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Leckebusch et al.: European property damage potentials
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
RT6.2 Meeting
Helsinki, 26.-27.4.2007
Leckebusch et al.: European property damage potentials
Introduction: Storm damages in the past
Economic and insured loss: Germany 1970 - 1998
Economic loss
Flashfloods
4%
Insured loss
Frost
Other
Flooding 5%
1%
8%
Other
3%
Frost
3%
Flooding
15%
Other Storms
7%
Hail
15%
RT6.2 Meeting
Other Storms
2%
Winter Storm
53%
Hail
20%
Winter Storms
64%
Helsinki, 26.-27.4.2007
Leckebusch et al.: European property damage potentials
Economic and insured losses
Source: Münchener Rück, Jahresrückblick Naturkatastrophen 2004
RT6.2 Meeting
Helsinki, 26.-27.4.2007
Leckebusch et al.: European property damage potentials
1000 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
RT6.2 Meeting
Helsinki, 26.-27.4.2007
Leckebusch et al.: European property damage potentials
1000 hPa Stormtrack (Winter)
20 IPCC GCMs
Ulbrich et al., submitted to J. Clim.
RT6.2 Meeting
Helsinki, 26.-27.4.2007
Leckebusch et al.: European property damage potentials
Validation: Cyclone Track density; All systems
NCEP-Re
Winter: Oct.-Mar.
HadCM3
ECHAM4
HadAM3P
ECHAM5
Units: Cyclone
systems per winter
NCEP
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Helsinki, 26.-27.4.2007
Leckebusch et al.: European property damage potentials
Validation: Cyclone Track density; 5% strongest systems
Strong: exceedance of the 95th percentile of the Laplacian of MSLP
NCEP-Re
HadCM3
ECHAM4
NCEP-Re
Units: Cyclone
systems per winter
HadAM3P
RT6.2 Meeting
ECHAM5
Helsinki, 26.-27.4.2007
Leckebusch et al.: European property damage potentials
A2 - Climate Change Signal: Cyclone Track density; All systems
HadCM3
ECHAM4
Coloured:
90/95/99th
Significance
Level
HadAM3P
ECHAM5
Dashed lines:
negative
changes
Solid lines:
positive
changes
RT6.2 Meeting
Helsinki, 26.-27.4.2007
Leckebusch et al.: European property damage potentials
A2 - Climate Change: Track density; 5% strongest systems
HadCM3
ECHAM4
Coloured:
90/95/99th
Significance
Level
HadAM3P
ECHAM5
Dashed lines:
negative
changes
Solid lines:
positive
changes
Leckebusch & Ulbrich (2004) ; Leckebusch et al. (2006)
RT6.2 Meeting
Helsinki, 26.-27.4.2007
Leckebusch et al.: European property damage potentials
A2 - Climate Change: Number of systems: all vs. intense systems
Lambert & Fyfe (2006)
RT6.2 Meeting
Helsinki, 26.-27.4.2007
Leckebusch et al.: European property damage potentials
Circulation Weather Types during winter (ONDJFM) in
an ensemble of GCMs
frequency [%]
recent climate:
CWTs ERA40 and 20C 1961-2000 winter (ONDJFM)
45
40
35
30
25
20
15
10
5
0
Z
Difference A1B-20C [%]
climate change:
(A1B)
AZ
NE
E
SE
S
SW
W
NW
N
undef.
gale
CWTs - Climate change signal A1B-20C winter (ONDJFM)
10
8
6
4
2
0
-2
-4
-6
-8
-10
Z
RT6.2 Meeting
AZ
NE
E
SE
S
SW
W
NW
N
undef.
gale
Helsinki, 26.-27.4.2007
Leckebusch et al.: European property damage potentials
Circulation Weather Types on gale days
(ONDJFM)
[days/year]
recent climate (20C):
25
20
15
10
5
0
Z
AZ
NE
E
SE
S
SW
W
NW
N
undef.
E
SE
S
SW
W
NW
N
undef.
climate change (A1B-20C):
[days/year]
10
5
0
-5
-10
-15
Z
RT6.2 Meeting
AZ
NE
Helsinki, 26.-27.4.2007
Leckebusch et al.: European property damage potentials
98th percentile of daily max. wind speed (ONDJFM)
ERA40
ECHAM5-OM1
run1 (MPI-M)
ECHAM5-OM1
(DMI)
EGMAM
20C
A1B-20C
RT6.2 Meeting
Helsinki, 26.-27.4.2007
Leckebusch et al.: European property damage potentials
Storm (loss) days per winter
20C
6
[days/year]
5
4
• 98th
percentile typical threshold for loss damages
3
2
1
• Storm
(loss) day if 98th percentile is exceeded in
0
Z 20%
AZ
NE
E investigation
SE
S
SW
Warea
NW (red
N undef.
at least
of the
box)gale
[days/year]
A1B-20C (98th percentile not adapted)
12
10
8
6
4
2
0
-2
Z
NE
SE
SW
NW
undef.
NW
undef.
[days/year]
A1B-20C (98th percentile adapted)
12
10
8
6
4
2
0
-2
Z
RT6.2 Meeting
NE
SE
SW
Helsinki, 26.-27.4.2007
Leckebusch et al.: European property damage potentials
Model theory
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
• 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 ~ v3.
RT6.2 Meeting
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Leckebusch et al.: European property damage potentials
For property damages:
• Germany: Insurance companies pay when wind
speeds exceed Bft 8 = 17.2 – 20.7 m/s
This wind speed is approx. equal to the 98th percentile
of wind speeds at regular (non-coastal, no mountain)
stations in Germany
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Helsinki, 26.-27.4.2007
Leckebusch et al.: European property damage potentials
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, 725-732.
 vmax (region , day ) 

pop
(
region
)
*
 1


v98 (region )
regions
days 

year
Loss ≈
c*
3
for vmax  v98
„normalized cubic wind“
 v  v98 


 v98 
RT6.2 Meeting
3
for v  v98
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Leckebusch et al.: European property damage potentials
What have we achieved so far?
Model structure
1: Calculation of „normalized cubic wind“ from input data
(e.g. ERA40) per year
 vmax (region , day ) 

