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Interpreting low frequency sea level signals over the last decade
Rui Ponte(1) , Sergey Vinogradov(1) , and Carl Wunsch(2)
(1)
Atmospheric and Environmental Research, Inc.,
131 Hartwell Avenue,
Lexington, MA 02421-3126,
United States
(2) Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, United States
Abstract
Sea level variability on time scales from months to years can be
associated with a variety of processes, from warming of the water
column due to changes in surface heat flux to changes in the surface
circulation driven by variable wind stress. Correctly interpreting
the observed sea level signals can thus reveal important clues about
the nature of ocean and climate variability. Here an attempt is made
to unravel the processes behind sea level signals observed over the
period 1992-2004, from the seasonal cycle to long term trends. The
basic tool is the estimation procedure used by the ECCO-GODAE
consortium that constrains an ocean general circulation model in a
least-squares sense. Altimetric data, both time-dependent, and
time-mean are a large part of the 410 million data constraints used,
which also include CTDs, XBTs, ARGO float profiles, and meteorological
variables. The constrained solution produces a good fit of the
altimeter variability and compares well with a tide gauge dataset not
used in the optimization. Variability in sea level is decomposed into
bottom pressure, halosteric, and thermosteric terms, and each
respective contribution is analyzed as a function of time scale and
location. Both regional and global mean sea level signals are treated
in terms of their relation to surface forcing, relevant dynamic and
thermodynamic processes, along with discussion of shortcomings in
model formulation and overall uncertainties in the constrained
solution.
Workshop presentation
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