THE DETERMINATION OF THE LARGE-SCALE CIRCULATION OF THE PACIFIC-OCEANFROM SATELLITE ALTIMETRY USING MODEL GREENS-FUNCTIONS

A Green's function method for obtaining an estimate of the ocean circu lation using both a general circulation model and altimetric data is d emonstrated. The fundamental assumption is that the model is so accura te that the differences between the observations and the model-estimat ed fields obey a linear dynamics. In the present case, the calculation s are demonstrated for model/data differences occurring on very a larg e scale, where the Linearization hypothesis appears to be a good one. A semi-automatic linearization of the Bryan/Cox general circulation mo del is effected by calculating the model response to a series of isola ted (in both space and time) geostrophically balanced vortices. These resulting impulse responses Or ''Green's functions'' then provide the kernels for a linear inverse problem. The method is first demonstrated with a set of ''twin experiments'' and then with real data spanning t he entire model domain and a year of TOPEX/POSEIDON observations. Our present focus is on the estimate of the time-mean and annual cycle of the model. Residuals of the inversion/assimilation are largest in the western tropical Pacific, and are believed to reflect primarily geoid error. Vertical resolution diminishes with depth with 1 year of data. The model mean is modified such that the subtropical gyre is weakened by about 1 cm/s and the center of the gyre shifted southward by about 10 degrees. Corrections to the flow field at the annual cycle suggest that the dynamical response is weak except in the tropics, where the e stimated seasonal cycle of the low-latitude current system is of the o rder of 2 cm/s. The underestimation of observed fluctuations can be re lated to the inversion on the coarse spatial grid, which does not perm it full. resolution of the tropical physics. The methodology is easily extended to higher resolution, to use of spatially correlated errors, and to other data types.