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  Utilizing oceanic electromagnetic induction to constrain an ocean general circulation model: A data assimilation twin experiment

Irrgang, C., Saynisch, J., Thomas, M. (2017): Utilizing oceanic electromagnetic induction to constrain an ocean general circulation model: A data assimilation twin experiment. - Journal of Advances in Modeling Earth Systems, 9, 3, 1703-1720.
https://doi.org/10.1002/2017MS000951

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 Creators:
Irrgang, Christopher1, Author           
Saynisch, J.1, Author           
Thomas, M.1, Author           
Affiliations:
11.3 Earth System Modelling, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_146027              

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 Abstract: Satellite observations of the magnetic field induced by the general ocean circulation could provide new constraints on global oceanic water and heat transports. This opportunity is investigated in a model-based twin experiment by assimilating synthetic satellite observations of the ocean-induced magnetic field into a global ocean model. The general circulation of the world ocean is simulated over the period of one month. Idealized daily observations are generated from this simulation by calculating the ocean-induced magnetic field at 450 km altitude and disturbing these global fields with error estimates. Utilizing an ensemble Kalman filter, the observations are assimilated into the same ocean model with a different initial state and different atmospheric forcing. Compared to a reference simulation without data assimilation, the corrected ocean-induced magnetic field is improved throughout the whole simulation period and over large regions. The global RMS differences of the ocean-induced magnetic field are reduced by up to 17%. Local improvements show values up to 54%. RMS differences of the depth-integrated zonal and meridional ocean velocities are improved by up to 7% globally, and up to 50% locally. False corrections of the ocean model state are identified in the South Pacific Ocean and are linked to a deficient estimation of the ocean model error covariance matrices. Most Kalman filter induced changes in the ocean velocities extend from the sea-surface down to the deep ocean. Allowing the Kalman filter to correct the wind stress forcing of the ocean model is essential for a successful assimilation.

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Language(s): eng - English
 Dates: 2017
 Publication Status: Finally published
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.1002/2017MS000951
GFZPOF: p3 PT1 Global Processes
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Title: Journal of Advances in Modeling Earth Systems
Source Genre: Journal, SCI, Scopus, oa
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Pages: - Volume / Issue: 9 (3) Sequence Number: - Start / End Page: 1703 - 1720 Identifier: CoNE: https://gfzpublic.gfz.de/cone/journals/resource/160525