPCC SRES scenarios Source: IPCC

19 GLOBAL TEMPERATURE RISE due to four SRES emissions scenarios Source: Hadley Centre

20 DMIHadRossbyEs ETH IPCC MPI GKSS Meteo T42 100km 12 km

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22 Relating to observed trends Flooding Heat wave

23 Recent European Summer Climate Trends and Extremes Summer precipitation over much of Europe and the Mediterranean Basin has shown a decreasing trend in recent decades The intensity of summer precipitation events has shown predominant increases throughout Europe The western European summer drought of 2003 is considered one of the severest on record. –Heat related casualties in France, Italy, the Netherlands, Portugal, the United Kingdom, and Spain reached nearly 20,000. –Many countries are experiencing their worst harvest since World War II. In contrast, during 2002, many European countries experienced one of their wettest summers on record. –Weather systems brought widespread heavy rainfall to central Europe, causing severe flooding along all the major rivers. –The Elbe River reached its highest level in over 500 years of record

24 What can PRUDENCE say? Christensen&Christensen (2003;2004) Change in JAS mean precip ( minus )

25 Christensen & Christensen, Nature (2003) Sensitivity due to GCM and RCM resolution ECHAM Hadley 50kmHadley 25km

26 Changes in heavy and mean precipitation ( => )

27 Schär et al. (2004)

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29 Changes in Summer 500 hPa Geopotential Heights (  meters) B2 Scenario ( ) minus ( ) NCEP Reanalysis ( ) minus ( ) Pal et al. (2004)

30 Change in Summer Precipitation B2 Scenario ( ) minus ( ) (% change) CRU Observations ( ) minus ( )

31 Changes in Summer Extremes: B2 Scenario (% change) (  Days) Max Dry Spell Length ( ) minus ( ) Max 5-Day Precipitation ( ) minus ( )

32 B2 Precipitation Distribution REF  ref  B2  B2  ref More Droughts More Floods Drier Summers

33 Conclusions I In both the A2 and B2 scenarios we find summer warming and drying over most of the European region. Maximum dry spell length (drought), maximum precipitation intensity (flood) and interannual variability increase in summer throughout most of Europe Shift and change in shape of the precipitation distribution The results from the climate change simulations are consistent with trends of summer climate observed over Europe in recent decades

34 Impacts Hydrology

35 Prudence basins

36 Baltic Basin

37 7 RCMs … A2 same GCM boundary

38 7 RCMs ~50km … A2 2 RCMs ~25km … A2 same GCM boundary

39 9 RCMs ~50km … A2 2 RCMs ~25km … A2 2 GCMs

40 9 RCMs ~50km … A2 2 RCMs ~25km … A2 3 RCMs ~50km … B2 2 GCMs

41 7 RCMs ~50km … A2 1 GCM ~150km … A2 same GCM boundary

42 Conclusions 2 Ensemble information from different models provides valuable information about the degree of uncertainty in the impact signal Seasonal shift in hydrological cycle confirmed

43 Impacts Hydrology Storm surges

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49 Conclusions 3 More intensive surge in warmer climate –Up to 30% increase in high percentiles, no change in mean. –Magnitude of shift is highly dependant on location. Valid for all four RCM simulations, driven with same GCM (HC) and also similar signal for simulation, driven with another GCM

50 Impacts Hydrology Storm surges Simple indices

51 Potential shifts in extreme climatic events => risks in society and ecosystems CLIMATIC CHANGE IN:IMPACT SECTORSADAPTATION OPTIONS Maximum 1-day and 5-day precipitation total Water resources, agriculture Regulation guidelines, flood gates, land use planning Maximum length of dry spells Water resources, agriculture Increases in water-use efficiency, water recycling Total number of frost daysEcosystems, transport, heating, building Preparedness for decreases in energy consumption Total number of days crossing the 0ºC threshold Wintertime road maintenance Timing of salting of roads Frost-free seasonEcosystems, transportTiming of cultivation practices Snow seasonRecreation, tourismArtificial snow in ski centres Maximum ice cover over the Baltic Sea Wintertime shippingTiming and efficiency of ice- breaking

52 Changes in frost days and min temperature =>

53 Impacts Hydrology Storm surges Simple indices Agriculture

54 Thermal suitability for grain maize (baseline ’s) green – baseline suitability red – suitability extension for all RCMs blue – RCM uncertainty in extension Suitable area Observed baseline (CRU) 3 RCMs B2, HadAM3H-driven 9 RCMs A2, HadAM3H-driven

55 Thermal suitability for grain maize in 2080’s 1 GCM CSIRO-Mk2 A1FI, A2, B1 and B2 4 GCMs CSIRO, CCCma, EH4OPYC, HadCM3 A2 RCM-uncertainty GCM-uncertainy Emissions-uncertainy 9 RCMs A2, HadAM3H-driven green – baseline suitability red – suitability extension for all RCMs blue – RCM uncertainty in extension

56 Winter wheat yield in 2080’s (example from 1 RCM) Modelled 2080’sDifference to CRU baseline

57 Nitrate leaching from wheat in 2080’s (example from 1 RCM) Modelled 2080’sDifference to CRU baseline

58 Conclusions 4 General productivity increases for agricultural crops in Northern Europe and decreases in Southern Europe has low uncertainty, although the option to cultivate crops during the winter in some Mediterranean countries needs more consideration Impacts of nitrate leaching (and possibily other environmental effects of agriculture) may have a completely different spatial structure than the yield effect

59 Impacts Hydrology Storm surges Simple indices Agriculture Society

60 To compare the future climate of Paris and the present climate of a gridpoint x’, we define 3 distances: –d T measures the mean absolute distance between the 12 monthly mean temperatures –d A P measures the relative distance between the annual mean precipitations (to account for the total water availability) –d M P measures the mean relative distance between the 12 monthly mean precipitations (to account for the precipitation seasonal cycle) 10 European cities: Athens, Barcelona, Berlin, Geneva, London, Madrid, Marseille, Paris, Roma and Stockholm. Methodology

61 A global shift southward Results based on ARPEGE

62 A global shift southward Results based on HadRM3H

63 Impacts Hydrology Storm surges Simple indices Agriculture Society Surprises?

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67 Dec 2001 Sept 2002 Oct 2003 Sept 2004 Thank you all

68 Utilisation of PRUDENCE data for regional analysis Ekstrøm et al. (2004)

69 Assessing uncertainty of regional changes Construct a probability distribution function (PDF) of climate change Combine PDF from –global annual mean temperature increase –change in regional temperature/precipitation – per degree of global temperature increase (Jones, 2000) (Uniform distributions from within a range) Normal distribution* of PDF for the scaling variables, log normal for global increase Full range of uncertainty * (estimated from ANalysis Of VAriance (ANOVA) )

70 ( ) wrt. ( ) Temperature Precipitation Ekström et al. (in press)

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