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Decisions, Policies and Adaptation to Climate Change

Decisions, Policies and Adaptation to Climate Change. Walter E. Baethgen Head, Regional and Sectorial Research Program Leader, Latin America and Caribbean. Climate Change. Mitigation is the Key: Energy sources, Deforestation/Afforestation, Transportation,

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Decisions, Policies and Adaptation to Climate Change

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  1. Decisions, Policies and Adaptation • to Climate Change Walter E. Baethgen Head, Regional and Sectorial Research Program Leader, Latin America and Caribbean

  2. Climate Change Mitigation is the Key: Energy sources, Deforestation/Afforestation, Transportation, Carbon Sequestration (including Land Use Changes), Reduction of Methane, N2O from Agriculture… But: Inertia of current and past emissions: Effects on Climate in the next 40-50 years Need to Adapt

  3. Planning, Decision Making, Policy Making Adaptation to What? What Can We Expect? Future Climate Scenarios

  4. Adapt to What? Climate Change Scenarios: Using Climate Models (GCMs) Complex models that simulate physical processes in the atmosphere, oceans and land

  5. Great advances in science and in Climate Models: Spatial Resolution of Climate Models (grid size) is much better E.g., IPCC Assessment Reports Vertical layers 10 30 1 30 FAR AR4

  6. Climate Models: Simulating Past ObservedClimate Example: SE South America SONDJF Anomalies (mm/month) IPCC Model Range and Mean

  7. Climate Models: Simulating Past ObservedClimate Example: SE South America SONDJF Observed Anomalies (mm/month) IPCC Model Range and Mean

  8. Adapt to What? Climate Change Scenarios: Using Climate Models (GCMs) Complex models that simulate physical processes in the atmosphere, oceans and land • Great advances in science, • but still lots to understand: • Limitations of the Models 2. Key Input: GHG Emissions Assumptions: (e.g., in 2080-2100) Technologies? Energy Sources? Deforestation rates? Population? Uncertainties (IPCC Scenarios)

  9. Climate and Socioeconomic Scenarios CO2 atmospheric concentration for different development options In AR5: Radiative Forcing Values (similar assumptions) Source: IPCC, 2001

  10. Expected Global Temperature For Different Socioeconomic Scenarios (Reference: 1986 – 2005) Source: IPCC, 2013 (Draft) Uncertainty

  11. Precipitation Projections for 2090-2099 Precipitation in DJF For Rainfall uncertainties are much larger IPCC, 2007

  12. At Regional level Uncertainties are larger Individual Model Runs and Averages East Africa This is for large “Windows” At Local level Uncertainties are much larger Giannini et al., 2007

  13. Conclusion: Climate Change Scenarios are Uncertain IPCC’s objective was not to create scenarios for impact assessment However: Published articles with Crop Yield Projections for 2020, 2050, 2080 2020 2050 2080 Percent change in Crop Yields for one climate change scenario • PROBLEM: • This is easily understood • Can be “erroneously” believed Uncertainty?

  14. Climate Change Scenarios and Decision Makers: Decision Makers (including Policy Makers): Pressure to act on immediate to short-term problems Scientific Community: Scenarios for 2080, 2100 Great for Public Awareness, but CC is a problem of the FUTURE CC scenarios: Uncertainty at regional / local level is large Result: CC is often not in the policy agendas, planning Can Adaptation be incorporated into development?

  15. A Complementary Approach to “Traditional” Climate Change: Climate Risk Management Climate Change is a problem of the PRESENT (happening already) as opposed to a problem of the FUTURE Some of the most damaging impacts of Climate Change are expected to be due to increased Climate Variability (droughts, floods) Learning to adapt to current climate variability will lead to less Vulnerable societies better prepared to confront future Climate Work in “Near-term” Climate Change (i.e., 10-30 years) Existing User Demand: Infrastructure, Water Reservoirs, Glaciers in the Andes, Long-term business plans, Development Programs Informing policy, decisions: Understand and try to reduce UNCERTAINTIES

