Morrison, T., Dukhovskoy, D. S., McClean, J., Gille, S. T., & Chassignet, E. (2018). Causes of the anomalous heat flux onto the Greenland continental shelf. In
American Geophysical Union (Vol. Fall Meeting).
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.
O'hara, S. H., Arko, R. A., Clark, D., Chandler, C. L., Elya, J. L., Ferrini, V. L., et al. (2018). Rolling Deck to Repository (R2R) Program Data Services for the Oceanographic Research Community. In
American Geophysical Union (Vol. American Geophysical Union, Fall Meeting 2018).
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.
Zheng, Y., Bourassa, M. A., & Dukhovskoy, D. S. (2018). Upper-Ocean Processes Controlling the Sea Surface Temperature in the Western Gulf of Mexico. In
American Geophysical Union (Vol. Fall Meeting).
Abstract: This study examines the upper-ocean processes controlling the mixed layer temperature in the western Gulf of Mexico (GOM) through estimating the contributing terms in the heat equation, with an emphasis on eddies' role. The major heat contributing terms for the upper GOM were estimated using two ocean reanalysis datasets: an eddy-resolving HYbrid Coordinate Ocean Model (HYCOM) and a Simple Ocean Data Assimilation (SODA). Analysis of net surface heat fluxes from four datasets reveals that the long-term mean net surface heat flux cools the northern GOM and warms the southern GOM. Two regions are focused for analysis: an eddy-rich region where LCEs are energetic, and the southwestern Gulf where eddy activity is relatively weak and the features of near surface temperature differ from the eddy-rich region. An eddy-rich region in the western GOM is defined based on the eddy kinetic energy derived from satellite sea surface heights. The long-term mean horizontal heat advection causes a weak warming over most of the eddy rich region, partly attributed to the flow-temperature configuration that the long-term and seasonally mean flow is nearly parallel to the corresponding mean isotherms. By contrast, the temporal mean vertical heat advection causes a strong warming in the eddy rich region, partly balancing the cooling caused by net surface heat flux. The temporal mean eddy heat flux convergence in the western GOM, whose positive and negative values are not small at some locations, appears heterogeneous in space, resulting in a small term for the western GOM when area averaged. The persistent warm water in the southwestern Gulf is primarily caused by the net warming from net surface heat flux rather than from eddies and heat advection.
Jacob, J. C., Armstrong, E. M., Bourassa, M. A., Cram, T., Elya, J. L., Greguska, F. R., III, et al. (2018). OceanWorks: Enabling Interactive Oceanographic Analysis in the Cloud with Multivariate Data. In
American Geophysical Union (Vol. Fall Meeting).
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.
Hernandez, F., Bertino, L., Brassington, G., Chassignet, E., Cummings, james, Davidson, F., et al. (2009). Validation and Intercomparison Studies Within GODAE.
Oceanog., 22(3), 128–143.
Chassignet, E., Hurlburt, H., Metzger, E. J., Smedstad, O., Cummings, J., Halliwell, G., et al. (2009). US GODAE: Global Ocean Prediction with the HYbrid Coordinate Ocean Model (HYCOM).
Oceanog., 22(2), 64–75.
Özgökmen, T., Chassignet, E., Dawson, C., Dukhovskoy, D., Jacobs, G., Ledwell, J., et al. (2016). Over What Area Did the Oil and Gas Spread During the 2010 Deepwater Horizon Oil Spill?
Oceanog, 29(3), 96–107.
Bourassa, M., Gille, S., Jackson, D., Roberts, J. B., & Wick, G. (2010). Ocean Winds and Turbulent Air-Sea Fluxes Inferred From Remote Sensing.
Oceanog., 23(4), 36–51.
Cornillon, P., Adams, J., Blumenthal, M. B., Chassignet, E., Davis, E., Hankin, S., et al. (2009). NVODS and the Development of OPeNDAP.
Oceanog., 22(2), 116–127.
Hurlburt, H., Brassington, G., Drillet, Y., Kamachi, M., Benkiran, M., Bourdallé-Badie, R., et al. (2009). High-Resolution Global and Basin-Scale Ocean Analyses and Forecasts.
Oceanog., 22(3), 110–127.