Assimilation of Argo Temperature and Salinity Profiles Using a Bias-Aware EnOI Scheme for the Labrador Sea

Abstract

AbstractIn this study, temperature and salinity profiles from Argo floats are assimilated into a coupled ice?ocean model over the North Atlantic Ocean and Arctic using an ensemble optimal interpolation (EnOI) scheme, with the aim of improving the thermohaline structure of the Labrador Sea estimated by the model. Data assimilation experiments are carried out from September 2014 to April 2015 both with and without a one-step bias correction method from the literature. It is found that assimilation of the Argo profiles reduces the errors in the model temperature and salinity when verification is done against both withheld Argo profiles and sea surface temperature from satellite data. The assimilation also leads to deeper mixed layer depth in the Labrador Sea, closer to observations shown in other studies, in particular when bias correction is used. We hypothesize that this is because the bias field leads to vertical density profiles that are less stratified, and hence requiring less energy for mixing, than when bias correction is not used.