 1

v98 (region )
days 

year
3
2: 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
3: Fitting the calculated values per year and region to observed losses
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Leckebusch et al.: European property damage potentials
Application of loss model on climate simulations
Loss Ratio in ECHAM5/OM1, 20C, run 1
Loss Ratio [‰]
1
0,8
0,6
0,4
0,2
jährl. Werte
2000
1999
1998
0,1507
Std. deviation
0,0894
0,0707
0,1494
2095
2094
2093
2092
2091
2090
2089
2088
2087
2086
2085
2084
2083
2082
2081
2080
2079
2078
2077
2076
2075
2074
2073
2100
0,1284
2099
0,1395
2098
Mean value
2072
2071
Loss Ratio [‰]
1997
(2071-2100)
2097
(1971-2000)
2096
(1971-2000)
jährl. Werte
Mittelwert
+ 17 %
RT6.2 Meeting
EH5/OM1, A1B
Mittelw ert
Loss Ratio in ECHAM5/OM1, A1B, run 1
1
0,8
0,6
0,4
0,2
0
1996
EH5/OM1, 20C
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
ERA 40
1984
1983
1982
1981
1980
1979
1978
1977
1976
1975
1974
1973
1972
1971
0
+ ~110 %
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Leckebusch et al.: European property damage potentials
Loss ratio: Control Climate
ACC signal (A2):
Leckebusch et al., 2007, GRL
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Leckebusch et al.: European property damage potentials
Model improvements in ENSEMBLES
Input parameter: Wind gusts (Forecasts!)
Loss Ratio based on momentary wind values vs. daily maximum gust from ERA40
0,700
0,600
loss ration [‰]
0,500
0,400
0,300
0,200
0,100
19
70
19
71
19
72
19
73
19
74
19
75
19
76
19
77
19
78
19
79
19
80
19
81
19
82
19
83
19
84
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
0,000
GdV
c165/166
c49
Correlation with insurance data (GdV):
Overestimation in 1993
Underestimation in 1990
RT6.2 Meeting
c165/166
c49
1970-2000Further
investigation
0,78
0,83
with respect to the kind
of exceedance
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Leckebusch et al.: European property damage potentials
GERMANY:
Exceedance of 98th Percentile (1971-2000) in ERA40
• 1993 more weak events than 1990
• 1990 more extreme exceedances of 98th Percentile than 1993
Approach 1 („static“):
Approach 2 („dynamic“):
Loss limit consistently increased
Loss limit individually adjusted after
loss events
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Leckebusch et al.: European property damage potentials
„dynamic approach“
Schadensatz [0,01€ pro 1000€] auf Basis von P98
80
70
60
50
40
30
20
10
0
1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
GdV
P98_c49_jahr
P98_c49_winter
P98_0.1v_d500
P98_0.1v_d500_ES
P98_0.1v_d1000
P98_0.1v_d1500
Correlation with real damage data (GdV)
1970-1999
RT6.2 Meeting
P98_jahr
P98_winter
0.1v_d500
0.1v_d1000
0.1v_d1500
0,83
0,90
0,877
0,883
0,878
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Leckebusch et al.: European property damage potentials
Regional Climate Model analysis:
98th percentile of maximum wind speed (ONDJFM)
ERA40
Max of 4
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gust forecast
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Leckebusch et al.: European property damage potentials
98th percentile of maximum wind speed (ONDJFM)
RCMs forced by ERA40
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Leckebusch et al.: European property damage potentials
Loss Ratios, RCMs (ERA40-driven) wssmax
0,800
0,700
0,600
0,500
0,400
0,300
0,200
0,100
0,000
1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
GdV
ERA40_code49
ERA40_MaxOf4
CHMI-ALADIN_wssmax
DMI-HIRHAM_wssmax
SMHI-RCA_wssmax
GdV
Korrelation mit GdV (1970-2000)
ERA40
ERA40
code 49
MaxOf4
0,89
Korrelation mit ERA40 code49
ETHZ-CLM_wssmax
CNRM-RM4.5_wssmax
MPI-M-REMO_wssmax
KNMI-RACMO2_wssmax
ETHZCLM
CNRMRM4.5
MPI-MREMO
KNMIRACMO2
CHMIALADIN
DMIHIRHAM
SMHIRCA
0,86
0,82
0,79
0,73
0,76
0,75
0,78
0,64
0,97
0,88
0,72
0,82
0,83
0,70
0,86
0,80
0,80
0,62
0,69
0,79
0,71
0,82
0,79
Korrelation mit ERA40 MO4
Mittelwert
0,15
0,15
0,15
0,15
0,14
0,15
0,16
0,14
0,16
0,15
Standardabweichung
0,12
0,12
0,11
0,07
0,09
0,10
0,10
0,09
0,10
0,08
RT6.2 Meeting
Helsinki, 26.-27.4.2007
Leckebusch et al.: European property damage potentials
Data problem: (March 2007)
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:
Requested, but not made available yet
HadGem1 (METO-HC)
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-CM3
Available 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.
RT6.2 Meeting
Helsinki, 26.-27.4.2007