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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


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


                 Last modified: 07.10.03