jcm.chooseclimate.org Stabilisation under uncertainty probabalistic & interactive exploration using.

Slides:



Advertisements
Similar presentations
jcm.chooseclimate.org UNFCCC Article 2 Article 6, A web-based climate model for global dialogue.
Advertisements

Quantifying future emission paths: What is needed from whom to keep stabilization in reach 18 October 2005 Niklas Höhne, ECOFYS Cologne,
jcm.chooseclimate.org Stabilisation under uncertainty probabalistic & interactive exploration of.
jcm.chooseclimate.org UNFCCC Article 2 Article 6, Stabilisation scenarios under Uncertainty A web-based.
Connecting Science & Policy, from Emissions to Impacts Dr Ben Matthews Currently at: Klima & UmweltPhysik, Univ Bern DEA-CCAT /Energimiljoradet.
Presentation at GRID/GVU Arendal 11 Jun 2007 CONNECTING GLOBAL CLIMATE SCIENCE, POLICY, TEACHING AND OUTREACH WITH AN INTERACTIVE JAVA MODEL IN CONTEXT.
The innovation challenge STAKEHOLDER CONFERENCE "Post-2012 climate policy for the EU" 22 NOVEMBER 2004 Niklas Höhne ECOFYS Cologne,
1 Background EEA A European Union institution Established by EU Regulation Staff: about 80 Budget: 22 Meuro Copenhagen EEA home page:
1 Achieving the 2ºC target in the Copenhagen Accord: an assessment using a global model E3MG Terry Barker Presentation to the Institute for Sustainable.
Stabilisation of GHG concentrations in the atmosphere Findings of the IPCC Bert Metz co-chairman IPCC Working Group III INTERGOVERNMENTAL PANEL ON CLIMATE.
Atmospheric Research Using Risk Assessment to Inform Adaptation Roger N. Jones In-session Workshop on Impacts Of, and Vulnerability and Adaptation To,
1 Climate change impacts and adaptation: An international perspective Chris Field Carnegie Institution: Department of Global Ecology
Scientific aspects of UNFCCC Article 2, Stabilisation scenarios, and Uncertainty. Ben Matthews Jean-Pascal van Ypersele
Factors to be considered in choosing metrics Shengmin Yu Energy Research Institute of NDRC, China Bonn, April 2012 Workshop on common metrics to calculate.
Avoiding „Dangerous“ Climate Change Jennifer L. Morgan April 24, 2006.
Master Narratives & Global Climate Change Charlie Vars Dave Bella Court Smith IPCC January 29, 2013.
IPCC Synthesis Report Part IV Costs of mitigation measures Jayant Sathaye.
1/18 Long-term Scenarios for Climate Change-Implications for Energy, GHG Emissions and Air Quality Shilpa Rao, International Institute of Applied Systems.
Factors Shaping Long- Term Future Global Energy Demand and Carbon Emissions 7 th International Carbon Dioxide Conference September 25-30, 2005 Jae Edmonds,
RIVM (the Netherlands) and ETH (Switzerland) 1 Emission implications of long-term climate targets - a work-in-progress report - Michel den Elzen (RIVM,
Future climate (Ch. 19) 1. Enhanced Greenhouse Effect 2. CO 2 sensitivity 3. Projected CO 2 emissions 4. Projected CO 2 atmosphere concentrations 5. What.
Understanding the relevance of climate model simulations to informing policy: An example of the application of MAGICC to greenhouse gas mitigation policy.
The Role of Aerosols in Climate Change Eleanor J. Highwood Department of Meteorology, With thanks to all the IPCC scientists, Keith Shine (Reading) and.
IPCC Synthesis Report Part I Overview How to address the issue of “dangerous anthropogenic perturbation” to the climate system The relationship between.
Sciencephotolibrary. UNFCCC COP and MOP outcomes – a brief history and current status Parliament 27 th October 2011 Dr Guy Midgley Chief Director South.
Anthropogenic Climate Change The Greenhouse Effect that warms the surface of the Earth occurs because of a few minor constituents of the atmosphere.
Climate change risk in an unknowable future Ed Mathez American Museum of Natural History 18 November 2011.
Does Shale Gas have a role in Annex 1 climate change commitments? Prof Kevin Anderson and Dr John Broderick Tyndall Manchester.
Title written in CAPITAL letters, broken into 2 lines, if it fits with the length of the words Optional: Cover this area with photo. Proportions are approx.
Climate Change: Responses By Bangladesh Centre for Advanced Studies (BCAS), Dhaka, Bangladesh 8-9 April 2008 Dhaka.
Climate Change Curriculum: UPM Experiences
Working with Uncertainty Population, technology, production, consumption Emissions Atmospheric concentrations Radiative forcing Socio-economic impacts.
Prof. Dr. Olav Hohmeyer PIARC XXIII World Road Congress Folie 1 Latest Results on Climate Change and Implications for Road Transport Prof. Dr. Olav Hohmeyer.
We are now acting because the risks of inaction would be far greater. G.W. Bush’s Speech on Iraq March To me the question of the environment is.
Greenhouse Effect and Global Warming Greenhouse Effect Key Factors Earth-Sun Temperature Differences Greenhouse Gas Concentrations The atmosphere is.
Climate and Energy Webinar Series February 18, 2010 Welcome to: A Climate Modeling Tutorial Cindy Shellito University of Northern Colorado.
June 2011 The UNEP Java Climate Model Cindy Shellito University of Northern Colorado.
Global Climate Alteration: A Survey of the Science and Policy Implications D. Warner North (presenter), replacing Stephen H. Schneider, Stanford University,
Contact info: Jean-Pascal van Ypersele Ben Matthews Institut d'astronomie et de géophysique.
Projecting changes in climate and sea level Thomas Stocker Climate and Environmental Physics, Physics Institute, University of Bern Jonathan Gregory Walker.
