1. L i n k i n g S c i e n c e t o S o c i e t y cover box Global change information needs for decision makers dealing with food security Walter E. Baethgen Maxx Dilley International Research Institute for Climate Prediction (IRI) The Earth Institute Columbia University

2. L i n k i n g S c i e n c e t o S o c i e t y Decision Makers (including Policy makers): Extremely Heterogeneous Community (like “Users”) Different Decision Makers require different Information (demanded information is also extremely heterogeneous) Global / International ... Country ... Village Global change information needs for decision makers dealing with food security

3. L i n k i n g S c i e n c e t o S o c i e t y cover box Example: Climate Change Information Typically: Food security maps for 2050’s- 2080’s Global change information needs for decision makers dealing with food security

4. L i n k i n g S c i e n c e t o S o c i e t y Season Length 1961-90 Season Length 2080’s Multiple cropping zones 1961-90 Multiple cropping zones 2080 Rainfed cereals: CC Impacts 2080’s

5. L i n k i n g S c i e n c e t o S o c i e t y cover box Global change information needs for decision makers dealing with food security Food Security Maps at Global Level: Excellent for COP negotiators (UNFCCC) Excellent for increasing general awareness Useful for UN-type organizations (FAO, UNDP, WB, IFPRI) At Country Level: Place Climate Change as a “Problem of the Future” Beyond the agenda of Decision / Policy Makers (2080’s)

6. L i n k i n g S c i e n c e t o S o c i e t y cover box Global change information needs for decision makers dealing with food security At Country Level: Most commonly, Global information is not easily applicable 1.Degree of Uncertainty 2.Full agenda with immediate-term issues (vs 2050’s) requiring immediate action. Challenge: Overcome the “Incompatibility” of Time Frames Introduce Global Change Issues in Development Agenda

7. L i n k i n g S c i e n c e t o S o c i e t y Global change information needs for decision makers dealing with food security Overcoming the “Incompatibility” of Time Frames 1. Climate Change is happening now (vs 2050’s, 2080’s) 2. Climate change is affecting and will continue to affect societies through increased Climate Variability often including more frequent and more damaging Extreme Events (droughts, floods, etc.)

8. Premise prepared and adapt to possible Climate Change scenarios better cope with current Climate Variability One of the most effective ways for assisting agricultural stakeholders to be prepared and adapt to possible Climate Change scenarios, is by helping them to better cope with current Climate Variability Overcomes time frame Incompatibility: Actions are needed within Policy Makers term Results of actions can be verified also within the PM term

9. L i n k i n g S c i e n c e t o S o c i e t y cover box Global change information needs for decision makers dealing with food security Examples of Information that can assist Decision Makers at Country (or smaller) scale Decision Support tools tailored for different Policy Makers but focused on Climate Variability and its impacts (on food security and other)

10. L i n k i n g S c i e n c e t o S o c i e t y cover box A few common features of Decision Support Systems with shown success: Understanding the past effects (linking CV, crop yields, responses, etc) Strong component: MONITORING (measuring) the present Adequate and understandable FORECASTS Risk Assessment / Risk Management Approach

11. Understanding the Baseline: Measuring food security Slides courtesy T. Boudreau, Food Economy Group/FEWS)

12. Households become food insecure when they cannot meet 100% of food requirements % annual food requirements Climate Variability

13. Food Economy Zones (baseline)

14. Baseline and Method for Running Scenarios: Simple Spreadsheet… Exploring possible responses

15. Climate Change/Variability impacts on food security Assess Past Impacts Develop good Monitoring Improve Forecasts / Scenarios Explore/Propose Responses

16. Forecasting food security variables from climate models, Oct-Dec season (climate prediction research by M. Indeje, IRI) The following slides show "hindcast" and forecast skill between observed and predicted rainfall values for October-December for high- skill areas in the Greater Horn of Africa (Prediction skill for March-May or June-September is lower)

17. Corr_coef. = 0.8 Model -MOS CORRECTED OBSERVATION Statistically corrected ECHAM4 GCM Oct-Dec precipitation to a station

18. Correlation between statistically corrected climate model output and observed rainfall, Oct-Dec

19. L i n k i n g S c i e n c e t o S o c i e t y cover box Still one step is needed: Results are expressed in “terms” that Decision Makers do not use (e.g., Rainfall) Need to “Translate” information to the same terms that Decision Makers use (crop yields, pasture availability, water in reservoirs, etc.)

