This activity engages learners to make a model of sediment cores using different kinds of glass beads and sand. They learn how to examine the types, numbers, and conditions of diatom skeletons in the model sediment cores and tell something about the hypothetical paleoclimate that existed when they were deposited. The students get to be climate detectives.

In this activity, students will use oxygen isotope values of two species of modern coral to reconstruct ambient water temperature over a four-year period. They use Microsoft Excel, or similar application, to create a spreadsheet of temperature values calculated from the isotope values of the corals by means of an algebraic equation. Students then use correlation and regression techniques to determine whether isotope records can be considered to be good proxies for records of past temperatures.

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 activity with a lab report instructs students to solve and plot 160,000 years' worth of ice core data from the Vostok ice core using Excel or similar spreadsheets to analyze data. Students learn about ice cores and what they can tell us about past atmospheric conditions and the past atmospheric concentrations of CO2 and CH4.

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.

In this activity, students compare carbon dioxide (CO2) data from Mauna Loa Observatory, Barrow (Alaska), and the South Pole over the past 40 years to help them better understand what controls atmospheric carbon dioxide. This activity makes extensive use of Excel.

A detailed Google Earth tour of glacier change over the last 50 years is given in class as an introduction. Students are then asked to select from a group of glaciers and create their own Google Earth tour exploring key characteristics and evident changes in that glacier.

This activity focuses on reconstructing the Paleocene-Eocene Thermal Maximum (PETM) as an example of a relatively abrupt global warming period. Students access Integrated Ocean Drilling Program (IODP) sediment core data with Virtual Ocean software in order to display relevant marine sediments and their biostratigraphy.

This teaching activity addresses regional variability as predicted in climate change models for the next century. Using real climatological data from climate models, students will obtain annual predictions for minimum temperature, maximum temperature, precipitation, and solar radiation for Minnesota and California to explore this regional variability. Students import the data into a spreadsheet application and analyze it to interpret regional differences. Finally, students download data for their state and compare them with other states to answer a series of questions about regional differences in climate change.

This activity engages learners in examining data pertaining to the disappearing glaciers in Glacier National Park. After calculating percentage change of the number of glaciers from 1850 (150) to 1968 (50) and 2009 (26), students move on to the main glacier-monitoring content of the module--area vs. time data for the Grinnell Glacier, one of 26 glaciers that remain in the park. Using a second-order polynomial (quadratic function) fitted to the data, they extrapolate to estimate when there will be no Grinnell Glacier remaining (illustrating the relevance of the question mark in the title of the module).

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