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.

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.

Scientific data are often represented by assigning ranges of numbers to specific colors. The colors are then used to make false color images which allow us to see patterns more easily. Students will make a false-color image using a set of numbers.

Information from satellites if often used to display information about objects. This information can include how things appear, as well as their contents. Explore how pixel data sequences can be used to create an image and interpret it.

What is the hydrosphere and why is it important?

Oceanography covers a wide range of topics, including marine life and ecosystems, ocean circulation, plate tectonics and the geology of the seafloor, and the chemical and physical properties of the ocean.

A model analyst develops models to help visualize, observe, and predict complicated data. Model analysis is the process of taking large amounts of data and separate it into a structure that makes it intelligible to the binary process of computers. An analyst also manages the flow of information between different user groups through the use of relational databases.

Students will analyze a pie chart (circle graph) showing the distribution of different parts of the Earth system's absorption and reflection of energy. 

Remote sensing scientists use sensors to analyze data and solve regional, national and global concerns. For instance, natural resource management, urban planning, and climate and weather prediction are applications of remote sensing. Many scientists develop new sensor systems, analytical techniques, or new applications for existing systems. 

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.