Students analyze four data visualizations focused on the topic of sea level.  They use a jigsaw method to explore and communicate their findings to their peers.

Students will analyze a graph showing the amounts of peak energy received at local noon each day over the year changes with different latitudes. 

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.

In this lesson, Observing Earth’s Seasonal Changes, students observe patterns of average snow and ice amounts as they change from one month to another, as well as connect the concepts of the tilt and orbit of the Earth (causing the changing of seasons) with monthly snow/ice data from January 2008

Students watch a video and answer questions on Dr. Patrick Taylor (Atmospheric Scientist, NASA Langley Research Center) as he discusses the study of clouds and Earth's energy budget by analyzing data from Low Earth Orbit satellites. 

In this lesson, students will investigate the drivers of climate change, including adding carbon dioxide and other greenhouse gases to the atmosphere, sea level rise, and the effect of decreasing sea ice on temperatures.

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.

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, establish cause and effect relationships, identify patterns, and determine relationships among variables.  

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.