Abstract
We present a new method for assimilating observations of sea surface height (SSH) into a high‐resolution primitive equation model. The method is based on the concept of reinitialization. First, the surface velocity increments necessary to adjust the model forecast to the observed geostrophic surface currents are projected onto deep velocity increments by a linear regression method. Second, changes in the density field required to balance the changes in the velocity field geostrophically are obtained from an inversion of the thermal wind equation. A unique partition of the density increments into corresponding temperature and salinity changes is realized by conserving the local θ‐S relation of the model forecast. In contrast to pure statistical methods that infer temperature and salinity changes from correlations with SSH anomalies, our approach explicitly conserves water mass properties on isopycnals. For the assimilation experiment we use optimally interpolated maps of Geosat SSH anomalies (the mean topography is taken from the model), which are assimilated into the World Ocean Circulation Experiment (WOCE) Community Modeling Effort (CME) model of the North Atlantic Ocean at 5‐day intervals covering the year 1987. It is shown that the assimilation significantly improves the model's representation of eddy activity, with the hydrographic structure of individual eddies agreeing well with independent hydrographic observations. The importance of a careful treatment of water mass properties in the assimilation process is discussed and further illustrated by comparing different assimilation schemes.
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