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Tomoko Hasegawa (NIES, Japan)
The 18th AIM international workshop, 14-16 Dec, 2012 1
“CMIP5”: Coupled Model Intercomparison Project Phase 5 “SSP”: Shared Socioeconomic Pathway
Crop yield can be affected by changes in temperature and precipitation in the future
The impacts will vary in different regions Several approaches were taken in the assessment
of climate change impact on agriculture and food supply so far.
Existing researches ◦ Not consider uncertainty of several factors ◦ Not calculate effect of adaptations ◦ Use SRES, not SSP
2
Aim to clarify Impacts of climate change and socioeconomic conditions on food consumption and risk of hunger
Effects of adaptations on the climate change impacts
3
M-GAEZ ◦ Calculate a crop potential
yield in each 2.5’ grid cell on the global scale considering biological conditions.
Global CGE model ◦ Calculate amounts of
production, consumption and trade in response to change in prices and factor availability
4
Socio-economic Scenario
SSP
Climate scenario
Crop model M-GAEZ
AIM/CGE
Crop yield
GDP Food supply & demand Hunger population
2005-2050 17 regions and countries 26 commodities (6 groups of crops, 3 groups
of livestock products and fisheries)
5
Code Regions Code RegionsJPN Japan TUR TurkeyCHN China CAN CanadaIND India USA United StatesXSE Southeast Asia BRA BrazilXSA Rest of Asia XLM Rest of South AmericaXOC Oceania XME Middle EastEU25 EU25 XNF North AfricaXER Rest of Europe XAF Rest of AfricaCIS Former Soviet Union
Rice Meat cattleWheat Dairy cattleCereal grains nec Other livestocksOil crops FishingSugar cropsCrops nec
Agricultural commodities
Optimistic SSP1
Middle SSP2
Pessimistic SSP3
No Climate change (NoCC)
Assume present climate condition in the future
With climate change
RCP2.6
With adaptation in developing countries
Without adaptation
in developing countries
RCP4.5 RCP6.0 RCP8.5
5 climate scenarios
3 socioeconomic scenarios
6
Adaptation: ◦ Change in crop variety and
planting dates ◦ Industrial & transition countries:
available ◦ Developing countries: available
(SSP1&2) & restricted (SSP3)
Population GDP per-capita
SSP1 Low High SSP2 Mid. Mid. SSP3 High Low
* “RCP”: Representative Concentration Pathway * “SSP”: Shared Socioeconomic Pathway
To clarify uncertainty associated with different climate models, we used 12 GCMs which participated in CMIP5
7
To clarify uncertainty associated with different
GCMRCP scenario
GridsLon.×lat.
Grid length on the
equator (km)2.6 4.5 6.0 8.5
BCC-CSM1.1 ✓ ✓ ☓ ✓ 128×64 313CanESM2 ✓ ✓ ☓ ✓ 128×64 313CNRM-CM5 ✓ ✓ ☓ ✓ 256×128 156GFDL-CM3 ✓ ✓ ✓ ✓ 144×90 222GFDL-ESM2G ✓ ✓ ✓ ✓ 144×90 222GFDL-ESM2M ✓ ✓ ✓ ✓ 144×90 222HadGEM2-ES ✓ ✓ ✓ ✓ 192×145 138MIROC5 ✓ ✓ ✓ ✓ 256×128 156MIROC-ESM ✓ ✓ ✓ ✓ 128×64 313MIROC-ESM-C ✓ ✓ ✓ ✓ 128×64 313MRI-CGCM3 ✓ ✓ ✓ ✓ 320×160 125NorESM1-M ✓ ✓ ☓ ✓ 144×96 208
“CMIP5”: Coupled Model Intercomparison Project Phase 5
▲ 150▲ 100▲ 50
050
100150200250
EU25
Oce
ania
Japa
nCa
nada
Uni
ted
Stat
esRe
st o
f Eur
ope
Turk
eyCh
ina
Indi
aBr
azil
Form
er S
ovie
t Uni
onSo
uthe
ast A
siaRe
st o
f Asia
Rest
of S
outh
Am
eric
aM
iddl
e Ea
stN
orth
Afr
ica
Rest
of A
fric
a
Chan
ge in
yie
ld [%
] (N
oCC=
100)
NoCC: IMPACT CC: climate change impacts on crop yield
calculated from M-GAEZ & LPJ
8
NoCC: IMPACT
Change in crop yield caused by CC in 2050 (RCP8.5, HadGEM2ES)
“CC”: reflecting damages due to climate change in the future. “NoCC”: assuming present climate condition in the future.
