The activity follows a progression that examines the CO2 content of various gases, explores the changes in the atmospheric levels of CO2 from 1958 to 2000 from the Mauna Loa Keeling curve, and the relationship between CO2 and temperature over the past 160,000 years. This provides a foundation for examining individuals' input of CO2 to the atmosphere and how to reduce it.
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 audio slideshow/video describes the Greenland ice sheet and the difficulties in getting scientific measurements at the interface between the ice and the ocean. It features the work of a researcher from Woods Hole Oceanographic Institute researcher. She gives a personal account of her work on the recent increase in melting of glaciers, the challenges of working in Greenland, and the reasons why so many climate scientists are looking there for answers to questions about climate change.
This interactive visualization provides a clear, well-documented snapshot of current and projected values of several climate variables for local areas in California. The climate variables include observed and projected temperatures, projected snowpack, areas vulnerable to flooding due to sea level rise, and projected increase in wildfires. The projected values come from expert sources and well-established climate models.
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.