Editorial Type:
Article
Article Type:
Research Article

A 4DVAR System for the Navy Coastal Ocean Model. Part I: System Description and Assimilation of Synthetic Observations in Monterey Bay

Hans Ngodock Naval Research Laboratory, Stennis Space Center, Mississippi

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Matthew Carrier Naval Research Laboratory, Stennis Space Center, Mississippi

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Print Publication:
01 Jun 2014
DOI:
https://doi.org/10.1175/MWR-D-13-00221.1
Page(s):
2085–2107
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Abstract

A 4D variational data assimilation system was developed for assimilating ocean observations with the Navy Coastal Ocean Model. It is described in this paper, along with initial assimilation experiments in Monterey Bay using synthetic observations. The assimilation system is tested in a series of twin data experiments to assess its ability to fit assimilated and independent observations by controlling the initial conditions and/or the external forcing while assimilating surface and/or subsurface observations. In all strong and weak constraint experiments, the minimization of the cost function is done with both the gradient descent method (in the control space) and the representer method (observation space). The accuracy of the forecasts following the analysis and the relevance of the retrieved forcing correction in the case of weak constraints are evaluated. It is shown that the assimilation system generally fits the assimilated and nonassimilated observations well in all experiments, yielding lower forecast errors.

Naval Research Laboratory Contribution Number JA/7320-13-1821.

Corresponding author address: Hans Ngodock, Naval Research Laboratory, Code 7321, Stennis Space Center, MS 39529. E-mail: hans.ngodock@nrlssc.navy.mil

Abstract

A 4D variational data assimilation system was developed for assimilating ocean observations with the Navy Coastal Ocean Model. It is described in this paper, along with initial assimilation experiments in Monterey Bay using synthetic observations. The assimilation system is tested in a series of twin data experiments to assess its ability to fit assimilated and independent observations by controlling the initial conditions and/or the external forcing while assimilating surface and/or subsurface observations. In all strong and weak constraint experiments, the minimization of the cost function is done with both the gradient descent method (in the control space) and the representer method (observation space). The accuracy of the forecasts following the analysis and the relevance of the retrieved forcing correction in the case of weak constraints are evaluated. It is shown that the assimilation system generally fits the assimilated and nonassimilated observations well in all experiments, yielding lower forecast errors.

Naval Research Laboratory Contribution Number JA/7320-13-1821.

Corresponding author address: Hans Ngodock, Naval Research Laboratory, Code 7321, Stennis Space Center, MS 39529. E-mail: hans.ngodock@nrlssc.navy.mil
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