In this video, students learn how scientific surveys of wildlife are performed at a site in Yosemite, California, and how these surveys are being used -- in conjunction with studies from the early 1900s -- to provide evidence that animal populations in Yosemite have shifted over time in response to rising temperatures.
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.
Students explore the carbon cycle and the relationship between atmospheric carbon dioxide concentrations and temperature. Students create and compare graphs of carbon dioxide and temperature data from one local (Mauna Loa, Hawaii) meteorological station and one NASA global data set. These graphs, as well as a global vegetation map and an atmospheric wind circulation patterns diagram, are used as evidence to support the scientific claims they develop through their analysis and interpretation.
This video from NASA features scientists who describe the role of salt in the oceans and global oceanic circulation, especially the effect of salinity on the density of water and its global circulation, with reference to global climate change.
This video is part two of a seven-part National Academies series, Climate Change: Lines of Evidence. The video outlines, with the use of recent research and historical data, how we know that the Earth is warming.
This video describes the role that dendrochronology plays in understanding climate change, especially changes to high elevation environments at an upper tree line. Dendrochronologists from the Big Sky Institute sample living and dead trees, describe how correlations between trees are made, and explain how tree cores record climate changes.
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 or forecast the future, there is value in long-term data collection.