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A Wind and Boundary Driven Circulation Model of the Ross Sea

  • V. Commodari
  • S. Pierini

Abstract

The application of a barotropic primitive equation model to the Ross Sea has allowed to determine the main features of the vertically integrated transport as induced locally by the wind and forced by the external action of the East Wind Drift during the ice-free season. Furthermore, the implementation of the same model with higher resolution to a coastal area including Terra Nova Bay has provided information on the local circulation regime. The circulation model of the Ross Sea is implemented in a domain including the Ross Sea and an external zone which allows for the formation of the Ross Sea gyre. A regular grid of 20 km resolution is defined on a adapted Gauss-Boaga projection which reduces notably the deformation of the distances. The model is first forced by an idealized wind system representing schematically the local atmospheric circulation on a global scale and the runs are carried out up to the steady state. The Ross Sea gyre and an overall cyclonic circulation in the interior of the Ross Sea locally shaped by the topography are observed. on the other hand, the response inside the Ross Sea to the remote effect of a boundary forcing given by the Antarctic Circumpolar Current and of the East Wind Drift in the absence of winds is found to be very weak. This puts in evidence that the wind is by far the most energetic forcing of the local barotropic circulation. These numerical results are found to be in good agreement with classical observational data and with current meter measurements taken within the Italian P.N.R.A.. The model is then applied to a coastal zone around Terra nova Bay with a 2 km resolution. This model is forced by an idealized wind and nested with the coarse resolution model of the Ross Sea. Information are thus obtained on the local circulation.

Keywords

Antarctic Circumpolar Current Cyclonic Gyre Internal Circulation High Resolution Model Coarse Resolution Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Italia, Milano 1999

Authors and Affiliations

  • V. Commodari
    • 1
  • S. Pierini
    • 2
  1. 1.Istituto di Meteorologia e OceanografiaIstituto Universitario NavaleNapoliItaly
  2. 2.Dipartimento di FisicaUniversità dell’AquilaCoppito (AQ)Italy

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