Variational data assimilation for a sea dynamics model-Reference-Cited by-同舟云学术

Variational data assimilation for a sea dynamics model

Published:2022-06-01 Issue:3 Volume:37 Page:131-142
ISSN:0927-6467
Container-title:Russian Journal of Numerical Analysis and Mathematical Modelling
language:en
Short-container-title:

Author:

Agoshkov Valery¹²,Zalesny Vladimir¹,Shutyaev Victor¹³,Parmuzin Eugene¹³,Zakharova Natalia¹

Affiliation:

1. Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences , Moscow , Russia

2. Lomonosov Moscow State University , Moscow , Russia

3. Moscow Institute of Physics and Technology , Dolgoprudny , Russia

Abstract

Abstract The 4D variational data assimilation technique is presented for modelling the sea dynamics problems, developed at the Marchuk Institute of Numerical Mathematics of the Russian Academy of Sciences (INM RAS). The approach is based on the splitting method for the mathematical model of sea dynamics and the minimization of cost functionals related to the observation data by solving an optimality system that involves the adjoint equations and observation and background error covariances. Efficient algorithms for solving the variational data assimilation problems are presented based on iterative processes with a special choice of iterative parameters. The technique is illustrated for the Black Sea dynamics model with variational data assimilation to restore the sea surface heat fluxes.

Publisher

Walter de Gruyter GmbH

Subject

Modeling and Simulation,Numerical Analysis

Link

https://www.degruyter.com/document/doi/10.1515/rnam-2022-0011/pdf

Reference30 articles.

1. V. I. Agoshkov, Methods of Optimal Control and Adjoint Equations in Problems of Mathematical Physics. INM RAS, Moscow, 2003 (in Russian).

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, 133–161.

3. V. I. Agoshkov, E. I. Parmuzin, and V. P. Shutyaev, Numerical algorithm for variational assimilation of sea surface temperature data. Comp. Math. and Math. Physics 48 (2008), 1293–1312.

4. V. I. Agoshkov, E. I. Parmuzin, V. B. Zalesny, V. P. Shutyaev, N. B. Zakharova, and A. V. Gusev, Variational assimilation of observation data in the mathematical model of the Baltic Sea dynamics. Russ. J. Numer. Anal. Math. Modelling 30 (2015), No. 4, 203–212.

5. V. I. Agoshkov, V. B. Zalesny, E. I. Parmuzin, V. P. Shutyaev, and V. M. Ipatova, Problems of variational assimilation of observational data for ocean general circulation models and methods for their solution. Izv. Atmos. Ocean. Phys. 46 (2010), 677–712.