Shaping climate-resilient development - a framework for decision making

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Shaping climate-resilient development - a framework for decision making

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Shaping climate-resilient development - a framework for decision making

  1. 1. Shaping Climate-resilient Development – A Framework for Decision-making Dr. David N. Bresch, Head Sustainability, Swiss Re on behalf of the Economics of Climate Adaptation Working Group
  2. 2. Climate-compatible development requires both mitigation and adaptation Development Achieving the Millennium Development Goals Low-carbon Climate- development resilient development Climate- compatible development Mitigation Adaptation Climate- proofed abatement Please find the full study at www.swissre.com/climatechange 2
  3. 3. Economics of climate adaptation (ECA) study group Partner consortium: Please find the full study at www.swissre.com/climatechange 3
  4. 4. Climate-resilient development needs to address total climate risk Objectives:  Provide decision makers with the facts and methods necessary to design and execute a climate adaptation strategy  Supply insurers, financial institutions, and potential funders with the information required to unlock and deepen global risk transfer markets Key features:  Developed a methodology to quantify local total climate risks, meaning it looked at the combination of  today’s climate risk,  the economic development paths that might put greater population and value at risk  the additional risks presented by climate change. Swiss Re’s role:  Lead contributor to the research. Swiss Re defined the assessment and risk modelling approach and provided overall risk assessment knowledge Please find the full study at www.swissre.com/climatechange 4
  5. 5. Today's How we address total climate risk focus  Measure success and adjust  Identify areas strategies as What are the Where most at risk given scenarios change outcomes and and what relevant hazards, lessons? is the population, and threat? economic value TCR  Develop  Implement a How do manage- frequency and severity scenarios holistic climate we execute? ment for most relevant risk strategy that What is hazard(s) overcomes at stake? barriers, and  Quantify value at launch initiatives risk How could  Determine vulner- we respond? ability to the hazard  Price tag on total  Select time frame for measure climate risk analysis  Identify potential adaptation measures  Determine feasibility  Determine societal costs and benefits www.swissre.com/climatechange 5
  6. 6. We simulate natural catastrophes in great detail 6
  7. 7. We simulate hundred thousands of possible events 7
  8. 8. The probabilistic set historic ~100 years probabilistic ~10‘000 years 8
  9. 9. The working group studied eight regions with diverse climate hazards U.K. / Hull China Mali North, Northeast Florida India Maharashtra Tanzania Samoa Samoa Guyana Please find the full study at www.swissre.com/climatechange 9
  10. 10. TEST CASE ON MAHARASHTRA, INDIA – FOCUS ON DROUGHT RISK TO AGRICULTURE 10
  11. 11. 1. Where and what is the threat? Focus on drought due to its large impact on agriculture and human livelihood India, Maharashtra case study Please find the full study at www.swissre.com/climatechange 11 Source: ECA group
  12. 12. 2. What is at stake? Three scenarios for climate change to capture uncertainty India, Maharashtra case study • Predicting local climate is inexact 2030 scenarios Description given limited data. Therefore, 1 Today’s • Historic rainfall and 3 scenarios were developed for climate drought data used to rainfall change in the 2030 estimate rainfall frequency timeframe – Based on temp and precipitation predictions from 22 global 2 “Moderate” • Average change based on climate models change the mean rainfall – Distribution in rainfall varied predicted from 22 GCMs1 from 92-102% of today’s value • While some regional climate models 3 “High” • Extreme change based on change average of 90th percentile exist assessing at a higher values for predicted rainfall resolution and smaller grid area from 22 GCMs than GCMs, the science behind these models is still developing GCM results consistent with output from • Climate scenarios were later used regional models (A2 and B2) for Maharashtra to develop 3 hazard scenarios 1 22 GCMs for Maharashtra, run with the A1B scenario SOURCE: Results for GCMs from Prof. Reto Knutti, ETH Zurich; RCM results for A2 and B2 from Prof. Krishna Kumar, Indian Institute of Tropical Meteorology www.swissre.com/climatechange 12 Source: ECA group
