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| Author | Armstrong, E. M.; Bourassa, M. A.; Cram, T.; Elya, J. L.; Greguska, F. R., III; Huang, T.; Jacob, J. C.; Ji, Z.; Jiang, Y.; Li, Y.; McGibbney, L. J.; Quach, N.; Smith, S. R.; Tsontos, V. M.; Wilson, B. D.; Worley, S. J.; Yang, C. P. | ||||
| Title | An information technology foundation for fostering interdisciplinary oceanographic research and analysis | Type | $loc['typeAbstract'] | ||
| Year | 2018 | Publication | American Geophysical Union | Abbreviated Journal | AGU |
| Volume | Fall Meeting | Issue | Pages | ||
| Keywords | 1914 Data mining, INFORMATICSDE: 4805 Biogeochemical cycles, processes, and modeling, OCEANOGRAPHY: BIOLOGICAL AND CHEMICALDE: 4273 Physical and biogeochemical interactions, OCEANOGRAPHY: GENERALDE: 4504 Air/sea interactions, OCEANOGRAPHY: PHYSICAL | ||||
| 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. | ||||
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| Call Number | COAPS @ user @ | Serial | 1004 | ||
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| Author | Bourassa, M.A.; Freilich, M.H.; Legler, D.M.; Liu, W.T.; O'Brien, J.J. | ||||
| Title | Wind observations from new satellite and research vessels agree | Type | $loc['typeJournal'] | ||
| Year | 1997 | Publication | Eos, Transactions American Geophysical Union | Abbreviated Journal | Eos Trans. AGU |
| Volume | 78 | Issue | 51 | Pages | 597 |
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| ISSN | 0096-3941 | ISBN | Medium | ||
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| Call Number | COAPS @ mfield @ | Serial | 726 | ||
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| Author | Gille, S.; Bourassa, M.A.; Clayson, C.A. | ||||
| Title | Improving Observations of High-Latitude Fluxes Between Atmosphere, Ocean, and Ice: Surface Fluxes: Challenges at High Latitudes; Boulder, Colorado, 17-19 March 2010 | Type | $loc['typeMagazine Article'] | ||
| Year | 2010 | Publication | Eos, Transactions American Geophysical Union | Abbreviated Journal | Eos Trans. AGU |
| Volume | 91 | Issue | 35 | Pages | 307 |
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| ISSN | 0096-3941 | ISBN | Medium | ||
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| Call Number | COAPS @ mfield @ | Serial | 379 | ||
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| Author | Gould, W.J.; Smith, S.R. | ||||
| Title | Research vessels: Underutilized assets for climate observations | Type | $loc['typeJournal Article'] | ||
| Year | 2006 | Publication | Eos, Transactions American Geophysical Union | Abbreviated Journal | Eos Trans. AGU |
| Volume | 87 | Issue | 22 | Pages | 214 |
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| Funding | NOAA | Approved | $loc['no'] | ||
| Call Number | COAPS @ mfield @ | Serial | 710 | ||
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| Author | Hanson, H.P.; Bozek, A.; Duerr, A.E.S. | ||||
| Title | The Florida Current: A clean but challenging energy resource | Type | $loc['typeJournal Article'] | ||
| Year | 2011 | Publication | Eos, Transactions American Geophysical Union | Abbreviated Journal | Eos Trans. AGU |
| Volume | 92 | Issue | 4 | Pages | 29 |
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| Call Number | COAPS @ mfield @ | Serial | 323 | ||
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| Author | Jacob, J. C.; Armstrong, E. M.; Bourassa, M. A.; Cram, T.; Elya, J. L.; Greguska, F. R., III; Huang, T.; Ji, Z.; Jiang, Y.; Li, Y.; McGibbney, L. J.; Quach, N.; Smith, S. R.; Tsontos, V. M.; Wilson, B. D.; Worley, S. J.; Yang, C. P. | ||||
| Title | OceanWorks: Enabling Interactive Oceanographic Analysis in the Cloud with Multivariate Data | Type | $loc['typeAbstract'] | ||
| Year | 2018 | Publication | American Geophysical Union | Abbreviated Journal | AGU |
| Volume | Fall Meeting | Issue | Pages | ||
| Keywords | 910 Data assimilation, integration and fusion, INFORMATICSDE: 1916 Data and information discovery, INFORMATICSDE: 1926 Geospatial, INFORMATICSDE: 1942 Machine learning, INFORMATICS | ||||
