Variational assimilation with covariance matrices of observation data errors for the model of the Baltic Sea dynamics
Autor: | Valery Agoshkov, E. I. Parmuzin, Victor P. Shutyaev, N. B. Zakharova |
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Rok vydání: | 2018 |
Předmět: |
Numerical Analysis
010504 meteorology & atmospheric sciences Dynamics (mechanics) Covariance 010502 geochemistry & geophysics 01 natural sciences Baltic sea Modeling and Simulation Statistical physics Variational assimilation Observation data Physics::Atmospheric and Oceanic Physics 0105 earth and related environmental sciences Mathematics |
Zdroj: | Russian Journal of Numerical Analysis and Mathematical Modelling. 33:149-160 |
ISSN: | 1569-3988 0927-6467 |
Popis: | The mathematical model of the Baltic Sea dynamics developed at the Institute of Numerical Mathematics of RAS is considered. The problem of variational assimilation of average daily data for the sea surface temperature (SST) is formulated and studied with the use of covariance matrices of observation data errors. Based on variational assimilation of satellite observation data, we propose an algorithm for solving the inverse problem of the heat flux reconstruction on the sea surface. The results of numerical experiments on reconstruction of the heat flux function are presented for the problem of variational assimilation of observation SST data. |
Databáze: | OpenAIRE |
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