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Julian R - Adapting to progressive climate change PAU Nov 2010
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Julian R - Adapting to progressive climate change PAU Nov 2010

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Presentation done at the Punjab Agricultural University, Ludhiana, India. Explains the CCAFS Theme 1 workplan and gives an overview on CCAFS.

Presentation done at the Punjab Agricultural University, Ludhiana, India. Explains the CCAFS Theme 1 workplan and gives an overview on CCAFS.

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  • 1. Adapting agriculture to progressive climate change Julian Ramirez & Theme 1 team (c) Neil Palmer (CIAT)
  • 2. Contents • Background – The problem: Climate, climate change and agriculture – The framework: CCAFS • Theme 1 workplan • Modelling impacts of climate change • An example with beans (c) Neil Palmer (CIAT)
  • 3. Background: climate, climate change and agriculture • Agriculture is a niche-dependent activity – Located in suitable AND subjectively selected areas – Affected by variations in climatic and social drivers • Yet there are shared strengths and weaknesses, each system is an specific case • Climate is the least predictabl driver of agriculture • Climate will change (c) Neil Palmer (CIAT)
  • 4. • Population growth • Non-environmentally friendly technologies/practices LEAD TO GREENHOUSE GASES EMISSIONS OUTBREAKS
  • 5. Background: CCAFS • Stands for Challenge Program on Climate Change, Agriculture and Food Security • Created by the Consultative Group on International Agricultural Research (CGIAR) “Assessing impacts of climate change, facilitate adaptation and alleviate poverty under changing conditions”
  • 6. Background: CCAFS • Who does the research? 15 centres + ~70 regional offices
  • 7. Background: CCAFS • Where is it commited to work? Why? Prone to drought & flooding, but with strong regional climate institutions for adapting Prone to drought & flooding (cyclones), and risk from sea level rise
  • 8. Background: CCAFS • How does it act? (2030s)
  • 9. Theme 1: Adaptation pathways under progressive climate change • What does a 2C degree warmer world mean for agriculture? • What precipitation trend is expected for the different regions • What practices and technologies do exist? • Which of these can be transferred to facilitate adaption? How? • What new need to be developed/adjusted for adaption • How to communicate all this?
  • 10. Assessing impacts of future climate
  • 11. Climate model projections by 2030s
  • 12. Research areas: Available and usable climate data BCCR-BCM2.0 CCCMA-CGCM3.1-T47 CNRM-CM3 CSIRO-MK3.0 CSIRO-MK3.5 GFDL-CM2.0 GFDL-CM2.1 INGV-ECHAM4 INM-CM3.0 IPSL-CM4 MIROC3.2-MEDRES MIUB-ECHO-G MPI-ECHAM5 MRI-CGCM2.3.2A NCAR-CCSM3.0 NCAR-PCM1 UKMO-HADCM3 UKMO-HADGEM1
  • 13. Temperature trend 21st century
  • 14. Modelling approaches • Selection of crops to assess • Selection of crop models to use • Collating input climate and agricultural data • Design of experiments • Calibration, validation and crop model runs (c) Neil Palmer (CIAT)
  • 15. Developing adaptation strategies • Explore adaptation options –Genetic improvement –On-farm management practices • Test them via modelling • Build “adaptation packages” • Assess technology transfer options (c) Neil Palmer (CIAT)
  • 16. Examples: Modelling bean production Growing season (days) 90 Killing temperature (°C) 0 Minimum absolute temperature (°C) 13.6 Minimum optimum temperature (°C) 17.5 Minimum absolute rainfall (mm) 200 Minimum optimum rainfall (mm) 363 Maximum optimum rainfall (mm) 450 Maximum absolute rainfall (mm) 710 Growing season (days) 90 Killing temperature (°C) 0 Minimum absolute temperature (°C) 13.6 Minimum optimum temperature (°C) 17.5 Maximum optimum temperature (°C) 23.1 Maximum absolute temperature (°C) 25.6
  • 17. What will likely happen? 2020 – A2 2020 – A2 - changes
  • 18. Developing adaption strategies Most effective genetic improvement strategy for areas that are likely to be vulnerable to the 2050s climate.