• DocumentCode
    2698135
  • Title

    Ensemble Data Assimilation Simulation Experiments for the Coastal Ocean: Impact of Different Observed Variables

  • Author

    Hoffman, R. ; Ponte, R.M. ; Kostelich, E. ; Blumberg, A. ; Szunyogh, I. ; Vinogradov, S.V.

  • Author_Institution
    Atmos. & Environ. Res., Inc., Lexington, MA
  • Volume
    5
  • fYear
    2008
  • fDate
    7-11 July 2008
  • Abstract
    A coastal ocean data assimilation system tested in simulation earlier is examined for sensitivity to the different types of observational data. The system couples an advanced ensemble Kalman filter algorithm to a detailed and sophisticated primitive equations coastal ocean model. It is found that assimilating only one type of data, say temperature, greatly slows down the approach to asymptotic behavior of the analysis of the other variables. Assimilating temperature alone does not help to infer salinity and vice versa.
  • Keywords
    Kalman filters; data assimilation; geophysical signal processing; ocean temperature; oceanographic techniques; seawater; sensitivity analysis; ensemble Kalman filter algorithm; ensemble data assimilation simulation; ocean temperature; primitive equations coastal ocean model; salinity; sensitivity analysis; Atmospheric modeling; Data assimilation; Error analysis; Filtering; Kalman filters; Mathematics; Ocean temperature; Sea measurements; Sea surface; Statistics; Kalman filtering; coastal ocean model; data assimilation; data impact;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International
  • Conference_Location
    Boston, MA
  • Print_ISBN
    978-1-4244-2807-6
  • Electronic_ISBN
    978-1-4244-2808-3
  • Type

    conf

  • DOI
    10.1109/IGARSS.2008.4780123
  • Filename
    4780123