Rockhampton, Australia, January Estimates of extreme weather risk trends and future changes

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1 Rockhampton, Australia, January 2011 Estimates of extreme weather risk trends and future changes

2 Overview Trends and normalisation studies Projection studies Conclusions and outlook 2

3 Great weather-related disasters Meteorological events (Storm) Hydrological events (Flood, mass movement) Climatological events (Extreme temperature, drought, forest fire) Munich Re GeoRisks Research, January

4 Increasing damages due to climate change? Bouwer in press, BAMS 4

5 Human contribution to changes in extremes IPCC WG1, 2007: Table SPM.2 5

6 Increasing damages due to climate change? Bouwer in press, BAMS 6

7 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

8 Simple extremes: rainfall damages in The Netherlands Water-related damage, share [%] of total household damages buildings household content Dutch Association of Insurers

9 Simple extremes: hail damage in The Netherlands Estimates for 2050: % increase for outdoor crops +200% increase for greenhouse horticulture Botzen et al. 2010, REE 9

10 Simple extremes: heavy precipitation and flash floods 10

11 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

12 ENSO and peak river discharge sensitivities 1-day max 7-day max Ward et al. 2010, GRL 12

13 Normalised losses: Australia Mean normalised insured loss (AUD million) data: Crompton et al ESP; Insurance Council of Australia website 13

14 Loss projection studies Two examples on flood risks Comparison of recent studies Role of exposure change vs. climate change 14

15 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

16 Potential flood damage in 2040 (no adaptation) +719% +96% Bouwer et al 2010, GEC 16

17 Effect of flood prevention in % +215% Bouwer et al 2010, GEC 17

18 Future potential flood casualties in The Netherlands 0 10 kilometres Amsterdam Den Haag Leiden Rotterdam Maaskant et al. 2009, ESP 18

19 Future potential flood casualties in The Netherlands Maaskant et al. 2009, ESP 19

20 Future potential flood casualties in The Netherlands Maaskant et al. 2009, ESP 20

21 Casualties potential in 2040 (no adaptation) +294% Maaskant et al. 2009, ESP 21

22 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 Other Tropical storm USA 1 - Nordhaus IAM Tropical storm Global 4 - Narita et al Hybrid Tropical storm USA 1 - Hallegatte 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 Hybrid Tropical storm USA 1 1 Schmidt et al Hybrid Tropical storm USA 4 - Bender et al IAM Extra-tropical storm High latitude 1 - Narita et al Risk Extra-tropical storm Europe 3 - Schwierz et al. in press 12 Risk Extra-tropical storm UK, Germany 4 - Leckebusch et al Risk Extra-tropical storm Europe 1 - ABI 2005a; 2005b 14 Risk Extra-tropical storm UK 3 - ABI Hybrid Extra-tropical storm Netherlands 2 4 Dorland et al Risk River flooding Netherlands 2 2 Bouwer et al Risk River flooding Europe 2 - Feyen et al Risk River flooding UK 3 - ABI Risk River flooding Spain (Mardid) 1 1 Feyen et al Risk Local flooding Australia 2 - Schreider et al Risk Local flooding Netherlands 1 0/4 Hoes 2007 Bouwer, submitted to Risk Analysis 22

23 Comparison of climate impacts in % +15% +65% +172% Bouwer, submitted to Risk Analysis 23

24 Comparison of climate impacts in % +15% +65% +172% Bouwer, submitted to Risk Analysis 24

25 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

26 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

27 Thank you! Some references to our work: Botzen et al. 2010, REE Bouwer in press, BAMS Bouwer et al. 2010, GEC Bouwer et al. 2007, Science Maaskant et al. 2009, ESP Ward et al. 2010, GRL 27

The IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation

The IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A changing climate leads to changes in extreme weather and climate events 2 How do changes