Centre for Regional Change in the Earth System - CRES

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1 Centre for Regional Change in the Earth System - CRES Jens Hesselbjerg Christensen Danish Meteorological Institute

2 From science to decisions Thanks to Markku Rummukainen

3 Outline Something from CRES Something about outreach Something about the CRES platform Complementary projects International linkage Ways ahead

4 Objective extend knowledge of and reduce the uncertainties surrounding regional climate change and its impacts thereby support future climate change adaptation and mitigation policies, targeting Danish and wider regional needs. This includes enhancing the knowledge base and direct advisory capacity for Danish actors, including government and the private sector

5 CRES Strategic Research Centre Danish Council of Strategic Research 4 mio. Euro Overall budget 6 mio. Euro

6 CRES Research DMI (lead) GEUS University of Copenhagen University of Aarhus Technical University DHI

7 CRES National partners: International partners: Dansk Vand- og Spildevandsforening (DANVA) Videncentret for Landbrug Forsikring og Pension KL Odense og Århus Kommuner Bjerknes Centret, Norway SMHI, Sweden Uni Lund, Sweden UCL, UK BC3, Spain and. FP6 FP7, NASA, ESA,

8 WB1 Center functions: practitioner involvement, open door policy management, education and dissemination WB2 Changes in climate and sea level WB3 Changes in hydrology WB4 Changes in biosphere WB5 Extreme events and tipping points WB6 Integrated assessment applied to cases WB7 New regional change tool: From uncertainty to risk management

9 ENSEMBLES Summer temperatures - ERA40 driven OBS Ens Mean Bias Christensen et al. (2010)

10 JJA <T change >= <T T >

11 <T change >= <T T > JJA

12 Boberg & Christensen (2012) Temperature dependent bias ( ) ( ) ( ) ( )

13 <T change >= <T T > - <BC> Boberg & Christensen (2012)

14 How reliable are our sea level rise projections? Observed sea level rise tends to follow the uppermost dashed line of the IPCC scenarios, namely the one "including land ice uncertainty IPCC models underpredict rates of sea level rise by ~40% (Rahmstorf et al., 2007). Comparison of the 2001 IPCC sea-level scenarios (starting in 1990) and observed data. Church and White (2006) data based primarily on tide gauges (annual, red) and the satellite altimeter data (updated from Cazenave and Nerem 2004, 3-month data spacing, blue, up to mid-2006) are shown with their trend lines. Figure credit: realclimate.org

15 Grinsted Best estimate (A1B, ΔGMSL=78cm)

16 Grinsted High-end estimate (for ΔGMSL = 130cm)

17 Projections of extreme precipitation for Aarhus WB3 status Statistical downscaling using weather generators Changes in extreme precipitation downscaled from 20 RCMs from ENSEMBLES

18 Flooding in Aarhus (100-year event) first results High scenario 2100 Low scenario WB6 status

19 Strategic dialogs Tid Oktober 2011 (December 2011 Forsikring & Pension) 00 Velkomst ved VFL og KFT/CRES Præsentation af formålet med workshoppen 10 Præsentation af VFL samt deres videnbehov (VFL) se nedenfor 30 Præsentation om klimaforandringerne i Danmark (CRES) se nedenfor 70 Kort pause 80 Dialog mellem forskere og interessenter (ordstyrer: VFL) Debat om VFL s videnbehov og hvordan klimainformation benyttes i organisationen (dvs. hvad vil man helst have at vide, hvem er brugerne, er der barrierer inden for organisationen, osv.) Debat af formidlingen til VFL; forslag til at styrke dialogen inden for området 150 Opsamling, afrunding på workshoppen Forslag om evt. nye møder

20 New lines of outreach Science 101-CRES and beyond Advanced knowledge cruise Up to 3 visits per year PIs and senior staff Special CC science workshops Other DFS projects Open to end-users Dedicated results (open and closed parts) Refsgaard et al. 2012: The role of uncertainty in climate change adaptation strategies A Danish water management example (Mitig Adapt Strateg Glob Change) How good are our models to predict climate change and its impacts? (Copenhagen Oct , 2012) -> publication 2013

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