IN002-04
Using Cloud and On-Premise PO.DAAC and ESDIS Data and Services for Ocean and Hydrology Studies.

Monday, 7 December 2020: 07:12
Virtual
Catalina M Oaida1, Cassandra Nickles2, Jessica Hausman3, Edward M Armstrong3, Jack McNelis4, Mike Gangl5 and Suresh Vannan3, (1)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (2)Northeastern University, Boston, MA, United States, (3)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States, (4)NASA Jet Propulsion Laboratory, PO.DAAC, Pasadena, United States, (5)NASA Jet Propulsion Laboratory, Pasadena, United States
Recorded Presentation
Abstract:
The Physical Oceanography Distributed Active Archive Center (PO.DAAC), NASA’s archive for oceanographic data, is migrating its services and data to the cloud, and broadening its scope to include future terrestrial hydrosphere satellite data products. Guiding users through this transition is of utmost importance. In this session we will demo recent developments by PO.DAAC and Earth Science Data and Information System (ESDIS) Project that enable science and application exploratory analysis workflows in both the traditional “download and analyze” paradigm and “analysis in place” use case.

Using a mixture of on-premise and cloud data products from multiple missions hosted by PO.DAAC, we created a Python tutorial in Jupyter Notebooks to highlight a practical use case that analyzes seasonal impacts on the interface between the ocean and terrestrial hydrosphere, a coastal application in the Amazon River estuary. The tutorial analyzes relationships between six data products from five missions: GRACE-FO land water equivalent thickness, MEaSUREs Pre-SWOT river height virtual gauges, SMAP and Aquarius sea surface salinity, and MODIS sea surface temperature and chlorophyll. A second Jupyter Notebook will demo an analysis-in-place oceanography workflow using ESDIS transformation services to leverage cloud-optimized formats (e.g. Zarr) for analysis-ready data. For those less familiar with the cloud, an ESDIS Cloud Primer will be publicly available, which complements in-cloud data applications.

These tutorials, which will be made publicly available through Github, facilitate data ease of access and provide common methods for data discovery, visualization, transformations and exploratory analysis, providing a starting point for end users to develop ground-breaking research and applications use cases. They leverage cloud-based data, tools and API approaches. Challenges, opportunities and the roadmap for future cloud-based data and data services will also be discussed.

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