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 Keldysh Institute preprints, 2018, 037, 17 pp. (Mi ipmp2399)

Analysis of the results of ocean dynamics modeling using various methods of assimilation of observational data

K. P. Belyaev, A. A. Kuleshov, I. N. Smirnov

Abstract: The paper presents the results of comparing the application of two different data assimilation methods. the method of generalized Kalman filtration (GKF) developed by the authors and standard objective ensemble interpolation method (EnOI) that is a partial case of extended Kalman filter scheme (EnKF). Those methods are applied in conjunction with the ocean dynamical model Hybrid Circulation Ocean Model (HYCOM). The methods are compared with respect to various criteria, in particular, with respect to minimum of the forecast error and with respect of a posterior error over a given time-interval. As observed data we used the Archiving Validating and Interpolating Satellite Observation (AVISO) i.e. altimetry data. It is shown that the method GKF has a number of advantages comparing with the method EnOI.

Keywords: ocean modelling, data assimilation, generalized Kalman filter, ensemble interpolation method, satellite altimetry data.

DOI: https://doi.org/10.20948/prepr-2018-37

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Citation: K. P. Belyaev, A. A. Kuleshov, I. N. Smirnov, “Analysis of the results of ocean dynamics modeling using various methods of assimilation of observational data”, Keldysh Institute preprints, 2018, 037, 17 pp.

Citation in format AMSBIB
\Bibitem{BelKulSmi18} \by K.~P.~Belyaev, A.~A.~Kuleshov, I.~N.~Smirnov \paper Analysis of the results of ocean dynamics modeling using various methods of assimilation of observational data \jour Keldysh Institute preprints \yr 2018 \papernumber 037 \totalpages 17 \mathnet{http://mi.mathnet.ru/ipmp2399} \crossref{https://doi.org/10.20948/prepr-2018-37} \elib{https://elibrary.ru/item.asp?id=32610434}