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PO.DAAC Migrates to the Cloud and the River
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  • Cassandra Nickles,
  • Catalina Oaida,
  • Alireza Farahmand,
  • Suresh Vannan,
  • Jinbo Wang,
  • Mike Gangl,
  • Frank Greguska,
  • Cedric David
Cassandra Nickles
NASA Jet Propulsion Laboratory

Corresponding Author:[email protected]

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Catalina Oaida
NASA Jet Propulsion Laboratory
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Alireza Farahmand
NASA Jet Propulsion Laboratory
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Suresh Vannan
Jet Propulsion Laboratory, California Institute of Technology
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Jinbo Wang
NASA Jet Propulsion Laboratory
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Mike Gangl
NASA Jet Propulsion Laboratory
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Frank Greguska
NASA Jet Propulsion Laboratory
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Cedric David
Jet Propulsion Laboratory
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Abstract

The Physical Oceanography Distributed Active Archive Center (PO.DAAC) has traditionally hosted NASA’s Earth Observing System oceanography datasets, but is expanding its archive to include hydrology datasets from satellites like the upcoming Surface Water and Ocean Topography (SWOT) mission. The SWOT mission, expected to launch later this year (2022), will deliver approximately 20 TB of data per day! Though hydrologic and water resources applications will be enabled at a greater scale than ever before, an increase in data volume requires more efficient and scalable data management technologies. Cloud computing tools and services can help pave the way toward efficiency. By June 2022, PO.DAAC will have enabled all its data to be accessed in the NASA Earthdata Cloud hosted in Amazon Web Services (AWS). Other NASA DAACs are also in the process of migrating their Earth observations to the Earthdata Cloud, which will support seamless access across DAACs and disciplines. PO.DAAC desires to make data access, pre-processing, and analysis as seamless as possible for data users, supporting science and applications users alike with relevant tools and resources. In this presentation, after introducing the PO.DAAC, we highlight a new SWOT-specific data search mechanism (searching via the SWOT River Database (SWORD) pre-defined river reaches) and showcase a cloud computing workflow in the context of hydrologic applications by accessing and analyzing a proxy SWOT dataset, Pre-SWOT Making Earth System Data Records for Use in Research Environments (MEaSUREs) river heights. This cloud workflow can be easily adapted to other PO.DAAC datasets, or further developed with other DAAC data, offering effective guidance and support for a variety of science use cases and applications.