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.

The Quick Start Guide lists examples of NASA datasets and imagery that could be used for student investigations related to content and practices in the Framework for K-12 Science Education.    This Guide is part of an educator toolkit that features resources for grades K-12 that can support and frame student investigations with NASA data and content. Check out the toolkit and samplers for elementary, middle, and high school at https://www.strategies.org/education/educators-toolkit/.

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

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.

Check out the Arctic and Earth SIGNs video to explore how climate models are used in climate change research.

Students will use coloring sheets to create a color coded model of El Niño, then make comparisons using the actual model by answering questions. If the Data Literacy Map Cube is used with this, students will color their models first.

This lesson plan provides some generic maps, graphs, and data tables for use with the Data Literacy Cube. Because it is a differentiated resource, this lesson plan is appropriate for multiple grade bands. 

The Earth System Satellite Images help students observe and analyze global Earth and environmental data, understand the relationship among different environmental variables, and explore how the data change seasonally and over longer timescales.  

Students will make a claim about whether changing albedo contributes to changes in Arctic habitats.

This lesson walks students through the use of Landsat false-color imagery and identification of different land cover features using these as models.