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\section{Introduction} |
\section{Introduction} |
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\label{sec:intro} |
\label{sec:intro} |
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In the past five years, oceanographic state estimation has matured to the |
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extent that estimates of the evolving circulation of the ocean constrained by |
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in-situ and remotely sensed global observations are now routinely available |
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and being applied to myriad scientific problems \citep{wun07}. Ocean state |
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estimation is the process of fitting an ocean general circulation model (GCM) |
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to a multitude of observations. As formulated by the consortium Estimating |
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the Circulation and Climate of the Ocean (ECCO), an automatic differentiation |
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tool is used to calculate the so-called adjoint code of a GCM. The method of |
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Lagrange multipliers is then used to render the problem one of unconstrained |
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least-squares minimization. Although much has been achieved, the existing |
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ECCO estimates lack intercative sea ice. This limits the ability of ECCO to |
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utilize satellite data constraints over sea-ice covered regions. This also |
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limits the usefulness of the ECCO ocean state estimates for describing and |
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studying polar-subpolar interactions. |
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The availability of an adjoint model as a powerful research tool |
The availability of an adjoint model as a powerful research tool |
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complementary to an ocean model was a major design requirement early |
complementary to an ocean model was a major design requirement early |
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on in the development of the MIT general circulation model (MITgcm) |
on in the development of the MIT general circulation model (MITgcm) |
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