Students will analyze the monthly seasonal chlorophyll concentration images in our global oceans for the four different months of 2017, and then answer the following questions.
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The advance-and-retreat cycle of snow cover drastically changes the whiteness and brightness of Earth. Using two maps created using NASA satellite data for 2017, students review the seasonal differences of snow and ice extent and answer questions on their observations.
In this NASA investigation, "What's Hot at the Mall," students examine how shopping malls change natural environments by examining thermal images gathered by NASA showing an area in Huntsville, Alabama.
These six graphs show Ocean Chlorophyll Concentrations from 1998 - 2018 in a variety of locations: East Bering Sea, Gulf of Alaska, California Coast, Southeastern US/Gulf of Mexico, Northeastern US and the Scotian Shelf, and the Hawaiian Islands.
Students will analyze and interpret graphs to compare the flow of (shortwave) energy from the Sun toward China over the course of a year on cloudy versus clear days. Students will draw a conclusion and support it with evidence.
Students will analyze and interpret maps of the average net atmospheric radiation to compare the flow of energy from the Sun toward Earth in different months and for cloudy versus clear days. Students will draw conclusions and support them with evidence.
Students review the NASA video showing biosphere data over the North Atlantic Ocean as a time series animation displaying a decade of phytoplankton blooms and answer questions.
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.
The Earth System Satellite Images, along with the Data Literacy Cubes, helps the learner identify patterns in a specific image.
The Earth System Satellite Images, along with the Data Literacy Cubes, help the learner determine relationships among variables.