Hindcasting ocean climate variability using time-dependent surface data to drive a model: an idealized study

Abstract

This paper investigates the hindcasting of interdecadal climate events using an ocean circulation model driven by different combinations of time-varying surface flux, sea surface temperature (SST), and sea surface salinity (SSS) data. Data are generated from a control run, against which the subsequent model experiments are compared. The most robust results are obtained using flux boundary conditions on both surface temperature and salinity. For these boundary conditions, model results are relatively insensitive to noise in the surface data and take about 20 yr to overcome the imposition of an incorrect initial condition. To obtain meaningful results, SST data alone are not sufficient; SSS data are also required. -from Authors