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.

In this activity, students learn how to read, analyze, and construct climographs. These climographs are a graphic way of displaying monthly average temperature and precipitation. Students also practice matching climographs to various locations and summarize global-scale climate patterns revealed by comparing climographs.

In this activity, students download historic temperature datasets and then graph and compare with different locations. As an extension, students can download and examine data sets for other sites to compare the variability of changes at different distinct locations, and it is at this stage where learning can be individualized and very meaningful.

This simulation allows the user to project CO2 sources and sinks by adjusting the points on a graph and then running the simulation to see projections for the impact on atmospheric CO2 and global temperatures.

This is a jigsaw activity in which students are assigned to research one step out of five in the geochemical process stages of the organic carbon cycle. Students then teach their step in cross-step groups until everyone understands all five process stages.

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.

In this activity, students explore the increase in atmospheric carbon dioxide over the past 40 years with an interactive online model. They use the model and observations to estimate present emission rates and emission growth rates. The model is then used to estimate future levels of carbon dioxide using different future emission scenarios. These different scenarios are then linked by students to climate model predictions also used by the Intergovernmental Panel on Climate Change.

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.

This activity introduces students to global climate patterns by having each student collect information about the climate in a particular region of the globe. After collecting information, students share data through posters in class and consider factors that lead to differences in climate in different parts of the world. Finally, students synthesize the information to see how climate varies around the world.

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.

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