Sequential data assimilation

Information fusion of a numerical simulation and large scale observation data

Kazuyuki Nakamura, Tomoyuki Higuchi, Naoki Hirose

    Research output: Contribution to journalArticle

    18 Citations (Scopus)

    Abstract

    Data assimilation is a method of combining an imperfect simulation model and a number of incomplete observation data. Sequential data assimilation is a data assimilation in which simulation variables are corrected at every time step of observation. The ensemble Kalman filter is developed for a sequential data assimilation and frequently used in geophysics. On the other hand, the particle filter developed and used in statistics is similar in view of ensemble-based method, but it has different properties. In this paper, these two ensemble based filters are compared and characterized through matrix representation. An application of sequential data assimilation to tsunami simulation model with a numerical experiment is also shown. The particle filter is employed for this application. An erroneous bottom topography is corrected in the numerical experiment, which demonstrates that the particle filter is useful tool as the sequential data assimilation method.

    Original languageEnglish
    Pages (from-to)608-626
    Number of pages19
    JournalJournal of Universal Computer Science
    Volume12
    Issue number6
    Publication statusPublished - 2006

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    Data Assimilation
    Information fusion
    Information Fusion
    Numerical Simulation
    Geophysics
    Tsunamis
    Computer simulation
    Particle Filter
    Kalman filters
    Topography
    Experiments
    Statistics
    Simulation Model
    Ensemble
    Numerical Experiment
    Ensemble Kalman Filter
    Tsunami
    Matrix Representation
    Imperfect
    Observation

    All Science Journal Classification (ASJC) codes

    • Computer Science(all)

    Cite this

    Sequential data assimilation : Information fusion of a numerical simulation and large scale observation data. / Nakamura, Kazuyuki; Higuchi, Tomoyuki; Hirose, Naoki.

    In: Journal of Universal Computer Science, Vol. 12, No. 6, 2006, p. 608-626.

    Research output: Contribution to journalArticle

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