The “Pangaea” Simulator -- An Decision-Maker-Oriented International Climate Simulator Drew Jones Sustainability Institute Working with Ventana Systems and MIT System Dynamics Group September 2008

Simulation Creation Team Lead Modeler Dr. Tom Fiddaman, Ventana Systems http://www.metasd.com/index.html Modeling, Framing, and Presentation Design Andrew Jones, Sustainability Institute http://www.sustainabilityinstitute.org/ apjones@sustainer.org Dr. Lori Siegel, contractor to SI Modeling and Framing Dr. John Sterman, MIT http://web.mit.edu/jsterman/www/

“Climate Interactive” is a growing coalition of business, academic, & nonprofit organizations Creating a portfolio of fast, accessible, robust, transparent simulations to help address climate change

Climate Interactive Senior Team Members Dr. John Sterman, MIT Sloan School of Management Director, System Dynamics Group Author, Business Dynamics: Systems Thinking and Modeling for a Complex World Dr. Peter Senge, MIT Senior Lecturer, Sloan School of Management Founding Chairman, Society for Organizational Learning Author, The Fifth Discipline Dr. Michelle Erickson, Citigroup Director, Sustainable Information Technology Program Dr. Bill Moomaw, The Fletcher School, Tufts University Director of the Center for International Environment & Resource Policy Lead author, Intergovernmental Panel on Climate Change 2003 (IPCC)

Purpose of Simulator is to Help Decision Makers Understand Dynamics of Climate Mitigation Inputs Outputs Fossil fuel emissions by countries or “economy group” Land use emissions Additional sequestration from aforestation Other greenhouse gas emissions CO2 in the atmosphere Global temperature Total emissions Total removals to oceans, biomass etc. Sea level rise Emissions from Developed Major Economies And Developing Major Economies One goal And Non-Major Economies CO2 in the atmosphere

Simulator Helps Users Conduct Customized Tests: What If…..? (all graphs fossil fuel emissions) Business as usual All reduced 80% by 2050? Or by 2030? Developed Developing Non Major Some by 2030 and others 2060? Developed acts but undeveloped doesn’t? Starting in 2018?

What Would Be the Effect on CO2 Concentrations in the Atmosphere Over Time?

(fossil fuel emissions) What Would Total Emissions Looks Like, Divided by Economy Group, since 1900? (fossil fuel emissions) NonME Developing Developed MEs

How About for Specific Countries? (fossil fuel emissions) India China Japan Russia EU US

Or Cumulative Fossil Fuel Emissions? India China Japan Russia EU US

Or Global Temperature?

What If We Boost Removals With Sequestration Through Aforestation? C O 2 i n t h e A t m o s p h e r e S o u r c e s o f T o t a l R e m o v a l s 8 6 B 4 . 4 7 5 B 7 TonC/year oceans 2 . 9 5 B 6 seq. ppm 1 . 4 2 5 B 5 Goal biomass - 1 M 1 9 1 9 3 1 9 6 1 9 9 2 2 2 5 2 8 4 T i m e ( y e a r ) 3 2 2 2 2 4 2 6 2 8 2 1 Results with 80% reduction in fossil fuel emissions plus 1.6 GTC/year in additional sequestration by 2050

Users Move Sliders to Select “What If” Experiments Using the Prototype Control Panel

Historical Fit Results

Exploring Implications of Uncertainty in Parameters Through Sensitivity Testing

Overview of Model Structure Specific country emissions Developing major economies Other GHGs Specific country emissions Total fossil fuel CO2 emissions Developed major economies Carbon cycle Climate Temp GHGs in atm Specific country emissions Land use CO2 emissions Non major economies CO2 Sequestration Changes to: Aforestation Deforestation Forests 16

The Core of the Carbon Cycle Sector (7 layers) (7 layers)

The Core of the Climate Sector

We Use Metaphors to Help Explain Model Behavior: Think of CO2 in the Atmosphere as a Bathtub The tub is filled by emissions and drained by net removals into oceans and biomass. The inflow is roughly double the outflow Emissions CO2 in the atmosphere Net Removals The “flat path” caps emissions above removals. More is still flowing into the bathtub than is flowing out. So the level of water in the bathtub continues to rise.

For Example: 80% Reduction Brings Emissions Down to Meet Removals 2 4 B Emissions CO2 in the atmosphere 1 8 B TonC/year 1 2 B Emissions 6 B Net Removals Net Removals 2 2 2 2 4 2 6 2 8 2 1 So levels of CO2 in the atmosphere stabilize.

Our Simulator Use Philosophy Runs fast for high-iteration model testing Model simulates 500 years in less than .1 second Allows for practical analysis in areas such as uncertainty, trade-offs, optimization, and robustness Hands-on use by policy-makers Simulators designed to be used easily on a laptop by non-modelers Transparency We share model equations No black box models Understanding causes of dynamics We take the time to ensure users understand why the model is doing what it is doing. We don’t say, “because the model says so”.

Simulator to Benefit From and Supplement Other Models Pangaea uses data, structure and insights from other, larger, more disaggregated and detailed models EG, the Integrated Assessment Models (IAMs) Nations model generates internally consistent scenarios that could be tested and refined and verified in larger models Our purpose is to create a small model and make it useful to policy setting and learning about complex dynamics

Sources of Structure and Data Carbon Cycle and Temperature Bolin, B. 1986. Fiddaman. T.S. 1997. Nordhaus, W. D. 1992, 1994, 2000 Goudriaan, J. and P. Ketner. 1984. Oeschger, H., U. Siegenthaler, et al. 1975. Rotmans, J. 1990. Schwartz, S.E. 2007. Schneider, S.H., and S.L. Thompson. 1981. Socolow, R.H. And S.H. Lam. 2007. Wullschleger, S. D., W. M. Post, et al. 1995. Sea Level Rise Rahmstorf, S. 2007.

