...
C-LEARN is a Web-based version of C-ROADS, a simulation of Sustainability Institute and Ventana Systems that is part of the Climate Interactive effort. In the Collaboratorium, C-LEARN is the primary climate model. It takes greenhouse gas emission and deforestation/aforestation targets as inputs and provides outputs such as atmospheric concentrations
The model's inputs are:
- Targets for greenhouse gas emission reduction
- Targets for reductions in deforestation and increases in aforestation
Its outputs are:
- Atmospheric concentration of carbon dioxide (CO2)
...
- Increase in global mean temperature (GMT)
...
- above baseline year
This writeup about C-LEARN contains three primary sections
- C-LEARN overview
High level description of the model, ; information about its creators developers 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 C-LEARN's six sub-models:
- Regional CO2 emissions
- Other greenhouse
**- gases
- Land use
- Carbon cycle
**Global Average Surface Temperature
**Sea level rise
Overview
...
...
- Climate
...
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
...
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
...
...
- Sea level rise
...
Output variables Return to About the Climate Collaboratorium Models