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Presentation by Julian Ramirez-Villegas.

CCAFS workshop titled "Using Climate Scenarios and Analogues for Designing Adaptation Strategies in Agriculture," 19-23 September in Kathmandu, Nepal.

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- 1. The Analogues Methodology<br />Julian Ramirez-Villegas<br />
- 2. The method<br />Jointly developed by the Walker Institute (University of Reading, UK) and the Decision and Policy Analysis program (DAPA) at CIAT<br />Funded by CCAFS Theme 1: Adaptation to progressive climate change<br />And collaborating with some other people in different institutions<br />
- 3. Which questions can we answer?<br /><ul><li>Where can I find my site in the future? (FORWARD)
- 4. Where can I find a place that currently looks like how my site would be in the future? (BACKWARD)
- 5. Where can I find similar areas to my site currently or in the future? (NO-DIRECTION)</li></li></ul><li>Guiding principles and final aims<br /><ul><li>Facilitate farmer-to-farmer exchange of knowledge
- 6. Permit validation of computational models and trialing of new technologies and techniques
- 7. Learning from history
- 8. Ground climate change impacts and adaptation studies
- 9. Quantify the real effects of uncertainty in the process of adaptation</li></li></ul><li>How do we calculate dissimilarity?<br />In reality, this is a n-dimensional<br />space of m time-steps and v variables<br />
- 10. How do we calculate dissimilarity?<br />The CCAFS measure: a modified version of the Euclidean distance<br />m: time-step (e.g. month, day, quarter)<br />v: number of variables<br />V: Variable (i.e. temperature, rainfall, etc)<br />W: Weight (any number or variable)<br />f: reference scenario (e.g. future climate)<br />p: target scenario (e.g. current climate)<br />z: exponent (we normally assume 2)<br />Lagging<br />
- 11. How do we calculate dissimilarity?<br />Accounting for lag<br />Site A (southern)<br />Site B (northern)<br />
- 12. How do we calculate dissimilarity?<br />The CCAFS measure: weights with other variables<br />W: Weight value<br />X: Variable value<br />i: a given time step<br />j: a given variable<br />
- 13. How do we calculate dissimilarity?<br />As with the example data,<br />m: month (from 1 to 12)<br />f: reference value (e.g. future climate)<br />p: target value (e.g. present climate)<br />z: exponent (we normally assume 2)<br />T: Temperature<br />P: Precipitation<br />DTR: Diurnal temperature range<br />m-lag: month that produces a maximum match of climate parameters (precip, temp)<br />
- 14. How do we calculate dissimilarity?<br />Hallegatte et al. (2007): a rule based dissimilarity measure<br />Relative difference between total values less than “a”<br />Mean absolute relative differences between mean values for m steps less than “b”<br />Mean absolute difference between total values for m steps less than “c”<br />m: time-step (e.g. month, day, quarter)<br />V: Variable (i.e. temperature, rainfall, etc)<br />W: Weight (any number or variable)<br />f: reference scenario (e.g. future climate)<br />p: target scenario (e.g. current climate)<br />a, b, c: user defined parameters<br />
- 15. Do our two measures agree?<br /><ul><li>Could depend on the site, but so far, they do</li></li></ul><li>Analogues of what?<br /><ul><li>Of a site within all land areas of a given geographic domain</li></li></ul><li>Analogues of what?<br />Of one site to many others<br />Dissimilarity from a site in Ghana (future) to 35 other sites at present<br />(bars are the distribution of 24 GCMs)<br />
- 16. Analogues of what?<br /><ul><li>Of many points one versus the other (n-by-n sites matrix)</li></li></ul><li>How analogues?<br /><ul><li>On seasonal temperature?</li></li></ul><li>How analogues?<br /><ul><li>On seasonal rainfall?</li></li></ul><li>How analogues?<br /><ul><li>On seasonal combination of both?</li></li></ul><li>How certain are we?<br /><ul><li>Counting GCMs that choose a site as analogue</li></li></ul><li>Not so fast, though<br />Only certain variables are key for crop dev.<br />Storage in organs<br />
- 17. Not so fast, though<br />So we need to do it “through the eyes of the crop”<br />Temperature and CO2<br />Avail. water and solar radiation<br />Source: Bates, 2002<br />Source: Isdo et al., 1995 (sour orange trees)<br />
- 18. Agricultural analogues<br /><ul><li>How much of this difference is due to the environment?</li></ul>West et al. 2010, based on Monfreda et al. 2008<br />
- 19. Agricultural analogues<br /><ul><li>Dissimilarities and agricultural yields</li></ul>Very similar high yield<br />Very dissimilar and low yields<br />
- 20. Important science questions<br /><ul><li>Could we relate our dissimilarity index with growth parameters and yields?
- 21. If so, which variables do we need to use?
- 22. Rainfall + temperature?
- 23. Rainy days?
- 24. Days with extreme (very low, very high) temperatures?
- 25. Evapotranspiration?
- 26. Total thermal times?
- 27. Soils?
- 28. Varietal targeting and testing?
- 29. Cropland expansion/optimisation/migration?
- 30. Coupling with crop models for validation and adaptation-strategy testing?</li></li></ul><li>Messages<br /><ul><li>Grounding results is required due to the large local variability
- 31. Decision support tool, but must be validated</li></li></ul><li>In this course you will learn…<br /><ul><li>The main principles of the analogues method and its potential use
- 32. How to calculate climate analogues online and via R
- 33. The different sensitivities of this method (variables, weights, direction)
- 34. How should we validate the results of the analogues tool</li></li></ul><li>A couple of clarifications…<br />Impacts on Sorghum suitability by 2030, re-calibrated<br />
- 35. A couple of clarifications…<br />Similarity between EcoCrop response and other models<br />

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