This Earth Exploration Toolbook chapter is a detailed computer-based exploration in which students learn how various climatic conditions impact the formations of sediment layers on the ocean floor. They analyze sediment core data from the Ross Ice Shelf in Antarctica for evidence of climate changes over time. In addition, they interact with various tools and animations throughout the activity, in particular the Paleontological Stratigraphic Interval Construction and Analysis Tool (PSICAT) that is used to construct a climate change model of a sediment core from core images.

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 Niño and La Niña 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 Niño and La Niña events that occurred during that time period. At the end, students analyze a season of their own choosing to determine if an El Niño or La Niña SST pattern emerged in that year's data.

This long classroom activity introduces students to a climate modeling software. Students visualize how temperature and snow coverage might change over the next 100 years. They run a 'climate simulation' to establish a baseline for comparison, do a 'experimental' simulation and compare the results. Students will then choose a region of their own interest to explore and compare the results with those documented in the IPCC impact reports. Students will gain a greater understanding and appreciation of the process and power of climate modeling.

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 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 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.

Data-centric activity where students explore the connections between an observable change in the cryosphere and its potential impact in the hydrosphere and atmosphere. Students analyze the melt extents on the Greenland ice sheet from 1992-2003. Students also learn about how scientists collect the data.

In this activity students download satellite images displaying land surface temperature, snow cover, and reflected short wave radiation data from the NASA Earth Observation (NEO) Web site. They then explore and animate these images using the free tool ImageJ and utilize the Web-based analysis tools built into NEO to observe, graph, and analyze the relationships among these three variables.

In this Earth Exploration Toolbook chapter, students select, explore, and analyze satellite imagery. They do so in the context of a case study of the origins of atmospheric carbon monoxide and aerosols, tiny solid airborne particles such as smoke from forest fires and dust from desert wind storms. They use the software tool ImageJ to animate a year of monthly images of aerosol data and then compare the animation to one created for monthly images of carbon monoxide data. Students select, explore, and analyze satellite imagery using NASA Earth Observatory (NEO) satellite data and NEO Image Composite Explorer (ICE) tool to investigate seasonal and geographic patterns and variations in concentration of CO and aerosols in the atmosphere.