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 activity engages learners in examining data pertaining to the disappearing glaciers in Glacier National Park. After calculating percentage change of the number of glaciers from 1850 (150) to 1968 (50) and 2009 (26), students move on to the main glacier-monitoring content of the module--area vs. time data for the Grinnell Glacier, one of 26 glaciers that remain in the park. Using a second-order polynomial (quadratic function) fitted to the data, they extrapolate to estimate when there will be no Grinnell Glacier remaining (illustrating the relevance of the question mark in the title of the module).

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 teaching activity is an introduction to how ice cores from the cryosphere are used as indicators and record-keepers of climate change as well as how climate change will affect the cryosphere. Students learn through a guided web exercise how scientists analyze ice cores to learn about past climate conditions, how melting sea and land ice will contribute to sea level rise, and what areas of the world would be at risk if Antarctic and/or Greenland ice sheets were to melt away.

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.

In this activity, students download historic temperature datasets and then graph and compare with different locations. As an extension, students can download and examine data sets for other sites to compare the variability of changes at different distinct locations, and it is at this stage where learning can be individualized and very meaningful.

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 activity, students use Google Earth and team up with fictional students in Chersky, Russia to investigate possible causes of thawing permafrost in Siberia and other Arctic regions. Students explore the nature of permafrost and what the effects of thawing permafrost mean both locally and globally. Next, students use a spreadsheet to explore soil temperature data from permafrost boreholes and surface air temperature datasets from in and around the Chersky region for a 50-year time span.

In this activity, students review techniques used by scientists, as they analyze a 50-year temperature time series dataset. The exercise helps students understand that data typically has considerable variability from year to year and to predict trends or forecast the future, there is value in long-term data collection.

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.

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