Students observe seasonal images of Monthly Leaf Area, looking for any changes that are occurring throughout the year.
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What is sea-level rise and how does it affect us? This "Teachable Moment" looks at the science behind sea-level rise and offers lessons and tools for teaching students about this important climate topic.
This learning activity uses data acquired by the TOPEX/Poseidon altimeter, a joint project of NASA and the French Space Agency, to investigate the relationship between the topography of a sea-floor feature and the topography of the overlying sea surface.
Students analyze historic plant growth data (i.e., Peak Bloom dates) of Washington, D.C.’s famous cherry blossom trees, as well as atmospheric near surface temperatures as evidence for explaining the phenomena of earlier Peak Blooms in our nation’s capital.
Students move through a series of short activities to explore and evaluate global solar radiation data from NASA satellites. In this process, students make qualitative and quantitative observations about seasonal variations in net energy input to the Earth System.
Students observe seasonal images of Monthly Normalized Difference Vegetation, looking for any changes in vegetation that are occurring throughout the year. They put the images in order based on what they know about seasonal changes.
Students analyze map visualizations representing the amount of Sun’s energy received on the Earth as indicated by the amount that is reflected back to space, known as “albedo”.
Students interpret a double bar/column chart comparing the number of tropical cyclones in different locations.
The activities in this guide will help students understand variations in environmental parameters by examining connections among different phenomena measured on local, regional and global scales.
The Earth System Satellite Images, help the learner visualize how different Earth system variables change over time, establish cause and effect relationships for a specific variable, identify patterns, and determine relationships among variables over one year.