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MATCH paper 1: contributions to climate change SB-23 17 May 2006. Niklas Höhne. MATCH paper #1. Analysing countries’ contribution to climate change: Scientific uncertainties and methodological choices Michel den Elzen (RIVM, Netherlands) Jan Fuglestvedt (CICERO, Norway)

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Match paper 1 contributions to climate change sb 23 17 may 2006
MATCH paper 1: contributions to climate changeSB-23 17 May 2006

Niklas Höhne


Match paper 1
MATCH paper #1

Analysing countries’ contribution to climate change: Scientific uncertainties and methodological choices

  • Michel den Elzen (RIVM, Netherlands)

  • Jan Fuglestvedt (CICERO, Norway)

  • Niklas Höhne (Ecofys, Germany)

  • Cathy Trudinger (CSIRO, Australia)

  • Jason Lowe (Hadley, UK)

  • Ben Matthews (UCL, Belgium)

  • Bård Romstad (CICERO, Norway)

  • Christiano Pires de Campos (Brazil)

  • Natalia Andronova (UIUC, USA)

M. den Elzen, J. Fuglestvedt, N. Höhne, C. Trudinger, J. Lowe, B. Matthews, B. Romstad, C. Pires de Campos, N. Andronova, 2005: “Analysing countries’ contribution to climate change: Scientific uncertainties and methodological choices”, Environmental Science and Policy, 8 (2005) 614–636

Modelling and assessment of contributions to climate change


Cause effect chain
Cause-effect chain

Emissions

Region A

Emissions

Region B

Emissions

Region C

Emissions

Region D

Concentrations

Radiative forcing

Global average temperature change

Impact in

Region A

Impact in

Region B

Impact in

Region C

Impact in

Region D

Modelling and assessment of contributions to climate change


Attributed effects
Attributed effects

Temperature increase

Total temperature increase

Attributed temperature increase

Region A

Region B

Region C

Unattributed

Region D

Time

Attribution

start date,

e.g. 1900

Attribution period

Today


Choices
Choices

  • Policy choices (values can not be based on objective ‘scientific’ arguments) :

    • Indicator (e.g. temperature increase, radiative forcing, …)

    • Timeframes

    • Mixture of greenhouse gases

    • Attribution method

  • Scientific choices

    • Choice of the dataset on historical emissions

    • Choice of the representation of the climate system (different models)

Modelling and assessment of contributions to climate change


Main objective of paper 1
Main objective of paper #1

  • Summarise the studies and results so far (i.e. the contributions to the UNFCCC initiated process)

  • Present new attribution calculations with non-linear carbon cycle and climate models using non-linear attribution methodologies and updated historical emissions datasets

  • Investigate the effect of a range of scientific, methodological and policy-related choices on the attribution, but not the full range by all uncertainties.

Modelling and assessment of contributions to climate change


Models used
Models used

Modelling and assessment of contributions to climate change


Model show similar outcomes
Model show similar outcomes

Modelling and assessment of contributions to climate change


Models used1
Models used

Modelling and assessment of contributions to climate change


Model show similar outcomes1
Model show similar outcomes

Modelling and assessment of contributions to climate change


Policy choices
Policy choices

1. Indicator

2. Timeframes

3. Attribution method

4. Mixture of Greenhouse gases

Modelling and assessment of contributions to climate change


1 indicators
1. Indicators

Source: Ecofys-ACCC

Modelling and assessment of contributions to climate change


1 indicators1
1. Indicators

*: Also discounting most recent emissions

+: Can be made forward looking, when evaluating at a date after attributed emissions end. In such case also a time horizon is required

Modelling and assessment of contributions to climate change


1 indicators2
1. Indicators

Source: Ecofys-ACCC

Relative contributions using different indicators

Modelling and assessment of contributions to climate change


1 indicators3
1. Indicators

  • Conclusions

  • Two main factors:

    • Whether a source emitted ‘early’ versus ‘late’

    • The share of emissions of short-lived / long-lived gases.

  • Choosing the right indicator is ultimately a policy choice that also depends on the purpose of use of the results.

    • Temperate increase: use evaluation date after the attribution end date

    • ‘Backward discounting’ and ‘forward looking’: ‘weighted concentrations’ or ‘integrated temperatures’

    • Not ‘backward discounting’: GWP-weighted cumulative emissions could be an option, which is simple and approximately represents the integrated impact on temperature.

Modelling and assessment of contributions to climate change


2 timeframe
2.Timeframe

  • Start date emissions 1890, 1950 and 1990

  • End date emissions 1990, 2000, 2050 and 2100

  • Evaluation date of attribution 2000, 2050, 2100, 2500

Modelling and assessment of contributions to climate change


Start date
Start-date

  • Choosing a shorter time horizon (e.g. 1950 or 1990 instead of 1890) reduces the contributions of OECD90 countries ('early emitters') to temperature increase.

Source: RIVM-ACCC

Modelling and assessment of contributions to climate change


End date
End-date

  • A late end-date increases non-Annex-I contributions, because it gives more weight to their larger future emissions.

