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.

In this jigsaw activity, students explore meteorological data collected from Eureka, Canada to try to decide when would be the best time for an Arctic visit.

This is a classroom activity about the forcing mechanisms for the most recent cold period: the Little Ice Age (1350-1850). Students receive data about tree ring records, solar activity, and volcanic eruptions during this time period. By comparing and contrasting time intervals when tree growth was at a minimum, solar activity was low, and major volcanic eruptions occurred, they draw conclusions about possible natural causes of climate change and identify factors that may indicate climate change.

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 activity, students learn about the tools and methods paleoclimatologists use to reconstruct past climates. In constructing sediment cores themselves, students will achieve a very good understanding of the sedimentological interpretation of past climates that scientists can draw from cores.

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.

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 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 are introduced to tree rings by examining a cross section of a tree, also known as a 'tree cookie.' They discover how tree age can be determined by studying the rings and how ring thickness can be used to deduce times of optimal growing conditions. Next, they investigate simulated tree rings applying the scientific method to explore how climatic conditions varied over time.

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.

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