SIC, SIT, SST and SSS from HYCOM-CICE with LAON assimilation of SIC ...
This data is generated using the Norwegian High-resolution (3-5km) pan-Arctic ocean and sea ice Prediction System (NorHAPS), which is based on a coupled HYCOM-CICE model with the Local Analytical Optimal Nudging (LAON) for assimilation. The twin experiment simulations cover the pan-Arctic domain fro...
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| Format: | Dataset |
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Zenodo
2023
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| Online Access: | https://dx.doi.org/10.5281/zenodo.7533372 https://zenodo.org/record/7533372 |
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ftdatacite:10.5281/zenodo.7533372 |
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openpolar |
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ftdatacite:10.5281/zenodo.7533372 2023-12-03T10:16:33+01:00 SIC, SIT, SST and SSS from HYCOM-CICE with LAON assimilation of SIC ... Wang, Keguang Ali, Alfatih Wang, Caixin 2023 https://dx.doi.org/10.5281/zenodo.7533372 https://zenodo.org/record/7533372 unknown Zenodo https://dx.doi.org/10.5281/zenodo.7533371 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 sea ice concentration, sea ice thickness, sea surface temperature, sea surface salinity dataset Dataset 2023 ftdatacite https://doi.org/10.5281/zenodo.753337210.5281/zenodo.7533371 2023-11-03T11:00:21Z This data is generated using the Norwegian High-resolution (3-5km) pan-Arctic ocean and sea ice Prediction System (NorHAPS), which is based on a coupled HYCOM-CICE model with the Local Analytical Optimal Nudging (LAON) for assimilation. The twin experiment simulations cover the pan-Arctic domain from 1 January 2021 to 30 April 2022, with and without assimilation of sea ice concentration. The data includes sea ice concentration and thickness, sea surface temperature and salinity. ... Dataset Arctic Arctic Ocean Sea ice DataCite Metadata Store (German National Library of Science and Technology) Arctic Arctic Ocean |
| institution |
Open Polar |
| collection |
DataCite Metadata Store (German National Library of Science and Technology) |
| op_collection_id |
ftdatacite |
| language |
unknown |
| topic |
sea ice concentration, sea ice thickness, sea surface temperature, sea surface salinity |
| spellingShingle |
sea ice concentration, sea ice thickness, sea surface temperature, sea surface salinity Wang, Keguang Ali, Alfatih Wang, Caixin SIC, SIT, SST and SSS from HYCOM-CICE with LAON assimilation of SIC ... |
| topic_facet |
sea ice concentration, sea ice thickness, sea surface temperature, sea surface salinity |
| description |
This data is generated using the Norwegian High-resolution (3-5km) pan-Arctic ocean and sea ice Prediction System (NorHAPS), which is based on a coupled HYCOM-CICE model with the Local Analytical Optimal Nudging (LAON) for assimilation. The twin experiment simulations cover the pan-Arctic domain from 1 January 2021 to 30 April 2022, with and without assimilation of sea ice concentration. The data includes sea ice concentration and thickness, sea surface temperature and salinity. ... |
| format |
Dataset |
| author |
Wang, Keguang Ali, Alfatih Wang, Caixin |
| author_facet |
Wang, Keguang Ali, Alfatih Wang, Caixin |
| author_sort |
Wang, Keguang |
| title |
SIC, SIT, SST and SSS from HYCOM-CICE with LAON assimilation of SIC ... |
| title_short |
SIC, SIT, SST and SSS from HYCOM-CICE with LAON assimilation of SIC ... |
| title_full |
SIC, SIT, SST and SSS from HYCOM-CICE with LAON assimilation of SIC ... |
| title_fullStr |
SIC, SIT, SST and SSS from HYCOM-CICE with LAON assimilation of SIC ... |
| title_full_unstemmed |
SIC, SIT, SST and SSS from HYCOM-CICE with LAON assimilation of SIC ... |
| title_sort |
sic, sit, sst and sss from hycom-cice with laon assimilation of sic ... |
| publisher |
Zenodo |
| publishDate |
2023 |
| url |
https://dx.doi.org/10.5281/zenodo.7533372 https://zenodo.org/record/7533372 |
| geographic |
Arctic Arctic Ocean |
| geographic_facet |
Arctic Arctic Ocean |
| genre |
Arctic Arctic Ocean Sea ice |
| genre_facet |
Arctic Arctic Ocean Sea ice |
| op_relation |
https://dx.doi.org/10.5281/zenodo.7533371 |
| 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_doi |
https://doi.org/10.5281/zenodo.753337210.5281/zenodo.7533371 |
| _version_ |
1784263498468950016 |