| Abstract | NASA's Advanced Information System Technology (AIST) Program sponsors the OceanWorks project to establish an integrated data analytics center at the Physical Oceanography Distributed Active Archive Center (PO.DAAC). OceanWorks provides a series of interoperable capabilities that are essential for cloud-scale oceanographic research. These include big data analytics, data search with subsecond response, intelligent ranking of search results, subsetting based on data quality metrics, and rapid spatiotemporal matchup of satellite measurements with distributed in situ data. The software behind OceanWorks is being developed as an open source project in the Apache Incubator Science Data Analytics Platform (SDAP – http://sdap.apache.org). In this presentation we describe how OceanWorks enables efficient, scalable, interactive and interdisciplinary oceanographic analysis with multivariate data. Interactivity is enabled by a number of SDAP features. First, SDAP provides Representational State Transfer (REST) interfaces to a number of built-in cloud analytics to compute time series, time-averaged maps, correlation maps, climatological maps, Hovmöller maps, and more. To access these, users simply navigate to a properly constructed parameterized URL in their web browser or issue web services calls in a variety of programming languages or in a Jupyter notebook. Alternatively, Python clients can make function calls via the NEXUS Command Line Interface (CLI). Authenticated users can even inject their own custom code via REST calls or the CLI. To enable interdisciplinary science, OceanWorks provides access to a rich collection of multivariate satellite and in situ measurements of the oceans (e.g., sea surface temperature, height and salinity, chlorophyll and circulation) and other Earth science data (e.g., aerosol optical depth and wind speed), coupled with on-demand processing capabilities close to the data. We partition the data across space or time into tiles and store them into cloud-aware databases that are collocated with the computations. We will provide examples of scientific studies directly enabled by OceanWorks' multivariate data and cloud analytics. |
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| Call Number | COAPS @ user @ | Serial | 1005 | ||
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| Author | Meyers, S.D.; O'Brien, J.J. | ||||
| Title | Pacific Ocean influences atmospheric carbon dioxide | Type | $loc['typeJournal Article'] | ||
| Year | 1995 | Publication | Eos, Transactions American Geophysical Union | Abbreviated Journal | Eos Trans. AGU |
| Volume | 76 | Issue | 52 | Pages | 533-533 |
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| ISSN | 0096-3941 | ISBN | Medium | ||
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| Call Number | COAPS @ mfield @ | Serial | 716 | ||
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| Author | Morey, S. L.; Wienders, N.; Dukhovskoy, D. S.; Bourassa, M. A. | ||||
| Title | Impact of Stokes Drift on Measurements of Surface Currents from Drifters and HF Radar | Type | $loc['typeAbstract'] | ||
| Year | 2018 | Publication | American Geophysical Union | Abbreviated Journal | AGU |
| Volume | Fall Meeting | Issue | Pages | ||
| Keywords | 3307 Boundary layer processes, ATMOSPHERIC PROCESSESDE: 4504 Air/sea interactions, OCEANOGRAPHY: PHYSICALDE: 4560 Surface waves and tides, OCEANOGRAPHY: PHYSICALDE: 4572 Upper ocean and mixed layer processes, OCEANOGRAPHY: PHYSICAL | ||||
| Abstract | Concurrent measurements by surface drifters of different configurations and HF radar reveal substantial differences in estimates of the near-surface seawater velocity. On average, speeds of small ultra-thin (5 cm) drifters are significantly greater than co-located drifters with a traditional shallow drogue design, while velocity measurements from the drogued drifters closely match HF radar velocity estimates. Analysis of directional wave spectra measurements from a nearby buoy reveals that Stokes drift accounts for much of the difference between the velocity measurements from the drogued drifters and the ultra-thin drifters, except during times of wave breaking. Under wave breaking conditions, the difference between the ultra-thin drifter velocity and the drogued drifter velocity is much less than the computed Stokes drift. The results suggest that surface currents measured by more common approaches or simulated in models may underrepresent the velocity at the very surface of the ocean that is important for determining momentum and enthalpy fluxes between the ocean and atmosphere and for estimating transport of material at the ocean surface. However, simply adding an estimate of Stokes drift may also not be an appropriate method for estimating the true surface velocity from models or measurements from drogued drifters or HF radar under all sea conditions. | ||||
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| Call Number | COAPS @ user @ | Serial | 1008 | ||
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| Author | Morrison, T.; Dukhovskoy, D. S.; McClean, J.; Gille, S. T.; Chassignet, E. | ||||
| Title | Causes of the anomalous heat flux onto the Greenland continental shelf | Type | $loc['typeAbstract'] | ||
