Students visit a NASA Website called "Eyes on the Earth" to view satellite missions in 3D circling the Earth and learn to navigate to specific satellites to learn about their capability of analyzing our changing planet and air quality.

This activity invites students to simulate and observe the different effects on sea level from melting sea-ice.

Steve Nerem is the leader of NASA’s Sea Level Change team. His project, Observation-Driven Projections of Future Regional Sea Level Change, focuses on using NASA satellite and in situ observations and climate modeling to estimate future regional sea level change.

In this activity, students will learn about sea ice and land ice. They will observe ice melting on a solid surface near a body of water and ice melting in a body of water.

For over 20 years, satellite instruments have measured the sea surface height of our ever-changing oceans.  This video of images shows the complicated patterns of rising and falling ocean levels across the globe from 1993 to 2015.

This activity invites students to model and observe the effect of melting ice sheets (from land) on sea level and the difference between the effect of melting sea-ice to that of melting land ice on sea level.

Chemists study atomic and molecular structures and their interactions. 

What is sea-level rise and how does it affect us? This "Teachable Moment" looks at the science behind sea-level rise and offers lessons and tools for teaching students about this important climate topic. 

The Earth System Satellite Images, along with the Data Literacy Cubes, helps the learner identify patterns in a specific image.  

At the core of scientific visualization is the representation of data graphically - through images, animations, and videos - to improve understanding and develop insight. Data visualizers develop data-driven images, maps, and visualizations from information collected by Earth-observing satellites, airborne missions, and ground measurements. Visualizations allow us to explore data, phenomena and behavior; they are particularly effective for showing large scales of time and space, and "invisible" processes (e.g. flows of energy and matter) as integral parts of the models.