This series of videos highlights how NASA Climate Scientists use mathematics to solve everyday problems. These educational videos to illustrate how math is used in satellite data analysis.
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This activity invites students to model and observe the effect of melting ice sheets (from land) on sea level and the difference between the effect of melting sea-ice to that of melting land ice on sea level.
This USGS activity leads students to an understanding of what remote sensing means and how researchers use it to study changes to the Earth’s surface, such as deforestation.
In this activity, you will use an inexpensive spectrophotometer* to test how light at different visible wavelengths (blue, green, red) is transmitted, or absorbed, through four different colored water samples.
In this lesson, students investigate and identify various phytoplankton using images that were previously taken with a compound microscope. Credit: This lesson is modified from a lesson of the same name created by The Center for Microbial Oceanography: Research and Education (C-MORE)
In this activity, students explore the Urban Heat Island Effect phenomenon by collecting temperatures of different materials with respect to their locations. This activity was modified from The NASA PUMAS Collection's "What makes cities hot?
In this activity, students make a claim about the cause of ocean currents and then develop a model to explain the role of temperature and density in deep ocean currents. This lesson is modified from "Visit to an Ocean Planet" Caltech and NASA/Jet Propulsion Laboratory.
In this experiment, students make a claim about the cause of ocean currents and then develop a model to explain the role of salinity and density in deep ocean currents. This lesson is modified from "Visit to an Ocean Planet" Caltech and NASA/Jet Propulsion Laboratory.
Students will engage in a “Zoom In Inquiry” learning routine to understand the symbols on a world map that shows population-weighted concentrations of PM2.5.
Students will engage in a “Zoom In Inquiry” learning routine to understand a world map that shows changes in PM2.5-attributable mortality per 100,000 population (Bondie, 2013).