| Year | 2018 | Publication | American Geophysical Union | Abbreviated Journal | AGU |
| Volume | Fall Meeting | Issue | Pages | ||
| Keywords | 0726 Ice sheets, CRYOSPHEREDE: 4207 Arctic and Antarctic oceanography, OCEANOGRAPHY: GENERALDE: 4215 Climate and interannual variability, OCEANOGRAPHY: GENERALDE: 4255 Numerical modeling, OCEANOGRAPHY: GENERAL | ||||
| Abstract | On the continental shelf around Greenland, warm-salty Atlantic water at depth fills the deep narrow fjords where Greenland's tidewater glaciers terminate. Changes in the quantity or properties of this water mass starting in the mid 1990s is thought to be largely responsible for increased ocean-driven melting of the Greenland Ice Sheet. Using high-resolution (nominal 0.1-degree) ocean circulation models we cannot accurately resolve small-scale processes on the shelf or within fjords. However, we can assess changes in the flux of heat via Atlantic water onto the continental shelf. To understand the causes of the anomalous heat that has reached the shelf we examine heat content of subtropical gyre water and shifts in the North Atlantic and Atlantic Multidecadal Oscillations. We compare changes in heat transport in two eddy permitting simulations: a global 0.1 degree (5-7km around Greenland) resolution coupled hindcast (1970-2009) simulation of the Parallel Ocean Program (POP) and a regional 0.08 degree (3-5km around Greenland) resolution coupled HYbrid Coordinate Ocean Model (HYCOM) hindcast (1993-2016) simulation. Both models are coupled to the Los Alamos National Laboratory Community Ice CodE version 4 and forced by atmospheric reanalysis fluxes. In both models we look for processes that could explain the increase in heat; processes that are present in both are likely to be robust causes of warming. |
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| Call Number | COAPS @ user @ | Serial | 1009 | ||
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| Author | O'hara, S. H.; Arko, R. A.; Clark, D.; Chandler, C. L.; Elya, J. L.; Ferrini, V. L.; McLain, K.; Olson, C. J.; Sellers, C. J.; Smith, S. R.; Stocks, K. I.; Stolp, L.; Carbotte, S. M. | ||||
| Title | Rolling Deck to Repository (R2R) Program Data Services for the Oceanographic Research Community | Type | $loc['typeAbstract'] | ||
| Year | 2018 | Publication | American Geophysical Union | Abbreviated Journal | AGU |
| Volume | American Geophysical Union, Fall Meeting 2018 | Issue | Pages | ||
| Keywords | OCEANOGRAPHY: GENERAL | ||||
| Abstract | Research vessels supported by NSF are critical platforms contributing to academic oceanographic research in the US. The “underway” data sets obtained from the continuously operating geophysical, water column, and meteorological sensors aboard these vessels provide characterization of basic environmental conditions for the oceans and are of high scientific value for building global syntheses, climatologies, and historical time series of ocean properties (e.g the World Ocean Atlas, the GMRT bathymetric synthesis, ICOADS). The Rolling deck to Repository program (www.rvdata.us) provides a central shore-side data gateway that ensures the basic documentation, assessment and submission of all environmental data from ship operators to the NOAA long-term archives for these data. R2R provides a set of data services for the oceanographic research community, including: publishing an online, searchable and browsable master cruise catalog, supported by cruise and data set DOIs; organizing, archiving, and disseminating original underway data and documents; assessing data quality on select data types; creating select post-field data products; and supporting at-sea event logging. In this presentation we will discuss new developments in R2R data services and challenges associated with ship-based data management. A significant challenge is the dramatic increase in data volumes associated with new sensors (e.g. the EK80 Sonar systems) whereby individual cruise distributions can be several terabytes. Ship operators, R2R and NCEI must design a way to move and store these growing volumes. R2R is also working to make information more accessible and complete. A new website has been launched along with API web services that allow users to find and use data more easily. R2R is working to improve device metadata, including working to identify the time sources for all environmental sensors to support accurate comparison and merging of data sets. | ||||
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| Call Number | COAPS @ user @ | Serial | 1020 | ||
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