Presentation done for the Institute for Climate and Atmospheric Science (ICAS) at the University of Leeds, UK, as part of Julian Ramirez-Villegas' PhD work and as a requisite for the PhD transfer.

1. Assessing the impacts of climate change on Sub-Saharan Africa and South-East Asian agriculture Julian Ramirez-Villegas Climate Impacts Group, ICAS (c) Neil Palmer (CIAT)

2. Contents Project title and supervision Background and rationale Objectives Research topics To-date results: aspects of climate relevant to crop production modelling Other results

3. Project title and supervision (c) Neil Palmer (CIAT) Title: Informing the adaptation of agricultural systems in Africa and Asia to progressive climate change over the coming decades Supervision Andy Challinor (principal @SEE, Leeds) Andy Jarvis (external @CIAT, Colombia) Doug Parker (nominal @SEE, Leeds) Assessment Peter Knippertz (RSG member @SEE, Leeds)

4. Background and rationale Agriculture contribution to GDP is between 3 to 61% in developed countries (World Bank, 2008)

5. Background and rationale By 2100, novel climates could happen in 10-48% of the earth (Williams et al. 2007) Climate change is predicted to decrease agricultural yields (many authors), with major impacts in the DW (many authors) Source: Lobell et al., 2008

6. Background and rationale Hence, three challenges are expected Adapting agriculture to future stresses Meeting the future food demand Mitigating GHG emissions Requiring some R&D to be done: Generating base information for I.A. Assessing impacts on agriculture at different scales Development of adaptation strategies Test and transfer of these strategies

7. General objectives Assess the impact of climate change on agriculture in 12 countries of Africa and South-East Asia for a set of important crop production systems Produce a set of recommendations on how to adapt these systems to avoid crop yield drops in the future.

8. Workflow 1 2 3

9. Research overview Research focus regions

10. Research topics 1. Assessing relevant climate data for agricultural applications Climate datasets screening Assessment of available and relevant data Quality Uncertainties Analysis of GCM skill (CMIP3 and CMIP5) on crop-growth related variables Future climate projections uncertainty quantification

11. Research topics 2. Assessing impacts of climate change on agricultural production Selection of crops based on regional relevance Development, calibration and evaluation of EcoCrop for the target crops Knowledge gap filling, calibration and evaluation of GLAM for the target crops Predicting current, future yields and suitability Detecting vulnerable areas and systems

12. Research topics: aspects of climate relevant to crop production modelling Photosynthesis is the fundamental process of interest Storage in organs

13. Research topics: aspects of climate relevant to crop production modelling And is affected by a number of factors Temperature and CO2 Avail. water and solar radiation Source: Bates, 2002 Source: Isdo et al., 1995 (sour orange trees)

14. EcoCropRamirez et al. (acceptedforpublication) Itevaluatesonmonthlybasisifthere are adequateclimaticconditionswithin a growingseasonfortemperature and precipitation… …and calculatestheclimaticsuitability of theresultinginteractionbetweenrainfall and temperature… Forassessingcropclimaticsuitability…

15. GLAMChallinor et al. (2004) Designed at climate model scale to capitalise on known large-scale relationships between climate and crop yield, thus avoiding over-parameterisation. Uses grid-scaled agricultural statistics to simulate yields To simulate yields at climate model scale Large-area models are able to reproduce large-scale historical yield responses to climate and inter-annual variability Observed peanut yields (kg/ha) Rate of simulated to observed yields

16. Research topics 3. Adapting agriculture to climate change through crop management and genetic adjustments Genetic level modifications Drought and waterlogging tolerance Heat and cold tolerance Management strategies Tillage as an improvement of soil phys. Characteristics Shading as in albedo or extinction coefficient Determining best combinations of Management-Genetic improvements

17. Research topics: useful- and uniqueness Many studies focusing on the developing world Many using process-based models Few with broad coverage Few with adaptation-focus Few with proper uncertainty quantification (avg. num. future scenarios is 3) Few with solid background on climate science Few using niche-based approaches None using niche-based AND process-based models at the same time…

18. Results to date

19. Results: aspects of climate relevant to crop production modelling So, accurate measurements are required Field measurements AND Climatologically robust future prediction methods Common sources of future climate data Common sources of present-day climate data *on the basis of 205 peer-reviewed papers Source: Ramirez and Challinor, in prep.

20. Results: aspects of climate relevant to crop production modelling Complexity of the system IGP Humid west Africa East African highlands Sahel East Africa arid lands +++Constraints to data and uncertainty quantification

21. Results: aspects of climate relevant to crop production modelling Global climate model skill (IPCC 4AR) Annual December-February June-July-August Diurnal temperature range Mean temperature Rainfall Source: Ramirez and Challinor, in prep.

22. Results: aspects of climate relevant to crop production modelling Climate model skill (CMIP3) 1961-1990 Rainfall 1961-1990 Temperature Source: Ramirez and Challinor, in prep.

23. GISS-MODEL-EH Range: 1-347 Mean: 41 ± 63 points/gridcell R-square (observed vs. climate model) - RAINFALL NCAR-CCSM3.0 Range: 1-80 Mean: 10 ± 12 points/gridcell

24. GISS-MODEL-EH Mean bias rate (observed vs. climate model) - RAINFALL NCAR-CCSM3.0 Rain is mostly overestimated

25. Other results Development and evaluation of the EcoCrop model and a case-study with sorghum (Crop-climate ensembles Special Issue in AFM) Crop data being organised in a database with stable design

26. Future plans Year 2: Finalise data collection (agricultural statistics and crop-presence) Gather and asses CMIP5 climate model outputs Physiology knowledge gap filling in GLAM Crop model (EcoCrop) calibration and evaluation for other crops Crop model (GLAM) calibration and evaluation Year 3: Queries to experts and literature on priority traits and realistic ranges Modifications to crop models to test realistic ranges of genetic and/or management strategies Assessing adaptation options

27. Thanks