• DocumentCode
    1790492
  • Title

    Issues and progress in the prediction of ocean submesoscale features and internal waves

  • Author

    Duda, Timothy F. ; Zhang, Weifeng Gordon ; Helfrich, Karl R. ; Newhall, Arthur E. ; Lin, Yan-Tin ; Lynch, James F. ; Lermusiaux, Pierre F. J. ; Haley, P.J. ; Wilkin, John

  • Author_Institution
    Appl. Ocean Phys. & Eng. Dept., Woods Hole Oceanogr. Instn., Woods Hole, MA, USA
  • fYear
    2014
  • fDate
    14-19 Sept. 2014
  • Firstpage
    1
  • Lastpage
    9
  • Abstract
    Data-constrained dynamical ocean modeling for the purpose of detailed forecasting and prediction continues to evolve and improve in quality. Modeling methods and computational capabilities have each improved. The result is that mesoscale phenomena can be modeled with skill, given sufficient data. However, many submesoscale features are less well modeled and remain largely unpredicted from a deterministic event standpoint, and possibly also from a statistical property standpoint. A multi-institution project is underway with goals of uncovering more of the details of a few submesoscale processes, working toward better predictions of their occurrence and their variability. A further component of our project is application of the new ocean models to ocean acoustic modeling and prediction. This paper focuses on one portion of the ongoing work: Efforts to link nonhydrostatic-physics models of continental-shelf nonlinear internal wave evolution to data-driven regional models. Ocean front-related effects are also touched on.
  • Keywords
    ocean waves; oceanographic techniques; underwater sound; computational capabilities; continental-shelf nonlinear internal wave evolution; data-constrained dynamical ocean modeling; data-driven regional models; deterministic event standpoint; mesoscale phenomena; multiinstitution project; nonhydrostatic-physics models; ocean acoustic modeling; ocean acoustic prediction; ocean front-related effects; ocean submesoscale features; statistical property standpoint; Acoustics; Computational modeling; Data models; Mathematical model; Predictive models; Tides; Ocean modeling; dynamical modeling; internal tides; internal waves; nonlinear waves; ocean prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Oceans - St. John's, 2014
  • Conference_Location
    St. John´s, NL
  • Print_ISBN
    978-1-4799-4920-5
  • Type

    conf

  • DOI
    10.1109/OCEANS.2014.7003282
  • Filename
    7003282