1. Walter E. Baethgen 2013 Decisions, Policies and Adaptation to Climate Change Walter E. Baethgen Head, Regional and Sectorial Research Program Leader, Latin America and Caribbean

2. Walter E. Baethgen 2013 Mitigation is the Key: Energy sources, Deforestation/Afforestation, Transportation, Carbon Sequestration (including Land Use Changes), Reduction of Methane, N 2 O from Agriculture… But: Inertia of current and past emissions: Effects on Climate in the next 40-50 years Need to Adapt Climate Change

3. Walter E. Baethgen 2013 Planning, Decision Making, Policy Making Adaptation to What? What Can We Expect? Future Climate Scenarios

4. Walter E. Baethgen 2013 Adapt to What? Climate Change Scenarios: Using Climate Models (GCMs) Complex models that simulate physical processes in the atmosphere, oceans and land

5. Walter E. Baethgen 2013 Great advances in science and in Climate Models: Spatial Resolution of Climate Models (grid size) is much better E.g., IPCC Assessment Reports 10 1 30 Vertical layers FAR AR4

6. Walter E. Baethgen 2013 Climate Models: Simulating Past Observed Climate Example: SE South America SONDJF IPCC Model Range and Mean Anomalies (mm/month)

7. Walter E. Baethgen 2013 Observed IPCC Model Range and Mean Climate Models: Simulating Past Observed Climate Example: SE South America SONDJF Anomalies (mm/month)

8. Walter E. Baethgen 2013 Adapt to What? Climate Change Scenarios: Using Climate Models (GCMs) Complex models that simulate physical processes in the atmosphere, oceans and land 1.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. Walter E. Baethgen 2013 CO 2 atmospheric concentration for different development options Source: IPCC, 2001 Climate and Socioeconomic Scenarios In AR5: Radiative Forcing Values (similar assumptions)

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

11. Walter E. Baethgen 2013 IPCC, 2007 Precipitation Projections for 2090-2099 For Rainfall uncertainties are much larger Precipitation in DJF

12. Walter E. Baethgen 2013 Giannini et al., 2007 At Regional level Uncertainties are larger This is for large “Windows” At Local level Uncertainties are much larger East Africa Individual Model Runs and Averages

13. Walter E. Baethgen 2013 However: Published articles with Crop Yield Projections for 2020, 2050, 2080 Uncertainty? 2020 2050 2080 Conclusion: Climate Change Scenarios are Uncertain IPCC’s objective was not to create scenarios for impact assessment PROBLEM: This is easily understood Can be “erroneously” believed Percent change in Crop Yields for one climate change scenario

14. Walter E. Baethgen 2013 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. Walter E. Baethgen 2013 A Complementary Approach to “Traditional” Climate Change: Climate Risk Management 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 Some of the most damaging impacts of Climate Change are expected to be due to increased Climate Variability (droughts, floods) Climate Change is a problem of the PRESENT (happening already) as opposed to a problem of the FUTURE Learning to adapt to current climate variability will lead to less Vulnerable societies better prepared to confront future Climate Informing policy, decisions: Understand and try to reduce UNCERTAINTIES

16. Walter E. Baethgen 2013 One Example: Seasonal Climate Forecasts Probability of Next Season being “NORMAL” 33% ANBANB 10% 30% 60% Understand / Reduce Uncertainties: Providing Relevant Information of the FUTURE White Areas in Map

17. Walter E. Baethgen 2013 Pick 15 years randomly Mean Monthly Rainfall in Mato Grosso (1930 – 2000) Understand / Quantify / Reduce Uncertainties: Providing Relevant Information of the FUTURE Soybeans “Safrinha” (2 nd Crop)

18. Walter E. Baethgen 2013 Mato Grosso: Monthly Precipitation (15 Randomly Selected Years) “Safrinha”??

19. Walter E. Baethgen 2013 None of the years behaves like the long term mean Probability of a year being “Average” = ZERO Can we do better? Seasonal Climate Forecasts Understand Historical Variability / associated risks Still, Planning/Decisions are often based on “AVERAGE” year

20. Walter E. Baethgen 2013 Current Paradigm: “Noah’s Ark” Rafael Terra, IMFIA, Uruguay “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 Adaptation to Climate Change: We need a shift in Paradigm:

21. Walter E. Baethgen 2013 Approx 1,000m from epicenter in Hiroshima Ginkgo biloba (2,000,000 year old tree species) Rafael Terra, IMFIA, Uruguay 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 Paradigm 2: Ginkgo biloba

22. Walter E. Baethgen 2013 International Research Institute Local University Agricultural Research Institute Extension Service, Adviser, NGO Farmer Knowledge Generation Knowledge “Translation”, “Tailoring” Boundary Organizations Knowledge Application Operation Policy New Research Questions New Knowledge Demands Here are the main Challenges: Need a “new type” of Scientist? (Translator, Integrator) 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) Take Advantage, Understand constraints, etc of Existing Information Networks: “Simplified” Example in Agriculture Science and Society: Information Chains, Networks Ministry, Agribusiness, Insurance Conceptual Framework (1): Advances in Science not proportional to their Applications

23. Walter E. Baethgen 2013 Science and Society: Information Networks (Very) Simplified Example in Agriculture International Research Climate Local University Agricultural Research Institute Advisers Farmers Farmer Ministry Regional Research Institute International Research Agriculture Local University Local University Rural Social Research Institute Climate Research Institute Extension Service, NGO Advisers Ministry Insurance Agribusiness Meteorological Service Meteorological Service Financial Services Financial Services Understand the Network (links, processes) Strengthen links, communication

24. Walter E. Baethgen 2013 Gap between Science and Applications / Society 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) 1.Decision-makers approach problems holistically and often intuitively Conceptual Framework (2): Advances in Science not proportional to their Applications

25. Walter E. Baethgen 2013 Science-based Resources to Inform Policy Integrated Information: Decision Support Systems, considering Uncertainties Understandable and Actionable! 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

26. Walter E. Baethgen 2013 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) 680-4459 email:baethgen@iri.columbia.edu Internet:http://iri.columbia.edu/