In this activity, students make a model sea floor sediment core using two types of buttons to represent fossil diatoms. They then compare the numbers of diatom fossils in the sediment at different depths to determine whether the seas were free of ice while the diatoms were alive.

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.

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.

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.

In this activity, students work in groups, plotting carbon dioxide concentrations over time on overheads and estimating the rate of change over five years. Stacked together, the overheads for the whole class show an increase on carbon dioxide over five years and annual variation driven by photosynthesis. This exercise enables students to practice basic quantitative skills and understand how important sampling intervals can be when studying changes over time. A goal is to see how small sample size may give incomplete picture of data.

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

In this exercise learners use statistics (T-test using Excel) to analyze an authentic dataset from Lake Mendota in Madison, WI that spans the last 150 years to explore ice on/ice off dates. In addition, students are asked to investigate the IPCC Likelihood Scale and apply it to their statistical results.

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.

This is a sequence of 5 classroom activities focusing on the El NiÃo climate variability. The activities increase in complexity and student-directedness. The focus of the activities is on accessing and manipulating real data to help students understand El NiÃo as an interaction of Earth systems.

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.

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