Dr. Norman Loeb, an atmospheric scientist at NASA’s Langley Research Center in Hampton, Virginia, is the principal investigator for an experiment called the Clouds and the Earth’s Radiant Energy System (CERES). CERES instruments measure how much of the sun’s energy is reflected back to space and how much thermal energy is emitted by Earth to space.
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Students will explore the Nitrogen Cycle by modeling the movement of a nitrogen atom as it passes through the cycle. Students will stop in the different reservoirs along the way, answering questions about the processes that brought them to the different reservoirs.
This lesson was based on an activity from UCAR Center for Science Education.
Data scientists work with data captured by scientific instruments or generated by a simulator, as well as data that is processed by software and stored in computer systems. They work with scientists to analyze databases and files using data management techniques and statistics. From changes in sea level, atmospheric composition, or land use, data scientists help make sense of the petabytes of data that NASA collects and stores.
Follow along as NASA visualizer Kel Elkins walks you through three visualizations (Dust Crossing, Typhoon Hagupit, and Aquarius Sea Surface Salinity) and answers questions about his work, education, and career.
Software engineers play an important role at NASA as this field supports the success of our missions on Earth and beyond. This field will continue to grow as it helps NASA address the many challenges that our agency faces.
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.