Per capita calorie intake ◦ Income elasticity of food demand by regions and
commodities is calculated based on Bruinsma et al, (2010)
Bioenergy consumption ◦ A ratio of bioenergy consumption to the total
expenditure is assumed to be constant for the future
9
Calculate calorie intake from tonne-based consumption
Calculate population at the risk of hunger from calorie intake
10
Calculate calorie intake from tonne-based
Per-capita consumption
Per-capita calorie intake
Population at the risk of hunger
Calorie per 100 grammes
Relation between per-capita calorie intake and a ratio of population at the risk of hunger
Extraction ratio
y = 1,557.06973 e(0.00189)x
R² = 0.92883
0
20
40
60
80
100
0 1000 2000 3000 4000
飢餓リスク人口割合
(%)
kcal/person/day
Rate
of h
unge
r pop
ulat
ion
(%)
per-capita calorie intake
11
In industrial countries, production in SSP3 will be lowest among the SSP because population decreases in SSP3.
In developing countries, production in SSP3 will be highest among the SSPs as a result of higher population growth and lower income improvement.
Future low income improvement causes large per-capita consumption of crops rather than meat.
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4In
dust
rial
Tran
sitio
n
Deve
lopi
ng
Indu
stria
l
Tran
sitio
n
Deve
lopi
ng
Indu
stria
l
Tran
sitio
n
Deve
lopi
ng
Indu
stria
l
Tran
sitio
n
Deve
lopi
ng
Indu
stria
l
Tran
sitio
n
Deve
lopi
ng
Rice Wheat Cereal grains nec Sugar crops Oil crops
Prod
uctio
n [b
illio
n to
n]
2005
SSP1
SSP2
SSP3
Indu
stria
l
Tran
sitio
n
12
• Range: Uncertainty of multi-RCPs and multi-General Circulation Model (GCMs)
2,300
2,500
2,700
2,900
3,100
3,300
3,500
3,700
2005 2030 2050
Per-
capi
ta-c
alor
ie [k
cal/
pers
on/d
ay]
SSP3
SSP1
SSP2
Per-capita calorie intake has a large difference among the SSPs.
Socioeconomic condition is a large factor in food consumption.
NoCC
Median
A socioeconomic scenarios seems to be a strong factor in climate change impacts.
Even in RCP 2.6 where mitigation challenges will be high, climate change will impact food consumption.
In RCP 8.5, the calorie intake will be lower than RCP 2.6. Differences among RCPs are not as large as that among SSPs.
13
-3.5%
-3.0%
-2.5%
-2.0%
-1.5%
-1.0%
-0.5%
0.0%
RCP2
.6
RCP4
.5
RCP6
.0
RCP8
.5
RCP2
.6
RCP4
.5
RCP6
.0
RCP8
.5
RCP2
.6
RCP4
.5
RCP6
.0
RCP8
.5
SSP1 SSP2 SSP3
Chan
ge in
per
-cap
ita ca
lorie
inta
ke
[No
Clim
ate
Chan
ge=1
00]
High Low Median
In India, Rest of Asia and Rest of Africa, 2.2% to 10% lower calorie intake than NoCC
In India, 10% is a result of large climate change impacts and small amounts of extra arable land.
This situation causes greater land scarcity, higher crop prices and less food consumption.
14
▲ 12.0▲ 10.0▲ 8.0▲ 6.0▲ 4.0▲ 2.00.02.0
0500
100015002000250030003500400045005000
EU25
Oce
ania
Japa
nCa
nada
Uni
ted
Stat
esRe
st o
f Eur
ope
Turk
eyCh
ina
Indi
aBr
azil
Form
er S
ovie
t Uni
onSo
uthe
ast A
siaRe
st o
f Asia
Rest
of S
outh
Am
eric
aM
iddl
e Ea
stN
orth
Afr
ica
Rest
of A
fric
a
Chan
ge ra
tio in
cal
orie
inta
ke [%
](N
oCC=
100)
Per-
capi
ta c
alor
ie in
take
[k
cal/
day/
pear
son]
NoCC SSP3&RCP8.5
15
0.00.10.20.30.40.50.60.70.80.91.0
2005 2030 2050
Risk
of h
unge
r [bi
llion
peo
ple]
SSP3
SSP1SSP2
0.00.10.20.30.40.50.60.70.80.91.0
2005 2030 2050
Risk
of h
unge
r [bi
llion
peo
ple] SSP3
SSP1
SSP2
0.00.10.20.30.40.50.60.70.80.91.0
2005 2030 2050
Risk
of h
unge
r [bi
llion
peo
ple]
SSP3
SSP1
SSP2
DevelopingTransition
WorldSSP3 & RCP8.5 0.89 bil. people (0.86 to 0.94 bil. people)
NoCC
Future population at risk of hunger depends strongly on socioeconomic conditions.