  13. 13. 2. What is at stake? The economic value at risk – driven by economic growth and climate change India, Maharashtra case study Expected loss from exposure to climate High climate change scenario, 2008 USD millions 570 • Expected loss is driven by current risk, 23% of 2030 total agricultural growth, expected loss 200 and climate change • Agriculture income growth would contribute 132 to an additional 23% 238 of 2030 upper bound 35% of 2030 loss total expected • Climate change loss (occurring in combination with income growth) will 2008, Incremental Incremental 2030, total account for 35% of Today’s increase from increase from expected 2030 upper expected economic climate loss bound loss loss growth; no change climate change www.swissre.com/climatechange 13 Source: ECA group
  14. 14. 3. How could we respond? Managing total climate risk requires a cost-effective adaptation portfolio Portfolio of responses Hazards Infrastructure and asset- based responses Technological and procedural Total optimization responses Climate Risk Systemic and Vulnerability behavioral responses Risk transfer and Value contingent financing Please find the full study at www.swissre.com/climatechange 14 Source: ECA group
  15. 15. 3. How could we respond? Measures are analyzed in respect of costs and benefits (averted loss) in great detail India, Maharashtra case study Measure* Cost (mn $) Benefit (mn $) Cost/Benefit ($/$) Loss averted (mn $) 1 Drainage systems (rf) -80 74 -2.13 3 2 Soil techniques -197 1,109 -0.18 21 3 Drainage systems (ir) -74 447 -0.16 16 4 Irrigation controls 14 1,438 0.01 59 5 Drip irrigation 139 7,978 0.02 547 6 Crop engineering (ir) 81 1,155 0.07 64 7 Sprinkler irrigation 285 3,280 0.12 225 8 Integrated Pest Mgmt. (ir) 49 551 0.09 36 9 IPM (ir) 146 1,374 0.11 91 10 Watershed +rwh 534 4,545 0.12 312 A Last mile irrigation 1,553 5,467 0.28 227 B Rehab. of irrigation systems 966 2,733 0.35 113 C Ground water pumping 1,837 2,733 0.67 113 11 Crop engineering (rf) 271 1,384 0.73 35 D Planned irrigation projects 8,987 12,027 0.75 499 E Canal lining 16 20 0.81 1 12 Insurance 1,035 1,035 1.00 1,036 Relief and rehabilitation NA NA NA 556 Totals 2,200 24,370 NA 3,000 • Only 80% of the expected loss can be mitigated by 12 measures. The remaining 20% is “residual” loss, which will require additional penetration of insurance, or relief and rehabilitation to address *All figures are in terms of PV values, in current prices, up to 2030 www.swissre.com/climatechange 15 Source: ECA group
  16. 16. 3. How could we respond? Adaptation measures were prioritized according to their costs and benefits www.swissre.com/climatechange 16
  17. 17. 3. How could we respond? In addition to agricultural ‘best practice’, index-based micro insurance is a powerful tool India, Maharashtra case study Please find the full study at www.swissre.com/climatechange 17 Source: ECA group 1 Estimated present value out to 2030 at 2009 dollars
  18. 18. 3. How could we respond? Micro insurance ( a form of risk transfer) reduces the volatility www.swissre.com/climatechange 18 Source: ECA group
  19. 19. TEST CASE ON SAMOA – FOCUS ON RISKS CAUSED BY SEA LEVEL RISE 19
  20. 20. 2. What is at stake? Huge economic value is already at risk from the climate –risks will rise as the climate changes and economies grow Expected loss from exposure to climate SAMOA EXAMPLE High climate change scenario, USD millions 77 Potential impact from economic 26 growth x 3.1 Potential 26 impact from 25 change in climate 2008, Economi Climate 2030, total today’s c growth change expected expected loss loss Incremental increase www.swissre.com/climatechange 20
  21. 21. 3. How could we respond? How could we respond? Approx. 60% of expected loss can be avoided cost effectively 60% www.swissre.com/climatechange 21
  22. 22. 3. How could we respond? Risk transfer is an efficient way of providing coverage for high-severity / low-frequency events SAMOA EXAMPLE Expected loss for 250-year event Percent of GDP 34 Loss covered 5 Percent of residual Annual cost risk to be covered USD millions 18 Further risk 11 mitigation 49% 23 measures Total Maximum Loss Residual Risk transfer 100% 7 expect bearable averted risk -ed loss by cost to be loss efficient covered measures Please find the full study at www.swissre.com/climatechange 22
  23. 23. Annualized losses of 1-12% of GDP today are likely to rise up to 19% of GDP by 2030 www.swissre.com/climatechange 23
  24. 24. Between 40 and 68 percent of the expected economic loss in the regions studied can be averted cost-effectively Introduction of cash crops Please find the full study at www.swissre.com/climatechange david_bresch@swissre.com on behalf of the Economics of Climate Adaptation Working Group 24

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