  16. Understand / Reduce Uncertainties: Providing Relevant Information of the FUTURE One Example: Seasonal Climate Forecasts White Areas in Map 10% 30% 60% A N B 33% 33% 33% Probability of Next Season being “NORMAL” "Wetter" "Drier"

  17. Understand / Quantify / Reduce Uncertainties: Providing Relevant Information of the FUTURE Mean Monthly Rainfall in MatoGrosso (1930 – 2000) Pick 15 years randomly Soybeans “Safrinha” (2nd Crop)

  18. MatoGrosso: Monthly Precipitation (15 Randomly Selected Years) “Safrinha”??

  19. None of the years behaves like the long term mean Probability of a year being “Average” = ZERO Still, Planning/Decisions are often based on “AVERAGE” year • Can we do better? • Seasonal Climate Forecasts • Understand Historical Variability / associated risks

  20. Adaptation to Climate Change: We need a shift in Paradigm: Current Paradigm: “Noah’s Ark” “Perfect” Information about the Future: a Climatic Cataclism is coming Actionable Information: Build infrastructure and save Biodiversity But: We do not have (will not have) Perfect Information of the Future Climate Rafael Terra, IMFIA, Uruguay

  21. Paradigm 2: Ginkgo biloba 2 million years of Evolution Adapted to a wide range of conditions Unexpected extreme event (A-bomb) Somehow 6 Ginkgos Survived • New Paradigm: Adapt with “flexibility” • We will not have “perfect” information • Adapt to a Range of plausible conditions • Identify Interventions likely to succeed • Start by Adapting to today’s conditions Approx 1,000m from epicenter in Hiroshima Ginkgo biloba (2,000,000 year old tree species) Rafael Terra, IMFIA, Uruguay

  22. Conceptual Framework (1): Advances in Science not proportional to their Applications • Science and Society: Information Chains, Networks Knowledge “Translation”, “Tailoring” Boundary Organizations • Knowledge • Application • Operation • Policy Knowledge Generation New Knowledge Demands New Research Questions Here are the main Challenges: Need a “new type” of Scientist? (Translator, Integrator) Take Advantage, Understand constraints, etc of Existing Information Networks: “Simplified” Example in Agriculture International Research Institute Agricultural Research Institute Extension Service, Adviser, NGO Local University Farmer Ministry, Agribusiness, Insurance When the Links / Chains are not present we try to create them (The solution is not to “skip links”, but to create/strengthen the links)

  23. Science and Society: Information Networks • (Very) Simplified Example in Agriculture Rural Social Research Institute Extension Service, International Research Agriculture Local University Advisers Ministry Farmer Meteorological Service International Research Climate Local University Ministry Advisers Farmers Agricultural Research Institute Agribusiness Local University Regional Research Institute Insurance NGO Financial Services Climate Research Institute • Understand the Network (links, processes) • Strengthen links, communication

  24. Conceptual Framework (2): Advances in Science not proportional to their Applications Gap between Science and Applications / Society Decision-makers approach problems holistically and often intuitively 2. Science traditional reductionist approach: Create ‘islands of knowledge in a sea of ignorance’ Need Tools/Approaches to Integrate Knowledge (Decision Support Systems) (Meinke et al., 2007; 2009)

  25. Final Comments • Climate Risk Management and Adaptation to Climate Change • Improve Adaptation to Future Climate starting by Improving Adaptation to TODAY’S Climate • Shift from “Noah's Ark” to “Gingko Biloba”: Adapt with flexibility • Climate Science – Society/Policy Interface: • Knowledge/Information Chains: Basic Science – Applied Science – Implementation • Identify weak / missing links, strengthen / create links • Science-based Resources to Inform Policy • Integrated Information: Decision Support Systems, considering Uncertainties • Understandable and Actionable!

  26. Thank you, Obrigado Walter E. Baethgen Head, Regional and Sectorial Research Program Leader, Latina America and Caribbean IRI, The Earth Institute at Columbia University Tel:  (845) 680-4459email: baethgen@iri.columbia.edu Internet: http://iri.columbia.edu/

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