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An information technology foundation for fostering interdisciplinary oceanographic research and analysis
  • +14
  • Edward Armstrong,
  • Mark Bourassa,
  • Thomas Cram,
  • Jocelyn Elya,
  • Frank Greguska,
  • Thomas Huang,
  • Joseph Jacob,
  • Zaihua Ji,
  • Yongyao Jiang,
  • Yun Li,
  • Lewis McGibbney,
  • Nga Quach,
  • Shawn Smith,
  • Vardis Tsontos,
  • Brian Wilson,
  • Steven Worley,
  • Chaowei Phil Yang
Edward Armstrong
NASA Jet Propulsion Laboratory

Corresponding Author:[email protected]

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Mark Bourassa
Florida State Univ
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Thomas Cram
National Center for Atmospheric Research
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Jocelyn Elya
Florida State University
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Frank Greguska
NASA Jet Propulsion Laboratory
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Thomas Huang
Jet Propulsion Laboratory
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Joseph Jacob
Jet Propulsion Laboratory
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Zaihua Ji
Nat'l Ctr for Atmospheric Research
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Yongyao Jiang
George Mason University Fairfax
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Yun Li
George Mason University Fairfax
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Lewis McGibbney
NASA Jet Propulsion Laboratory
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Nga Quach
NASA Jet Propulsion Laboratory
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Shawn Smith
Florida State University
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Vardis Tsontos
NASA/JPL
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Brian Wilson
Jet Propulsion Laboratory
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Steven Worley
NCAR
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Chaowei Phil Yang
George Mason Univ.
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Abstract

Before complex analysis of oceanographic or any earth science data can occur, it must be placed in the proper domain of computing and software resources. In the past this was nearly always the scientist’s personal computer or institutional computer servers. The problem with this approach is that it is necessary to bring the data products directly to these compute resources leading to large data transfers and storage requirements especially for high volume satellite or model datasets. In this presentation we will present a new technological solution under development and implementation at the NASA Jet Propulsion Laboratory for conducting oceanographic and related research based on satellite data and other sources. Fundamentally, our approach for satellite resources is to tile (partition) the data inputs into cloud-optimized and computation friendly databases that allow distributed computing resources to perform on demand and server-side computation and data analytics. This technology, known as NEXUS, has already been implemented in several existing NASA data portals to support oceanographic, sea-level, and gravity data time series analysis with capabilities to output time-average maps, correlation maps, Hovmöller plots, climatological averages and more. A further extension of this technology will integrate ocean in situ observations, event-based data discovery (e.g., natural disasters), data quality screening and additional capabilities. This particular activity is an open source project known as the Apache Science Data Analytics Platform (SDAP) (https://sdap.apache.org), and colloquially as OceanWorks, and is funded by the NASA AIST program. It harmonizes data, tools and computational resources for the researcher allowing them to focus on research results and hypothesis testing, and not be concerned with security, data preparation and management. We will present a few oceanographic and interdisciplinary use cases demonstrating the capabilities for characterizing regional sea-level rise, sea surface temperature anomalies, and ocean hurricane responses.