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Apportioning climate change indicators between regional
emitters
Jason Lowe and Geoff Jenkins
Hadley Centre for Climate Prediction and Research
25th September 2002
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What this talk is not about
This talk is not about the HadCM3 validationdata. Choice of this validation was arbitrary andother datasets are available.
What this talk is aboutThis talk is about the Hadley Centre contributionto this simple modelling exercise.
Building our capacity in this area
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Contents
Introduction and models Results of phase 1 Results of phase 2 Conclusions
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Estimating regional share
CONCENTRATIONS FROM EACH REGION
EMISSIONS FROM EACH REGION
RADIATIVE FORCING FOR EACH REGION
TEMPERATURE CHANGE FOR EACH REGION
SHARE
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Choice of model units (1)Input data:-Linearly interpolated between values
Carbon cycle model:-Impulse response function fitted to Bern model
Default case uses the SAR standard parameters
CH4 and N2O:-Single fixed lifetime for each gas, taken from TAR (page 244)
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Choice of model units (2)“Climate model”:-Impulse response function fitted to Hadley Centre 4xCO2stabilisation experiment.
The forcing caused by a doubling of CO2 quoted in the IPCC TAR (page 358) is 3.71 Wm-2.
Forcing expressed as a multiple of the 4xCO2 forcing.
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Extended model
In order to achieve a better fit to the A2 CO2 and temperature
predicted by more complex models the forcing and emissions were modified by temperature dependent functions.
The form of these functions was chosen arbitrarily. An iterative
calculation was used to calculate the CO2 and temperatures.
Carbon cycle function
=0.46(1+0.7(T/Tmax)2)
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Choices and uncertainties
Start year End year for emissions End year for calculation Emissions scenario Attribution method Choice of species Size of regional groupings
Gas cycle parameters Climate model Feedback Emissions scenario Attribution method Choice of species Aerosols and other forcing Choice of historical
emissions Size of regional groupings
ScientificPolicy options
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Contents
Introduction and models Results of phase 1 Results of phase 2 Conclusions
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CDIAC (CO2) – Basic model
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CDIAC – Extended model (feedback)
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Can we simulate B1 CO2 concentrations using a simple
model? Input to HadCM3 is used as a comparison
B1 CO2 Concentrations
0
200
400
600
800
1000
1890 1950 2000 2050 2100
HadCM3
nofeedback
feedback
HadCM3 CO2 concentrations derived from Bern carbon cycle model.
Pre-1990 values agree well with observations
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Can we simulate A1FI CO2 concentrations using a simple
model?Input to HadCM3 is used as a comparison
A1fi CO2 Concentrations
0
200
400
600
800
1000
1890 1950 2000 2050 2100
HadCM3
nofeedback
feedback
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Can we simulate temperature rise using a simple model?
HadCM3 simulation is used as a comparison
A2
Had
CM
3
A2
nofe
edba
ck
A2
feed
back
A1f
i Had
CM
3
A1f
i nof
eedb
ack
A1f
i fee
dbac
k
B2
Had
CM
3
B2
nofe
edba
ck
B2
feed
back
B1
Had
CM
3
B1
nofe
edba
ck
B1
feed
back
00.5
11.5
22.5
33.5
44.5
5
Temperature rise from 1890
1990 2100
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Contents
Introduction and models Results of phase 1 Results of phase 2 Conclusions
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Attribution methods1. “All minus one” - Marginal2. Differential
Base case Simple linear version of model Edgar Hyde historic emissions + A2
future 1890 is start year for emissions
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Global temperature rise from regional emissions
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Regional share of temperature rise
0
0.1
0.2
0.3
0.4
0.5
0.6
OECD REF ASIA ALM
2000
2100
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Sensitivity Studies Choice of indicator Effect of different emissions start years Effect of different emissions scenarios Effect of different climate and carbon cycle
parameters Effect of including a temperature feedback Effect of different attribution methods
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Regional share for various indicators
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Choice of indicator?
0
0.1
0.2
0.3
0.4
0.5
0.6
OECD REF ASIA ALM
Emit
Total Emit
Conc
Force
Temp
Share estimated at year 2000
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Regional share of temperature rise for different emission start
dates
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Are the results different for other scenarios?
A2
A1FI B1
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Does the amount of carbon cycle fertilization affect the
result?
Bern high caseBern low case
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Does a slower climate response (only long time constant) affect the result?
Slow climate model response
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Does using the extended model affect the apportionment
calculation?
Basic model Extended model
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Does using the extended model affect the apportionment
calculation?
0
0.1
0.2
0.3
0.4
0.5
0.6
OECD REF ASIA ALM
No feedback
Feedback
At year 2000
0
0.1
0.2
0.3
0.4
0.5
0.6
OECD REF ASIA ALM
No feedback
Feedback
At year 2100
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Comparing attribution methods
All minus oneDifferential
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Conclusions The apportionment calculation has been carried out with a number of
greenhouse gases and for a range of future emissions scenarios.
Using a more elaborate model (which includes temperature feedback) improves the simulation of gas concentrations and temperature. There is also an effect on the apportionment calculation.
If the share is not evaluated until the end of the period (2100), the results vary with emissions scenario. If the share is evaluated earlier the difference between scenarios is smaller.
Not including emissions before 1950 or 1990 tends to reduce the share of earlier emitters (e.g. OECD).
A shorter atmospheric carbon lifetime or a slower climate response can both modify the attribution results.