In this activity for undergraduates, students explore the CLIMAP (Climate: Long-Range Investigation, Mapping and Prediction) model results for differences between the modern and the Last Glacial Maximum (LGM) and discover the how climate and vegetation may have changed in different regions of the Earth based on scientific data.

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 is the first of nine lessons in the Visualizing and Understanding the Science of Climate Change website. This lesson is an introduction to Earth's climate and covers key principles regarding Earth's unique climate, atmosphere, and regional and temporal climate differences.

In this activity, students compare carbon dioxide data from Mauna Loa Observatory, Barrow, Alaska, and the South Pole over the past 40 years. Students use the data to learn about what causes short-term and long-term changes in atmospheric carbon dioxide. This activity makes extensive use of Excel.

In this activity, students use authentic Arctic climate data to unravel some causes and effects related to the seasonal melting of the snowpack and to further understand albedo.

This lesson sequence guides students to learn about the geography and the unique characteristics of the Arctic, including vegetation, and people who live there. Students use Google Earth to explore the Arctic and learn about meteorological observations in the Arctic, including collecting their own data in hands-on experiments. This is the first part of a three-part curriculum about Arctic climate.

This set of activities is about carbon sources, sinks, and fluxes among them - both with and without anthropogenic components.

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.

In this activity, students analyze data maps of sea surface temperature anomalies for a 14-year interval and create an ENSO time line in a case study format. Based on their findings, students determine the recurrence interval of the ENSO system.

In this activity, students work with climate data from the tropical Pacific Ocean to understand how sea-surface temperature and atmospheric pressure affect precipitation in the tropical Pacific in a case study format.

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