This graphic organizer may be used to help students analyze the processes and components of Earth System phenomena.
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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.
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.
The Hurricane Dynamics Implementation Sequence provides a series of lessons and activities for students to learn how hurricanes affect the different spheres within the Earth System by using maps and other geographic representations, tools, and technologies to acquire, process, and report informat
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
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.
Students review an animation of monthly average wind speed at 10 meters above the ocean surface for our global ocean to analyze the relationship between winds and ocean surface currents.
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.
Many of our archived lessons date back to as early as 2004 when our learning community first formed and unfortunately contain links to content that is no longer updated or exist.