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 Likelihoodscale and apply it to their statistical results.

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 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 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 Nino and La Nina 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.

This teaching activity addresses regional variability as predicted in climate change models for the next century. Using real climatological data from climate models, students will obtain annual predictions for minimum temperature, maximum temperature, precipitation, and solar radiation for Minnesota and California to explore this regional variability. Students import the data into a spreadsheet application and analyze it to interpret regional differences. Finally, students download data for their state and compare them with other states to answer a series of questions about regional differences in climate change.

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.

In this lesson, students examine and interpret varied observational datasets and are asked to determine whether the data supports or does not support the statement: climate change is occurring in Colorado.

The activity takes a hands-on approach to understanding El Niño by physically showing and feeling the process. It consists of an El Niño demo to be performed by the teacher and observed by the class as well as an experiment to be conducted by the students themselves individually or in pairs to illustrate the connection between water temperature and atmospheric temperature. Students are asked to make conclusions based on their findings and then examine the chain of events stemming from El Niño.

In this activity, students reconstruct past climates using lake varves as a proxy to interpret long-term climate patterns and to understand annual sediment deposition and how it relates to weather and climate patterns.

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.

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