Increase in SSP3&RCP8.5 is caused partially by a higher ratio of population at risk of hunger due to lower per-capita calorie intakes and population increase.
Range: Uncertainty of multi-RCPs & multi-GCMs
16
-1001020304050607080
0
50
100
150
200
250
300
350
Chin
a
Indi
a
Sout
heas
t Asia
Rest
of A
sia
Braz
il
Rest
of S
outh
Amer
ica
Form
er S
ovie
tU
nion
Mid
dle
East
Rest
of A
fric
a
Chan
ge in
pop
ulat
ion
at ri
sk o
f hun
ger
[%](N
oCC=
100)
Popu
latio
n at
risk
of h
unge
r [%
] (N
oCC=
100)
NoCC SSP3&RCP8.5
In India, Rest of Asia and Rest of Africa, the populations are expected to be larger by 120 mil., 16 mil. and 3 mil people than those of NoCC.
In contrast, in the Former Soviet Union, the population is less by 0.2 million people than those of NoCC.
Climate change impact on risk of hunger is different among regions because levels of calorie intakes and climate change impacts on crop yield vary region by region.
Change ratio
Which is stronger factor to risk of hunger, socioeconomic or climate conditions?
How much is the effect of adaptation measures?
17
Which is stronger factor to risk
SSP1 & SSP2 SSP3 With
adaptation in developing countries Without
adaptation in developing countries
Population & GDP
18
0.00.10.20.30.40.50.60.70.80.91.0
2005 2030 2050
Risk
of h
unge
r [bi
llion
peo
ple] SSP3
SSP1
SSP2
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
2005 2030 2050
Risk
of h
unge
r [bi
llion
peo
ple]
SSP3 without adaptationSSP3 with adaptationSSP2 without adaptationSSP2 with adaptationSSP1 without adaptationSSP1 with adaptationSSP1 with adaptation (median)SSP1 without adaptation (median)SSP2 with adaptation (median)SSP2 without adaptation (median)SSP3 with adaptation (median)SSP3 without adaptation (median)SSP1 (No climate change)SSP2 (No climate change)SSP3 (No climate change)
SSP3
SSP1
SSP2
Other adaptations such as irrigation implementation will be necessary to lower the increase in population at risk of hunger.
Range: Uncertainty of multi-RCPs & multi-GCMs
We analyzed climate change impacts on food consumption and population at risk of hunger using 3SSPs, 4RCPs & 12GCMs
Climate change impacts on food consumption and population at
risk of hunger depends more strongly on socioeconomic conditions rather than climate conditions
Even in the most optimistic scenarios: SSP1&RCP2.6, climate change is expected to make the impacts.
Levels of the impacts will vary in different countries and regions
Adaptation measures; changes in crop variety and planting dates do not contribute to lower risk of hunger, but contribute to narrow the range of future uncertainty of the risk caused by multi-GCMs.
To lower the increase in risk of hunger due to climate change, other resource-intensive adaptation such as irrigation and further utilization of fertilizer will be necessary.
19
We analyzed climate change impacts on food consumption and population at risk of We analyzed climate change impacts on food consumption and population at risk of We analyzed climate change impacts on food consumption and
hunger using 3SSPs, 4RCPs & 12GCMsWe analyzed climate change impacts on food consumption and
hunger using 3SSPs, 4RCPs & 12GCMsWe analyzed climate change impacts on food consumption and
20
21
0
5000
10000
15000
2005
2010
2015
2020
2025
2030
2035
2040
2045
2050
Mil
num
ber
World Population
SSP1
SSP2
SSP3
0
50000
100000
150000
200000
2005
2010
2015
2020
2025
2030
2035
2040
2045
2050
bil 2
005
US$
/yea
r
World GDP
SSP1
SSP2
SSP3