NASA EOSDIS Data Centers - Connecting Us to a Changing Planet

Physics

Scientific paper

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6344 System Operation And Management

Scientific paper

NASA Earth Observing System Data and Information System (EOSDIS) data centers support over 18 operational NASA satellite missions including the flagship EOS missions: Terra, Aqua, and Aura. The EOS missions collect data for the key physical variables needed to advance understanding of the entire Earth system and develop a deeper comprehension of the components of that system and the interactions among the components. These components (the atmosphere, land, oceans, and cryosphere) are characterized by the key measurements identified by the Earth science community known as the 24 EOS measurements. The observations and data products resulting from these measurements are processed and managed at geographically distributed facilities. Processing facilities generate data products for selected mission instruments and deliver them to the data centers for archive and user distribution. The data centers serve one or more specific Earth science disciplines to provide the user community with data products, information, services, and tools unique to its particular science. In addition to data from the EOS satellites, EOSDIS data centers house socioeconomic data, data from pre-EOS missions, and data from field campaigns. With the continued growth of the data centers holdings and the addition of the Crustal Dynamics Data and Information System to EOSDIS researchers have more data and knowledge to enhance their scientific studies of global change. We describe each processing facility and data center, its expertise, and its disciplines. We indicate the physical location of the data products that are associated with the 24 science measurements. We provide a diagrammatic mapping of the components, disciplines, and measurements to the data centers to facilitate understanding of the individual centers and to show the interrelated nature of the data center holdings. We present lessons learned in developing and managing data set diversity.

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