Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, European property damage potentials: development and application of a simple storm regression model to global and regional simulations G.C. Leckebusch M. Donat U. Ulbrich FU Berlin MSC Napoli

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, Economic lossInsured loss Economic and insured loss: Germany Introduction: Storm damages in the past

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, Economic and insured losses Source: Münchener Rück, Jahresrückblick Naturkatastrophen 2004

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, hPa Stormtrack (Winter) Stormtrack is originally defined as bandpass (2.5-8 days) filtered standard deviation of the geopotential height in 500 hPa Thus, the stormtrack reflects the variability caused by travelling extra-tropical cyclones and high-pressure systems in the mid-latitudes In this study we used the 1000 hPa level, due to data availability, for winter. Data used: On IPCC AR4 Model Data Portal available 20 contributing models

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, hPa Stormtrack (Winter) Ulbrich et al., submitted to J. Clim. 20 IPCC GCMs

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, NCEP-ReECHAM4 HadAM3PECHAM5 HadCM3 NCEP Validation: Cyclone Track density; All systems Units: Cyclone systems per winter Winter: Oct.-Mar.

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, HadCM3ECHAM4 HadAM3PECHAM5 Validation: Cyclone Track density; 5% strongest systems NCEP-Re Units: Cyclone systems per winter NCEP-Re Strong: exceedance of the 95 th percentile of the Laplacian of MSLP

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, A2 - Climate Change Signal: Cyclone Track density; All systems ECHAM4 ECHAM5HadAM3P HadCM3 Coloured: 90/95/99 th Significance Level Dashed lines: negative changes Solid lines: positive changes

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, A2 - Climate Change: Track density; 5% strongest systems HadCM3 HadAM3PECHAM5 ECHAM4 Coloured: 90/95/99 th Significance Level Dashed lines: negative changes Solid lines: positive changes Leckebusch & Ulbrich (2004) ; Leckebusch et al. (2006)

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, A2 - Climate Change: Number of systems: all vs. intense systems Lambert & Fyfe (2006)

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, Circulation Weather Types during winter (ONDJFM) in an ensemble of GCMs recent climate: climate change: (A1B)

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, Circulation Weather Types on gale days (ONDJFM) recent climate (20C): climate change (A1B-20C):

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, th percentile of daily max. wind speed (ONDJFM) ERA40 ECHAM5-OM1 run1 (MPI-M) ECHAM5-OM1 (DMI) EGMAM 20C A1B-20C

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, Storm (loss) days per winter 98th percentile typical threshold for loss damages Storm (loss) day if 98th percentile is exceeded in at least 20% of the investigation area (red box) 20C A1B-20C (98th percentile not adapted) A1B-20C (98th percentile adapted)

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, Model theory Loss depends on - local gust wind speed - insured property or amount of forest in the area insured property values can roughly be estimated from population density Loss increases with wind speed above a threshold. Different storm-loss functions have been proposed, a frequent one is: loss ~ v 3. Estimation of future changes in climate extremes and their relation to property damage Following the multi model approach direct use of GCM/RCM output in the impact model

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, This wind speed is approx. equal to the 98 th percentile of wind speeds at regular (non-coastal, no mountain) stations in Germany Germany: Insurance companies pay when wind speeds exceed Bft 8 = 17.2 – 20.7 m/s For property damages:

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, Loss for normalized cubic wind for Approach 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,

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, : GIS (ArcGIS) - including global population distribution data on 1x1 degree grid - including interpolation of forestry data to model grid via GIS (at present: nearest neighbour) - Calculation of accumulated damage potential for different time slices and/or regions 1: Calculation of normalized cubic wind from input data (e.g. ERA40) per year Model structure 3: Fitting the calculated values per year and region to observed losses What have we achieved so far?

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, Application of loss model on climate simulations ERA 40 ( ) EH5/OM1, 20C ( ) EH5/OM1, A1B ( ) Mean value0,1395 0,1284 0,1507 Std. deviation0,08940,07070, % + ~110 %

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, Loss ratio: Control Climate Leckebusch et al., 2007, GRL ACC signal (A2):

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, Model improvements in ENSEMBLES c165/166c ,780,83 Correlation with insurance data (GdV): Input parameter: Wind gusts (Forecasts!) Overestimation in 1993 Underestimation in 1990 Further investigation with respect to the kind of exceedance

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, more weak events than more extreme exceedances of 98th Percentile than 1993 Approach 2 (dynamic): Loss limit individually adjusted after loss events Approach 1 (static): Loss limit consistently increased GERMANY: Exceedance of 98th Percentile ( ) in ERA40

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, dynamic approach P98_jahrP98_winter0.1v_d5000.1v_d v_d ,830,900,8770,8830,878 Correlation with real damage data (GdV)

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, th percentile of maximum wind speed (ONDJFM) ERA40 Regional Climate Model analysis: Max of 4 gust forecast

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, th percentile of maximum wind speed (ONDJFM) RCMs forced by ERA40

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, GdV ERA40 code 49 ERA40 MaxOf4 ETHZ- CLM CNRM- RM4.5 MPI-M- REMO KNMI- RACMO2 CHMI- ALADIN DMI- HIRHAM SMHI- RCA Korrelation mit GdV ( )0,890,860,820,790,730,760,750,780,64 Korrelation mit ERA40 code490,970,880,720,820,830,700,860,80 Korrelation mit ERA40 MO40,800,620,69 0,79 0,710,820,79 Mittelwert0,15 0,140,150,160,140,160,15 Standardabweichung0,12 0,110,070,090,10 0,090,100,08

Leckebusch et al.: European property damage potentials RT6.2 Meeting Helsinki, Availability of data from RT2A: Milestones M2A.2.2/M2A.2.3 Provision of Stream One simulations [...] on servers or on request (due in August 2006) seems NOT fulfilled adequately yet and leads to a delay in further analysis, as even on request data availability seems poor (see table). Availability of GCM data: HadGem1 (METO-HC) Requested, but not made available yet IPSL-CM4 (IPSL)Available at PCMDI (IPCC AR4)* ECHAM5/MPI-OM (MPIMET)Available via CERA / on request ECHAM5/MPI-OM (DMI)Available on request EGMAM (FUB)Available on request CNRM-CM3Available at PCMDI (IPCC AR4)* ARPEGE-MICOM-OASIS (NERSC)Requested, but not made available yet * Output of IPCC AR4 runs at PCMDI is onlay available in a daily resolution (daily mean values). For some analysis we plan to do, 6-hourly values are required. Thus, model output from PCMDI archive is only partly suitable for our analysis in ENSEMBLES. Data problem: (March 2007)