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Assimilation of the seabird and ship drift data in the north-eastern sea of Japan into an operational ocean nowcast/forecast system
At the present time, ocean current is being operationally monitored mainly by combined use of numerical ocean nowcast/forecast models and satellite remote sensing data. Improvement in the accuracy of the ocean current nowcast/forecast requires additional measurements with higher spatial and temporal...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4668391/ https://www.ncbi.nlm.nih.gov/pubmed/26633309 http://dx.doi.org/10.1038/srep17672 |
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author | Miyazawa, Yasumasa Guo, Xinyu Varlamov, Sergey M. Miyama, Toru Yoda, Ken Sato, Katsufumi Kano, Toshiyuki Sato, Keiji |
author_facet | Miyazawa, Yasumasa Guo, Xinyu Varlamov, Sergey M. Miyama, Toru Yoda, Ken Sato, Katsufumi Kano, Toshiyuki Sato, Keiji |
author_sort | Miyazawa, Yasumasa |
collection | PubMed |
description | At the present time, ocean current is being operationally monitored mainly by combined use of numerical ocean nowcast/forecast models and satellite remote sensing data. Improvement in the accuracy of the ocean current nowcast/forecast requires additional measurements with higher spatial and temporal resolution as expected from the current observation network. Here we show feasibility of assimilating high-resolution seabird and ship drift data into an operational ocean forecast system. Data assimilation of geostrophic current contained in the observed drift leads to refinement in the gyre mode events of the Tsugaru warm current in the north-eastern sea of Japan represented by the model. Fitting the observed drift to the model depends on ability of the drift representing geostrophic current compared to that representing directly wind driven components. A preferable horizontal scale of 50 km indicated for the seabird drift data assimilation implies their capability of capturing eddies with smaller horizontal scale than the minimum scale of 100 km resolved by the satellite altimetry. The present study actually demonstrates that transdisciplinary approaches combining bio-/ship- logging and numerical modeling could be effective for enhancement in monitoring the ocean current. |
format | Online Article Text |
id | pubmed-4668391 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-46683912015-12-09 Assimilation of the seabird and ship drift data in the north-eastern sea of Japan into an operational ocean nowcast/forecast system Miyazawa, Yasumasa Guo, Xinyu Varlamov, Sergey M. Miyama, Toru Yoda, Ken Sato, Katsufumi Kano, Toshiyuki Sato, Keiji Sci Rep Article At the present time, ocean current is being operationally monitored mainly by combined use of numerical ocean nowcast/forecast models and satellite remote sensing data. Improvement in the accuracy of the ocean current nowcast/forecast requires additional measurements with higher spatial and temporal resolution as expected from the current observation network. Here we show feasibility of assimilating high-resolution seabird and ship drift data into an operational ocean forecast system. Data assimilation of geostrophic current contained in the observed drift leads to refinement in the gyre mode events of the Tsugaru warm current in the north-eastern sea of Japan represented by the model. Fitting the observed drift to the model depends on ability of the drift representing geostrophic current compared to that representing directly wind driven components. A preferable horizontal scale of 50 km indicated for the seabird drift data assimilation implies their capability of capturing eddies with smaller horizontal scale than the minimum scale of 100 km resolved by the satellite altimetry. The present study actually demonstrates that transdisciplinary approaches combining bio-/ship- logging and numerical modeling could be effective for enhancement in monitoring the ocean current. Nature Publishing Group 2015-12-03 /pmc/articles/PMC4668391/ /pubmed/26633309 http://dx.doi.org/10.1038/srep17672 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Miyazawa, Yasumasa Guo, Xinyu Varlamov, Sergey M. Miyama, Toru Yoda, Ken Sato, Katsufumi Kano, Toshiyuki Sato, Keiji Assimilation of the seabird and ship drift data in the north-eastern sea of Japan into an operational ocean nowcast/forecast system |
title | Assimilation of the seabird and ship drift data in the north-eastern sea of Japan into an operational ocean nowcast/forecast system |
title_full | Assimilation of the seabird and ship drift data in the north-eastern sea of Japan into an operational ocean nowcast/forecast system |
title_fullStr | Assimilation of the seabird and ship drift data in the north-eastern sea of Japan into an operational ocean nowcast/forecast system |
title_full_unstemmed | Assimilation of the seabird and ship drift data in the north-eastern sea of Japan into an operational ocean nowcast/forecast system |
title_short | Assimilation of the seabird and ship drift data in the north-eastern sea of Japan into an operational ocean nowcast/forecast system |
title_sort | assimilation of the seabird and ship drift data in the north-eastern sea of japan into an operational ocean nowcast/forecast system |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4668391/ https://www.ncbi.nlm.nih.gov/pubmed/26633309 http://dx.doi.org/10.1038/srep17672 |
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