Sequential forecasting of the surface and subsurface conditions in the Japan Sea

Abstract

This study estimates a realistic change of the Japan Sea by assimilating satellite measurements into an eddy-resolving circulation model. Suboptimal but feasible assimilation schemes of approximate filtering and nudging play essential roles in the system. The sequential update of error covariance significantly outperforms the asymptotic covariance in the sequential assimilation due to the irregular sampling patterns from multiple altimeter satellites. The best estimates show an average rms difference of only 1.2°C from the radiometer data, and also explain about half of the sea level variance measured by the altimeter observation. The subsurface conditions associated with the mesoscale variabilities are also improved, especially in the Tsushima Warm Current region. It is demonstrated that the forecast limit strongly depends on variable, depth, and location.