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.

This lesson explores the chemistry of some of the greenhouse gases that affect Earth's climate. Third in a series of 9 lessons from an online module entitled 'Visualizing and Understanding the Science of Climate Change'.

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.

In this short, hands-on activity, students build simple molecular models of 4 atmospheric gases (O2, N2, C02, and methane), compare their resonant frequencies, and make the connection between resonant frequency and the gas's ability to absorb infrared radiation.

This activity introduces students to visualization capabilities available through NASA's Earth Observatory, global map collection, NASA NEO and ImageJ. Using these tools, students build several animations of satellite data that illustrate carbon pathways through the Earth system.

This activity involves plotting and comparing monthly data on atmospheric C02 concentrations over two years, as recorded in Mauna Loa and the South Pole, and postulating reasons for differences in their seasonal patterns. Longer-term data is then examined for both sites to see if seasonal variations from one site to the other carry over into longer term trends.

In this activity, students are guided through the process of locating and graphing web-based environmental data that has been collected by GLOBE Program participants using actual data collected by students in Pennsylvania and comparing them to their local climatic boundary conditions. This activity highlights the opportunities for using GLOBE data to introduce basic concepts of Earth system science.

Students investigate how much greenhouse gas (carbon dioxide and methane) their family releases into the atmosphere each year and relate it to climate change. To address this, students use the Environmental Protection Agency Personal Emissions Calculator to estimate their family's greenhouse gas emissions and to think about how their family could reduce those emissions.

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.

In this activity, students work in groups, plotting carbon dioxide concentrations over time on overheads and estimating the rate of change over five years. Stacked together, the overheads for the whole class show an increase on carbon dioxide over five years and annual variation driven by photosynthesis. This exercise enables students to practice basic quantitative skills and understand how important sampling intervals can be when studying changes over time. A goal is to see how small sample size may give incomplete picture of data.

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