Abstract
For the model of ocean thermodynamics developed at the Institute of Numerical Mathematics of RAS, the problem of variational data assimilation is considered in order to restore heat fluxes on the ocean surface and initial state of the model. Iterative solution algorithms are proposed for the optimality system, justification of these algorithms is given based on properties of the control operator. The results of numerical experiments for the model of the Black Sea dynamics are presented.
Funding statement: The work was supported by the Russian Science Foundation (project 20–11–20057, in the part of research of Sections 2–4) and the Moscow Center for Fundamental and Applied Mathematics (agreement with the Ministry of Education and Science of the Russian Federation, No. 075–15–2019–1624).
References
[1] V. I. Agoshkov, Methods of Optimal Control and Adjoint Equations in Problems of Mathematical Physics INM RAS, Moscow, 2003 (in Russian).Search in Google Scholar
[2] V. I. Agoshkov, A. V. Gusev, N. A. Diansky, and R. V. Oleinikov, An algorithm for the solution of the ocean hydrothermo-dynamics problem with variational assimilation of the sea level function data. Russ. J. Numer. Anal. Math. Modelling 22 (2007), No. 2, 1–10.10.1515/RJNAMM.2007.007Search in Google Scholar
[3] V. I. Agoshkov, N. R. Lezina, E. I. Parmuzin, T. O. Sheloput, V. P. Shutyaev, and N. B. Zakharova, Methods of variational data assimilation with application to problems of hydrotermodenamics of marine water areas. Russ. J. Numer. Anal. Math. Modelling 35 (2020), No. 4, 189–202.10.1515/rnam-2020-0016Search in Google Scholar
[4] V. I. Agoshkov, E. I. Parmuzin, and V. P. Shutyaev, Numerical algorithm for variational assimilation of sea surface temperature data. Comput. Maths. Math. Phys. 48 (2008), No. 8, 1293–1312.10.1134/S0965542508080046Search in Google Scholar
[5] V. I. Agoshkov, E. I. Parmuzin, and V. P. Shutyaev, Observational data assimilation in the problem of Black Sea circulation and sensitivity analysis of its solution. Izvestiya, Atmospheric and Oceanic Physics 49 (2013), No. 6, 592–602.10.1134/S0001433813060029Search in Google Scholar
[6] V. V. Alekseev and V. B. Zalesny, Numerical model of large-scale ocean dynamics. In: Vychislitelnye Processy i Sistemy (Computational Processes and Systems), Nauka, Moscow, 1993, pp. 232–253.Search in Google Scholar
[7] M. Asch, M. Bocquet, and M. Nodet, Data Assimilation: Methods, Algorithms, and Applications SIAM, Philadelphia, 2016.10.1137/1.9781611974546Search in Google Scholar
[8] A. Carrassi, M. Bocquet, L. Bertino, and G. Evensen, Data assimilation in the geosciences: An overview of methods, issues, and perspectives. WIREs Clim. Change 9 (2018), No. 5, e535.10.1002/wcc.535Search in Google Scholar
[9] S. J. Fletcher, Data Assimilation for the Geosciences: from Theory to Application Elsevier, Amsterdam, Netherlands, 2017.10.1016/B978-0-12-804444-5.00023-4Search in Google Scholar
[10] F. X. Le Dimet and O. Talagrand, Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects. Tellus 38A (1986), 97–110.10.1111/j.1600-0870.1986.tb00459.xSearch in Google Scholar
[11] J. L. Lions, Contrôle optimal des systèmes gouvernés par des équations aux dérivées partielles Dunod, Paris, 1968.Search in Google Scholar
[12] V. I. Lebedev and S. A. Finogenov, The order of choice of iteration parameters in the cyclic Chebyshev iteration method. USSR Comput. Maths. Math. Phys. 11 (1971) No. 2, 155–170.10.1016/0041-5553(71)90169-8Search in Google Scholar
[13] E. A. Lupyan, A. A. Matveev, I. A. Uvarov, T. Yu. Bocharova, O. Yu. Lavrova, and M. I. Mityagina, ‘See the Sea’ satellite service, instrument for studying processes and phenomena on the ocean surface. In: Sovremennye Problemy Distantsionnogo Zondirovaniya Zemli iz KosmosaProblems in Remote Sensing of the Earth from Space 9 (2012), No. 2, 251–261.Search in Google Scholar
[14] G. I. Marchuk, Adjoint Equations and Analysis of Complex Systems Kluwer, Dordrecht, 1995.10.1007/978-94-017-0621-6Search in Google Scholar
[15] G. I. Marchuk, V. P. Dymnikov and V. B. Zalesny, Mathematical Models in Geophysical Hydrodynamics and Numerical Methods of their Implementation Gidrometeoizdat, Leningrad, 1987 (in Russian).Search in Google Scholar
[16] G. I. Marchuk and V. I. Lebedev, Numerical Methods in the Theory of Neutron Transport Harwood Academic Publ., New York, 1986.Search in Google Scholar
[17] V. V. Penenko, Numerical Modelling Methods for Atmospheric Processes Gidrometeoizdat, Leningrad, 1981 (in Russian).Search in Google Scholar
[18] V. Penenko and N. N. Obraztsov, A variational initialization method for the fields of the meteorological elements. Soviet Meteorol. Hydrol. 11 (1976), 1–11.Search in Google Scholar
[19] Y. K. Sasaki, An objective analysis based on the variational method. J. Meteor. Soc. Japan 36 (1958), 77–88.10.2151/jmsj1923.36.3_77Search in Google Scholar
[20] V. P. Shutyaev, Control Operators and Iterative Algorithms in Problems of Variational Data Assimilation Nauka, Moscow, 2001 (in Russian).10.1515/jiip.2001.9.2.177Search in Google Scholar
[21] V. P. Shutyaev, Adjoint equations in variational data assimilation problems. Russ. J. Numer. Anal. Math. Modelling 33 (2018), No. 2, 137–147.10.1515/rnam-2018-0012Search in Google Scholar
[22] V. P. Shutyaev, Methods for observation data assimilation in problems of physics of atmosphere and ocean. Izvestiya, Atmospheric and Oceanic Physics 55 (2019), No. 1, 17–31.10.1134/S0001433819010080Search in Google Scholar
[23] A. N. Tikhonov, On solution of ill-posed problems and regularization method. Doklady Akad. Nauk SSSR 151 (1963), No. 3, 501–504.Search in Google Scholar
[24] V. B. Zalesny, N. F. Diansky, V. V. Fomin, S. N. Moshonkin, and S. G. Demyshev, Numerical model of the circulation of the Black Sea and the Sea of Azov. Russ. J. Numer. Anal. Math. Modelling 27 (2012), No. 1, 95–112.10.1515/rnam-2012-0006Search in Google Scholar
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Articles in the same Issue
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- Numerical model of gravity segregation of two-phase fluid in porous media based on hybrid upwinding
- Numerical stochastic modelling of spatial and spatio-temporal fields of the wind chill index in the South of Western Siberia
- Numerical solution of the problem of variational data assimilation to restore heat fluxes and initial state for the ocean thermodynamics model
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Articles in the same Issue
- Frontmatter
- Single and multiple springback technique for construction and control of thick prismatic mesh layers
- Numerical model of gravity segregation of two-phase fluid in porous media based on hybrid upwinding
- Numerical stochastic modelling of spatial and spatio-temporal fields of the wind chill index in the South of Western Siberia
- Numerical solution of the problem of variational data assimilation to restore heat fluxes and initial state for the ocean thermodynamics model
- Corrigendum to: Mathematical immunology: from phenomenological to multiphysics modelling