1 ENSEMBLES GA 2007, Prague – WP6.2 Meeting 12 Nov Estimates of Windstorm induced Loss in Europe RT6, WP 6.2 Meeting ENSEMBLES GA 2007 – 12 Nov - 16 Nov.

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1 ENSEMBLES GA 2007, Prague – WP6.2 Meeting 12 Nov Estimates of Windstorm induced Loss in Europe RT6, WP 6.2 Meeting ENSEMBLES GA 2007 – 12 Nov - 16 Nov 2006, Prague Markus Donat Gregor Leckebusch Uwe Ulbrich

2 ENSEMBLES GA 2007, Prague – WP6.2 Meeting 12 Nov FUBs objective: Estimation of loss potential due to extreme wind storms in the ENSEMBLES climate model simulations (GCMs and RCMs) Main topic: estimation of robustness of the scenario changes considering the different ensemble members Task 6.2.3: Design of sensitivity analyses based on existing climate projections and some initial performance tests Task 6.2.5: Development of models for understanding and evaluating the impacts of extremes. These models will operate within a probabilistic framework, incorporating where possible effects of adaptation and acclimatisation to climate change. Task : Preliminary evaluation of the impacts of extreme events using selected impact models for crops, human health, forest fire, forest damage, intense precipitation, drought, wind and temperature extremes from available climate projections

3 ENSEMBLES GA 2007, Prague – WP6.2 Meeting 12 Nov Data GCMs in ENSEMBLES: ModelResolution20CSRES A1B# runs MPI-ECHAM5T63 (ca. 1,9°) DMI-ECHAM5T63 (ca. 1,9°) IPSL-CM42,5x3,75° FUB-EGMAMT30 (ca. 4°) (3) CNRM-CM3T42 (ca. 2,2°) BCCR-BCM2T42 (ca. 2,2°) HadGEM11,25x1,875°

4 ENSEMBLES GA 2007, Prague – WP6.2 Meeting 12 Nov Large-scale atmospheric circulation Mean MSLP-Fields (winter ONDJFM) MEAN of 9 ENSEMBLES GCM runs

5 ENSEMBLES GA 2007, Prague – WP6.2 Meeting 12 Nov Large-scale atmospheric circulation Jones et al. (1993), Jenkinson and Collison(1977) Classification of daily (geostrophic) circulation at 50N, 10E Calculation of Directional Flow (F) and Shear Vorticity (Z) based on MSLP data on 2.5°x2.5° grid [unit=hPa per 10°] Classification into Circulation Weather Types (CWTs) Types: directional, (anti-) cyclonal, hybrid types, undefined Additionally: Gale Days (if G=sqrt(F²+(0.5Z)²) > 30)

6 ENSEMBLES GA 2007, Prague – WP6.2 Meeting 12 Nov Large-scale atmospheric circulation Daily Circulation Weather Types (CWTs) 20C, winter ONDJFM Changes in CWT frequencies A1B-20C, 95% significant

7 ENSEMBLES GA 2007, Prague – WP6.2 Meeting 12 Nov Gale days

8 ENSEMBLES GA 2007, Prague – WP6.2 Meeting 12 Nov Cyclone Tracks Track Density MEAN of 9 ENSEMBLES GCM runs ENSEMBLE MEAN 20C Winter ENSEMBLE MEAN A1B-20C Winter

9 ENSEMBLES GA 2007, Prague – WP6.2 Meeting 12 Nov Cyclone Tracks Intensity (Lapl. P) MEAN of 9 ENSEMBLES GCM runs

10 ENSEMBLES GA 2007, Prague – WP6.2 Meeting 12 Nov Extreme Wind Speeds: 95th percentile of daily maximum wind MEAN of 9 ENSEMBLES GCM runs

11 ENSEMBLES GA 2007, Prague – WP6.2 Meeting 12 Nov Storm loss model Loss estimation based on Klawa, M. und U. Ulbrich, 2003: A model for the estimation of storm losses and the identification of severe winter storms in Germany Natural Hazards and Earth System Sciences, Vol. 3, annual loss for normed loss velocity for

12 ENSEMBLES GA 2007, Prague – WP6.2 Meeting 12 Nov Estimation of storm loss Loss Ratio 20C-Period [unit: per 1000] Leckebusch et al. (2007), GRL Climate Change Signal (A2): Loss ratio ERA40HadCM3HadAM3PECHAM4/ OPYC3 ECHAM5/ OM1 GERAVE STD UKAVE STD Loss ratioHadCM3HadAM3PECHAM4/ OPYC3 ECHAM5/ OM1 Ensemble average Average with adaption Average without adaption STD with STD without

13 ENSEMBLES GA 2007, Prague – WP6.2 Meeting 12 Nov 1st Analysis of RCM Data 98th percentile of daily maximum wind (ONDJFM) Data: ERA ; ENSEMBLES RCM-Simulations (ERA40-driven, 50km)

14 ENSEMBLES GA 2007, Prague – WP6.2 Meeting 12 Nov Estimation of storm loss Data: GdV; ERA ; ENSEMBLES RCM-Simulations (ERA40-driven, 50km) GdVERA40 code 49 ERA40 MaxOf4 ETHZ- CLM CNRM- RM4.5 MPI-M- REMO KNMI- RACMO2 CHMI- ALADIN DMI- HIRHAM SMHI- RCA Correlation to GdV ( ) 0,890,860,820,790,730,760,750,780,64 Correlation to ERA40 code49 0,970,880,720,820,830,700,860,80 Correlation to ERA40 MO4 0,800,620,690,790,710,820,79 MEAN 0,15 0,140,150,160,140,160,15 STD 0,12 0,110,070,090,10 0,090,100,08 (max. wind speed)

15 ENSEMBLES GA 2007, Prague – WP6.2 Meeting 12 Nov Estimation of storm loss Data: GdV; ERA ; ENSEMBLES RCM-Simulations (ERA40-driven, 50km) GdVERA40 code 49 ERA40 MaxOf4 ETHZ- CLM MPI-M- REMO KNMI- RACMO2 SMHI- RCA Correlation to GdV ( ) 0,890,860,610,730,720,67 Correlation to ERA40 code49 0,970,770,820,850,82 Correlation to ERA40 MO4 0,770,690,820,79 MEAN 0,15 0,140,15 STD 0,12 0,110,070,100,080,09 (max. gust)

16 ENSEMBLES GA 2007, Prague – WP6.2 Meeting 12 Nov Contribution to Deliverables D6.15: Assessing the uncertainty in projected changes in climate extremes and their impacts on the following sectors: health, forestry, flood risk, property damage, agriculture. Month 48 D6.16: Joint WP 6.2 paper: Impacts of projected changes in climate extremes over Europe to 2100: a review of key sectors. Month 54