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Estimating a Mean Ocean State from Hydrography and Sea-Surface Height Data with a Nonlinear Inverse Section Model: Twin Experiments with a Synthetic Dataset-
Article in a journal
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Area Oceanography |
Author(s)
Martin Losch
, René Redler
, Jens Schröter
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Published in
Journal of Physical Oceanography |
Year 2002 |
Abstract The recovery of the oceanic flow field from in situ data is one of the oldest problems of modern oceanography. In this study, a stationary, nonlinear inverse model is used to estimate a mean geostrophic flow field from hydrographic data along a hydrographic section. The model is augmented to improve these estimates with measurements of the absolute sea-surface height by satellite altimetry. Measurements of the absolute sea-surface height include estimates of an equipotential surface, the geoid. Compared to oceanographic measurements, the geoid is known only to low accuracy and spatial resolution, which restricts the use of sea-surface height data to applications of large-scale phenomena of the circulation. Dedicated satellite missions that are designed for high precision, high-resolution geoid models are planned and/or in preparation. This study, which relies on twin experiments, assesses the important contribution of improved geoid models to estimating the mean flow field along a hydrographic section. When the sea-surface height data are weighted according to the error estimates of the future highly accurate geoid models GRACE (Gravity Recovery And Climate Experiment) and GOCE (Gravity Field and Steady-State Ocean Circulation Explorer), integrated fluxes of mass and temperature can be determined with an accuracy that is improved over the case with no sea-surface height data by up to 55%. With the error estimates of the currently best geoid model EGM96, the reduction of the estimated flux errors does not exceed 18%. |
AD Tools TAMC |
AD Theory and Techniques Adjoint, Hessian |
BibTeX
@ARTICLE{
Losch2002EaM,
author = "Martin Losch and Ren{\'e} Redler and Jens Schr{\"o}ter",
title = "Estimating a Mean Ocean State from Hydrography and Sea-Surface Height Data with a
Nonlinear Inverse Section Model: Twin Experiments with a Synthetic Dataset",
journal = "Journal of Physical Oceanography",
year = "2002",
volume = "32",
number = "7",
pages = "2096--2112",
ad_tools = "TAMC",
ad_area = "Oceanography",
pdf = "http://hdl.handle.net/10013/epic.14983.d001",
ad_theotech = "Adjoint, Hessian",
doi = "10.1175/1520-0485(2002)032<2096:EAMOSF>2.0.CO;2",
abstract = "The recovery of the oceanic flow field from in situ data is one of the oldest
problems of modern oceanography. In this study, a stationary, nonlinear inverse model is used to
estimate a mean geostrophic flow field from hydrographic data along a hydrographic section. The
model is augmented to improve these estimates with measurements of the absolute sea-surface height
by satellite altimetry. Measurements of the absolute sea-surface height include estimates of an
equipotential surface, the geoid. Compared to oceanographic measurements, the geoid is known only to
low accuracy and spatial resolution, which restricts the use of sea-surface height data to
applications of large-scale phenomena of the circulation. Dedicated satellite missions that are
designed for high precision, high-resolution geoid models are planned and/or in preparation. This
study, which relies on twin experiments, assesses the important contribution of improved geoid
models to estimating the mean flow field along a hydrographic section. When the sea-surface height
data are weighted according to the error estimates of the future highly accurate geoid models GRACE
(Gravity Recovery And Climate Experiment) and GOCE (Gravity Field and Steady-State Ocean Circulation
Explorer), integrated fluxes of mass and temperature can be determined with an accuracy that is
improved over the case with no sea-surface height data by up to 55\%. With the error estimates
of the currently best geoid model EGM96, the reduction of the estimated flux errors does not exceed
18\%."
}
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