Numerical Modeling of Marine Circulation with 4D Variational Data Assimilation

Vladimir Zalesny,Eugene Parmuzin,Victor Shutyaev,Valeriy Agoshkov,Natalia Zakharova

doi:10.3390/jmse8070503

Vladimir Zalesny, Eugene Parmuzin + Show 3 more

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https://doi.org/10.3390/jmse8070503

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Abstract

The technology is presented for modeling and prediction of marine hydrophysical fields based on the 4D variational data assimilation technique developed at the Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences (INM RAS). The technology is based on solving equations of marine hydrodynamics using multicomponent splitting, thereby solving an optimality system that includes adjoint equations and covariance matrices of observation errors. The hydrodynamic model is described by primitive equations in the sigma-coordinate system, which is solved by finite-difference methods. The technology includes original algorithms for solving the problems of variational data assimilation using modern iterative processes with a special choice of iterative parameters. The methods and technology are illustrated by the example of solving the problem of circulation of the Baltic Sea with 4D variational data assimilation of sea surface temperature information.

Highlights

Numerical models of the dynamics of oceans and seas are important components of modern technologies for monitoring and forecasting the global hydrosphere, oceans and inland and marginal seas
Let us present the results of numerical experiments for the problem of reconstructing the heat flux function Q in the Baltic Sea by variational assimilation of the observed sea surface temperature data
In this paper the methods and technology for modeling and analysis of marine hydrophysical fields based on 4D variational assimilation of observational data are presented

Summary

Introduction

Numerical models of the dynamics of oceans and seas are important components of modern technologies for monitoring and forecasting the global hydrosphere, oceans and inland and marginal seas. They allow one to simulate complex hydrodynamic processes, and to study the fine structure of hydrophysical fields and their spatio-temporal variability [1,2,3,4]. Coupling plays an important role both for very small space-time scales (order of km and hours) and for very large scales (synoptic scale for short term and climatological approaches) [20,21,22,23].

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