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Regional climate change – European perspectives
Martin Stendel Danish Climate Centre Danish Meteorological Institute 1st EIONET Workshop on CLIMATE CHANGE VULNERABILITY, IMPACTS AND ADAPTATION EEA, Copenhagen, November 2007
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Outline Regional climate change – the IPCC approach
Europe as an example Research needs
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Future climate – all scenarios
AR4, with respect to
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Projected surface temperature changes for the early and late 21st century (relative to 1980–1999)
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Uncertainties in climate scenario calculations
Observational uncertainties Lots of model validations Emission scenario uncertainties Multiple scenarios Natural climate variability Ensemble simulations Climate sensitivity Use several models AND/OR improve credibility of climate models Large-scale, coordinated effort required
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Agreement amongst AR4 GCMs (21 models) in the A1B scenario - Europe
Annual DJF JJA Temperature change (°C) Precipitation change (%) Number of models (out of 21) projecting prec. change >0 IPCC 2007
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standard deviations After Tebaldi et al. (2006)
Ann. total prec. divided by # of wet days Difference minus standard deviations Changes in extremes based on multi-model simulations from nine global coupled climate models, adapted from Tebaldi et al. (2006). a). b) Changes of spatial patterns of precipitation intensity based on simulations between two 20-year means (2080–2099 minus 1980–1999) for the A1B scenario. c) Globally averaged changes in dry days (defined as the annual maximum number of consecutive dry days). d) changes of spatial patterns of dry days based on simulations between two 20-year means (2080–2099 minus 1980–1999) for the A1B scenario. Solid lines in panels a and c are the 10-year smoothed multi-model ensemble means, the envelope indicates the ensemble mean standard deviation. Stippling in panels b and d denote areas where at least 5 of the 9 models concur in determining that the change is statistically significant. Extreme indices are calculated only over land. Extremes indices are calculated following Frich et al. (2002). Each model's timeseries has been centered around its 1980–1999 average and normalized (rescaled) by its standard deviation computed (after detrending) over the period 1960–2099, then the models were aggregated into an ensemble average, both at the global average and at the grid-box level. Thus, changes are given in units of standard deviations. Ann. max. # of consecutive dry days Stippled: ≥5 (of 9) models show significant change After Tebaldi et al. (2006)
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PRUDENCE GCM-RCM EU FP5 project CNRM DMI ETHZ GKSS HC ICTP KNMI MPI
SMHI UCM A2+HadAM3H 3 1 A2+ECHAM4 A2+ARPEGE3 B2+HadAM3H B2+ECHAM4 B2+ARPEGE3 EU FP5 project
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PRUDENCE domains BI SC ME EA FR AL IP MD
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Model biases Jacob et al. 2007
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Climate change Christensen & Christensen 2007
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Change in mean temperature
ECHAM HIRHAM Winter
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Change in mean temperature
ECHAM HIRHAM Summer
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Extreme event analysis
Change in JAS mean precipitation ( minus ) Christensen & Christensen Nature 2003 EU PRUDENCE project
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Change in precipitation (%)
Mean 99% percentile Christensen & Christensen Nature 2003
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Schär et al. Nature 2004
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Schär et al. Nature 2004
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ENSEMBLES GCM-RCM Matrix
Global model Regional model METO-HC MPIMET IPSL CNRM NERSC CGCM3 Total number £ 2 (4) * 2 DMI ETH 1 KNMI ICTP SMHI UCLM C4I GKSS** Met.No** CHMI** OURANOS** Total ( ) 4 (6) 6 3 18 (20) EU FP6 project
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Example: Denmark Change /°C global warming 0.0 1.0 2.0 -5.0 0.0 5.0
Temperature[ºC] (ann) <x>=1.1 <s>=0.2 <med>=1.1 <p95>=1.4(1.3,1.5) <p50>=1.1(1.0,1.2) <p05>=0.7(0.6,0.8) Temperature[ºC] (DJF) (MAM) (JJA) (SON) 1.0 1.1 1.2 0.2 1.4(1.3,1.6) 1.4(1.3,1.5) 1.6(1.5,1.7) 1.0(1.0,1.1) 1.0(0.9,1.1) 1.1(1.0,1.1) 1.2(1.2,1.3) 0.6(0.5,0.8) 0.7(0.6,0.8) 0.9(0.7,1.0) 0.0 1.0 2.0 Precipitation [%] (ann) <x>=2.4 <s>=2.0 <med>=2.5 <p95>=5.6(4.5,6.6) <p50>=2.4(1.7,3.0) <p05>=-0.9(-1.9,0.2) Precipitation [%] (DJF) (MAM) (JJA) (SON) 9.8 3.6 -6.4 1.5 3.7 2.2 3.5 4.1 10.1 3.3 -7 1.7 15.9(13.8,17.9) 7.3(6.1,8.4) -0.6(-2.3,1.2) 8.3(6.1,10.5) 9.8(8.5,11.1) 3.6(2.9,4.4) -6.4(-7.5,-5.2) 1.5(0.0,2.9) 3.7(1.7,5.7) -0.0(-1.2,1.1) -12.2(-14.1,-10.3) -5.3(-7.5,-3.0) -5.0 0.0 5.0
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Climate analogues Hallegatte et al. 2006
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1) Very likely annual mean increase in most of northern Europe and the Arctic (largest in cold season), Canada, and the North-East USA; and winter (DJF) mean increase in Northern Asia and the Tibetan Plateau. (2) Very likely annual mean decrease in most of the Mediterranean area, and winter (JJA) decrease in southwestern Australia. (3) Likely annual mean increase in tropical and East Africa, Northern Pacific, the northern Indian Ocean, the South Pacific (slight, mainly equatorial regions), the west of the South Island of New Zealand, Antarctica and winter (JJA) increase in Tierra del Fuego. (4) Likely annual mean decrease in and along the southern Andes, summer (DJF) decrease in eastern French Polynesia, winter (JJA) decrease for Southern Africa and in the vicinity of Mauritius, and winter and spring decrease in southern Australia. (5) Likely annual mean decrease in North Africa, northern Sahara, Central America (and in the vicinity of the Greater Antilles in JJA) and in South-West USA. (6) Likely summer (JJA) mean increase in Northern Asia, East Asia, South Asia and most of Southeast Asia, and likely winter (DJF) increase in East Asia. (7) Likely summer (DJF) mean increase in southern Southeast Asia and southeastern South America (8) Likely summer (JJA) mean decrease in Central Asia, Central Europe and Southern Canada. (9) Likely winter (DJF) mean increase in central Europe, and southern Canada (10) Likely increase in extremes of daily precipitation in northern Europe, South Asia, East Asia, Australia and New Zealand. (11) Likely increase in risk of drought in Australia and eastern New Zealand; the Mediterranean, central Europe (summer drought); in Central America (boreal spring and dry periods of the annual cycle). (12) Very likely decrease in snow season length and likely to very likely decrease in snow depth in most of Europe and North America.
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Conclusions – focus on Europe
In many regions a shift to more extreme weather is projected. This goes along with an increased risk for both flooding and drought. Northern Europe and Arctic: precipitation increase, increased intensity, less dry days Southern Europe: less precipitation, increased drought, but at the same time increased risk for heavy precipitation
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Next step? ENSEMBLES-like approach can be used to give a quantitative estimation of future changes and associated probabilities. Climate scenarios can be used for planning of adaptation strategies We do not have to focus on long-term climate changes (100 years), but can instead make qualified estimates also for shorter periods (20-50 years).
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