An eddy resolving tidal-driven model of the South China Sea assimilating along-track SLA data using the EnOI

The upper ocean circulation in the South China Sea (SCS) is driven by the Asian monsoon, the Kuroshio intrusion through the Luzon Strait, strong tidal currents, and a complex topography. Here, we demonstrate the benefit of assimilating along-track altimeter data into a nested configuration of the HY...

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Main Authors: J. Xie, F. Counillon, J. Zhu, L. Bertino
Format: Article
Language:English
Published: Copernicus Publications 2011-10-01
Series:Ocean Science
Online Access:http://www.ocean-sci.net/7/609/2011/os-7-609-2011.pdf
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spelling doaj-537e30b4799c44de8c898f92c0cac49e2020-11-25T01:34:05ZengCopernicus PublicationsOcean Science1812-07841812-07922011-10-017560962710.5194/os-7-609-2011An eddy resolving tidal-driven model of the South China Sea assimilating along-track SLA data using the EnOIJ. XieF. CounillonJ. ZhuL. BertinoThe upper ocean circulation in the South China Sea (SCS) is driven by the Asian monsoon, the Kuroshio intrusion through the Luzon Strait, strong tidal currents, and a complex topography. Here, we demonstrate the benefit of assimilating along-track altimeter data into a nested configuration of the HYbrid Coordinate Ocean Model that includes tides. Including tides in models is important because they interact with the main circulation. However, assimilation of altimetry data into a model including tides is challenging because tides and mesoscale features contribute to the elevation of ocean surface at different time scales and require different corrections. To address this issue, tides are filtered out of the model output and only the mesoscale variability is corrected with a computationally cheap data assimilation method: the Ensemble Optimal Interpolation (EnOI). This method uses a running selection of members to handle the seasonal variability and assimilates the track data asynchronously. The data assimilative system is tested for the period 1994–1995, during which time a large number of validation data are available. Data assimilation reduces the Root Mean Square Error of Sea Level Anomalies from 9.3 to 6.9 cm and improves the representation of the mesoscale features. With respect to the vertical temperature profiles, the data assimilation scheme reduces the errors quantitatively with an improvement at intermediate depth and deterioration at deeper depth. The comparison to surface drifters shows an improvement of surface current by approximately −9% in the Northern SCS and east of Vietnam. Results are improved compared to an assimilative system that does not include tides and a system that does not consider asynchronous assimilation.http://www.ocean-sci.net/7/609/2011/os-7-609-2011.pdf
collection DOAJ
language English
format Article
sources DOAJ
author J. Xie
F. Counillon
J. Zhu
L. Bertino
spellingShingle J. Xie
F. Counillon
J. Zhu
L. Bertino
An eddy resolving tidal-driven model of the South China Sea assimilating along-track SLA data using the EnOI
Ocean Science
author_facet J. Xie
F. Counillon
J. Zhu
L. Bertino
author_sort J. Xie
title An eddy resolving tidal-driven model of the South China Sea assimilating along-track SLA data using the EnOI
title_short An eddy resolving tidal-driven model of the South China Sea assimilating along-track SLA data using the EnOI
title_full An eddy resolving tidal-driven model of the South China Sea assimilating along-track SLA data using the EnOI
title_fullStr An eddy resolving tidal-driven model of the South China Sea assimilating along-track SLA data using the EnOI
title_full_unstemmed An eddy resolving tidal-driven model of the South China Sea assimilating along-track SLA data using the EnOI
title_sort eddy resolving tidal-driven model of the south china sea assimilating along-track sla data using the enoi
publisher Copernicus Publications
series Ocean Science
issn 1812-0784
1812-0792
publishDate 2011-10-01
description The upper ocean circulation in the South China Sea (SCS) is driven by the Asian monsoon, the Kuroshio intrusion through the Luzon Strait, strong tidal currents, and a complex topography. Here, we demonstrate the benefit of assimilating along-track altimeter data into a nested configuration of the HYbrid Coordinate Ocean Model that includes tides. Including tides in models is important because they interact with the main circulation. However, assimilation of altimetry data into a model including tides is challenging because tides and mesoscale features contribute to the elevation of ocean surface at different time scales and require different corrections. To address this issue, tides are filtered out of the model output and only the mesoscale variability is corrected with a computationally cheap data assimilation method: the Ensemble Optimal Interpolation (EnOI). This method uses a running selection of members to handle the seasonal variability and assimilates the track data asynchronously. The data assimilative system is tested for the period 1994–1995, during which time a large number of validation data are available. Data assimilation reduces the Root Mean Square Error of Sea Level Anomalies from 9.3 to 6.9 cm and improves the representation of the mesoscale features. With respect to the vertical temperature profiles, the data assimilation scheme reduces the errors quantitatively with an improvement at intermediate depth and deterioration at deeper depth. The comparison to surface drifters shows an improvement of surface current by approximately −9% in the Northern SCS and east of Vietnam. Results are improved compared to an assimilative system that does not include tides and a system that does not consider asynchronous assimilation.
url http://www.ocean-sci.net/7/609/2011/os-7-609-2011.pdf
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