The prediction data analyzed in "Seasonal Arctic sea ice prediction using a newly developed fully coupled regional model with the assimilation of satellite sea ice observations"

The outputs of seasonal predictions with the new modeling system analyzed in the article including: Sea ice concentration (SIC) Sea ice thickness (SIT) Sea surface temperature (SST) Near surface air temperature (T2)

Bibliographic Details
Main Authors: Yang, Chao-Yuan, Liu, Jiping, Xu, Shiming
Format: Dataset
Language:unknown
Published: Zenodo 2019
Subjects:
Arctic
Sea ice
Online Access:https://dx.doi.org/10.5281/zenodo.3524767
https://zenodo.org/record/3524767
id ftdatacite:10.5281/zenodo.3524767
record_format openpolar
spelling ftdatacite:10.5281/zenodo.3524767 2023-05-15T14:53:16+02:00 The prediction data analyzed in "Seasonal Arctic sea ice prediction using a newly developed fully coupled regional model with the assimilation of satellite sea ice observations" Yang, Chao-Yuan Liu, Jiping Xu, Shiming 2019 https://dx.doi.org/10.5281/zenodo.3524767 https://zenodo.org/record/3524767 unknown Zenodo https://dx.doi.org/10.5281/zenodo.3524766 Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess CC-BY dataset Dataset 2019 ftdatacite https://doi.org/10.5281/zenodo.3524767 https://doi.org/10.5281/zenodo.3524766 2021-11-05T12:55:41Z The outputs of seasonal predictions with the new modeling system analyzed in the article including: Sea ice concentration (SIC) Sea ice thickness (SIT) Sea surface temperature (SST) Near surface air temperature (T2) Dataset Arctic Sea ice DataCite Metadata Store (German National Library of Science and Technology) Arctic
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
description The outputs of seasonal predictions with the new modeling system analyzed in the article including: Sea ice concentration (SIC) Sea ice thickness (SIT) Sea surface temperature (SST) Near surface air temperature (T2)
format Dataset
author Yang, Chao-Yuan
Liu, Jiping
Xu, Shiming
spellingShingle Yang, Chao-Yuan
Liu, Jiping
Xu, Shiming
The prediction data analyzed in "Seasonal Arctic sea ice prediction using a newly developed fully coupled regional model with the assimilation of satellite sea ice observations"
author_facet Yang, Chao-Yuan
Liu, Jiping
Xu, Shiming
author_sort Yang, Chao-Yuan
title The prediction data analyzed in "Seasonal Arctic sea ice prediction using a newly developed fully coupled regional model with the assimilation of satellite sea ice observations"
title_short The prediction data analyzed in "Seasonal Arctic sea ice prediction using a newly developed fully coupled regional model with the assimilation of satellite sea ice observations"
title_full The prediction data analyzed in "Seasonal Arctic sea ice prediction using a newly developed fully coupled regional model with the assimilation of satellite sea ice observations"
title_fullStr The prediction data analyzed in "Seasonal Arctic sea ice prediction using a newly developed fully coupled regional model with the assimilation of satellite sea ice observations"
title_full_unstemmed The prediction data analyzed in "Seasonal Arctic sea ice prediction using a newly developed fully coupled regional model with the assimilation of satellite sea ice observations"
title_sort prediction data analyzed in "seasonal arctic sea ice prediction using a newly developed fully coupled regional model with the assimilation of satellite sea ice observations"
publisher Zenodo
publishDate 2019
url https://dx.doi.org/10.5281/zenodo.3524767
https://zenodo.org/record/3524767
geographic Arctic
geographic_facet Arctic
genre Arctic
Sea ice
genre_facet Arctic
Sea ice
op_relation https://dx.doi.org/10.5281/zenodo.3524766
op_rights Open Access
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
info:eu-repo/semantics/openAccess
op_rightsnorm CC-BY
op_doi https://doi.org/10.5281/zenodo.3524767
https://doi.org/10.5281/zenodo.3524766
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