This video is about Greenland's ice sheet, accompanied by computer models of the same, to show how the ice is melting, where the meltwater is going, and what it is doing both on the surface and beneath the ice.
This video is accompanied by supporting materials including background essay and discussion questions. The focus is on changes happening to permafrost in the Arctic landscape, with Alaska Native peoples and Western scientists discussing both the causes of thawing and its impact on the ecosystem. The video shows the consequences of erosion, including mudslides and inland lakes being drained of water. An Inuit expresses his uncertainty about the ultimate effect this will have on his community and culture.
In this lesson, students examine and interpret varied observational datasets and are asked to determine whether the data supports or does not support the statement: climate change is occurring in Colorado.
This web-based activity tackles the broad reasons for undertaking ocean exploration - studying the interconnected issues of climate change, ocean health, energy and human health. Students examine the types of technology ocean scientists use to collect important data.
This video focuses on the science of climate change and its impacts on wildlife on land and in the sea, and their habitats in the U.S. There are short sections on walruses, coral reefs, migrating birds and their breeding grounds, freshwater fish, bees, etc. Video concludes with some discussion about solutions, including reduce/recyle/reuse, energy conservation, backyard habitats, citizen scientists.
This short video, the sixth in the National Academies Climate Change, Lines of Evidence series, explores the hypothesis that changes in solar energy output may be responsible for observed global surface temperature rise. Several lines of evidence, such as direct satellite observations, are reviewed.
In this activity, students download historic temperature datasets and then graph and compare with different locations. As an extension, students can download and examine data sets for other sites to compare the variability of changes at different distinct locations, and it is at this stage where learning can be individualized and very meaningful.