The CMCC Eddy-permitting Global Ocean Physical Reanalysis (C-GLORS v5, 1980-2014), links to NetCDF files ...

The CMCC Global Ocean Physical Reanalysis System (C-GLORS) is used to simulate the state of the ocean in the last decades. It consists of a variational data assimilation system (OceanVar), capable of assimilating all in-situ observations along with altimetry data, and a forecast step performed by th...

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Main Authors: Storto, Andrea, Masina, Simona
Format: Dataset
Language:English
Published: PANGAEA 2016
Subjects:
Online Access:https://dx.doi.org/10.1594/pangaea.857995
https://doi.pangaea.de/10.1594/PANGAEA.857995
id ftdatacite:10.1594/pangaea.857995
record_format openpolar
spelling ftdatacite:10.1594/pangaea.857995 2024-06-09T07:49:29+00:00 The CMCC Eddy-permitting Global Ocean Physical Reanalysis (C-GLORS v5, 1980-2014), links to NetCDF files ... Storto, Andrea Masina, Simona 2016 text/tab-separated-values https://dx.doi.org/10.1594/pangaea.857995 https://doi.pangaea.de/10.1594/PANGAEA.857995 en eng PANGAEA http://c-glors.cmcc.it/index/index.html https://hs.pangaea.de/model/C-GLORSv5/C-GLORSv5.zip http://c-glors.cmcc.it/index/index.html https://dx.doi.org/10.1002/2013jc009067 https://dx.doi.org/10.1109/36.843033 https://dx.doi.org/10.1175/2007jcli1824.1 https://dx.doi.org/10.1002/qj.2673 https://dx.doi.org/10.1175/1520-0493(2003)131<0845:mgsiwa>2.0.co;2 https://hs.pangaea.de/model/C-GLORSv5/C-GLORSv5.zip Creative Commons Attribution 3.0 Unported https://creativecommons.org/licenses/by/3.0/legalcode cc-by-3.0 DATE/TIME File name File size Uniform resource locator/link to file Dataset dataset 2016 ftdatacite https://doi.org/10.1594/pangaea.85799510.1002/2013jc00906710.1109/36.84303310.1175/2007jcli1824.110.1002/qj.267310.1175/1520-0493(2003)131<0845:mgsiwa>2.0.co;2 2024-05-13T12:44:57Z The CMCC Global Ocean Physical Reanalysis System (C-GLORS) is used to simulate the state of the ocean in the last decades. It consists of a variational data assimilation system (OceanVar), capable of assimilating all in-situ observations along with altimetry data, and a forecast step performed by the ocean model NEMO coupled with the LIM2 sea-ice model.KEY STRENGTHS:- Data are available for a large number of ocean parameters- An extensive validation has been conducted and is freely available- The reanalysis is performed at high resolution (1/4 degree) and spans the last 30 yearsKEY LIMITATIONS:- Quality may be discontinuos and depend on observation coverage- Uncertainty estimates are simply derived through verification skill scoresNote (2017-02-09): C-GLORSv5 is dissemniated on PANGAEA at reduced resolution, i.e. a regular 0.5x0.5 degree grid. For full resolution data sets see "CMCC Global Ocean Reanalysis System (C-GLORS), external website" (Related to:) ... Dataset Sea ice DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic DATE/TIME
File name
File size
Uniform resource locator/link to file
spellingShingle DATE/TIME
File name
File size
Uniform resource locator/link to file
Storto, Andrea
Masina, Simona
The CMCC Eddy-permitting Global Ocean Physical Reanalysis (C-GLORS v5, 1980-2014), links to NetCDF files ...
topic_facet DATE/TIME
File name
File size
Uniform resource locator/link to file
description The CMCC Global Ocean Physical Reanalysis System (C-GLORS) is used to simulate the state of the ocean in the last decades. It consists of a variational data assimilation system (OceanVar), capable of assimilating all in-situ observations along with altimetry data, and a forecast step performed by the ocean model NEMO coupled with the LIM2 sea-ice model.KEY STRENGTHS:- Data are available for a large number of ocean parameters- An extensive validation has been conducted and is freely available- The reanalysis is performed at high resolution (1/4 degree) and spans the last 30 yearsKEY LIMITATIONS:- Quality may be discontinuos and depend on observation coverage- Uncertainty estimates are simply derived through verification skill scoresNote (2017-02-09): C-GLORSv5 is dissemniated on PANGAEA at reduced resolution, i.e. a regular 0.5x0.5 degree grid. For full resolution data sets see "CMCC Global Ocean Reanalysis System (C-GLORS), external website" (Related to:) ...
format Dataset
author Storto, Andrea
Masina, Simona
author_facet Storto, Andrea
Masina, Simona
author_sort Storto, Andrea
title The CMCC Eddy-permitting Global Ocean Physical Reanalysis (C-GLORS v5, 1980-2014), links to NetCDF files ...
title_short The CMCC Eddy-permitting Global Ocean Physical Reanalysis (C-GLORS v5, 1980-2014), links to NetCDF files ...
title_full The CMCC Eddy-permitting Global Ocean Physical Reanalysis (C-GLORS v5, 1980-2014), links to NetCDF files ...
title_fullStr The CMCC Eddy-permitting Global Ocean Physical Reanalysis (C-GLORS v5, 1980-2014), links to NetCDF files ...
title_full_unstemmed The CMCC Eddy-permitting Global Ocean Physical Reanalysis (C-GLORS v5, 1980-2014), links to NetCDF files ...
title_sort cmcc eddy-permitting global ocean physical reanalysis (c-glors v5, 1980-2014), links to netcdf files ...
publisher PANGAEA
publishDate 2016
url https://dx.doi.org/10.1594/pangaea.857995
https://doi.pangaea.de/10.1594/PANGAEA.857995
genre Sea ice
genre_facet Sea ice
op_relation http://c-glors.cmcc.it/index/index.html
https://hs.pangaea.de/model/C-GLORSv5/C-GLORSv5.zip
http://c-glors.cmcc.it/index/index.html
https://dx.doi.org/10.1002/2013jc009067
https://dx.doi.org/10.1109/36.843033
https://dx.doi.org/10.1175/2007jcli1824.1
https://dx.doi.org/10.1002/qj.2673
https://dx.doi.org/10.1175/1520-0493(2003)131<0845:mgsiwa>2.0.co;2
https://hs.pangaea.de/model/C-GLORSv5/C-GLORSv5.zip
op_rights Creative Commons Attribution 3.0 Unported
https://creativecommons.org/licenses/by/3.0/legalcode
cc-by-3.0
op_doi https://doi.org/10.1594/pangaea.85799510.1002/2013jc00906710.1109/36.84303310.1175/2007jcli1824.110.1002/qj.267310.1175/1520-0493(2003)131<0845:mgsiwa>2.0.co;2
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