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Stéphane Hallegatte

A methodological roadmap to assess the costs and benefits of adapting to climate change The case of natural risks. Stéphane Hallegatte Centre International de Recherche sur l’Environnement et le Développement (CIRED) et École Nationale de la Météorologie, Météo-France. A methodological roadmap.

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Stéphane Hallegatte

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  1. A methodological roadmap to assess the costs and benefits of adapting to climate changeThe case of natural risks Stéphane Hallegatte Centre International de Recherche sur l’Environnement et le Développement (CIRED) et École Nationale de la Météorologie, Météo-France

  2. A methodological roadmap

  3. A methodological roadmap

  4. Global climate and socio-economic scenario • A 10-percent increase in hurricane potential intensity, consistent with a +2K warming of sea surface temperature in the Atlantic. • At a later stage: the use of several Global Climate Models would be required. • Socio-economic scenario: unchanged economy in the U.S. • At a later stage: the use of several economic growth and population distribution scenarios

  5. A methodological roadmap Landfall probabilities: information needed by risk managers

  6. Regional climate change and change in hazards • Global Climate models cannot be used to assess changes in hurricane risks. • Instead, we use the Emanuel hurricane model, which takes as input large-scale climate indicators and generates hurricane tracks and intensities. • Generation of 3000 tracks in the present climate • Generation of 3000 tracks in a climate with a 10-percent increase in potential intensity Annual probabilities of landfall for all categories, according to the data and to the model in the present climate (PC), and in the modified climate (MC).

  7. Landfall probability in the present climate

  8. Landfall probability in the modified climate

  9. A methodological roadmap Future changes in direct losses: information needed by insurers

  10. Change in direct losses • Vulnerability of each county on the U.S. Atlantic and Gulf coastline is estimated using past hurricane landfalls and the relationship:L = ai W3 • This vulnerability is used to assess how modified hurricane intensities would translate into modified hurricane direct losses. • A 10-percent increase in potential intensity would translate into a 54-percent increase in annual mean direct losses from hurricane landfalls.

  11. A methodological roadmap Future changes in total losses: information needed by local authorities and governments

  12. Change in total losses including economic response and indirect impacts • Direct losses: • Casualties and injuries • Direct economic losses (i.e., value of what has been destroyed or damaged) • Indirect losses: • Emergency costs (Katrina: $8 billion) • Business interruption, supply-chain disruption, lost production during reconstruction • Demand surge (larger repair costs due to lack of workers and materials) • Macro-economic feedbacks (e.g., through loss of jobs and tax revenue) • Long-term adverse consequences on economic growth (developing countries) • Other costs: • Political destabilization • Psychological trauma and social network disruption

  13. Assessment of production losses in Louisiana due to the landfall of Katrina We start from (quite uncertain) estimates of damages in 15 sectors.

  14. An Input-Output Economic Model • We model the regional economy of Louisiana using the ARIO (Adaptive Regional Input-Output) Model. • 1/ To assess the propagations among sectors: • we use BEA data on the exchanges between sectors, households and government (input-output table); • we assume simple “adaptation” rules (e.g., substitution with imports) 2/ To assess the reconstruction duration and demand surge, we assume that all sectors have a limited production capacity.

  15. Disaster consequences in economic modelsThe Katrina case Production changes in 15 sectors in Louisiana, in the Katrina’s aftermath, using the ARIO (Adaptive Regional Input-Output) Model. • An input-output model of the local economy, with 15 sectors that interact with each other. • We investigate the interplay of: • the decrease in production capacity due to damages; • the increase in demand due to reconstruction needs

  16. Disaster consequences in economic modelsThe Katrina case Production changes in 15 sectors in Louisiana, in the Katrina’s aftermath, using the ARIO (Adaptive Regional Input-Output) Model. Direct losses: $107b Production losses: $23b Housing service losses: $19b Total losses: $149b Boom and constraints in the construction sector Cross-sectoral propagations Decrease in production capacity

  17. Imperfect results, but orders of magnitude are consistent with data

  18. Imperfect results, but orders of magnitude are consistent with data Small business bankruptcy? See “the other” Venice meeting. Value added losses per sector, data and model

  19. Change in total losses including economic response and indirect impacts Results from the ARIO model in Louisiana The 54% increase in direct losses translates into a 60% increase in total losses. Doubling of the probability of total losses larger than $50b. Katrina

  20. A methodological roadmap

  21. Adaptation to reduce direct losses • In this assessment, county vulnerability is unchanged in the future. • Adaptation measures can make this vulnerability decrease: building norms, seawalls, risk-adverse land-use management… • The assessment of adaptation options can most of the time only be done at the local scale. • Example on a GIS-based analysis of storm surge risks in Miami: Work in progress, preliminary results

  22. Adaptation to reduce direct losses Work in progress, preliminary results In any climate, there are very efficient opportunity to reduce risks in many places. The cost of doing so is often small. Climate change makes only risk management more desirable. B A

  23. A methodological roadmap

  24. Adaptation to reduce indirect losses • Adaptation strategy can also reduce indirect losses without reducing direct losses: insurance schemes, government support of affected businesses, emergency planning, etc. Soft adaptation: insurance, foreign aid, support to small-businesses, support to evacuees, etc. Hard adaptation: dikes, seawalls, reinforced buildings, etc. Katrina

  25. Adaptation to reduce indirect losses • In a Mumbai case study using ARIO, increase insurance penetration from 10 to 100% would have reduced the production losses due to the 2005 flooding by 40% (from about US$300m to about US$200m) Besides macroeconomic benefits, insurance would help poor households cope with the disaster and restart economic production (e.g., individual businesses).

  26. CONCLUSIONS Landfall probabilities: information needed by risk managers Future changes in direct losses: information needed by insurers Future changes in total losses: information needed by local authorities and governments

  27. CONCLUSIONS • For the U.S. coastline: • In absence of adaptation, a 2K warming of Atlantic Ocean could translate into a 60% increase in hurricane total losses in the U.S. • The real concern is about the most powerful hurricanes, with a doubling of the probability of total losses larger than US$50 billion. • The result is based on the Emanuel model, which is particularly pessimistic: this outcome is not impossible, but is very uncertain. • From a methodological point of view: • The assessment of climate change impacts requires the taking into account of indirect impacts and ripple effects, especially when considering significant shocks to the economy. • Efficient adaptation options to control risks are available at low cost, and are often “no-regret,” i.e. bring benefits in an unchanging climate. • Adaptation options do not have to focus only on direct losses: efficient strategies exist to reduce indirect losses. • Someone has to explore the consequences of an absence of climate stabilization. What about a +6K scenario?

  28. CONCLUSIONS • From a decision-making point of view: • How can we make ‘adaptation’ decision considering the large uncertainty in all available assessments? • Adaptation decisions must not be made based only on (weak) cost-benefit analysis, but also using robustness and flexibility criteria. • Many options can be proposed that bring benefits in the present climate (no-regret) and in most possible future climate (robustness), and/or that can be adjusted when new information is available (flexibility)

  29. Examples of adaptation options This work is presented in a series of papers available on my website or on request to: hallegatte@centre-cired.fr

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