Abstract

Abstract This paper is an evaluation of the role of salinity in the framework of temperature data assimilation in a global ocean model that is used to initialize seasonal climate forecasts. It is shown that the univariate assimilation of temperature profiles, without attempting to correct salinity, can induce first-order errors in the subsurface temperature and salinity fields. A recently developed scheme by A. Troccoli and K. Haines is used to improve the salinity field. In this scheme, salinity increments are derived from the observed temperature, by using the model temperature and salinity profiles, assuming that the temperature–salinity relationship in the model profiles is preserved. In addition, the temperature and salinity fields are matched below the observed temperature profile by vertically displacing the original model profiles. Two data assimilation experiments were performed for the 6-yr period 1993–98. These show that the salinity scheme is effective at maintaining the haline and thermal str...

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call