C-Learn is a simplified version of the C-ROADS simulator. Its primary purpose is to help users understand the long-term climate effects (CO2 concentrations, global temperature, sea level rise) of various customized actions to reduce fossil fuel CO2 emissions, reduce deforestation, and grow more trees. Students can ask multiple, customized what-if questions and understand why the system reacts as it does.
This interactive visualization allows users to compare future projections of Wisconsin's average annual temperature with the actual changes of the last five decades. Text on the web page encourages students to think about the challenges Wisconsin could face if these changes occur.
The Climate Momentum Simulation allows users to quickly compare the resulting sea level rise, temperature change, atmospheric CO2, and global CO2 emissions from six different policy options: 1) Business As Usual, 2) March 2009 Country Proposals, 3) Flatten CO2 emissions by 2025, 4) 29% below 2009 levels by 2040, 5) 80% reduction of global fossil fuel plus a 90% reduction in land use emissions by 2050, and 6) 95 reduction of CO2 emissions by 2020). Based on the more complex C-ROADS simulator.
This simulation allows the user to project CO2 sources and sinks by adjusting the points on a graph and then running the simulation to see projections for the impact on atmospheric CO2 and global temperatures.
This is a simulation that illustrates how temperature will be affected by global CO2 emission trajectories. It addresses the issue that even if global emissions begin to decrease, the atmospheric concentration of CO2 will continue to increase, resulting in increased global temperatures.
This is a series of NASA Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images taken over a 10 year period, 2000-2010, showing the extent of deforestation in the State of Rondonia in western Brazil over that period of time.
This is an interactive webtool that allows the user to choose a state or country and both assess how climate has changed over time and project what future changes are predicted to occur in a given area.