In this activity students work with data to analyze local and global temperature anomaly data to look for warming trends. The activity focuses on the Great Lakes area.

In this activity, students learn about the urban heat island effect by investigating which areas of their schoolyard have higher temperatures - trees, grass, asphalt, and other materials. Based on their results, they hypothesize how concentrations of surfaces that absorb heat might affect the temperature in cities - the urban heat island effect. Then they analyze data about the history of Los Angeles heat waves and look for patterns in the Los Angeles climate data and explore patterns.

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

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.

This is an activity designed to allow students who have been exposed to the El NiÃo-Southern Oscillation to analyze the La NiÃa mechanism and predict its outcomes in a case study format.

In this activity, students examine climate variability in the North Atlantic associated with the North Atlantic Oscillation (NOA) in a case study format.

This activity uses two interactive simulations to illustrate climate change, 1) at the micro/molecular level - modeling the impact of increasing concentrations of greenhouse gases in the atmosphere on surface temperature and 2) at the macro level - modeling changes in glacier thickness and flow as a result of rising surface temperature.

In this activity, students are guided through graphs of surface air temperature anomaly data and Vostok ice core data to illustrate how scientists use these data to develop the basis for modeling how climate is likely to change in the future.

This activity involves plotting and comparing monthly data on atmospheric C02 concentrations over two years, as recorded in Mauna Loa and the South Pole, and postulating reasons for differences in their seasonal patterns. Longer-term data is then examined for both sites to see if seasonal variations from one site to the other carry over into longer term trends.

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