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Challenges for the simulation of crop yields in a changing climate Tim Wheeler Crops and Climate Group

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Presentation on theme: "Challenges for the simulation of crop yields in a changing climate Tim Wheeler Crops and Climate Group"— Presentation transcript:

1 Challenges for the simulation of crop yields in a changing climate Tim Wheeler Crops and Climate Group t.r.wheeler@rdg.ac.uk

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3 What are effects of climate on crops? Can we forecast the productivity of crops in a changing climate?

4 Harvest records at Chilgrove, Sussex, 1769-1910 Data from, Russell, 1920

5 Harvest records at Chilgrove, Sussex, 1769-1910

6 Climate and weather are vital for crops but …

7 Climate change that is important for crops By 2100 … Carbon dioxide, CO 2 (emissions of 550 to 950 ppm) Temperature (+1.4 to +5.5 o C) Rainfall amount (huge regional range) Variability in weather (more intense storms, increased drought risk; more frequent hot days) from IPCC TAR (2001)

8 How are these effects on crops investigated? Plant Environment Laboratory, University of Reading

9 How are these effects on crops investigated? Free Air CO 2 Enrichment, FACE Courtesy of Steve Long, University of Illinois

10 Effects of elevated CO 2 Elevated CO2 was 475-600 ppmfrom Ainsworth and Long (2005) Maize, millet, sorghum, sugar cane will not benefit

11 Effects of warmer temperature from Lawlor & Mitchell (2000), Baker et al (1995), Daymond et al (1997) Some adaptation is possible through use of varieties

12 Rice Warmer season... … or a few hot days

13 Groundnut From Vara Prasad et al (2001) Warmer season... … or a few hot days

14 sowflowerharvest Groundnut crop growing in Andhra Pradesh, India Heat stress

15 Variability in rainfall within a season 1975 Total rainfall: 394mm Yield = 1360 kg/ha 1981 Total rainfall 389mm Yield = 901 kg/ha Groundnut crop growing in Andhra Pradesh, India

16 Soyabean - 8 days of up to 40oC / 40% water supply during early seed-filling at 360 / 700 ppm CO 2 from Ferris et al, 1999 Variability in rainfall and temperature within a season -30% +22% -26% +32%

17 What are effects of climate on crops? Can we forecast the productivity of crops in a changing climate?

18 Changes in crop yield from the present day to the 2080s Unmitigated emissions Parry et al., University of East Anglia Potential change in cereal yields (%) No data 10 – 5 0 – -2.5 -5 – -10 -2.5 – -5 -10 – -20 2.5 – 0 5 – 2.5

19 Linking climate information to crop models general circulation model crop model

20 Groundnut (peanut) production in India, 1965 - 1990

21 Patterns of seasonal rainfall and yield of groundnut in India District level groundnut yields (kg ha -1 ) Mean of 1966 - 1990 Data source: ICRISAT

22 Patterns of seasonal rainfall and yield of groundnut in India Sub-divisional level seasonal rainfall (JJAS, cm) Mean of 1966 - 1990 Data source: IITM

23 Correlation between patterns of seasonal rainfall and yield First principal component of rainfall yield

24 Correlation between patterns of seasonal rainfall, yield and circulation First principal component of rainfall yield and PC3 of 850hPa circulation

25 Sites/weather stations in the main maize producer region Surrounding counties, to each weather station (micro-regions) Correlation between seasonal rainfall and yield of maize Rio Grande do Sul, Brasil 1990-2005 Homero Bergamaschi, et al. 2006

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28 Combines: the benefits of more empirical approaches (low input data requirements, validity over large spatial scales) with the benefits of the process-based approach (e.g. the potential to capture intra-seasonal variability, and so cope with changing climates) General Large Area Model for Annual Crops (GLAM) Challinor et. al. (2004)

29 d(HI)/dt YieldBiomass transpiration efficiency Root system DevelopmentTranspirationradiation stagetemperature RH rainfall waterSoil water stress C YG Leaf canopy General Large Area Model for Annual Crops (GLAM)

30 Hindcasts of groundnut yield for India from Challinor et al (2004)

31 Impact of extreme temperatures Hadley Centre PRECIS model, A2 (high emission) scenario 2071-2100 Number of years when the total number of pods setting is below 50%. Sensitive varietyTolerant variety Challinor et al., 2005

32 1975 Total rainfall: 394 mm Model: 1059 kg/ha Obs: 1360 kg/ha 1981 Total rainfall 389 mm Model: 844 kg/ha Obs: 901 kg/ha Impacts of variability in rainfall within a season Groundnut yield in Gujarat

33 Modelling the impacts of climate change on rice Changes in rice production across Asia under 2 x CO 2 from Matthews & Wassmann (2003)

34 Using probabilistic climate forecasts Use of DEMETER multi-model ensemble for groundnut yield in Gujarat, 1998 from Challinor et al (2005) Model average63 ensemble members Observed 775 kg ha -1 713 kg ha -1

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36 Fully coupled crop-climate simulation to represent crop-climate feedbacks Crops ‘growing’ in HadAM3 Osborne et al., (2006)

37 All-India groundnut yield (red) with simulated mean yield (black) and spatial standard deviation (grey shading). Fully coupled crop-climate simulation Osborne et al., (2006)

38 FAO statistics Area mean s.d (spatial variability) Representation of feedbacks between crops and atmosphere at an early stage A coupled crop-climate model run Tom Osborne, University of Reading

39 Summary. The effects of climate on crops Crop growth and yield will be enhanced by elevated CO 2 Warmer seasons will be shorter and yields less … but, adaptation can counter this to some extent … but, benefit could be less on farmer’s fields A few days of hot temperature can severely reduce yields Crops will be vulnerable to variability in rainfall.

40 Summary. Forecasting crop yields Crop models summarise observations and allow predictions ahead of time Most crop models simulate fields of crops, … but, crop forecasts often needed over countries and regions, nearer to the scale of climate model predictions New developments in crop and climate modelling should improve our forecasts of crops in a changing climate

41 Crop observations –Magnitude of CO 2 effect, effects of climate extremes and poor soil fertility Climate models not ideal for crop prediction –Differences in spatial and temporal scale –Precipitation is key and is a difficult variable to predict Combining crop and climate models –Cascade of uncertainties Summary. Challenges for the simulation of crop yields in a changing climate

42 Many thanks to … t.r.wheeler@rdg.ac.uk Andrew Challinor Julia Slingo Peter Craufurd David Grimes Tom Osborne Laurence Hansen Richard Betts


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