An OSSE Study for Deep Argo Array using the GFDL Ensemble Coupled Data Assimilation System View Full Text


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Article Info

DATE

2018-06

AUTHORS

You-Soon Chang, Shaoqing Zhang, Anthony Rosati, Gabriel A. Vecchi, Xiaosong Yang

ABSTRACT

An observing system simulation experiment (OSSE) using an ensemble coupled data assimilation system was designed to investigate the impact of deep ocean Argo profile assimilation in a biased numerical climate system. Based on the modern Argo observational array and an artificial extension to full depth, “observations” drawn from one coupled general circulation model (CM2.0) were assimilated into another model (CM2.1). Our results showed that coupled data assimilation with simultaneous atmospheric and oceanic constraints plays a significant role in preventing deep ocean drift. However, the extension of the Argo array to full depth did not significantly improve the quality of the oceanic climate estimation within the bias magnitude in the twin experiment. Even in the “identical” twin experiment for the deep Argo array from the same model (CM2.1) with the assimilation model, no significant changes were shown in the deep ocean, such as in the Atlantic meridional overturning circulation and the Antarctic bottom water cell. The small ensemble spread and corresponding weak constraints by the deep Argo profiles with medium spatial and temporal resolution may explain why the deep Argo profiles did not improve the deep ocean features in the assimilation system. Additional studies using different assimilation methods with improved spatial and temporal resolution of the deep Argo array are necessary in order to more thoroughly understand the impact of the deep Argo array on the assimilation system. More... »

PAGES

179-189

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12601-018-0007-1

DOI

http://dx.doi.org/10.1007/s12601-018-0007-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1101294157


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