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 reconstruct past climates using lake varves as a proxy to interpret long-term climate patterns. Students use data from sediment cores to understand annual sediment deposition and how it relates to weather and climate patterns.

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 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 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.

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.

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 use a set of photographs and a 3-minute video on weather to investigate extreme weather events. They are posed with a series of questions that ask them to identify conditions predictive of these events, and record them on a worksheet. Climate and weather concepts are defined.

In this activity, students learn about sea ice extent in both polar regions (Arctic and Antarctic). They start out by forming a hypothesis on the variability of sea ice, testing the hypothesis by graphing real data from a recent 3-year period to learn about seasonal variations and over a 25-year period to learn about longer-term trends, and finish with a discussion of their results and predictions.

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.