NDLI: An ocean data assimilation system in the Indian Ocean and west Pacific Ocean

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An ocean data assimilation system in the Indian Ocean and west Pacific Ocean

Content Provider	Springer Nature Link
Author	Yan, Changxiang Zhu, Jiang Xie, Jiping
Copyright Year	2015
Abstract	The development and application of a regional ocean data assimilation system are among the aims of the Global Ocean Data Assimilation Experiment. The ocean data assimilation system in the regions including the Indian and West Pacific oceans is an endeavor motivated by this goal. In this study, we describe the system in detail. Moreover, the reanalysis in the joint area of Asia, the Indian Ocean, and the western Pacific Ocean (hereafter AIPOcean) constructed using multi-year model integration with data assimilation is used to test the performance of this system. The ocean model is an eddy-resolving, hybrid coordinate ocean model. Various types of observations including in-situ temperature and salinity profiles (mechanical bathythermograph, expendable bathythermograph, Array for Real-time Geostrophic Oceanography, Tropical Atmosphere Ocean Array, conductivity–temperature–depth, station data), remotely-sensed sea surface temperature, and altimetry sea level anomalies, are assimilated into the reanalysis via the ensemble optimal interpolation method. An ensemble of model states sampled from a long-term integration is allowed to change with season, rather than remaining stationary. The estimated background error covariance matrix may reasonably reflect the seasonality and anisotropy. We evaluate the performance of AIPOcean during the period 1993–2006 by comparisons with independent observations, and some reanalysis products. We show that AIPOcean reduces the errors of subsurface temperature and salinity, and reproduces mesoscale eddies. In contrast to ECCO and SODA products, AIPOcean captures the interannual variability and linear trend of sea level anomalies very well. AIPOcean also shows a good consistency with tide gauges.
Starting Page	1460
Ending Page	1472
Page Count	13
File Format	PDF
ISSN	02561530
Journal	Advances in Atmospheric Sciences
Volume Number	32
Issue Number	11
e-ISSN	18619533
Language	English
Publisher	Science Press
Publisher Date	2015-09-09
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	ocean data assimilation reanalysis ensemble optimal interpolation background error covariance Atmospheric Sciences Meteorology Geophysics/Geodesy
Content Type	Text
Resource Type	Article
Subject	Atmospheric Science

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