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 will observe monthly satellite data of the North Atlantic to identify relationships among key science variables that include sea surface salinity (SS), air temperature at the ocean surface (AT), sea surface temperature (ST), evaporation (EV), precipitation (PT), and evaporation minus pre

Students analyze the relationship between sea surface height and ocean surface currents by graphing sea height using satellite data.  Note: This lesson is modified from NASA's TOPEX/Poseidon lesson plan.

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.

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 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.

NASA visualizers take data – numbers, codes – and turn them into animations people can see and quickly understand.

The Earth System Satellite Images, along with the Data Literacy Cubes, helps the learner identify patterns in a specific image.  

Use the Data Literacy Cube to guide students’ exploration of data to enrich their observations and inferences.  This is a flexible resource that may be used with a variety of graphical representations of data.  This activity requires a graph for students to evaluate.   Fo

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.