1. matthews@climate.bematthews@climate.be vanyp@climate.be jcm.chooseclimate.org UNFCCC Article 2 Article 6, Stabilisation scenarios under Uncertainty A web-based climate model for global dialogue Ghent 17Nov 2003 Ben Matthews matthews@climate.be Jean-Pascal van Ypersele vanyp@climate.be Institut dastronomie et de géophysique G. Lemaître, Université catholique de Louvain, Louvain-la-Neuve, Belgium Web: www.climate.be (UCL-ASTR) jcm.chooseclimate.org (interactive model) JCM also developed with: DEA-CCAT Copenhagen, UNEP-GRID Arendal, KUP Bern

2. matthews@climate.bematthews@climate.be vanyp@climate.be jcm.chooseclimate.org UN Framework Convention on Climate Change Ultimate objective (Article 2): '...stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system. Such a level should be achieved within a time frame sufficient - to allow ecosystems to adapt naturally to climate change, - to ensure that food production is not threatened and - to enable economic development to proceed in a sustainable manner.' (technologies, lifestyles, policy instruments) Emissions pathways (biogeochemical cycles) Critical Levels (global temperature / radiative forcing) Critical Limits (regional climate changes) Key Vulnerabilities (socioeconomic factors) inverse calculation

3. matthews@climate.bematthews@climate.be vanyp@climate.be jcm.chooseclimate.org Temperature and « reasons for concern » Source: IPCC WG2 (2001)

4. matthews@climate.bematthews@climate.be vanyp@climate.be jcm.chooseclimate.org European Union 2 °C limit: EU Council Of Ministers 1996: "...the Council believes that global average temperatures should not exceed 2 degrees Celsius above pre-industrial level and that therefore concentration levels lower than 550 ppm CO 2 should guide global limitation and reduction efforts." "This means that the concentrations of all GHGs should also be stabilised. This is likely to require a reduction of emissions of GHGs other than CO 2, in particular CH 4 and N 2 O" However, widely varying interpretations of implications for emissions! Why? Java Climate Model may help to investigate...

5. matthews@climate.bematthews@climate.be vanyp@climate.be jcm.chooseclimate.org Stabilisation scenarios in Java Climate Model (Article 2: critical limits => critical levels => emissions pathways) Inverse calculation to stabilise CO 2 concentration (as IPCC "S"/ WRE scenarios) Radiative Forcing (all-gases, "CO 2 equivalent") Global Temperature (e.g. to stay below 2C limit) (Sea-level -difficult due to inertia in ocean / ice) JCM Core science very similar to IPCC-TAR models, but (unlike TAR SYR) includes mitigation of all greenhouse gases and aerosols. Iterative method to find concentrations attaining specified forcing/temperature. Very fast response. Explore interactively by dragging target curve with mouse. Or systematically calculate probabilistic analysis...

6. 81 Carbon cycle variants 3* Land-use-change emissions (Houghton, scaled), 3* CO 2 fertilisation of photosynthesis ("beta"), 3* Temperature-soil respiration feedback ("q10"), 3* Ocean mixing rate (eddy diffusivity of Bern-Hilda model) 6 Ratios of emissions of different gases Emissions of all gases (including CH4, N2O, HFCs, Aerosol and Ozone precursors) reduced by same proportion as CO2 with respect to one of six SRES baseline scenarios note: atmospheric chemistry feedbacks included, but not varied 84 Forcing/Climate Model variants 3 * Solar variability radiative forcing 4* Sulphate aerosol radiative forcing 7* GCM parameterisations climate sensitivity, ocean mixing/upwelling, surface fluxes (W-R UDEB model tuned as IPCC TAR appx 9.1) note: for sea-level rise, should add uncertainty in Ice-melt parameters

7. matthews@climate.bematthews@climate.be vanyp@climate.be jcm.chooseclimate.org Relative probability of each set of parameters derived from inverse of "error" (model - data) Measured global temperatures (CRU + proxies) Measured CO 2 concentration (Mauna Loa + others) Reject low-probability variants (kept 468 / 6804) Ensures coherent combinations of parameters, e.g. : More sensitive climate models with higher sulphate forcing High historical landuse emissions with higher fertilisation factor Still 2808 curves per plot (including 6 SRES per set) So show 10% cumulative frequency bands (using probabilities) Probability from fit to historical data

8. Carbon Cycle Other gases/Aerosols Climate Model

9. Carbon Cycle Other gases/Aerosols Climate Model

10. matthews@climate.bematthews@climate.be vanyp@climate.be jcm.chooseclimate.org What CO 2 level stabilises T<= 2°C ? Range: 380 - 620ppm, Mean ~ 475ppm, Median ~ 450ppm. Over 90% of variants are below 550ppm so a 550ppm target has a high risk of exceeding 2°C If we want 90% of variants below 2C, the concentration should not exceed 400ppm ! note: 550ppm "CO 2 equivalent" (all gases) would bring us close to 2C. However, to keep the temperature level, total radiative forcing (and hence CO2 equivalent) must decline gradually. This is possible while CO2 remains level, due to declining CH4 and O3 (short lifetime gases).

11. matthews@climate.bematthews@climate.be vanyp@climate.be jcm.chooseclimate.org Shifting the Burden of Uncertainty On average, all sets of scenarios stabilise at the same temperature level of 2°C above preindustrial level. But their uncertainty ranges are very different! (note picture in abstract book) A Temperature limit rather than a Concentration limit reduces the uncertainty for Impacts/ Adaptation... (assuming we commit to adjust emissions to stay below the limit, as the science evolves)...however this increases the uncertainty regarding emissions Mitigation pathways. Which is better?

