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Sibirskii Zhurnal Vychislitel'noi Matematiki, 2019, Volume 22, Number 2, Pages 229–242
DOI: https://doi.org/10.15372/SJNM20190208
(Mi sjvm712)
 

This article is cited in 7 scientific papers (total in 7 papers)

Sensitivity of functionals to observation data in a variational assimilation problem for the sea thermodynamics model

V. P. Shutyaevab, E. I. Parmuzina

a Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences, ul. Gubkina 8, Moscow, 119333 Russia
b Marine Hydrophysical Institute, Russian Academy of Sciences, ul. Kapitanskaya 2, Sevastopol, 299011 Russia
References:
Abstract: For the mathematical model of the sea thermodynamics, developed in the Institute of Numerical Mathematics of the Russian Academy of Sciences, the problem of variational assimilation of the sea surface temperature data is considered, with allowance for the observation data error covariance matrices. Based on the variational assimilation of satellite observation data, the inverse problem of restoring a heat flux on the sea surface is solved. The sensitivity of functionals with respect to observation data in a problem of variational assimilation is studied, and the results of numerical experiments for the model of the Baltic Sea dynamics are presented.
Key words: variational data assimilation, optimal control, adjoint equations, covariance matrices, sensitivity of functionals, sea surface temperature.
Funding agency Grant number
Russian Science Foundation 17-77-30001
Russian Foundation for Basic Research 18-01-00267_а
This work was supported by Russian Science Foundation (project no. 17-77-30001, for Sections 2 and 3) and the Russian Foundation for Basic Research (project no. 18-01-00267, for the numerical calculations).
Received: 25.04.2018
Revised: 20.06.2018
Accepted: 21.01.2019
English version:
Numerical Analysis and Applications, 2019, Volume 12, Issue 2, Pages 191–201
DOI: https://doi.org/10.1134/S1995423919020083
Bibliographic databases:
Document Type: Article
UDC: 519.6, 551.46
Language: Russian
Citation: V. P. Shutyaev, E. I. Parmuzin, “Sensitivity of functionals to observation data in a variational assimilation problem for the sea thermodynamics model”, Sib. Zh. Vychisl. Mat., 22:2 (2019), 229–242; Num. Anal. Appl., 12:2 (2019), 191–201
Citation in format AMSBIB
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Linking options:
  • https://www.mathnet.ru/eng/sjvm712
  • https://www.mathnet.ru/eng/sjvm/v22/i2/p229
  • This publication is cited in the following 7 articles:
    1. V. P. Shutyaev, E. I. Parmuzin, “Chuvstvitelnost funktsionalov k vkhodnym dannym v zadache variatsionnogo usvoeniya dlya modeli termodinamiki morya”, Sib. zhurn. vychisl. matem., 27:1 (2024), 97–112  mathnet  crossref
    2. V. P. Shutyaev, E. I. Parmuzin, “Sensitivity of Functionals to Input Data in a Variational Assimilation Problem for a Sea Thermodynamics Model”, Numer. Analys. Appl., 17:1 (2024), 80  crossref
    3. Victor P. Shutyaev, Eugene I. Parmuzin, Igor Yu. Gejadze, “The study of the local sensitivity of functionals of the optimal solution to observational data and the heat flux input data in a variational assimilation problem for the sea thermodynamics model”, Russian Journal of Numerical Analysis and Mathematical Modelling, 38:6 (2023), 381  crossref
    4. Kochergin Vladimir Sergeevich, Kochergin Sergey Vladimirovich, Springer Geology, Processes in GeoMedia—Volume IV, 2022, 17  crossref
    5. Victor P. Shutyaev, Eugene I. Parmuzin, “Sensitivity of functionals of the solution to a variational data assimilation problem with heat flux reconstruction for the sea thermodynamics model”, Russian Journal of Numerical Analysis and Mathematical Modelling, 37:6 (2022), 373  crossref
    6. V. P. Shutyaev, E. I. Parmuzin, “Sensitivity of functionals of the solution of a variational data assimilation problem with simultaneous reconstruction of heat fluxes and the initial state for the sea thermodynamics model”, Num. Anal. Appl., 13:4 (2020), 382–392  mathnet  crossref  crossref  isi
    7. V V Penenko, E A Tsvetova, “Inverse problems for the study of climatic and ecological processes under anthropogenic influences”, IOP Conf. Ser.: Earth Environ. Sci., 386:1 (2019), 012036  crossref
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