IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i19p2371-d642225.html
   My bibliography  Save this article

Generalized Kalman Filter and Ensemble Optimal Interpolation, Their Comparison and Application to the Hybrid Coordinate Ocean Model

Author

Listed:
  • Konstantin Belyaev

    (Shirshov Institute of Oceanology, Russian Academy of Sciences, 117997 Moscow, Russia)

  • Andrey Kuleshov

    (Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, 125047 Moscow, Russia)

  • Ilya Smirnov

    (Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, 119991 Moscow, Russia)

  • Clemente A. S. Tanajura

    (Physics Institute and Center for Research in Geophysics and Geology, Federal University of Bahia, Salvador 40170-280, Brazil)

Abstract

In this paper, we consider a recently developed data assimilation method, the Generalized Kalman Filter (GKF), which is a generalization of the widely-used Ensemble Optimal Interpolation (EnOI) method. Both methods are applied for modeling the Atlantic Ocean circulation using the known Hybrid Coordinate Ocean Model. The along-track altimetry data taken from the Archiving, Validating and Interpolating Satellite Oceanography Data (AVISO) were used for data assimilation and other data from independent archives of observations; particularly, the temperature and salinity data from the Pilot Research Array in the Tropical Atlantic were used for independent comparison. Several numerical experiments were performed with their results discussed and analyzed. It is shown that values of the ocean state variables obtained in the calculations using the GKF method are closer to the observations in terms of standard metrics in comparison with the calculations using the standard data assimilation method EnOI. Furthermore, the GKF method requires less computational effort compared to the EnOI method.

Suggested Citation

  • Konstantin Belyaev & Andrey Kuleshov & Ilya Smirnov & Clemente A. S. Tanajura, 2021. "Generalized Kalman Filter and Ensemble Optimal Interpolation, Their Comparison and Application to the Hybrid Coordinate Ocean Model," Mathematics, MDPI, vol. 9(19), pages 1-15, September.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:19:p:2371-:d:642225
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/19/2371/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/19/2371/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Konstantin Belyaev & Andrey Kuleshov & Natalia Tuchkova & Clemente A.S. Tanajura, 2018. "An optimal data assimilation method and its application to the numerical simulation of the ocean dynamics," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 24(1), pages 12-25, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhijun Li & Minxing Sun & Qianwen Duan & Yao Mao, 2022. "Robust State Estimation for Uncertain Discrete Linear Systems with Delayed Measurements," Mathematics, MDPI, vol. 10(9), pages 1-24, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Konstantin P. Belyaev & Andrey K. Gorshenin & Victor Yu. Korolev & Anastasiia A. Osipova, 2024. "Comparison of Statistical Approaches for Reconstructing Random Coefficients in the Problem of Stochastic Modeling of Air–Sea Heat Flux Increments," Mathematics, MDPI, vol. 12(2), pages 1-21, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:9:y:2021:i:19:p:2371-:d:642225. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.