This interactive animation focuses on the carbon cycle and includes embedded videos and captioned images to provide greater clarification and detail of the cycle than would be available by a single static visual alone.
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.
The purpose of this activity is to identify global patterns and connections in environmental data contained in the GLOBE Earth Systems Poster, to connect observations made within the Earth Systems Poster to data and information at the National Snow and Ice Data Center, and to understand the connections between solar energy and changes at the poles, including feedback related to albedo.
This video features University of Wisconsin-Madison researcher John Magnuson, who studies the ecology of freshwater systems. He explains the difference between weather and climate using data on ice cover from Lake Mendota in Madison, WI. Analysis of the data indicates a long-term trend that can be connected to climate change.
This is a simulation that illustrates how temperature will be affected by global CO2 emission trajectories. It addresses the issue that even if global emissions begin to decrease, the atmospheric concentration of CO2 will continue to increase, resulting in increased global temperatures.
This video considers the current estimates of sea level rise as possibly too conservative and discusses more recent data on ice melt rates coming from Antarctica and Greenland, showing rates of melt at up to 5 times as rapid. Scientists discuss what levels and rates of sea level rise have occurred in the past, including the Pliocene, which demonstrated 1m rise every 20 years.
In this exercise learners use statistics (T-test using Excel) to analyze an authentic dataset from Lake Mendota in Madison, WI that spans the last 150 years to explore ice on/ice off dates. In addition, students are asked to investigate the IPCC Likelihood Scale and apply it to their statistical results.
This multi-part activity introduces users to normal seasonal sea surface temperature (SST) variation as well as extreme variation, as in the case of El NiÃo and La NiÃa events, in the equatorial Pacific Ocean. Via a THREDDS server, users learn how to download seasonal SST data for the years 1982 to 1998. Using a geographic information system (GIS), they visualize and analyze that data, looking for the tell-tale SST signature of El NiÃo and La NiÃa events that occurred during that time period. At the end, students analyze a season of their own choosing to determine if an El NiÃo or La NiÃa SST pattern emerged in that year's data.
This lesson explores El NiÃo by looking at sea surface temperature, sea surface height, and wind vectors in order to seek out any correlations there may be among these three variables using the My NASA Data Live Access Server. The lesson guides the students through data representing the strong El NiÃo from 1997 to 1998. In this way, students will model the methods of researchers who bring their expertise to study integrated science questions.