20. NDVI forecast skill, Oct-Dec Correlation between: 1.GCM precipitation for October- December (runs from September*) 2.December NDVI values. (Eastern Kenya r=0.74) (*) persisted-SST and 850mb zonal wind forecasts

21. COF11 – Forecast Crop Conditions at End of Season Actual Crop Conditions at End of Season Slide Courtesy G. Galu Predicting end-of-season crop conditions using the Water Requirements Satisfaction Index

22. Translating Climate Information into Food Security Information Regional food security outlooks based on climate forecast-derived projections of crop yields, livestock condition and other food security-related variables, and use as input into a livelihoods- based food security analysis

23. Involving the Decision Makers: Developing Trust Affecting / Changing Decisions Assisting policies L i n k i n g S c i e n c e t o S o c i e t y

24. December 1999 January 2000February 2000 November 1999October 1999 Example in Uruguay Decision Support System Provided this Information to MAF and to National Emergency System (Evolution of the Drought) IMPORTANCE of MONITORING

25. 19 January23 March Volume Changes in Water Reservoirs during the 1999/2000 drought (prepared for the National Emergency System) Example in Northern Uruguay Remote Sensing

26. Ing. Juan Notaro, Uruguayan Minister of Agriculture in 1999/2000 (Letter to our INIA-IFDC-NASA Project) "(...) The results of your work during the recent drought were useful for making both, operational and political decisions. From the operational standpoint, your work allowed us to concentrate our efforts in the regions highlighted as being the ones with the worst and longest water deficit. We prioritized those identified regions for concentrating the use of our resources, both financial aid and machines for dams, water reservoirs, etc. (...) From the strictly political standpoint, your work provided us with objective information to defend our prioritization of regions, in a moment in which every governor, politician and farmer in the country was asking for aid. We received no complaints in this respect. In the same line, your work also allowed to mitigate pressures since we provided the press and the general public with transparent, technically sound and precise information ”.

27. Ing. Juan Notaro, Uruguayan Minister of Agriculture in 1999/2000 (Letter to our INIA-IFDC-NASA Project) "(...) The results of your work during the recent drought were useful for making both, operational and political decisions. From the operational standpoint, your work allowed us to concentrate our efforts in the regions highlighted as being the ones with the worst and longest water deficit. We prioritized those identified regions for concentrating the use of our resources, both financial aid and machines for dams, water reservoirs, etc. (...) From the strictly political standpoint, your work provided us with objective information to defend our prioritization of regions, in a moment in which every governor, politician and farmer in the country was asking for aid. We received no complaints in this respect. In the same line, your work also allowed to mitigate pressures since we provided the press and the general public with transparent, technically sound and precise information ”. The results of your work during the recent drought were useful for making both, operational and political decisions.

28. Ing. Juan Notaro, Uruguayan Minister of Agriculture in 1999/2000 (Letter to our INIA-IFDC-NASA Project) "(...) The results of your work during the recent drought were useful for making both, operational and political decisions. From the operational standpoint, your work allowed us to concentrate our efforts in the regions highlighted as being the ones with the worst and longest water deficit. We prioritized those identified regions for concentrating the use of our resources, both financial aid and machines for dams, water reservoirs, etc. (...) From the strictly political standpoint, your work provided us with objective information to defend our prioritization of regions, in a moment in which every governor, politician and farmer in the country was asking for aid. We received no complaints in this respect. In the same line, your work also allowed to mitigate pressures since we provided the press and the general public with transparent, technically sound and precise information ”. your work provided us with objective information to defend our prioritization of regions, in a moment in which every governor, politician and farmer in the country was asking for aid.

29. Involving the Decision Makers (2): Move from “Supply” Approach To “Demand Driven” Approach

30. Regional Outlook Meetings IRI NOAA ECMWF Others Nat. Climate Res. Ctrs. IFDC INIA NASA Un.Fla. QSLD Tech. Reps. Agri-Business MAF Planning Policies NGOs Gov.Organiz. Growers Local Outlook Local Outlook Needs (Variables, Timing, Tools) Tools (IDSS) ENSO and “Global” Climate Forecasts Regional Outlook Media Internet IAI Met. Service Workshops (Quarterly) Pilot Project IFDC/INIA/NASA: Climate Forecast Applications in Agriculture “TWG” Insurance Credit

31. Nat. Climate Res. Ctrs. IFDC INIA NASA Un.Fla. QSLD Tech. Reps. Agri-Business MAF Planning Policies NGOs Gov.Organiz. Growers Local Outlook Needs (Variables, Timing, Tools) Tools (IDSS) Workshops (Quarterly) “TWG” Insurance Credit “Hands-on” Training (Education) for Users (CC, CV, probabilities, role of FCSTs, risks) Demand for Researchers (info and tools)

32. DS Tools: Risk Assessment Risk Management “Users” Who are the “clients”?

33. Ministries Agro, Health, Water Insurance Credit NGOs Advisers DS Tools: Risk Assessment Risk Management “Users”

34. Insurance Credit NGOs Advisers (Pilot Projects: Keep on track) “Users” Ministries Agro, Health, Water DS Tools: Risk Assessment Risk Management

35. L i n k i n g S c i e n c e t o S o c i e t y Final Comments Introduce Climate Change in current agendas overcoming time frame incompatibilities: CC is a current problem CV approach Translate Climate information to the terms that Decision Makers use to make decisions Develop Decision Support Systems (Risk Assessment/Risk Management approach) that assist: Understanding the past Monitoring the present Forecasting the future (probabilitistic scenarios) Involve Decision Makers from the start (Demand-driven approach)

36. L i n k i n g S c i e n c e t o S o c i e t y Thank you! Walter E. Baethgen Maxx Dilley International Research Institute for Climate Prediction The Earth Institute, Columbia University