Downscaling ocean conditions with application to the Gulf of Maine, Scotian Shelf and adjacent deep ocean

Katavouta, Anna ORCID: https://orcid.org/0000-0002-1587-4996; Thompson, Keith R.. 2016 Downscaling ocean conditions with application to the Gulf of Maine, Scotian Shelf and adjacent deep ocean. Ocean Modelling, 104. 54-72. https://doi.org/10.1016/j.ocemod.2016.05.007

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Official URL: http://dx.doi.org/10.1016/j.ocemod.2016.05.007

Abstract/Summary

The overall goal is to downscale ocean conditions predicted by an existing global prediction system and evaluate the results using observations from the Gulf of Maine, Scotian Shelf and adjacent deep ocean. The first step is to develop a one-way nested regional model and evaluate its predictions using observations from multiple sources including satellite-borne sensors of surface temperature and sea level, CTDs, Argo floats and moored current meters. It is shown that the regional model predicts more realistic fields than the global system on the shelf because it has higher resolution and includes tides that are absent from the global system. However, in deep water the regional model misplaces deep ocean eddies and meanders associated with the Gulf Stream. This is not because the regional model’s dynamics are flawed but rather is the result of internally generated variability in deep water that leads to decoupling of the regional model from the global system. To overcome this problem, the next step is to spectrally nudge the regional model to the large scales (length scales > 90 km) of the global system. It is shown this leads to more realistic predictions off the shelf. Wavenumber spectra show that even though spectral nudging constrains the large scales, it does not suppress the variability on small scales; on the contrary, it favours the formation of eddies with length scales below the cutoff wavelength of the spectral nudging.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1016/j.ocemod.2016.05.007
ISSN:	14635003
Date made live:	02 Oct 2020 08:41 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/528582

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1016/j.ocemod.2016.05.007

ISSN:

14635003

Date made live:

02 Oct 2020 08:41 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/528582