Students analyze and compare satellite data of Ocean Chlorophyll Concentrations with Sea Surface Temperatures, beginning with the North Atlantic region, while answering questions about the global patterns of these phenomenon.
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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 observe monthly images of changing vegetation patterns, looking for seasonal changes occurring throughout 2017. These data can be used by students to develop their own models of change.
The Earth System Satellite Images, along with the Data Literacy Cubes, help the learner determine relationships among variables.
The Earth System Satellite Images, along with the Data Literacy Cubes, help the learner visualize how different Earth system variables change over time, identify patterns, and determine relationships among two variables in three months.
Students will examine a 2014-2015 El Niño Southern Oscillation (ENSO) event to identify relationships among sea surface height, sea surface temperature, precipitation, and wind vectors.
Students will use coloring sheets to create a color coded model of El Niño, then make comparisons using the actual model by answering questions. If the Data Literacy Map Cube is used with this, students will color their models first.
Students review Earth System phenomena that are affected by soil moisture. They analyze and evaluate maps of seasonal global surface air temperature and soil moisture data from NASA satellites. Building from their observations, students will select a location in the U.S.
The Earth System Satellite Images, along with the Data Literacy Cubes, help the learner visualize how different Earth system variables change over time, establish cause and effect relationships, identify patterns, and determine relationships among variables.