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Mean dynamic topography estimates purely based on GOCE gravity field models and altimetry
Author(s) -
Becker S.,
Brockmann J. M.,
Schuh W.D.
Publication year - 2014
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1002/2014gl059510
Subject(s) - geodesy , gravitational field , ocean surface topography , data assimilation , geology , altimeter , covariance , sea surface height , covariance matrix , gravity anomaly , geoid , field (mathematics) , remote sensing , geophysics , meteorology , algorithm , computer science , geography , mathematics , measured depth , paleontology , statistics , physics , astronomy , oil field , pure mathematics
The quality of mean dynamic topography (MDT) models derived from an altimetric mean sea surface and a gravity field model mainly depends on the spatial resolution and accuracy of the particular gravity field model. We use an integrated approach which allows for estimating the MDT and its (inverse) covariance matrix on a predefined grid which is one of the requirements for ocean data assimilation. The quality and accuracy of the MDT directly reflects the quality and accuracy of the used gravity field model. For the first time, MDT estimates along with its full error covariance matrix based on Gravity Field and Steady‐State Ocean Circulation Explorer (GOCE) data can be provided. We demonstrate the progress accomplished with GOCE processing and the valuable contribution of the GOCE gravity field models regarding the estimation of the MDT by showing results based on altimetric observations of Jason‐1 and Envisat in combination with different GOCE gravity field models for the North Atlantic.