Sequential updating assimilation of simulated Geosat altimeter data from mesoscale features into a two-layer quasi-geostrophic model

Abstract

A sequential updating method for assimilating Geosat altimeter data into an eddyresolving, quasi-geostrophic model is examined using simulated data of mesoscale features taken from a control run solution. The upper-layer streamfunction in the model is updated by the “altimeter” data on satellite tracks (at ∼110 km intervals) at times of observations (with 17-day cycles). To evaluate data suitability, the correlation between the data and the assimilation solution just before update is compared with the correlation between the two data with a 1-cycle separation: i.e., predictability is compared with persistence. The assimilation method is tested on mesoscale features such as linear Rossby waves, unstable mesoscale meanders in a jet and dipole eddies over realistic deep ocean topography. The assimilation method is successful for reconstructing the mesoscale features that evolve gradually or extend over more than one track. Assimilation is degraded by quick evolution of smaller scale features; i.e the unstable meanders that have short wavelengths and are not well captured by the altimeter with the low cross-track resolution, and the mesoscale features, whose lower layer component receives effects of bottom topography in the data but is underestimated due to inefficient downward transfer of the surface data in the assimilation.