Abstract

There is a growing need for ocean circulation models that conserve mass rather than volume (as in traditional Boussinesq models). One reason is bottom pressure data expected to flow from satellite-mounted gravity-measuring instruments, and another is to provide a complete interpretation of data from satellite altimeters such as TOPEX/Poseidon. In this paper, it is shown that existing, hydrostatic Boussinesq ocean model codes can easily be modified, with only a modest increase in the CPU requirement, to integrate the hydrostatic, non-Boussinesq equations. The method can be used to integrate both coarse-resolution and eddy-resolving non-Boussinesq models. The basic equations can also be used to formulate a fully nonhydrostatic, non-Boussinesq model. The method is illustrated for the case of the Parallel Ocean Program (POP), the parallel version of the Bryan‐Cox‐Semtner code developed at Los Alamos National Laboratory. A comparison of eddy-permitting model solutions under double-gyre wind forcing shows that the error in making the Boussinesq approximation is, reassuringly, only a few percent. The authors also consider a coarse-resolution global ocean model under seasonal forcing. The nonBoussinesq model shows a seasonal variation in global mean sea surface height (SSH) with a range of about 3 cm, attributable mostly to changes in the mass of the ocean due to the freshwater flux forcing, but with a roughly 25% contribution from the steric expansion effect. The seasonal cycles of model-computed SSH are also compared with TOPEX/Poseidon data from the South Pacific and South Atlantic Oceans. It is shown that the seasonal cycle in global mean SSH contributes to the model-computed seasonal cycle, and improves the model performance compared to the data. It is found that the difference between the seasonal cycles in the Boussinesq and nonBoussinesq models is almost entirely accounted for by the seasonal cycle in global mean SSH. On the other hand, on longer timescales the difference field between the non-Boussinesq and Boussinesq models shows spatial variability of several centimeters that is not accounted for by a globally uniform correction to the Boussinesq model.

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