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In the Collaboratorium, C-LEARN is the primary climate model. It takes greenhouse Greenhouse gas emission and deforestation/aforestation targets as inputs and provides outputs such as are its primary inputs. Its primary outputs are atmospheric concentrations of carbon dioxide (CO2) and increase in global mean temperature (GMT).
This writeup about C-LEARN contains three primary sections
- C-LEARN overview
High level description of the model, information about its creators and their institutional affiliation, the model's history and how it can be accessed, documentation and key publications. - C-LEARN attributes
The model's geographic scope and resolution; its start date, end date, and time step; its data sources; its approach for dealing with uncertainty; and its overall structure. - C-LEARN modules
Brief sections on descriptions of C-LEARN's six sub-models:- Regional CO2 emissions
- Other greenhouse gasses (CH4 and N2O)
- Land use
- Carbon cycle
- Global Average Surface Temperature
- Sea level rise
Overview
Name C-LEARN
Brief description C-LEARN is a simplified, Web-accessible version of the Climate Rapid Overview and Decision Support Simulator (CROADS), which is designed for use by policy makers to enable real time assessment of proposals under consideration as a part of the United Nations Framework Convention on Climate Change (UNFCCC) process.
Model developer(s) Tom Fiddaman, Lori S. Siegel, Elizabeth Sawin, Andrew P. Jones, John Sterman
Institutional affiliation of developer(s) Sustainability Institute, Ventana Systems, and System Dynamics Group, MIT Sloan School of Management
Date created 2008
Date of most recent revision 2009
Model accessibility C-LEARN is available on the Web at http://forio.com/simulation/climate-development/index.htm. C-ROADS can be run on a personal computer using VenSim, a simulation application developed by Ventana Systems. At present the C-ROADS model is used solely in workshops and events moderated by members of the Climate Interactive team.
Documentation Tom Fiddaman, Lori S. Siegel, Elizabeth Sawin, Andrew P. Jones, and John Sterman. C-ROADS Simulator Reference Guide. January, 2009.
Key publications Robert Watson, Eric Beinhocker, Bert de Vries, Klaus Hasselmann, David Lane, Jorgen Randers, Stephen Schneider. Summary Statement from the C‐ROADS Scientific Review Panel. February 2009 (see here for a brief description of the scientific review process and its findings).
Elizabeth R. Sawin, Andrew P. Jones, Tom Fiddaman, Lori S. Siegel, Diana Wright, Travis Franck, Andreas Barkman, Tom Cummings, Felicitas von Peter, Jacqueline McGlade, Robert W. Corell, and John Sterman. Current Emissions Reductions Proposals in the Lead-Up to COP-15 are Likely to be Insufficient to Stabilize Atmospheric CO2 Levels: Using C-ROADS—A Simple Computer Simulation of Climate Change—To Support Long-Term Climate Policy. Climate Change—Global Risks, Challenges, and Decisions Conference, University of Copenhagen. March 2009.
Model attributes
Model type Quick running climate model (get exact text from scientific review)
Geographic scope Global
Geographic resolution 3 regions or emission reduction targets, global for deforestation/aforestation targets
Start date 1850
End date 2100
Time step 0.25 year
Approach for addressing risk/uncertainty Model outputs to not show level of uncertainty associated with simulation
Data sources
- Country-level CO2 emissions from fossil fuels from Global, Regional, and National Fossil Fuel CO2 Emissions. Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory, U.S. Department of Energy.
- CO2 emissions from changes in land use from Carbon Flux to the Atmosphere from Land-Use Changes 1850-2005 Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory, U.S. Department of Energy.
- GDP and population from Statistics on World Population, GDP and Per Capita GDP, 1-2006 AD Conference Board and Groningen Growth and Development Centre, Total Economy Database.
- Business As Usual CO2 emissions projections are calibrated to the scenarios in the IPCC's Special Report on Emissions Scenarios (SRES), with the International Energy Agency (IEA)’s World Energy Outlook 2007 allocations between regions. The C-LEARN default BAU scenario is the IPCC's A1F1 scenario. For an overview of the IPCC scenarios, see "What is the range of GHG emissions in the SRES scenarios and how do they relate to driving forces?" in Summary for Policy Makers section of the SRES.
- Population and GDP projections are based on the United Nations’ World Population Prospects 2004 forecast and U.S. Energy Information Agency (EIA)'s International Energy Outlook 2008 GDP forecast, respectively.
Model structure
Module: Regional CO2 emissions
Description
Input variables
Key assumptions Explain in words and include equations if available
Output variables
Module: Other greenhouse gasses (CH4 and N2O)
Description
Input variables
Key assumptions Explain in words and include equations if available
Output variables
Module: Land use
Description
Input variables
Key assumptions Explain in words and include equations if available
Output variables
Module: Carbon cycle
Description
Input variables
Key assumptions Explain in words and include equations if available
Output variables
Module: Global Average Surface Temperature
Description
Input variables
Key assumptions Explain in words and include equations if available
Output variables
Module: Sea level rise
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