12. matthews@climate.bematthews@climate.be vanyp@climate.be jcm.chooseclimate.org If using costs to analyse choice of policy tool / regime, beware that... A target closer to emissions source (e.g. C-tax, intensity, etc) might reduce cost of uncertainty for mitigators, but increase it for those responding to climate impacts. The chain has two ends! Using cost analysis for quota-allocation creates an incentive to exploit scientific uncertainties, each party overstating its mitigation costs and understating its gain from avoided regional climate impacts. A good regime should encourage honesty in risk assessment! Including adaptation costs may help to balance this game?

13. matthews@climate.bematthews@climate.be vanyp@climate.be jcm.chooseclimate.org Role-play on Article 2 with students Louvain la Neuve, Belgium, Dec 2002, as if COP11, Moscow, Dec 2005 UNFCCC-style-process,17 teams of National + NGO delegates. Quantitative interpretation of Article 2: Temperature rise (<1.9°C 2100-1990) + Sea-level rise (46cm 2100-1990) Principles for Adaptation funds : Tax on emissions trading / JI (/CDM?)+ Percapita emissions & GDP formula Final compromise between Russia and Tuvalu (after US quit) Equity implications were key aspect of discussion Scientific inconsistency maybe realistic in policy compromises? Delegates used Java Climate Model to explore options / uncertainties. By selecting parameters / indicators, same model can "justify" diverse positions! Such "games" also help us to identify scientific issues. Reconciling multi-criteria climate targets, Conversion to CO 2 "equivalents" To be reenacted at COP9 Milano side-event Fri 12 Dec 1pm!

14. matthews@climate.bematthews@climate.be vanyp@climate.be jcm.chooseclimate.org Article 2 needs global dialogue (Art 6) Risk/Value Judgements (including equity implications) : Impacts: Key Vulnerabilities? Acceptable level of Change? Risk: Target Indicator? Acceptable Level of Certainty? (choice of target indicator shifts the burden of uncertainty) Such risk/value decisions cannot be made by scientific experts alone. The ultimate integrated assessment model remains the global network of human heads. To reach effective global agreements, we need an iterative global dialogue including citizens / stakeholders. The corrective feedback process is more important than the initial guess. So let's start this global debate!

15. matthews@climate.bematthews@climate.be vanyp@climate.be jcm.chooseclimate.org Try JCM at jcm.chooseclimate.org Works in web browser, Instantly responding graphics, Based on IPCC-TAR methods / data, Open-source, Labels in 10 languages, 50000 words documentation JCM also used for teaching in several countries: Univ Cath de Louvain (BE) Open University (UK), Univ Bern (CH), Univ Washington (CA),... Role-play "games" with students may be a useful way to experiment wth the dialogue process and identify related scientific questions. Longterm Vision: link such courses to make real global dialogue linking students around the world. Please join in! Experiment with Java Climate Model

19. matthews@climate.bematthews@climate.be vanyp@climate.be jcm.chooseclimate.org Use of Java Climate Model in Role- Play (Belgium, Denmark, Russia, USA, Australia, Saudi-Arabia, Venezuela, Brazil, Burkina-Faso, Marroco, Tuvalu, India, Greenpeace, GCC, FAO, WB/IMF, Empêcheurs) Delegates used JCM to explore options and uncertainties By selecting different parameters, same model can "justify" diverse positions, from India to Australia, Burkina Faso to Saudi Arabia. Such "games" also help us to identify key science /policy questions. areas of potential confusion - e.g. definition of CO 2 equivalents how to handle potentially inconsistent multi-criteria targets JCM also used for teaching in several countries: Open University (UK), Univ Bern (CH), Univ Washington (CA),... Longterm Vision: link such courses to experiment with real global dialogue between students around the world.

20. matthews@climate.bematthews@climate.be vanyp@climate.be jcm.chooseclimate.org Article 2 in IPCC AR4 IPCC Plenary decided «the scientific, technical, and socio-economic issues associated with Article 2» would be a cross-cutting theme in AR4. Scoping paper suggests steps: =>Assess Key Vulnerabilities using WEHAB framework =>Critical Limits (Thresholds) of climate parameters =>Critical Levels (e.g. Concentrations) =>Possible Emissions Pathways All steps within a Risk / Uncertainty framework

21. matthews@climate.bematthews@climate.be vanyp@climate.be jcm.chooseclimate.org Risk and Value Judgements The global dialogue needs a quantitative framework. In practice, this will revolve around simple indicators, e.g. Global annual average Temperature, CO 2 (equivalent?) concentration. Interface with computer models essential to consider complex interacting issues and feedback processes. The Java Climate Model (JCM) enables anybody to explore both policy options and scientific uncertainties, simply by dragging controls on plots in a web browser.

22. Caveats Climate Sensitivity not well constrained by historical temperatures. May be higher than TAR model range (and increasing at higher temperatures). Mitigation of other gases in proportion to CO 2 reduction (w.r.t. SRES) is a simplistic assumption. Better to have a socioeconomic/landuse model. Several uncertain factors not yet varied: Atmospheric chemistry, Ice-melting etc. Shape of land-use emissions curve influences terrestrial carbon-cycle balancing Regional seasonal changes can be very different from global average!

23. matthews@climate.bematthews@climate.be vanyp@climate.be jcm.chooseclimate.org Inertia in the climate system Stabilising CO2 alone doesn't stabilise temperature (as below from TARSYR Q6) However stable CO2 may correspond to stable Temperature if other gases with shorter lifetimes are also mitigated to a similar extent.