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The avoided impacts of climate change on crop production Tom Osborne Thanks to: Simon Gosling, Gillian Fraser, Helen Greatrex, Tim Wheeler, Nigel Arnell.

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Presentation on theme: "The avoided impacts of climate change on crop production Tom Osborne Thanks to: Simon Gosling, Gillian Fraser, Helen Greatrex, Tim Wheeler, Nigel Arnell."— Presentation transcript:

1 The avoided impacts of climate change on crop production Tom Osborne Thanks to: Simon Gosling, Gillian Fraser, Helen Greatrex, Tim Wheeler, Nigel Arnell

2 Emissions scenarios CO 2 concentration Local change in climate Future crop yields Global warming Regional crop production A1B, and AVOID mitigation scenarios Pattern-scaling based upon GCMs echam5, hadcm3, ipsl, cgcm31,ccsm30 GLAM crop model at 0.5 resolution Maize, soybean, wheat 2030,2040,2050,… (Yield GLAM x Area observed )

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4 Global-GLAM crop model Original GLAM developed by Challinor et al (2004). Process-based crop growth and development with daily timestep. Crops: soybean, maize, wheat. Climate: 0.5 resolution using CRU based climate data. Daily weather generator. Extent: suitable grid cells and sowing date determined by separate algorithm. Varieties: 3 for maize and soybean, 1 for wheat Rain-fed simulation only. No irrigation.

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6 baseline: soybean

7 Wheat

8 Business-as-usual impact of climate change by 2050 on wheat production

9 Percentage of 2050 business-as-usual impact avoided with scenario: A1B L

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14 CO2 fertilisation alters effectiveness (relative and absolute) of AVOID scenarios

15 Maize

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22 Soybean

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29 Conclusions Wheat – Effect of mitigation varies regionally – CO 2 fertilisation influences effectiveness of mitigation – Interaction with climate change Maize – Relative effectiveness of scenarios unaffected by GCM or adaptation (as represented here) Soybean – Mitigation effectiveness insensitive to CO2 and adaptation – Positive CC impacts (S Asia) reduced by mitigation

30 Thank you

31 baseline: maize Inter-annual variability Spatial variability

32 baseline: wheat


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