julian r - adapting to progressive climate change pau nov 2010
DESCRIPTION
Presentation done at the Punjab Agricultural University, Ludhiana, India. Explains the CCAFS Theme 1 workplan and gives an overview on CCAFS.TRANSCRIPT
Adapting agriculture to progressive climate changeJulian Ramirez
& Theme 1 team
(c) Neil Palmer (CIAT)
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)
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)
• Population growth• Non-environmentally
friendly technologies/practices
LEAD TO GREENHOUSE GASES EMISSIONS OUTBREAKS
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”
Background: CCAFS
• Who does the research?15 centres + ~70 regional offices
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
Background: CCAFS
• How does it act?
(2030s)
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?
Assessing impacts of future climate
Climate model projections by 2030s
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
Temperature trend 21st century
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)
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)
Examples: Modelling bean production
Growing season (days) 90
13.6
17.5
23.1
25.6
Minimum absolute rainfall (mm)
200
Minimum optimum rainfall (mm)
363
Maximum optimum rainfall (mm)
450
Maximum absolute rainfall (mm)
710
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
What will likely happen?
2020 – A2
2020 – A2 - changes
Developing adaption strategies
Most effective genetic improvement strategy for areas that are likely to be vulnerable to the 2050s climate.