This is a sequence of 5 classroom activities focusing on the El NiÃo climate variability. The activities increase in complexity and student-directedness. The focus of the activities is on accessing and manipulating real data to help students understand El NiÃo as an interaction of Earth systems.
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 visualization graphically displays temperature and CO2 concentration in the atmosphere as derived from ice core data from 400,000 years ago to 1950. The data originates from UNEP GRID Arendal's graphic library of CO2 levels from Vostok ice core.
Two graphs from the NASA Climate website illustrate the change in global surface temperature relative to 1951-1980 average temperatures. The NASA plot is annotated with temperature-impacting historic events, which nicely connect an otherwise challenging graphic to real-world events.
In this lesson, students explore several facets of the impact of volcanic eruptions on the atmosphere. Students analyze three types of visual information: a graph of aerosol optical depth v. global temperature, a global map with temperature anomalies, and an ash plume photograph. In the hands-on activity, students use math to determine the rate and estimated time of arrival of an ash plume at an airfield.
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 Nino and La Nina 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.