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Sensitivity of Functionals to Observation Data in a Variational Assimilation Problem for a Sea Thermodynamics Model

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Abstract

A mathematical model of sea thermodynamics, developed at the Institute of Numerical Mathematics of the Russian Academy of Sciences, is considered. A problem of variational assimilation of sea surface temperature data is studied with allowance for observational error covariance matrices. Based on variational assimilation of satellite observation data, an inverse problem of restoring the heat flux on the sea surface is solved. The sensitivity of some functionals to observation data in the variational assimilation problem is investigated, and the results of numerical experiments with the model applied to Baltic Sea dynamics are presented.

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Authors and Affiliations

  1. Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences, ul. Gubkina 8, Moscow, 119333, Russia

    V. P. Shutyaev & E. I. Parmuzin

  2. Marine Hydrophysical Institute, Russian Academy of Sciences, ul. Kapitanskaya 2, Sevastopol, 299011, Russia

    V. P. Shutyaev

Authors
  1. V. P. Shutyaev
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  2. E. I. Parmuzin
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Correspondence to V. P. Shutyaev or E. I. Parmuzin.

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Russian Text © The Author(s), 2019, published in Sibirskii Zhurnal Vychislitel’noi Matematiki, 2019, Vol. 22, No. 2, pp. 229–242.

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Shutyaev, V.P., Parmuzin, E.I. Sensitivity of Functionals to Observation Data in a Variational Assimilation Problem for a Sea Thermodynamics Model. Numer. Analys. Appl. 12, 191–201 (2019). https://doi.org/10.1134/S1995423919020083

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  • DOI: https://doi.org/10.1134/S1995423919020083

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