Ensemble optimal interpolation schemes for assimilating Argo profiles into a hybrid coordinate ocean model

Xie, Jiping; Zhu, Jiang

doi:10.1016/j.ocemod.2010.03.002

Cited by 80 publications

(77 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The latter is dominated by the misplacement of mesoscale features, and varies in location and intensity seasonally. For this reason, Xie and Zhu (2010) use a "running" seasonal ensemble to assimilate Argo profiles in the Pacific Ocean. The ensemble is composed of 120 members, selected within a 100-day window from the target date from different years (see Fig.…”

Section: The Ensemble Optimal Interpolationmentioning

confidence: 99%

“…Due to its multivariate properties and computational efficiency, this method is widely used both in coarse ocean climate model (e.g. Fu et al, 2009;Xie and Zhu, 2010) and in eddy-resolving operational application (e.g. Oke et al, 2008;Counillon and Bertino, 2009a, b).…”

Section: Introductionmentioning

confidence: 99%

“…In the SCS, the monsoon phase has a large influence on the spatial distribution of the mesoscale activity. Therefore, the ensemble is composed by model states collected over the same period of the year as the assimilation time (Xie and Zhu, 2010). Thus, correlations are representative of the typical circulation of the season and spurious long-range correlations are reduced.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Xie

Counillon²,

Zhu

et al. 2011

Ocean Sci.

View full text Add to dashboard Cite

Abstract. 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.

show abstract

Section: The Ensemble Optimal Interpolationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Xie

Counillon²,

Zhu

et al. 2011

Ocean Sci.

View full text Add to dashboard Cite

show abstract

“…Secondly, layer thickness "observations" are assimilated to adjust the layer thickness and current fields. Lastly, the temperature or salinity profile observations are assimilated (Xie and Zhu, 2010).…”

Section: Assimilation Schemementioning

confidence: 99%

An Ocean Reanalysis System for the Joining Area of Asia and Indian-Pacific Ocean

Zhu

Xie

2010

Atmospheric and Oceanic Science Letters

View full text Add to dashboard Cite

“…Despite the high coverage of the remotely sensed data, it is restricted to the surface and is insufficient to characterize the subsurface thermodynamic variability (Chassignet et al 2006). In the subsurface, the Argo system plays an important role with over 3500 free-drifting profiling floats measuring temperature and salinity in the upper 2000 m providing many in situ data for assimilation systems and other purposes (Oke et al 2008;Xie and Zhu 2010).…”

Section: Introductionmentioning

confidence: 99%

Assimilation of sea-level anomalies and Argo data into HYCOM and its impact on the 24 hour forecasts in the western tropical and South Atlantic

Costa

Tanajura

2015

Journal of Operational Oceanography

View full text Add to dashboard Cite

Argo and along-track sea-level anomaly (SLA) data from satellites were assimilated into the Hybrid Coordinate Ocean Model in the western tropical and South Atlantic Ocean. An optimal interpolation method was employed in the assimilation, and the Cooper and Haines scheme projected the altimetry information into the subsurface. The run with assimilation of SLA and Argo data reduced the root mean square deviation of the 24 h forecasts of SLA, sea surface temperature, and subsurface temperature and salinity by 21.4%, 11.5%, 28.1%, and 15.8%, respectively, with respect to the control run without assimilation. Important improvements were also observed in the circulation.

show abstract

Ensemble optimal interpolation schemes for assimilating Argo profiles into a hybrid coordinate ocean model

Cited by 80 publications

References 54 publications

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

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

An Ocean Reanalysis System for the Joining Area of Asia and Indian-Pacific Ocean

Assimilation of sea-level anomalies and Argo data into HYCOM and its impact on the 24 hour forecasts in the western tropical and South Atlantic

Contact Info

Product

Resources

About