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Atmospheric scientists study the weather and climate and examine how those conditions affect human activity and the earth in general. Most atmospheric scientists work indoors in weather stations, offices, or laboratories. Occasionally, they do fieldwork, which means working outdoors to examine the weather. Some atmospheric scientists may have to work extended hours during weather emergencies.


Grade Level: 6-8, 9-12

Students watch a short video to gather information about sources of methane emissions and then extend their understanding of these sources to evaluate monthly trends in the Alaska region, ultimately making connections to Earth’s energy budget.



Grade Level: 6-8, 9-12

Students will analyze and interpret maps of the average net atmospheric radiation to compare the flow of energy from the Sun toward Earth in different months and for cloudy versus clear days. Students will draw conclusions and support them with evidence.



Grade Level: 6-8, 9-12

Students analyze two North Pole orthographic data visualizations produced from soil moisture data. After describing trends in the seasonal thaw of land surfaces, students demonstrate their understanding of Earth’s energy budget by explaining relationships and make predictions about the dataset.


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.


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. 


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