University of Oxfordtrillionthtonne.org Uncertainty in climate science: opportunities for reframing the debate Myles Allen Department of Physics, University.
The Velocity of Climate Change: 2011 Chris Field Carnegie Institution: Department of Global Ecology
INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE (IPCC) Working Group I Working Group I Contribution to the IPCC Fourth Assessment Report Climate Change 2007:
JTH COP6bis/SBSTA Briefing on WGI contribution Bonn: Tuesday 17 July 2001 The Scientific Basis Sir John Houghton Overview of WGI findings,
Directorate General for Energy and Transport Advanced fossil fuel boiler technologies for reaching the goals of the Kyoto protocol OPET-Seminar Celje,
Role of Integrated Assessment Modelling (IAM) in climate change policy analysis The Global Integrated Assessment Model (GIAM) An ABARE-CSIRO joint initiative.
COP9 Side-Event Linking Article 2 & Article 6 Experiences from a role-play of future climate negotiations with students from UCL Belgium, using the interactive.
The IPCC’s SRES scenarios EmissionsNarratives Concentrations Climate changeImpacts.
Overview on CDM By Ann Gordon Ministry of Natural Resources and the Environment 14 th July 2011.
jcm.chooseclimate.org UNFCCC Article 2, Stabilisation and Uncertainty probabalistic & interactive.
Long-term Greenhouse Gas Stabilization and the Risks of Dangerous Impacts M. Webster, C.E. Forest, H. Jacoby, S. Paltsev, J. Parsons, R. Prinn, J. Reilly,
Newton Paciornik BRAZIL Policy Goals and Common Metrics Implications Bonn, 04 April 2012 Workshop on common metrics to calculate the CO 2 equivalence of.
Prof. Gerbrand Komen (ex-) Director Climate Research KNMI 20 November 2008 KNGMG Conference Climate change facts - uncertainties - myths.
The international community’s response to climate change Halldor Thorgeirsson Deputy Executive Secretary UNFCCC.
The Tyndall Centre comprises nine UK research institutions. It is funded by three Research Councils - NERC, EPSRC and ESRC – and receives additional support.
Integrated Assessment and IPCC: Links between climate change and sub-global environmental issues presentation at Task Force Integrated Assessment Modelling,
© Crown copyright Met Office Uncertainties in the Development of Climate Scenarios Climate Data Analysis for Crop Modelling workshop Kasetsart University,
Energy and sustainable development Climate Stabilisation and RES Perspectives in Energy Scenarios Francesco Gracceva.
1 MET 112 Global Climate Change MET 112 Global Climate Change - Lecture 12 Future Predictions Eugene Cordero San Jose State University Outline  Scenarios.
CLIMATE CHANGE PROJECTIONS: SOURCES AND MAGNITUDES OF UNCERTAINTY Tom Wigley, National Center for Atmospheric Research, Boulder, CO 80307, USA
1 UIUC ATMOS 397G Biogeochemical Cycles and Global Change Lecture 25: Climate, Energy and Carbon Sequestration Don Wuebbles Department of Atmospheric Sciences.
The Paris Climate Change Agreement: game changer or more hot air? John Lanchbery.
Climate Change Mitigation and Complexity Agus P Sari Country Director, Indonesia EcoSecurities.
Schematic framework of anthropogenic climate change drivers, impacts and responses to climate change, and their linkages (IPCC, 2007).
TRENDS, IMPLICATIONS AND POLICY RESPONSES 1 Climate Change.
Anthropogenic Radiative Forcing. Global Mean Surface Air Temperature.
Where is the climate heading after COP21? Andrew Levan Physics.
Presentation IVIG 21 June 2011
Model Summary Fred Lauer
Presentation transcript:

jcm.chooseclimate.org Stabilisation under uncertainty probabalistic & interactive exploration using Java Climate Model ICTP Trieste 15/12/2003 Ben Matthews with Jean-Pascal van Ypersele Institut dastronomie et de géophysique G. Lemaître, Université catholique de Louvain, Louvain-la-Neuve, Belgium (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, 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) inverse calculation

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 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...

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) JCM stabilisation scenarios include mitigation of all greenhouse gases and aerosols, scaled w.r.t. SRES baseline.

Stabilisation scenarios in Java Climate Model CO2 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 d 2 c/dt 2 (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 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* 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

Carbon Cycle Other gases/Aerosols Climate Model

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?

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

Carbon Cycle Other gases/Aerosols Climate Model

What CO 2 level stabilises T<= 2°C ? Range: ppm, 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).

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.

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 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 !

jcm.chooseclimate.org Conclusions of role-play Equity 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 ) + Sea-level rise (46cm ) 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 CO 2 "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.

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?

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, words documentation