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.

This lesson contains a card sort activity that challenges students to predict relative albedo values of common surfaces. 

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 map visualizations representing the amount of Sun’s energy received on the Earth as indicated by the amount that is reflected back to space, known as “albedo”.

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

This unit plan is published by the NASA Climate Change Research Initiative's (CCRI) Applied Research STEM Curriculum Portfolio.  The CCRI Unit Plan, called “Urban Surface Temperatures and the Urban Heat Island Effects,“ has the purpose to educate students how climate is changi

Learners follow adventurous camper, Awenasa, as she travels the United States and attends various camp locations throughout the year.  Learners analyze data to find her location among the various campsites using monthly averaged NASA satellite data (Cloud Coverage, Surface (S

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

The El Niño Implementation Sequence provides a series of lessons and activities for students to learn about a condition that sometimes occurs in the Pacific Ocean, but it is so big that it affects weather all over the world.

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