Projection-Based Assimilation of Satellite-Derived Surface Data in an Indian Ocean Circulation Model

Abstract

Usefulness of satellite-derived surface data for nowcasting of oceanic circulation features has been explored in the study. Two types of surface data, namely the sea surface temperature (SST) and the sea level anomaly (SLA), have been used in various data assimilation experiments to ascertain their utility when assimilated in a sigma coordinate ocean circulation model configured for the Indian Ocean. Surface information has been projected into the vertical using predetermined correlation functions in combination with optimal interpolation. Evaluation of the assimilation skill has been carried out by comparing the assimilated results with independent observations. Combined assimilation of satellite-derived SST and SLA shows improved subsurface temperature at all depths, barring the thermocline region. As regards other variables such as the model simulated SLA and sea surface current, there is a regional dependence of assimilation. It could be, however, concluded that the combined assimilation is optimal in an overall sense.

Keywords:

• Data assimilation
• altimetry
• sea surface temperature
• Indian Ocean circulation model

Acknowledgements

Special thanks are due to INCOIS for providing the gridded Argo data set. The uninterrupted computer support provided by the manager, Computer Facility, and his team is also gratefully acknowledged. Finally, the authors wish to thank two anonymous reviewers for their helpful comments and suggestions.

Notes

For assimilation, daily averaged SLA data, as a merged product of all available altimeters, have been obtained from www.aviso.oceanobs.com.

The SST data is a blended product of the SSTs measured by AVHRR and AMSR obtained from ftp://eclipse.ncdc.noaa.gov.