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    State and parameter estimation with extended Kalman Filter. An alternative formulation of the model error dynamics.

    Authors
    Carrassi, A.
    Vannitsem, S.
    Discipline
    Earth and related Environmental sciences
    Subject
    Kalman filter
    ST-AEKF
    short-time Taylor
    Lorenz 36-variable model
    Audience
    General Public
    Scientific
    Date
    2011
    Publisher
    IRM
    KMI
    RMI
    Metadata
    Show full item record
    Description
    An alternative formulation of the extended Kalman filter for state and parameter estimation is presented, referred to as Short-Time Augmented Extended Kalman Filter (ST-AEKF). In this algorithm, the evolution of the model error generated by the uncertain parameters is described using a truncated short-time Taylor expansion within the assimilation interval. This allows for a simplification of the forward propagation of the augmented error covariance matrix with respect to the classical state augmented approach. The algorithm is illustrated in the case of a scalar unstable dynamics and is then more extensively analyzed in the context of the Lorenz 36-variable model. The results demonstrate the ability of the ST-AEKF to provide accurate estimate of both the system's state and parameters with a skill comparable to that of the full state augmented approach and in some cases close to the EKF in a perfect model scenario. The performance of the filter is analyzed for different initial parametric errors and assimilation intervals, and for the estimates of one or more model parameters. The filter accuracy is sensitive to the nature of the estimated parameter but more importantly to the assimilation interval, a feature connected to the short-time approximation on which the filter formulation relies. The conditions and the context of applications of the present approach are also discussed. Copyright © 2011 Royal Meteorological Society
    Citation
    Carrassi, A.; Vannitsem, S. (2011). State and parameter estimation with extended Kalman Filter. An alternative formulation of the model error dynamics.. , Issue Q. J. Royal Met. Soc.; 137, 435-451, IRM,
    Identifiers
    uri: https://orfeo.belnet.be/handle/internal/8883
    Type
    Article
    Peer-Review
    Not pertinent
    Language
    eng
    Links
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