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Ocean Science An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/os-2020-43
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-2020-43
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 03 Jun 2020

Submitted as: research article | 03 Jun 2020

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This preprint is currently under review for the journal OS.

Data assimilation of sea surface temperature and salinity using basin-scale EOF reconstruction: a feasibility study in the NE Baltic Sea

Mihhail Zujev, Jüri Elken, and Priidik Lagemaa Mihhail Zujev et al.
  • Department of Marine Systems, Tallinn University of Technology, Tallinn, EE12618, Estonia

Abstract. The tested data assimilation (DA) method based on EOF (Empirical Orthogonal Functions) reconstruction of observations decreased RMSD of surface temperature (SST) and salinity (SSS) in reference to observations in the NE Baltic Sea by 22 % and 34 %, respectively, compared to the control run without DA. The method is based on the covariance estimates from the long period model data. The amplitudes of the pre-calculated gravest EOF modes are estimated from point observations using least-squares optimization; the method builds the variables on the regular grid. The study used FerryBox observations along four ship tracks from 1 May to 31 December 2015, and observations from research vessels. In the reconstruction, this data amount was compressed into daily averages over 5’ N X 10’ E coarse grid. Skill was tested based on daily averages on the 0.5’ N X 1’ E original fine grid of the model. DA with EOF reconstruction technique was found feasible for further implementation studies, since: 1) the method that works on the large-scale patterns (mesoscale features are neglected by taking only the gravest EOF modes) improves the high-resolution model performance by comparable or even better degree than in the other published studies, 2) the method is computationally effective.

Mihhail Zujev et al.

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Mihhail Zujev et al.

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Latest update: 06 Jul 2020
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Short summary
The proposed method of data assimilation is capable of effectively correcting basin-scale mismatch of oceanographic model when the domain is under nearly coherent external forcing. The method uses basin scale EOF modes, calculated from the long-term model statistics. These modes are used to reconstruct gridded fields from point observations, which are further fed to the model using relaxation. Tests with sea surface temperature and salinity in the NE Baltic Sea were successful.
The proposed method of data assimilation is capable of effectively correcting basin-scale...
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