Data assimilation in a reduced gravity ocean model using ERS-l scatterometer and TOPEX altimeter data
DOI:
https://doi.org/10.54302/mausam.v48i4.4360Keywords:
Assimilation, Adjoint, Satellite, Altimeter, Scatterometer, Oceanography, ModelAbstract
This paper discusses import of ERS-1 scatterometer winds and assimilation of sea level variability data derived from TOPEX altimeter on the ocean model using adjoint approach. The model developed for the purpose is linear reduced gravity model for the north-western Indian ocean. Experiments have been done with forcing provided using ERS-l satellite scatterometer and analysed wind forcing provided by Florida State University (FSU). Impact on the model has been studied using the analysed wind stress as well as with ERS-l scatterometer-derived wind stress fields. The cost function has been defined as difference between the model derived sea level and altimeter observations. This misfit between model and observations has been minimised with the model equations as constraints. Assimilation has been done for 30 days using scatterometer wind forcing. It has been observed that assimilated sea level with scatterometer-derived wind forcing gives much better results in comparison to unassimilated sea level.
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