A balanced Kalman filter ocean data assimilation system with application to the South Australian Sea

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Title: A balanced Kalman filter ocean data assimilation system with application to the South Australian Sea
Author(s): Li, Y
Toumi, R
Item Type: Journal Article
Abstract: n this paper, an Ensemble Kalman Filter (EnKF) based regional ocean data assimilation system has been developed and applied to the South Australian Sea. This system consists of the data assimilation algorithm provided by the NCAR Data Assimilation Research Testbed (DART) and the Regional Ocean Modelling System (ROMS). We describe the first implementation of the physical balance operator (temperature-salinity, hydrostatic and geostrophic balance) to DART, to reduce the spurious waves which may be introduced during the data assimilation process. The effect of the balance operator is validated in both an idealised shallow water model and the ROMS model real case study. In the shallow water model, the geostrophic balance operator eliminates spurious ageostrophic waves and produces a better sea surface height (SSH) and velocity analysis and forecast. Its impact increases as the sea surface height and wind stress increase. In the real case, satellite-observed sea surface temperature (SST) and SSH are assimilated in the South Australian Sea with 50 ensembles using the Ensemble Adjustment Kalman Filter (EAKF). Assimilating SSH and SST enhances the estimation of SSH and SST in the entire domain, respectively. Assimilation with the balance operator produces a more realistic simulation of surface currents and subsurface temperature profile. The best improvement is obtained when only SSH is assimilated with the balance operator. A case study with a storm suggests that the benefit of the balance operator is of particular importance under high wind stress conditions. Implementing the balance operator could be a general benefit to ocean data assimilation systems.
Publication Date: 1-Aug-2017
Date of Acceptance: 19-Jun-2017
URI: http://hdl.handle.net/10044/1/52082
DOI: https://dx.doi.org/10.1016/j.ocemod.2017.06.007
ISSN: 1463-5003
Publisher: Elsevier
Start Page: 159
End Page: 172
Journal / Book Title: Ocean Modelling
Volume: 116
Copyright Statement: © 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Keywords: Science & Technology
Physical Sciences
Meteorology & Atmospheric Sciences
Oceanography
ROMS
EnKF
Multivariate balance
SEQUENTIAL DATA ASSIMILATION
CALIFORNIA CURRENT SYSTEM
QUASI-GEOSTROPHIC MODEL
GULF-OF-MEXICO
SURFACE TEMPERATURE
PACIFIC-OCEAN
GLOBAL OCEAN
ENSEMBLE
LOCALIZATION
Science & Technology
Physical Sciences
Meteorology & Atmospheric Sciences
Oceanography
ROMS
EnKF
Multivariate balance
SEQUENTIAL DATA ASSIMILATION
CALIFORNIA CURRENT SYSTEM
QUASI-GEOSTROPHIC MODEL
GULF-OF-MEXICO
SURFACE TEMPERATURE
PACIFIC-OCEAN
GLOBAL OCEAN
ENSEMBLE
LOCALIZATION
0405 Oceanography
Oceanography
Publication Status: Published
Embargo Date: 2018-08-01
Appears in Collections:Space and Atmospheric Physics
Physics
Faculty of Natural Sciences



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