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Variational assimilation of observation data in the mathematical model of the Baltic Sea dynamics
Ein Erratum zu diesem Artikel finden Sie hier:
https://doi.org/10.1515/rnam-2016-0006
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Valeriy I. Agoshkov
,
Vladimir B. Zalesny
Veröffentlicht/Copyright:
7. August 2015
Abstract
A mathematical model of the dynamics of the Baltic Sea is considered. A problem of variational assimilation of sea surface temperature (SST) data is formulated and studied. Based on variational assimilation of satellite observation data, an algorithm solving the inverse problem of heat flux restoration on the interface of two media is proposed. The results of numerical experiments reconstructing the heat flux functions in the problem of variational assimilation of SST observation data are presented. The influence of SST assimilation on other hydrodynamic parameters of the model is considered.
Keywords: Variational assimilation problem; numerical algorithm; determination of heat flux on the sea surface; sea surface temperature
Received: 2015-5-18
Accepted: 2015-5-25
Published Online: 2015-8-7
Published in Print: 2015-8-1
© 2015 by Walter de Gruyter Berlin/Boston
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Artikel in diesem Heft
- Frontmatter
- Variational assimilation of observation data in the mathematical model of the Baltic Sea dynamics
- On overturn of two-dimensional nonlinear plasma oscillations
- Simulation of tsunami waves generated by submarine landslides in the Black Sea
- The accurate continuous-discrete extended Kalman filter for continuous-time stochastic systems
- Monte Carlo simulation of ring-shaped returns for CCD LIDAR systems
Schlagwörter für diesen Artikel
Variational assimilation problem;
numerical algorithm;
determination of heat flux on the sea surface;
sea surface temperature
Artikel in diesem Heft
- Frontmatter
- Variational assimilation of observation data in the mathematical model of the Baltic Sea dynamics
- On overturn of two-dimensional nonlinear plasma oscillations
- Simulation of tsunami waves generated by submarine landslides in the Black Sea
- The accurate continuous-discrete extended Kalman filter for continuous-time stochastic systems
- Monte Carlo simulation of ring-shaped returns for CCD LIDAR systems
