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Shrira, VI and Almelah, RB (2020) What do we need to Probe Upper Ocean Stratification Remotely? Radiophysics and Quantum Electronics, 63 (1). 1 - 20. ISSN 0033-8443
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Abstract
We consider whether it is possible in principle to retrieve the key parameters of the mixed layer in the upper ocean (its thickness, bulk eddy viscosity and the pycnocline stratification below) using a theoretical model, which assumes the surface velocity and wind stress to be known from observations. To this end we examine the dynamics of the Ekman current in the novel two-layer model of the upper ocean made of two layers with greatly differing constant eddy viscosities. The presence of stratification manifests itself through suppression of turbulence and, hence, in much smaller value of the eddy viscosity compared to the bulk eddy viscosity ve1 in the mixed layer. Within this two-layer model the general solution in terms of Green’s function has been derived and analyzed. It was found that a spectral component of frequency ω of the Ekman current on the surface “feels” the presence of the stratified layer when the mixed layer depth d is less then or comparable to the Ekman scale 2ve1/f+ω−−−−−−−−−√, where f is the Coriolis parameter. Thus, under conditions of strong wind resulting in large eddy viscosity ve1, the depth of the mixed layer could be (in principle) inferred from the observations of wind and surface velocity. We conclude by stating that to retrieve the mixed layer parameters from the wind and surface velocity data, the theoretical model has to be extended by taking into account the effects of the Stokes drift due to surface waves and the possibility of intense mixing at the bottom of the mixed layer.
Item Type: | Article |
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Additional Information: | The final version of this article and all relevant information related to it can be found online at; https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/upperocean-ekman-current-dynamics-a-new-perspective/BD487AE60B8053C00DC5A79F94C8ADC9 |
Subjects: | G Geography. Anthropology. Recreation > GC Oceanography T Technology > T Technology (General) |
Divisions: | Faculty of Natural Sciences > School of Computing and Mathematics |
Depositing User: | Symplectic |
Date Deposited: | 18 Nov 2020 12:25 |
Last Modified: | 17 Oct 2021 01:30 |
URI: | https://eprints.keele.ac.uk/id/eprint/8890 |