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Quantifying spatial distribution of spurious mixing in ocean models
Numerical mixing is inevitable for ocean models due to tracer advection schemes. Until now, there is no robust way to identify the regions of spurious mixing in ocean models. We propose a new method to compute the spatial distribution of the spurious diapycnic mixing in an ocean model. This new meth...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Science Ltd
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5351820/ https://www.ncbi.nlm.nih.gov/pubmed/28344508 http://dx.doi.org/10.1016/j.ocemod.2016.11.002 |
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author | Ilıcak, Mehmet |
author_facet | Ilıcak, Mehmet |
author_sort | Ilıcak, Mehmet |
collection | PubMed |
description | Numerical mixing is inevitable for ocean models due to tracer advection schemes. Until now, there is no robust way to identify the regions of spurious mixing in ocean models. We propose a new method to compute the spatial distribution of the spurious diapycnic mixing in an ocean model. This new method is an extension of available potential energy density method proposed by Winters and Barkan (2013). We test the new method in lock-exchange and baroclinic eddies test cases. We can quantify the amount and the location of numerical mixing. We find high-shear areas are the main regions which are susceptible to numerical truncation errors. We also test the new method to quantify the numerical mixing in different horizontal momentum closures. We conclude that Smagorinsky viscosity has less numerical mixing than the Leith viscosity using the same non-dimensional constant. |
format | Online Article Text |
id | pubmed-5351820 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Elsevier Science Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-53518202017-03-23 Quantifying spatial distribution of spurious mixing in ocean models Ilıcak, Mehmet Ocean Model (Oxf) Article Numerical mixing is inevitable for ocean models due to tracer advection schemes. Until now, there is no robust way to identify the regions of spurious mixing in ocean models. We propose a new method to compute the spatial distribution of the spurious diapycnic mixing in an ocean model. This new method is an extension of available potential energy density method proposed by Winters and Barkan (2013). We test the new method in lock-exchange and baroclinic eddies test cases. We can quantify the amount and the location of numerical mixing. We find high-shear areas are the main regions which are susceptible to numerical truncation errors. We also test the new method to quantify the numerical mixing in different horizontal momentum closures. We conclude that Smagorinsky viscosity has less numerical mixing than the Leith viscosity using the same non-dimensional constant. Elsevier Science Ltd 2016-12 /pmc/articles/PMC5351820/ /pubmed/28344508 http://dx.doi.org/10.1016/j.ocemod.2016.11.002 Text en © 2016 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Ilıcak, Mehmet Quantifying spatial distribution of spurious mixing in ocean models |
title | Quantifying spatial distribution of spurious mixing in ocean models |
title_full | Quantifying spatial distribution of spurious mixing in ocean models |
title_fullStr | Quantifying spatial distribution of spurious mixing in ocean models |
title_full_unstemmed | Quantifying spatial distribution of spurious mixing in ocean models |
title_short | Quantifying spatial distribution of spurious mixing in ocean models |
title_sort | quantifying spatial distribution of spurious mixing in ocean models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5351820/ https://www.ncbi.nlm.nih.gov/pubmed/28344508 http://dx.doi.org/10.1016/j.ocemod.2016.11.002 |
work_keys_str_mv | AT ilıcakmehmet quantifyingspatialdistributionofspuriousmixinginoceanmodels |