This digital GLOBE Earth system (digital) poster images show global visualizations of different science variables for 2019, 2018, 2016, and 2013.  Students may use these images to find patterns among different environmental data, understand the relationships among different environmental parameters, and more. 

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.

Students move through a series of short activities to explore and evaluate global solar radiation data from NASA satellites.  In this process, students make qualitative and quantitative observations about seasonal variations in net energy input to the Earth System.

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

This lesson is designed to help students analyze the interaction between different cloud heights and Earth's incoming and outgoing energy. 

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. 

Students construct explanations about Earth’s energy budget by connecting a model with observations from side-by-side animat

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.  

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.