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1 00/XXXX © Crown copyright Apportioning climate change indicators between regional emitters Jason Lowe and Geoff Jenkins Hadley Centre for Climate Prediction and Research 25 th September 2002
2 00/XXXX © Crown copyright What this talk is not about This talk is not about the HadCM3 validation data. Choice of this validation was arbitrary and other datasets are available. What this talk is about This talk is about the Hadley Centre contribution to this simple modelling exercise. Building our capacity in this area
3 00/XXXX © Crown copyright Contents Introduction and models Results of phase 1 Results of phase 2 Conclusions
4 00/XXXX © Crown copyright Estimating regional share CONCENTRATIONS FROM EACH REGION EMISSIONS FROM EACH REGION RADIATIVE FORCING FOR EACH REGION TEMPERATURE CHANGE FOR EACH REGION SHARE
5 00/XXXX © Crown copyright 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 CH 4 and N 2 O:- Single fixed lifetime for each gas, taken from TAR (page 244)
6 00/XXXX © Crown copyright Choice of model units (2) “Climate model”:- Impulse response function fitted to Hadley Centre 4xCO2 stabilisation 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.
7 00/XXXX © Crown copyright Extended model In order to achieve a better fit to the A2 CO 2 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 CO 2 and temperatures. Carbon cycle function =0.46(1+0.7(T/T max ) 2 )
8 00/XXXX © Crown copyright 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
9 00/XXXX © Crown copyright Contents Introduction and models Results of phase 1 Results of phase 2 Conclusions
10 00/XXXX © Crown copyright CDIAC (CO 2 ) – Basic model
11 00/XXXX © Crown copyright CDIAC – Extended model (feedback)
12 00/XXXX © Crown copyright Can we simulate B1 CO2 concentrations using a simple model? Input to HadCM3 is used as a comparison HadCM3 CO2 concentrations derived from Bern carbon cycle model. Pre-1990 values agree well with observations
13 00/XXXX © Crown copyright Can we simulate A1FI CO2 concentrations using a simple model? Input to HadCM3 is used as a comparison
14 00/XXXX © Crown copyright Can we simulate temperature rise using a simple model? HadCM3 simulation is used as a comparison
15 00/XXXX © Crown copyright Contents Introduction and models Results of phase 1 Results of phase 2 Conclusions
16 00/XXXX © Crown copyright Attribution methods 1. “All minus one” - Marginal 2. Differential Base case Simple linear version of model Edgar Hyde historic emissions + A2 future 1890 is start year for emissions
17 00/XXXX © Crown copyright Global temperature rise from regional emissions
18 00/XXXX © Crown copyright Regional share of temperature rise
19 00/XXXX © Crown copyright 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
20 00/XXXX © Crown copyright Regional share for various indicators
21 00/XXXX © Crown copyright Choice of indicator? Share estimated at year 2000
22 00/XXXX © Crown copyright Regional share of temperature rise for different emission start dates
23 00/XXXX © Crown copyright Are the results different for other scenarios? A2 A1FIB1
24 00/XXXX © Crown copyright Does the amount of carbon cycle fertilization affect the result? Bern high caseBern low case
25 00/XXXX © Crown copyright Does a slower climate response (only long time constant) affect the result? Slow climate model response
26 00/XXXX © Crown copyright Does using the extended model affect the apportionment calculation? Basic modelExtended model
27 00/XXXX © Crown copyright Does using the extended model affect the apportionment calculation? At year 2000At year 2100
28 00/XXXX © Crown copyright Comparing attribution methods All minus oneDifferential
29 00/XXXX © Crown copyright 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.
Prof. Dr. Olav Hohmeyer IPCC AR4 (2007) Results WG III Folie 1 A Short Overview of the IPCC Report on Climate Change Mitigation 2007 (WG III) Prof. Dr.
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