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Surface wind mixing in the Regional Ocean Modeling System (ROMS)

Mixing at the ocean surface is key for atmosphere–ocean interactions and the distribution of heat, energy, and gases in the upper ocean. Winds are the primary force for surface mixing. To properly simulate upper ocean dynamics and the flux of these quantities within the upper ocean, models must repr...

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Autores principales: Robertson, Robin, Hartlipp, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067273/
https://www.ncbi.nlm.nih.gov/pubmed/32215239
http://dx.doi.org/10.1186/s40562-017-0090-7
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author Robertson, Robin
Hartlipp, Paul
author_facet Robertson, Robin
Hartlipp, Paul
author_sort Robertson, Robin
collection PubMed
description Mixing at the ocean surface is key for atmosphere–ocean interactions and the distribution of heat, energy, and gases in the upper ocean. Winds are the primary force for surface mixing. To properly simulate upper ocean dynamics and the flux of these quantities within the upper ocean, models must reproduce mixing in the upper ocean. To evaluate the performance of the Regional Ocean Modeling System (ROMS) in replicating the surface mixing, the results of four different vertical mixing parameterizations were compared against observations, using the surface mixed layer depth, the temperature fields, and observed diffusivities for comparisons. The vertical mixing parameterizations investigated were Mellor–Yamada 2.5 level turbulent closure (MY), Large–McWilliams–Doney Kpp (LMD), Nakanishi–Niino (NN), and the generic length scale (GLS) schemes. This was done for one temperate site in deep water in the Eastern Pacific and three shallow water sites in the Baltic Sea. The model reproduced the surface mixed layer depth reasonably well for all sites; however, the temperature fields were reproduced well for the deep site, but not for the shallow Baltic Sea sites. In the Baltic Sea, the models overmixed the water column after a few days. Vertical temperature diffusivities were higher than those observed and did not show the temporal fluctuations present in the observations. The best performance was by NN and MY; however, MY became unstable in two of the shallow simulations with high winds. The performance of GLS nearly as good as NN and MY. LMD had the poorest performance as it generated temperature diffusivities that were too high and induced too much mixing. Further observational comparisons are needed to evaluate the effects of different stratification and wind conditions and the limitations on the vertical mixing parameterizations.
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spelling pubmed-70672732020-03-23 Surface wind mixing in the Regional Ocean Modeling System (ROMS) Robertson, Robin Hartlipp, Paul Geosci Lett Research Letter Mixing at the ocean surface is key for atmosphere–ocean interactions and the distribution of heat, energy, and gases in the upper ocean. Winds are the primary force for surface mixing. To properly simulate upper ocean dynamics and the flux of these quantities within the upper ocean, models must reproduce mixing in the upper ocean. To evaluate the performance of the Regional Ocean Modeling System (ROMS) in replicating the surface mixing, the results of four different vertical mixing parameterizations were compared against observations, using the surface mixed layer depth, the temperature fields, and observed diffusivities for comparisons. The vertical mixing parameterizations investigated were Mellor–Yamada 2.5 level turbulent closure (MY), Large–McWilliams–Doney Kpp (LMD), Nakanishi–Niino (NN), and the generic length scale (GLS) schemes. This was done for one temperate site in deep water in the Eastern Pacific and three shallow water sites in the Baltic Sea. The model reproduced the surface mixed layer depth reasonably well for all sites; however, the temperature fields were reproduced well for the deep site, but not for the shallow Baltic Sea sites. In the Baltic Sea, the models overmixed the water column after a few days. Vertical temperature diffusivities were higher than those observed and did not show the temporal fluctuations present in the observations. The best performance was by NN and MY; however, MY became unstable in two of the shallow simulations with high winds. The performance of GLS nearly as good as NN and MY. LMD had the poorest performance as it generated temperature diffusivities that were too high and induced too much mixing. Further observational comparisons are needed to evaluate the effects of different stratification and wind conditions and the limitations on the vertical mixing parameterizations. Springer International Publishing 2017-11-02 2017 /pmc/articles/PMC7067273/ /pubmed/32215239 http://dx.doi.org/10.1186/s40562-017-0090-7 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research Letter
Robertson, Robin
Hartlipp, Paul
Surface wind mixing in the Regional Ocean Modeling System (ROMS)
title Surface wind mixing in the Regional Ocean Modeling System (ROMS)
title_full Surface wind mixing in the Regional Ocean Modeling System (ROMS)
title_fullStr Surface wind mixing in the Regional Ocean Modeling System (ROMS)
title_full_unstemmed Surface wind mixing in the Regional Ocean Modeling System (ROMS)
title_short Surface wind mixing in the Regional Ocean Modeling System (ROMS)
title_sort surface wind mixing in the regional ocean modeling system (roms)
topic Research Letter
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067273/
https://www.ncbi.nlm.nih.gov/pubmed/32215239
http://dx.doi.org/10.1186/s40562-017-0090-7
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