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.

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 create graphs of real temperature data to investigate climate trends by analyzing the global temperature record from 1867 to the present. Long-term trends and shorter-term fluctuations are both evaluated. The data is examined for evidence of the impact of natural and anthropogenic climate forcing mechanisms on the global surface temperature variability. Students are prompted to determine the difficulties scientists face in using this data to make climate predictions.

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.

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.

This activity introduces students to global climate patterns by having each student collect information about the climate in a particular region of the globe. After collecting information, students share data through posters in class and consider factors that lead to differences in climate in different parts of the world. Finally, students synthesize the information to see how climate varies around the world.

In this intermediate Excel activity, students import US Historical Climate Network mean temperature data into Excel from a station of their choice. They are then guided through the activity on how to use Excel for statistical calculations, graphing, and linear trend estimates. The activity assumes some familiarity with Excel and graphing in Excel.

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

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