matthews@climate.be vanyp@climate.be jcm.chooseclimate.org

Stabilisation under uncertainty probabalistic & interactive exploration using

“Java Climate Model”ICTP Trieste 15/12/2003

Ben Matthews matthews@climate.be

with Jean-Pascal van Ypersele vanyp@climate.be

Institut d’astronomie et de géophysique G. Lemaître,Université catholique de Louvain, Louvain-la-Neuve,

Belgium

www.climate.be (UCL-ASTR)jcm.chooseclimate.org (interactive model)

JCM also developed with: DEA-CCAT Copenhagen, UNEP-GRID Arendal, KUP Bern

One tool for both research and training

Interactive Java Climate Model Fast efficient science models are needed both for interactive tool and for integrated assessment. But complexity of presentation differs.

Research applications:

Article 2- Stabilisation under uncertainty

Equity- Distribution of responsibility (BP) and impacts

Training applications:

Role-play negotiation with students in UCL

other universities, unep.net, ...

One tool for both research and training

Interactive Java Climate Model try JCM at jcm.chooseclimate.org

Works in web browser, very efficient/compact

Instantly responding graphics, Cause-effect from emissions to impacts,

Based on IPCC-TAR methods / data,

New flexible stabilisation scenarios

Regional distributions of responsibility and climate fields.

Transparent, open-source code, modular, scriptable,

Interface in 10 languages, 50000 words documentation

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)

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Temperature and « reasons for concern »

Source: IPCC WG2 (2001)

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 CO2 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 CO2, in particular CH4 and N2O"

However, widely varying interpretations of implications for emissions!

Why? Java Climate Model may help to investigate...

Stabilisation scenarios in Java Climate Model(Article 2: critical limits => critical levels => emissions pathways)

Inverse calculation to stabilise● CO2 concentration (as IPCC "S"/ WRE scenarios)

● Radiative Forcing (all-gases, "CO2 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) JCM stabilisation scenarios include mitigation of all greenhouse gases and aerosols, scaled w.r.t. SRES baseline.

Stabilisation scenarios in Java Climate ModelCO2 concentration scenario is a Padé polynomial(similar to formula of Enting et al 1994 for IPCC S/WRE)defined by:

2000 concentration c, gradient, dc/dt, and second derivative d2c/dt2 (ensures smooth emissions trajectory),and final concentration and gradient.

If stabilising radiative forcing or temperature (or...) iterate to find best concentration and gradient in stabilisation year. Also to define quadratic curve from then until 2300.

Iterates 1-10 times, depending on magnitude of change (reuse of correction factors so efficient for dragging control).

•Explore interactively by dragging target curve with mouse

•Or systematically calculate probabilistic analysis ...

81 Carbon cycle variants 3* Land-use-change emissions (Houghton, scaled),

3* CO2 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 gasesEmissions 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 variants3 * 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

Carbon Cycle Other gases/Aerosols

Climate Model

Shifting the Burden of UncertaintyOn 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?

Relative probability of each set of parameters derived from inverse of "error" (model - data)

Measured global temperatures (CRU + proxies)

Measured CO2 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

Carbon Cycle Other gases/Aerosols

Climate Model

What CO2 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 "CO2 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).

Inertia in the climate systemStabilising 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.

Interpretation of Article 2 needs a global dialogue (Article

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!

Role-play on Article 2 with students

Louvain la Neuve, Belgium, Dec 2002, as if COP11, 2005,

Presented at COP9 Milano, Dec 2003

60 university students grouped in 17 delegations (Belgium, Denmark, Russia, USA, Australia, Saudi-Arabia, Venezuela, Brazil,

Burkina-Faso, Marroco, Tuvalu, India, Greenpeace, GCC, FAO, WB/IMF, Empêcheurs)

had the task to agree by consensus in a UNFCCC-style process:

* a quantitative interpretation of Article 2, * an equitable formula for funding adaptation.

Delegates used Java Climate Model to explore options / uncertainties.

Can "justify" diverse positions by selecting parameters / indicators !

matthews@climate.be vanyp@climate.be jcm.chooseclimate.org

Conclusions of role-playEquity implications were key aspect of discussion

Final compromise between Russia and Tuvalu (after US quit)

• 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 + Percapita emissions & GDP formula + Principles sufficiency/capacity

Such "games" also help us to identify scientific issues, e.g.: Reconciling multi-criteria climate targets (inconsistency maybe realistic in policy compromises)Meaning of CO2 "equivalents" in stabilisation context

Future development for global dialogue

Could we combine such tools and experiences to link groups from all corners of the world?

JCM also used for teaching in several countries:Univ Cath de Louvain (BE) Open University (UK),

Univ Bern (CH), Univ Waterloo (CA),...

Such web models might provide a quantative framework for a global dialogue. Model can be

shared by saving snapshots of model parameters to pass to others in asynchronous discussion

forum.

matthews@climate.be vanyp@climate.be jcm.chooseclimate.org

Relevance to developing countries

Distribution / Equity issues - compare distribution of responsibility (Brazilian Proposal)

with distribution of regional impacts.Apply polluter pays principle to adaptation funds?

To interest people more, we should complete the circle from local mitigation actions to regional climate impacts

(all under uncertainty).Future JCM development, link DDC, GIS etc.

How to reflect the reality of complex climate change, in a fast interactive tool?

matthews@climate.be vanyp@climate.be jcm.chooseclimate.org

Experiment with Java Climate Model

Try JCM at jcm.chooseclimate.org

Trying to combine research and outreach

Works in web browser, Instantly responding graphics,

Based on IPCC-TAR methods / data, Open-source, Scriptable,

Labels in 10 languages, 50000 words documentation