Successive correction of the mean sea surface height by the simultaneous assimilation of drifting buoy and altimetric data

Abstract

A simultaneous assimilation model of drifting buoy and altimetric data is proposed to determine the mean sea surface height (SSH) as well as the temporal evolution of the surface circulation on synoptic scales. To demonstrate the efficiency of our assimilation model, several identical twin experiments for the double-gyre circulation system are performed using a 11/2-layer primitive equation model. An optimal interpolation for the multivariate is used for the assimilation scheme that assumes the geostrophic relationship between the error fields of the velocity and the interface depth. To identify the nature of the assimilation of the buoy-derived velocities into the dynamical ocean model, the authors first conduct the assimilation experiment using the drifting buoy data alone. The result shows that realistic buoy deployment (32 in a 40° square) can effectively constrain the model variables; that is, both the absolute (mean plus time varying) velocity and SSH (interface depth) fields are significantly improved by this buoy data assimilation. Moreover, in the case of denser buoy deployment in the energetic western boundary current regions, where the mean SSH is comparable to the time-varying part and the geoid error is relatively large, the assimilation provides a better determination of the absolute velocity and SSH. This is because significant changes in the mean SSH lead to an improvement along the extensive buoy trajectories associated with the strong current. It is worth noting that the assimilation of drifting buoy data is more effective than that of moored velocity data, thanks to the Lagrangian information content of the drifting buoys. Successive correction of the mean SSH is made with simultaneous assimilation of drifting buoy and altimetric data. Consequently, a better correction of the mean SSH is obtained: The initial error of the mean SSH is reduced by approximately 40% after the 1-year experiment. In contrast, the assimilation experiment of altimetric data alone corrects only the time-varying part, but yields little error reduction for the mean SSH in our model. These results clearly show that the simultaneous assimilation of drifting buoy and altimetric data into the dynamical model is a very useful tool for improving the model's realism.