This activity develops students' understanding of climate by having them make in-depth examinations of historical climate patterns using both graphical and map image formats rather than presenting a general definition of climate. Students explore local climate in order to inform a pen pal what type of weather to expect during an upcoming visit. Students generate and explore a variety of graphs, charts, and map images and interpret them to develop an understanding of climate.

This lesson explores El Nino 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 Nino from 1997 to 1998. In this way, students will model the methods of researchers who bring their expertise to study integrated science questions.

This National Geographic video explains the origins of the El NiÃo Southern Oscillation using animations and shows the impacts on humans, wildlife and habitat, particularly in the United States.

This video shows 15 years of data obtained via Polar-orbiting satellites that are able to detect subtle differences in ocean color, allowing scientists to see where there are higher concentrations of phytoplankton - a proxy for the concentration of chlorophyll in the ocean.

This video features University of Wisconsin-Madison researcher John Magnuson, who studies the ecology of freshwater systems. He explains the difference between weather and climate using data on ice cover from Lake Mendota in Madison, WI. Analysis of the data indicates a long-term trend that can be connected to climate change.

In this video, a team of paleontologists, paleobotanists, soil scientists, and other researchers take to the field in Wyoming's Bighorn Basin to document how the climate, plants, and animals there changed during the Paleocene- Eocene Thermal Maximum (PETM) when a sudden, enormous influx of carbon flooded the ocean and atmosphere for reasons that are still unclear to scientists. The PTEM is used as an analog to the current warming occurring. The scientists' research may help inform our understanding of current increases in carbon in the atmosphere and ocean and the resulting impact on ecosystems. Supporting materials include essay and interactive overview of animals that existed in the Basin after the PETM event.

In this activity, students will use oxygen isotope values of two species of modern coral to reconstruct ambient water temperature over a four-year period. They use Microsoft Excel, or similar application, to create a spreadsheet of temperature values calculated from the isotope values of the corals by means of an algebraic equation. Students then use correlation and regression techniques to determine whether isotope records can be considered to be good proxies for records of past temperatures.

This activity with a lab report instructs students to solve and plot 160,000 years' worth of ice core data from the Vostok ice core using Excel or similar spreadsheets to analyze data. Students learn about ice cores and what they can tell us about past atmospheric conditions and the past atmospheric concentrations of CO2 and CH4.

This activity addresses naturally occurring climate change involving ENSO (El-NiÃo Southern Oscillation). In this activity, students play the role of a policy maker in Peru. First, they determine what sort of ENSO variation is occurring. Then, they must decide how to allocate Peru's resources to manage for possible weather-related problems.

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.

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