This activity addresses climate change impacts that affect all states that are part of the Colorado River Basin and are dependent on its water. Students examine available data, the possible consequences of changes to various user groups, and suggest solutions to adapt to these changes.
In this activity, students learn about the energy sources used by their local utility provider to generate electricity, and work in small groups to evaluate the sustainability of either a renewable or non-renewable energy source used to generate electricity.
In this role-play activity, students take the roles of various important players in the climate change policy debate including politicians, scientists, environmentalists, and industry representatives. Working in these roles, students must take a position, debate with others, and then vote on legislation designed to reduce greenhouse gas emissions in the United States. Can be used in a variety of courses including writing and rhetoric, and social sciences.
In this activity, students are introduced to tree rings by examining a cross section of a tree, also known as a 'tree cookie.' They discover how tree age can be determined by studying the rings and how ring thickness can be used to deduce times of optimal growing conditions. Next, they investigate simulated tree rings applying the scientific method to explore how climatic conditions varied over time.
Data-centric activity where students explore the connections between an observable change in the cryosphere and its potential impact in the hydrosphere and atmosphere. Students analyze the melt extents on the Greenland ice sheet from 1992-2003. Students also learn about how scientists collect the data.
In this activity, students research changes to the environment in the Arctic/Bering Sea over time using oral and photographic histories. Developed for Alaska Native students, this activity can be customized for other regions.
In this activity, students review techniques used by scientists as they analyze a 50-year temperature time series dataset. The exercise helps students understand that data typically has considerable variability from year to year and to predict trends, one needs to consider long-term data.