  • Impact of emissions scenarios (error bars)can be large

Source: RIVM-ACCC

Modelling and assessment of contributions to climate change


Evaluation date
Evaluation-date

  • A later evaluation-date raises OECD contributions due to: (1) their large share in historical CO2 emissions (long residence time) (2) and their small share of methane emissions (short residence time)

Source: RIVM-ACCC

Modelling and assessment of contributions to climate change


3 attribution methods
3.Attribution methods

  • Normalised marginal method - Attributes responsibility using total sensitivities determined "at the margin".

  • Residual (all-but-one) method - Attributes responsibility by leaving out the emissions of each region in turn.

  • Time-sliced - determines the effect of emissions from each time as if there were no subsequent emissions.

Modelling and assessment of contributions to climate change


3 attribution methods1
3.Attribution methods

  • The Residual method, although simple to implement and explain, can be rejected on scientific grounds (not additive).

  • The Normalised marginal and Time-sliced methods are harder to implement and explain. These methods differ in how they treat early vs. late emissions.

Modelling and assessment of contributions to climate change


3 attribution methods2
3.Attribution methods

  • The differences between methods are fairly small compared to the effects of many of the other choices already considered.

Source: CSIRO-SCM

Modelling and assessment of contributions to climate change


3 attribution methods3
3.Attribution methods

  • Differences between methods are greater for later evaluation date (2100)

  • In general, the results of the different methods vary most for regions with emissions that differ most from the average in terms of early versus late emissions, i.e. India and EU.

Source: CSIRO-SCM

Modelling and assessment of contributions to climate change


4 greenhouse gas mixture
4.Greenhouse gas mixture

Which gases are attributed to the regions?

  • Fossil CO2

  • All anthropogenic CO2

  • CO2, CH4, N2O

  • Kyoto basket (CO2, CH4, N2O, HFCs, PFCs, SF6)

  • Kyoto basket + more O3 precursors (NOx, CO and VOC)

Modelling and assessment of contributions to climate change


4 greenhouse gas mixture1
4.Greenhouse gas mixture

  • Two main effects i) Going from fossil fuel CO2 emissions only to total anthropogenic CO2 emissions, ii) Inclusion of CH4 and N2O.

Source: CICERO-SCM

Modelling and assessment of contributions to climate change


4 greenhouse gas mixture2
4.Greenhouse gas mixture

  • The effect is less pronounced on longer time scales (except for the shift from fossil CO2 to total CO2).

Source: CICERO-SCM

Modelling and assessment of contributions to climate change


Scientific uncertainties
Scientific uncertainties

  • Choice of the dataset on historical emissions

  • Choice of the representation of the climate system: carbon cycle and climate model and feedbacks

Modelling and assessment of contributions to climate change


1 historical datasets
1.Historical datasets

  • Fossil CO2 emissions: small differences in relative attribution

  • CO2 emissions from land-use changes: differences in estimates leading to large differences. Data sets need to be compared and improved.

  • CH4 and N2O: Only one dataset is available (EDGAR)

  • IVIG Dataset estimate is outside IPCC range; almost zero for DCs in 1980s!

Source: RIVM-ACCC

Modelling and assessment of contributions to climate change


2 other scientific uncertainties
2.Other scientific uncertainties

  • The influence of other climate model parameters (e.g. IRFs), based on simulation experiments with nine GCMs and climate models is limited

Source: RIVM-ACCC

Modelling and assessment of contributions to climate change


2 other scientific uncertainties1
2.Other scientific uncertainties

Source: UCL-SCM

Modelling and assessment of contributions to climate change


Overall conclusions
Overall conclusions

  • Policy choices (values can not be based on objective ‘scientific’ arguments) :

    • Indicator important

    • Timeframes important

    • Mixture of GHG important

    • Attribution method less important

  • Scientific choices

    • Choice of the dataset on historical emissions

      important

    • Choice of the representation of the climate system (different models) less important

      for relative contr.

Modelling and assessment of contributions to climate change


Overall conclusions1
Overall conclusions

  • First summary of the work undertaken so to date

  • Not a full assessment of the uncertainty range, but an evaluation of the influence of different policy-related and scientific choices

  • The influence of scientific choices is notable. Therefore research is ongoing (see paper #2)

  • However, the current work suggests, that the impact of policy choices, such as time horizon of emissions, climate change indicator and greenhouse-gas mix is larger than the impact of scientific uncertainties

  • Impact of uncertainties on the relative contributions is smaller than impact of uncertainties on the absolute changes in temperature.

  • Research needs: Historical emission datasets

Modelling and assessment of contributions to climate change



Policy choices1
Policy choices

Modelling and assessment of contributions to climate change


Models are calibrated
Models are calibrated

Modelling and assessment of contributions to climate change



Contribution to radiative forcing
Contribution to radiative forcing

Modelling and assessment of contributions to climate change


Aerosol forcing
Aerosol forcing

  • Inclusion of SO2 emissions reduces the contributions from ASIA and REF, but the effect disappear when there is a gap between attribution end date and evaluation date.

  • Again effect is less less pronounced on longer time scales

Source: CICERO-SCM

Modelling and assessment of contributions to climate change


Overall conclusions2
Overall conclusions

Modelling and assessment of contributions to climate change