challenges for the simulation of crop yields in a changing climate tim wheeler crops and climate...

Challenges for the simulation of crop yields in a changing climate

Tim Wheeler

Crops and Climate Group

t.r.wheeler@rdg.ac.uk

What are effects of climate on crops?

Can we forecast the productivity of crops in a changing climate?

180

200

220

240

260

1760 1780 1800 1820 1840 1860 1880 1900 1920

Year

day

of

har

vest

DOY 200 is 19 July

DOY 240 is 28 Aug

Harvest records at Chilgrove, Sussex,

1769-1910

Data from, Russell, 1920

Harvest records at Chilgrove,Sussex, 1769-1910

y = -11.294x + 321.31

R2 = 0.5168

180

200

220

240

260

7 8 9 10 11Central England mean surface air temperature (°C)

Day

of h

arve

st

Climate and weather are vital for crops

but …

Climate change that is important for crops

By 2100 …

• Carbon dioxide, CO2 (emissions of 550 to 950 ppm)

• Temperature (+1.4 to +5.5 oC)

• Rainfall amount (huge regional range)

• Variability in weather (more intense storms,

increased drought risk; more frequent hot days)

from IPCC TAR (2001)

How are these effects on crops investigated?

Plant Environment Laboratory, University of Reading

How are these effects on crops investigated?

Free Air CO2 Enrichment, FACE

Courtesy of Steve Long, University of Illinois

Effects of elevated CO2

Elevated CO2 was 475-600 ppm from Ainsworth and Long (2005)

0

10

20

30

40

50

all no stress drought

Incre

ase y

ield

(%

)

+19%

+40%

+28%

Maize, millet, sorghum, sugar cane will not benefit

Effects of warmer temperature

from Lawlor & Mitchell (2000), Baker et al (1995), Daymond et al (1997)

-12

-10

-8

-6

-4

-2

0

Wheat Rice Onion 1 Onion 2

Incr

ease

in y

ield

(%

)

-8%

-10% -10%

-4% Some adaptation is possible through use of varieties

Rice

Warmer season... … or a few hot days

Groundnut From Vara Prasad et al (2001)

Flower bud temperature (oC)

24 28 32 36 40 44 48

Fru

it se

t (%

)

0

20

40

60

Warmer season... … or a few hot days

20

22

24

26

28

30

32

34

36

38

T m

ax

(o

C)

20

22

24

26

28

30

32

34

36

38

T m

ax

(o

C)

180 200 220 240 260 280 300 320 340

Day of the year

0

10

20

30

40

50

60

70

80

Ra

infa

ll (m

m)

sow flower harvest

Groundnut crop growing in Andhra Pradesh, India

Heat stress

20

22

24

26

28

30

32

34

36

38

T m

ax

(o

C)

+2oC

Variability in rainfall within a season

1975Total rainfall: 394mm

Yield = 1360 kg/ha

1981Total rainfall 389mm

Yield = 901 kg/ha

Groundnut crop growing in Andhra Pradesh, India

-40

-30

-20

-10

0

10

20

30

40

elev CO2 HT WD HTWD

% c

han

ge

fro

m c

on

tro

l Seed yield

Seed number

Soyabean - 8 days of up to 40oC / 40% water supply during early seed-filling at 360 / 700 ppm CO2 from Ferris et al, 1999

Variability in rainfall and temperaturewithin a season

-30%

+22%

-26%

+32%

What are effects of climate on crops?

Can we forecast the productivity of crops in a changing climate?

Changes in crop yieldfrom the present day to the 2080s

Unmitigated emissionsParry 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 – 05 – 2.5

Linking climate informationto crop models

general circulation model

crop model

400

500

600

700

800

900

1000

1100

1200

1965 1970 1975 1980 1985 1990

Year

Gro

un

dn

ut

yie

ld (

kg

ha

-1)

National YieldStatistics

Groundnut (peanut) production in India, 1965 - 1990

Patterns of seasonal rainfall and yield of groundnut in India

District level groundnut yields (kg ha-1)

Mean of 1966 - 1990

Data source: ICRISAT

Patterns of seasonal rainfall and yield of groundnut in India

Sub-divisional level seasonal rainfall (JJAS, cm)

Mean of 1966 - 1990

Data source: IITM

Correlation between patterns of seasonal rainfall and yield

First principal component of

rainfall

yield

Correlation between patterns of seasonal rainfall, yield and circulation

First principal component of

rainfall

yield

and PC3 of

850hPa

circulation

Sites/weather stations in the main maize producer region

Surrounding counties, to each weather station (micro-regions)

Correlation between seasonal rainfalland yield of maize

Rio Grande do Sul, Brasil

1990-2005

Homero

Bergamaschi,

et al. 2006

Annual yield of maize in 11 micro-regions of RS State, Brazil (1990-2004) as function of rainfall from 5 days before to 40 days after tasseling

y = 6,5858x + 1276,6

R2 = 0,56790

500

1000

1500

2000

2500

3000

3500

4000

4500

0 50 100 150 200 250 300 350 400

Average rainfall in the 5-tasseling+40 days (mm)

Ave

rage

gra

in y

ield

(kg

ha-1

)

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 Modelfor Annual Crops (GLAM)

Challinor et. al. (2004)

d(HI)/dt

Yield Biomass

transpiration

efficiency

Root systemDevelopment Transpiration radiation

stage temperatureRH

rainfall

water Soil water

stressCYG

Leaf canopy

General Large Area Modelfor Annual Crops (GLAM)

Hindcasts of groundnut yield for India

400

600

800

1000

1200

1965 1970 1975 1980 1985 1990

Gro

un

dn

ut

yie

ld (

kg

ha

-1) National Yield Statistics

GLAM prediction

from Challinor et al (2004)

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 variety Tolerant variety

Challinor et al., 2005

1975Total rainfall: 394 mmModel: 1059 kg/haObs: 1360 kg/ha

1981Total rainfall 389 mmModel: 844 kg/haObs: 901 kg/ha

Impacts of variability in rainfall within a season

Groundnut yield in Gujarat

Modelling the impacts of climatechange on rice

Changes in rice production across Asia under 2 x CO2

from Matthews & Wassmann (2003)

Climate model

GFDL GISS UKMO

ORYZA

+6.5

-4.4

-5.6 Crop

model SIMRIW

+4.2

-10.4

-12.8

0

5

10

15

20

25

200 300 400 500 600 700 800 900 1000 1100 1200

Yield (kg ha-1)

Fre

qu

ency

Using probabilistic climate forecasts

Use of DEMETER multi-model ensemble for groundnut yield in Gujarat, 1998 from Challinor et al (2005)

Model average 63 ensemble members

Observed

775 kg ha-1

713 kg ha-1

Fully coupled crop-climate simulation to represent crop-climate feedbacks

Crops ‘growing’ in HadAM3

Osborne et al., (2006)

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)

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

Summary. The effects of climate on crops

Crop growth and yield will be enhanced by elevated CO2

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.

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

Crop observations

– Magnitude of CO2 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

Many thanks to …

t.r.wheeler@rdg.ac.uk

Andrew Challinor

Julia Slingo

Peter Craufurd

David Grimes

Tom Osborne

Laurence Hansen

Richard Betts