Assimilation of Sea Surface Height Data into an Isopycnic Ocean Model

Abstract

Two different methods for assimilating sea surface height data into an isopycnic primitive equation model were developed and tested for the idealized case of an analytical Gaussian warm core (anticyclonic) eddy, then implemented using remotely sensed data from the Brazil?Malvinas confluence region. The first method makes a geostrophic assumption about the flow to relate sea surface height field gradients to the model velocities. The second method nudges the model sea surface height itself toward the observed values using a linear vertical influence function in the upper layers. The relationship between the surface height observations and the layer interface displacements is derived from observations of eddies in different regions of the Atlantic Ocean. Both assimilation methods were successful in transferring the dynamical influence of the sea surface height measurements deep into the water column, but a combination of both gave the best results. The application of both methods reproduced the detailed mesoscale features of the real oceanic circulation when assimilating Geosat sea surface height measurements from the Brazil?Malvinas confluence region into an isopycnic ?box? ocean model. The velocity fields show deep anticyclonic (cyclonic) circulations of 66 cm s?1 (52 cm s?1), which are present in observations of eddies and meanders. When compared to the no assimilation run, the assimilated sea surface height field exhibits a richer spectrum, with energy in all spectral bands strongly correlated with the observed values. The resulting band of energy higher than 150 cm2 between 300 and 600 km is in agreement with previous studies of this region. The rms error between the model sea surface height and the Geosat data was reduced from ?13 cm in the no assimilation run to 2 cm rms after the assimilation. These experiments demonstrate the flexibility and effectiveness of the Newtonian relaxation (nudging) method for assimilating real data into a complex, multilayer primitive equation ocean model.