Model type
Quick running climate model that, according to the C-ROADS scientific review board, "reproduces the response properties of state-of-the-art three dimensional climate models...well within the uncertainties of the high resolution models...with sufficient precision to provide useful information" to policy makers and the general public.

Geographic scope Global

Geographic resolution

• 3 regions or emission reduction targets in C-LEARN (3, 7 or 15 regions in C-ROADS)
• Global for deforestation/aforestation targets

Start date 1850

End date 2100

Time step 0.25 year

Data sources

• Country-level CO2 emissions from fossil fuels
  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
  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
  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
  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/C-ROADS default BAU scenario is the IPCC's A1FI (rapid economic growth, fossil fuel intensive) scenario. On 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
  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.

Approach for addressing risk/uncertainty
Model outputs do not show level of uncertainty associated with simulation

Model structure

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