An inverse technique for reconstructing ocean’s density stratification from surface data

Subhajit Kar, Anirban Guha (Lead / Corresponding author)

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
91 Downloads (Pure)

Abstract

In this article, we propose an inverse technique that accurately reconstructs the ocean's density stratification profile simply from free surface elevation data. Satellite observations suggest that ocean surface contains the signature of internal tides, which are internal gravity waves generated by the barotropic tides. Since internal tides contain the information of ocean's density stratification, the latter can in principle be reconstructed from the free surface signature. We consider a simple theoretical model that approximates a continuously stratified ocean as discrete layers of constant buoyancy frequency; this facilitates the derivation of a closed-form dispersion relation. First, we numerically simulate internal tide generation for toy ocean scenarios and subsequently perform Space–Time Fourier Transform (STFT) of the free surface, which yields internal tide spectra with wavenumbers corresponding to the tidal frequency. The density profile is reconstructed by substituting these wavenumbers into the dispersion relation. Finally, we consider a more realistic situation with rotation, bottom topography, shear and density profiles representative of the Strait of Gibraltar. Density reconstruction in the presence and absence of shear is respectively found to be 90.2% and 94.2% accurate. The proposed method can be used to reconstruct climatological mean ocean density field of uniform spatial resolution using only surface elevation data obtained via satellite altimetry.

Original languageEnglish
Article number101561
JournalOcean Modelling
Volume147
Early online date3 Jan 2020
DOIs
Publication statusPublished - Mar 2020

Keywords

  • Climate
  • Density stratification
  • Internal tide
  • Inverse method
  • Mediterranean sea
  • Pycnocline

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Oceanography
  • Geotechnical Engineering and Engineering Geology
  • Atmospheric Science

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