NDLI: Argo data assimilation in ocean general circulation model of Northwest Pacific Ocean

Content Provider	Springer Nature Link
Author	Yin, Xunqiang Qiao, Fangli Yang, Yongzeng Xia, Changshui Chen, Xianyao
Copyright Year	2012
Abstract	The Argo temperature and salinity profiles in 2005–2009 are assimilated into a coastal ocean general circulation model of the Northwest Pacific Ocean using the ensemble adjustment Kalman filter (EAKF). Three numerical tests, including the control run (CTL) (without data assimilation, which serves as the reference experiment), ensemble free run (EnFR) (without data assimilation), and EAKF experiment (with Argo data assimilation using EAKF), are carried out to examine the performance of this system. Using the restarts of different years as the initial conditions of the ensemble integrations, the ensemble spreads from EnFR and EAKF are all kept at a finite value after a sharp decreasing in the first few months because of the sensitive of the model to the initial conditions, and the reducing of the ensemble spread due to Argo data assimilation is not much. The ensemble samples obtained in this way can well represent the probabilities of the real ocean states, and no ensemble inflation is necessary for this EAKF experiment. Different experiment results are compared with satellite sea surface temperature (SST) data and the Global Temperature-Salinity Profile Program (GTSPP) data. The comparison of SST shows that modeled SST errors are reduced after data assimilation; the error reduction percentage after assimilating the Argo profiles is about 10 % on average. The comparison against the GTSPP profiles, which are independent of the Argo profiles, shows improvements in both temperature and salinity. The comparison results indicated a great error reduction in all vertical layers relative to CTL and the ensemble mean of EnFR; the maximum value for temperature and salinity reaches to 85 % and 80 %, respectively. The standard deviations of sea surface height are employed to examine the simulation ability, and it is shown that the mesoscale variability is improved after Argo data assimilation, especially in the Kuroshio extension area and along the section of 10°N. All these results suggest that this system is potentially useful for improving the simulation ability of oceanic numerical models.
Starting Page	1059
Ending Page	1071
Page Count	13
File Format	PDF
ISSN	16167341
Journal	Deutsche Hydrografische Zeitschrift
Volume Number	62
Issue Number	7
e-ISSN	16167228
Language	English
Publisher	Springer-Verlag
Publisher Date	2012-06-05
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Argo profiles Ensemble adjustment Kalman filter Ensemble free runs Ensemble spread Mesoscale variability Environmental Monitoring/Analysis Fluid- and Aerodynamics Geophysics/Geodesy Meteorology/Climatology Oceanography
Content Type	Text
Resource Type	Article
Subject	Oceanography

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