Sources of Historical Data Historical FF CO2 Carbon Dioxide Information Analysis Center. http://cdiac.ornl.gov/ftp/ndp030/CSV-FILES/ Historical Population Carbon Dioxide Information Analysis Center. Calculated by dividing FF emissions by FF emissions per capita Historical GDP Department of Energy’s Energy Information Administration. http://www.eia.doe.gov/pub/international/iealf/tableh1cco2.xls. Historical CO2 atmospheric concentrations Mauna Loa – National Oceanic & Atmospheric Administration http://www.esrl.noaa.gov/gmd/ccgg/trends/ Siple Ice - Carbon Dioxide Information Analysis Center. 1994. Historical CO2 Record from the Siple Station Ice Core http://cdiac.ESD.ORNL.GOV/trends/co2/siple.htm Historical Temperature Changes HADCRUT3, Hadley Centre of the UK Met Office. National Climatic Data Center, NCDC. CFC Forcing Goddard Institute for Space Studies (GISS). http://data.giss.nasa.gov/modelforce/ghgases/ Other Forcings GISS. http://data.giss.nasa.gov/modelforce/

Sources of Projected Data Projected FF CO2 emissions, atmospheric concentrations, and temperature BAU: US MiniCAM EMF Standard Reference Europe AIM96 Standard Reference China MiniCAM EMF Standard Reference India MERGE 3.0 Ref World MiniCAM EMF14 Standard Reference World CETA EMF14 Standard Reference World AIM EMF14 Standard Reference World ASF SRES A1 Scenario Reduction: World MiniCAM EMF14 Accelerated Technology World CETA EMF14 Accelerated Technology Projected N2O and CH4 atmospheric concentrations IPCC Third Assessment Report. 2001. Chapter 6. Radiative Forcing of Climate Change. P.358.

We Have Calibrated Our Future Global Fossil Fuel Emissions to Track MiniCAM Most Closely tonsC/year 20 B 10 B 1990 2010 2030 2050 2070 2090 Time (year) World CO2 FF emissions : BAU MiniCAM EMF14 Standard Reference CETA EMF14 Standard Reference AIM96 Standard Standard Reference ASF SRES A1 Data

We Have Calibrated Our Country-Level Fossil Fuel Emissions to Track MiniCAM, AIM, and MERGE US Emissions Calibration 4 B 3 B 2 B 1 B 1990 2010 2030 2050 2070 2090 Time (year) tonsC/year CO2 FF emissions[US] : BAU USA MiniCAM EMF Stnd Ref US Emissions AIM EMF16 Mod Ref EU Emissions Calibration 4 B 3 B 2 B 1 B 1990 2010 2030 2050 2070 2090 Time (year) tonsC/year CO2 FF emissions[EU] : BAU EU Emissions AIM EMF16 Mod Ref China Emissions Calibration 8 B 6 B 4 B 2 B 1990 2010 2030 2050 2070 2090 Time (year) tonsC/year CO2 FF emissions[China] : BAU China MiniCAM EMF Stnd Ref China AIM96 Standard Scenario India Emissions Calibration 4 B 3 B 2 B 1 B 1990 2010 2030 2050 2070 2090 Time (year) tonsC/year CO2 FF emissions[India] : BAU India MERGE3 Ref

We Compared Our Model’s Business as Usual Scenario for CO2 Concentrations to Other Models IPCC CO2 Atm Conc Models vs Nations Model 1,000 750 ppm 500 250 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Time (year) ppm CO2 in Atmosphere : BAU MiniCAM Stnd Ref CETA EMF14 Stnd Ref RICE EMF14

Result when our carbon cycle is fed by MiniCAM’s emissions We Compared Our Model’s Response to the MiniCAM Business as Usual Fossil Fuel Emissions Scenario CO2 concentration in the atmosphere Result when our carbon cycle is fed by MiniCAM’s emissions 800 400 ppm 1990 2010 2030 2050 2070 2090 Time (year) Our Model MiniCAM

Result when our carbon cycle is fed by MiniCAM’s emissions We Compared Our Model’s Response to the MiniCAM “Accelerated Tech” Reduction Fossil Fuel Emissions Scenario CO2 concentration in the atmosphere 600 Result when our carbon cycle is fed by MiniCAM’s emissions 400 ppm 200 1990 2020 2050 2080 Time (year) Our Model MiniCAM

We Plan to Post the Sim Online for Global Use

More information Models on which the model that created these runs were based http://www.metasd.com/models/index.html#Climate Interactive version covering some of these ideas http://www.seed.slb.com/en/scictr/watch/climate_change/challenge.htm http://www.sustainabilityinstitute.org/tools_resources/climatebathtubsim.html http://web.mit.edu/jsterman/www/GHG.html Video version http://video.google.com/videoplay?docid=8235725143334110601&pr=goog-sl Other related simulations http://www.sustainabilityinstitute.org/climate_change/simulations.html \ Project blog http://climateinteractive.wordpress.com/ For an interactive, online demonstration, contact apjones@sustainer.org