Data Access and the ECCO Ocean and Ice State Estimate
Principal Investigator (PI): Patrick Heimbach, University Of Texas, Austin
The Estimating the Ocean Circulation and Climate (ECCO) global ocean state estimation system is the premier tool for synthesizing NASA's diverse Earth system observations into a complete physical description of Earth's time-evolving full-depth ocean and sea ice system. ECCO state estimates are of particular significance to NASA because on their own, all satellite observations, although global in coverage, remain sparse in space and time relative to the inherent scales of ocean variability, and are blind to the ocean's interior. With increased streams of data and better spatial resolution the scientific utility of the product is increasingly limited by (1) the inability to automate observing network ingestion and update in a rapid, robust manner, (2) the lack of tools for embedding the state estimate into NASA's Earth Observing System Data and Information System (EOSDIS) framework, and (3) the lack of capabilities to perform efficient online data analysis.
To overcome these hurdles we will develop and implement a production-ready cloud-native storage and data analysis system, called ECCO-Cloud, to manage the preprocessing and transformation of NASA Earth Science data and data products. The following three high-level goals will be accomplished:
I) expand and accelerate in a sustainable and scalable manner the integration of NASA Earth system data into ECCO through automated preprocessing and transformation;
II) radically streamline the integration of updated ECCO products into EOSDIS, specifically NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC)
III) facilitate and expand the scientific utilization of NASA remote sensing data integrated in ECCO by the growing community of interdisciplinary researchers in the oceanographic, sea-ice, sea level rise, and climate science fields.
The proposed work leverages (1) the latest ECCO ocean global state estimate, (2) new software tools developed to display, analyze, extract, subset, reproject, and download ocean physical parameters from the ECCO state estimate [temperature, salinity, currents, atmosphere-ocean heat fluxes, sea level, etc.], (3) experience in hosting and rapidly accessing the tens of gigabytes of binary output files that comprise the complete ECCO state estimate, and (4) new developments that now allow new simulations based on ECCO's Oceanic General Circulation Model (OGCM) to be run on the Amazon Elastic Compute Cloud (Amazon EC2).
Recently, progress has been made in the development of software tools that allow rapid online access (through pre-caching) and analysis of a subset of ECCO output via interactive web pages. These software tools were development for the "Sea Level Portal" (see https://sealevel.nasa.gov/data-analysis-tool). In the proposed project we intend to leverage and significantly extend these tools so that a much larger set, if not all, ECCO ocean parameters are made similarly available. The tools to access and conduct interactive analyses of these ocean parameters will be implemented on the ECCO's new website. Users will be provided links to the appropriate EOSDIS DAAC such as PO.DAAC and the National Snow and Ice Data Center DAAC (NSIDC DAAC) to access the original ocean and ice data products used in ECCO. This will also enable NASA's common access interface through the Earthdata enterprise Common Metadata Repository (CMR) and Earthdata Search (https://search.earthdata.nasa.gov) capability.
Finally, now that ECCO's OGCM has been ported to run on Amazon EC2, we will provide an online front-end for users so that they can (a) reproduce the full state estimate, and (b) formulate and conduct their own experimental simulations and then seamlessly analyze the output of those simulations using the same data analysis tools. We expect that the proposed work will contribute to fuller utilization of NASA Earth System data - especially ocean data and ECCO products - by the research community.
Last Updated: Jun 11, 2019 at 9:20 AM EDT