Students identify patterns in chlorophyll concentration data to formulate their explanations of phytoplankton distribution. 

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.

This graphic organizer may be used to help students analyze the processes and components of Earth System phenomena.

This video provides tips for teachers on helping students make sense of data to help them understand and work with data. It is based on the work of Kristin Hunter-Thomson of Dataspire.org and uses data from the My NASA Data Earth System Data Explorer.

Students watch a visualization video and answer questions on the potential of increasing megadroughts in the southwest and central United States from 1950-2095 using models created by soil moisture data.

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.

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

This StoryMap lesson plan allows students to explore global phytoplankton distribution using chlorophyll concentration data in a 5 E-learning cycle. Students will investigate the processes that allow phytoplankton populations to thrive, as well as how their role in the carbon cycle impacts the other spheres of the Earth System. 

Students will explore the Nitrogen Cycle by modeling the movement of a nitrogen atom as it passes through the cycle. Students will stop in the different reservoirs along the way, answering questions about the processes that brought them to the different reservoirs.  

This lesson was based on an activity from UCAR Center for Science Education. 

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.