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Parts of geodesy and physical oceanography are about to mature into a single modeling problem involving the simultaneous estimation
of the marine geoid and the general circulation. Both fields will benefit. To this end, we present an ocean state estimation
(data assimilation) framework which is designed to obtain a dynamically consistent picture of the changing ocean circulation
by combining global ocean data sets of arbitrary type with a general circulation model (GCM). The impact of geoid measurements
on such estimates of the ocean circulation are numerous. For the mean circulation, a precise geoid describes the reference
frame for dynamical signals in altimetric sea surface height observations. For the time-varying ocean signal, changing geoid
information might be a valuable new information about correcting the changing flow field on time scales from a few month to
a year, but the quantitative utility of such information has not yet been demonstrated. For a consistent estimate, some knowledge
of the prior error covariances of all data fields is required. The final result must be consistent with prior error estimates
for the data. State estimation is thus one of the few quantitative consistency checks for new geoid measurements anticipated
from forthcoming space missions. Practical quantitative methods will yield a best possible estimate of the dynamical sea surface
which, when combined with satellite altimetric surfaces, will produce a best-estimate marine geoid. The anticipated accuracy
and precision of such estimates raises some novel modeling error issues which have not conventionally been of concern (the
Boussinesq approximation, self-attraction and loading). Model skill at very high frequencies is a major concern because of
the need to de-alias the data obtained by the inevitable oceanic temporal undersampling dictated by realistic satellite orbit
configurations.
This revised version was published online in August 2006 with corrections to the Cover Date. 相似文献
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