Using various visualizations (i.e., images, charts, and graphs), students will explore the energy exchange that occurs when hurricanes extract heat energy from the ocean. This StoryMap is intended to be used with students who have access to the internet in a 1:1 or 1:2 setting. 

NASA Earth Observations (NEO) strives to make global satellite imagery as accessible as possible. Here you can browse and download imagery of satellite data from NASA's constellation of Earth Observing System satellites.

Students learn how to estimate the "energy efficiency" of photosynthesis, or the amount of energy that plants absorb for any given location on Earth. This is the ratio of the amount of energy stored to the amount of light energy absorbed and is used to evaluate and model photosynthesis efficiency.

Students construct explanations about Earth’s energy budget by connecting a model with observations from side-by-side animations of the monthly mapped data showing incoming and outgoing shortwave radiation from Earth’s surface.

Students compare climographs for two locations to determine the most likely months to expect the emergence of mosquitoes in each location.

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.

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, 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.  

Students analyze two North Pole orthographic data visualizations produced from soil moisture data. After describing trends in the seasonal thaw of land surfaces, students demonstrate their understanding of Earth’s energy budget by explaining relationships and make predictions about the dataset.