Rockhampton, Australia, January 2011 Estimates of extreme weather risk trends and future changes
Overview Trends and normalisation studies Projection studies Conclusions and outlook 2
Great weather-related disasters 1950-2010 16 14 Meteorological events (Storm) Hydrological events (Flood, mass movement) Climatological events (Extreme temperature, drought, forest fire) 12 10 8 6 4 2 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Munich Re GeoRisks Research, January 2011 3
Increasing damages due to climate change? Bouwer in press, BAMS 4
Human contribution to changes in extremes IPCC WG1, 2007: Table SPM.2 5
Increasing damages due to climate change? Bouwer in press, BAMS 6
Limitations of loss normalisation studies Method: Loss data uncertainty Requires longer period than analysing geophysical change Difficulty to capture temporal and spatial variability in exposure Changes in vulnerability often not assessed or disregarded Loss data mostly available for complex extremes: storms and floods (no human attribution) Solutions: 1) Look at simple extremes : temperature driven convective weather 2) Link climate variations and damages 7
Simple extremes: rainfall damages in The Netherlands Water-related damage, share [%] of total household damages buildings household content Dutch Association of Insurers 2010 8
Simple extremes: hail damage in The Netherlands Estimates for 2050: +25-50% increase for outdoor crops +200% increase for greenhouse horticulture Botzen et al. 2010, REE 9
Simple extremes: heavy precipitation and flash floods 10
Link between damages and climate variability Short-term co-variation overcomes 'shortness' of records First-order estimate of potential climate change impacts: Which damages are sensitive to climate fluctuations? Explanation of contemporary losses Prediction purposes? 11
ENSO and peak river discharge sensitivities 1-day max 7-day max Ward et al. 2010, GRL 12
Normalised losses: Australia 1967-2005 Mean normalised insured loss (AUD million) data: Crompton et al. 2008 ESP; Insurance Council of Australia website 13
Loss projection studies Two examples on flood risks Comparison of recent studies Role of exposure change vs. climate change 14
Future potential flood damage in The Netherlands 42 inundation scenarios Socio-economic scenarios Climate scenarios Inundation 1-i RC GE G W+ Probability p 1-i Land-use Scanner model Asset value Flood probability Exposure Land-use Asset factor f c Probability factor f p Damage Scanner loss model Loss 1-i Expected loss EL 2040 = (loss 1-i *p 1-i *f c *f p ) Bouwer et al 2010, GEC 15
Potential flood damage in 2040 (no adaptation) +719% +96% Bouwer et al 2010, GEC 16
Effect of flood prevention in 2040-25% +215% Bouwer et al 2010, GEC 17
Future potential flood casualties in The Netherlands 0 10 kilometres Amsterdam Den Haag Leiden Rotterdam Maaskant et al. 2009, ESP 18
Future potential flood casualties in The Netherlands 2000 2040 Maaskant et al. 2009, ESP 19
Future potential flood casualties in The Netherlands 2000 2040 Maaskant et al. 2009, ESP 20
Casualties potential in 2040 (no adaptation) +294% Maaskant et al. 2009, ESP 21
Comparison of climate impacts in 2040 No. Approach Hazard type Region Climate scenarios /GCMs Exposure scenarios Reference 1 Other Tropical storm Atlantic 2 2 Pielke 2007 2 Other Tropical storm USA 1 - Nordhaus 2010 3 IAM Tropical storm Global 4 - Narita et al. 2009 4 Hybrid Tropical storm USA 1 - Hallegatte 2007 5 Risk Tropical storm USA, Caribbean 3 - ABI 2005a; 2005b 6 Risk Tropical storm Japan 3 - ABI 2005a; 2005b 7 Risk Tropical storm China 3 - ABI 2009 8 Hybrid Tropical storm USA 1 1 Schmidt et al. 2009 9 Hybrid Tropical storm USA 4 - Bender et al. 2010 10 IAM Extra-tropical storm High latitude 1 - Narita et al. 2010 11 Risk Extra-tropical storm Europe 3 - Schwierz et al. in press 12 Risk Extra-tropical storm UK, Germany 4 - Leckebusch et al. 2007 13 Risk Extra-tropical storm Europe 1 - ABI 2005a; 2005b 14 Risk Extra-tropical storm UK 3 - ABI 2009 15 Hybrid Extra-tropical storm Netherlands 2 4 Dorland et al. 1999 16 Risk River flooding Netherlands 2 2 Bouwer et al. 2010 17 Risk River flooding Europe 2 - Feyen et al. 2009 18 Risk River flooding UK 3 - ABI 2009 19 Risk River flooding Spain (Mardid) 1 1 Feyen et al. 2009 20 Risk Local flooding Australia 2 - Schreider et al. 2000 21 Risk Local flooding Netherlands 1 0/4 Hoes 2007 Bouwer, submitted to Risk Analysis 22
Comparison of climate impacts in 2040 +30% +15% +65% +172% Bouwer, submitted to Risk Analysis 23
Comparison of climate impacts in 2040 +30% +15% +65% +172% Bouwer, submitted to Risk Analysis 24
Conclusions from projection studies Future climate change will increase disaster risk At least equal/but probably larger effect from increasing population and asset values Differences between types of weather hazards Amplification i effect of driving i factors Climate signal diffuclt to find, because of adaptation and climate variability 25
Conclusions and outlook Trends unlikely to be found in historic loss data of floods, storms, forest fires Heat waves, drought, convective weather (hail, intense rainfall) Continue to study normalised data: Try to explain variations, rather than trends Further explore role of exposure and vulnerability reduction Use knowledge for projections Forecasts of losses? 26
Thank you! laurens.bouwer@ivm.vu.nl Some references to our work: Botzen et al. 2010, REE http://dx.doi.org/10.1016/j.reseneeco.2009.10.004 Bouwer in press, BAMS http://dx.doi.org/10.1175/2010bams3092.1 Bouwer et al. 2010, GEC http://dx.doi.org/10.1016/j.gloenvcha.2010.04.002 Bouwer et al. 2007, Science http://dx.doi.org/10.1126/science.1149628 Maaskant et al. 2009, ESP http://dx.doi.org/10.1016/j.envsci.2008.11.004 Ward et al. 2010, GRL http://dx.doi.org/10.1029/2010gl043215 27