
On the statistical stability of the M 2 barotropic and baroclinic tidal characteristics from along‐track TOPEX/Poseidon satellite altimetry analysis
Author(s) -
Carrère Loren,
Le Provost Christian,
Lyard Florent
Publication year - 2004
Publication title -
journal of geophysical research: oceans
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2003jc001873
Subject(s) - barotropic fluid , baroclinity , altimeter , geology , geodesy , internal tide , mesoscale meteorology , internal wave , climatology , oceanography
An along‐track analysis of 7 years of TOPEX/Poseidon (T/P) data has been performed on the global ocean over the period 1993–1999. Such long time series allow us to determine the semidiurnal tidal component very accurately, while resolving the aliasing problems, at least for the main tidal wave M 2 . As already inferred by other authors, this along‐track analysis detects the surface signatures of the internal tides signal that maintains coherence with the M 2 astronomical forcing. By analyzing the T/P data in different periods of 3 years or more, the stability of the M 2 tidal characteristics is demonstrated for the barotropic component as well as for the baroclinic signal observed in the altimetric data. This stability varies with location. For the barotropic component the dispersion of the results as a function of the length and period of analysis is only significant over the areas of ocean mesoscale activity (noise impact) and of large barotropic tidal signal (separating the different components of the tidal signal proves difficult). The baroclinic tidal signal appears to be surprisingly stable over many areas located around strong topographic gradients like submarine ridges. A methodology has been developed to draw a map of these areas. This can be of help for ocean modelers to specify areas of higher vertical mixing associated with internal tidal wave activity and for those who assimilate altimetric data in their models by giving guidance on where to increase the uncertainty of the altimeter data over these areas.