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.

In this activity, students use Google Earth to explore global temperature changes during a recent 50 - 58 year period. They also explore, analyze, and interpret climate patterns of 13 different cities, and analyze differences between weather and climate patterns.

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.

In this lab activity, students use a chemical indicator (bromothymol blue) to detect the presence of carbon dioxide in animal and plant respiration and in the burning of fossil fuels and its absence in the products of plant photosynthesis. After completing the five parts of this activity, students compare the colors of the chemical indicator in each part and interpret the results in terms of the qualitative importance of carbon sinks and sources.

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

In this activity, students are guided through the process of locating and graphing web-based environmental data that has been collected by GLOBE Program participants using actual data collected by students in Pennsylvania and comparing them to their local climatic boundary conditions. This activity highlights the opportunities for using GLOBE data to introduce basic concepts of Earth system science.

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 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 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.

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.

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