1. Meteo Mali Agrometeorological Program Evaluation: Preliminary Report Edward R. Carr Department of Geography University of South Carolina

2. Assessment Background June 2011 meeting in Dakar Demand-driven assessment – Lessons learned/good practices – Scaling up

3. Assessment Design Three components Science assessment – IRI Institutional assessment – CCAFS Field assessment – CCAFS/IER/University of South Carolina

4. Science Assessment Goals What climate information is provided to farmers? What is the scientific basis for this information? What is the translation and dissemination process? What opportunities are there for improving the quality and relevance products? What challenges have been encountered in satisfying specific user needs?

5. Science Assessment February 2012 Meetings with Mali Meteo Consultations with AGRHYMET and ACMAD Review of methods and documentation Integration with field assessment findings

6. Science Assessment Draft Assessment prepared at the end of July 2012 Example challenges – Difficulty of providing reliable local-scale forecasts Onset of the rainy season Timing of possible dry spell. – Need for monthly forecasts – Lack of verification information + Raingauge * Agroclimate o Synoptic Mali’s network of meteorological stations

7. Science Assessment Draft Assessment Example opportunities – Prospects for improved downscaling Merging satellite and station data – Using Global Producing Centre (GPC) model outputs to strengthen seasonal and monthly forecasts Distribution of known GLAM villages

8. Institutional Assessment Learn what institutional factors contributed to program success Narrative program history Identification of product development process Mapping of the changing flow of information, products, and resources in the program

9. Institutional Assessment June – November 2012 Responses from 12 informants – Follow-ups ongoing Draft document prepared

10. Institutional Assessment

11. Example draft findings Coordinating group was highly interdisciplinary but informal Continuous project funding allowed time to learn Opportunities – Broader focus for information (including livestock and fisheries) – Formalized frameworks that entrench and support the interdisciplinarity of the program

12. Field Assessment Goal Identify current impacts of the program on participants Explain the causes of these impacts Both extraordinarily difficult to do post-hoc

13. Field Assessment January 2012 – March 2012 36 villages – 18 GLAM, 18 control 144 focus groups 720 interviews – Men and women – Young and old

16. Field Assessment Broad assessment Livelihoods practices Agricultural activities Engagement with NGOs Engagement with the Agromet program

17. Field Assessment Analysis ongoing Over 430,000 data Validation of controls – No baselines – Too long a duration Identification of groupings for analysis

20. Field Assessment Initial findings Opportunities to build on end-user delivery Opportunities to better target end-user needs – Current and in preparation for future needs Opportunities to expand the user base – Heavily focused on younger men

21. Field Assessment Initial findings Suggestions of impact – Differential numbers of crops grown/varieties used by those who use agromet data and those who do not – Varies by grouping/agroecological zone Complex impact by crop

22. Field Assessment Limitations – Will have difficulty talking about yield impact – Will have difficulty establishing causality for impact Addressing the Limitations – Re-running the survey in February-March 2013 – Qualitative work in selected villages in May-July 2013

23. Coming soon… Integration of science and field assessments – Will look at science constraints and opportunities in context of end-user demands Rigorous assessment of impact at the end- user level Integrated lessons learned and good practices – Connecting science, institutional context, and end-user impact

24. Acknowledgements