This video, along with a background essay, focuses on impacts of climate change on the lives of Native Alaskans around Barrow, Alaska. Specific changes include the timing of the changes in the formation and breakout of sea ice and the impacts on subsistence living.
In this activity, students learn about the urban heat island effect by investigating which areas of their schoolyard have higher temperatures - trees, grass, asphalt, and other materials. Based on their results, they hypothesize how concentrations of surfaces that absorb heat might affect the temperature in cities - the urban heat island effect. Then they analyze data about the history of Los Angeles heat waves and look for patterns in the Los Angeles climate data and explore patterns.
This Flash-based simulation explores the relationship between carbon emissions and atmospheric carbon dioxide using two main displays: (1) graphs that show the level of human-generated CO2 emissions, CO2 removals, and the level of CO2 in the atmosphere, and (2) a bathtub animation that shows the same information as the graphs. The bathtub simulation illustrates the challenges of reducing greenhouse gas concentrations in the atmosphere.
This video describes why tropical ice cores are important and provide different information than polar ice cores, why getting them now is important (they are disappearing), and how scientists get them. The work of glaciologist Lonnie Thompson is featured, with a focus on his work collecting cores of ice from high mountain glaciers that contain significant data about past climate change.
This video is the second of three short videos showcasing the dramatic changes in Alaska's marine ecosystems. The video highlights the marine mammals and birds and how they depend on Arctic sea ice, as well as questions about how these animals will cope in the face of climate change.
This activity involves plotting and comparing monthly data on atmospheric C02 concentrations over two years, as recorded in Mauna Loa and the South Pole, and postulating reasons for differences in their seasonal patterns. Longer-term data is then examined for both sites to see if seasonal variations from one site to the other carry over into longer term trends.