Evaluation of sea-ice thickness reanalysis data from the coupled ocean-sea-ice data assimilation system TOPAZ4

Abstract With the assimilation of satellite-based sea-ice thickness (SIT) data, the new SIT reanalysis from the Towards an Operational Prediction system for the North Atlantic European coastal Zones (TOPAZ4) was released from 2014 to 2018. Apart from assimilating sea-ice concentration and oceanic va...

Full description

Bibliographic Details
Published in:Journal of Glaciology
Main Authors: Xiu, Yongwu, Min, Chao, Xie, Jiping, Mu, Longjiang, Han, Bo, Yang, Qinghua
Format: Article in Journal/Newspaper
Language:English
Published: Cambridge University Press (CUP) 2021
Subjects:
Online Access:http://dx.doi.org/10.1017/jog.2020.110
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143020001100
id crcambridgeupr:10.1017/jog.2020.110
record_format openpolar
spelling crcambridgeupr:10.1017/jog.2020.110 2024-05-19T07:33:37+00:00 Evaluation of sea-ice thickness reanalysis data from the coupled ocean-sea-ice data assimilation system TOPAZ4 Xiu, Yongwu Min, Chao Xie, Jiping Mu, Longjiang Han, Bo Yang, Qinghua 2021 http://dx.doi.org/10.1017/jog.2020.110 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143020001100 en eng Cambridge University Press (CUP) http://creativecommons.org/licenses/by/4.0/ Journal of Glaciology volume 67, issue 262, page 353-365 ISSN 0022-1430 1727-5652 journal-article 2021 crcambridgeupr https://doi.org/10.1017/jog.2020.110 2024-04-25T06:51:31Z Abstract With the assimilation of satellite-based sea-ice thickness (SIT) data, the new SIT reanalysis from the Towards an Operational Prediction system for the North Atlantic European coastal Zones (TOPAZ4) was released from 2014 to 2018. Apart from assimilating sea-ice concentration and oceanic variables, TOPAZ4 further assimilates CS2SMOS SIT. In this study, the 5-year reanalysis is compared with CS2SMOS, the Pan-Arctic Ice-Ocean Modeling and Assimilating System (PIOMAS) and the Combined Model and Satellite Thickness (CMST). Moreover, we evaluate TOPAZ4 SIT with field observations from upward-looking sonar (ULS), ice mass-balance buoys, Operation IceBridge Quicklook and Sea State Ship-borne Observations. The results indicate TOPAZ4 well reproduces the spatial characteristics of the Arctic SIT distributions, with large differences with CS2SMOS/PIOMAS/CMST mainly restricted to the Atlantic Sector and to the month of September. TOPAZ4 shows thinner ice in March and April, especially to the north of the Canadian Arctic Archipelago with a mean bias of −0.30 m when compared to IceBridge. Besides, TOPAZ4 simulates thicker ice in the Beaufort Sea when compared to ULS, with a mean bias of 0.11 m all year round. The benefit from assimilating SIT data in TOPAZ4 is reflected in a 34% improvement in root mean square deviation. Article in Journal/Newspaper Arctic Archipelago Arctic Beaufort Sea Canadian Arctic Archipelago Journal of Glaciology North Atlantic Sea ice Cambridge University Press Journal of Glaciology 67 262 353 365
institution Open Polar
collection Cambridge University Press
op_collection_id crcambridgeupr
language English
description Abstract With the assimilation of satellite-based sea-ice thickness (SIT) data, the new SIT reanalysis from the Towards an Operational Prediction system for the North Atlantic European coastal Zones (TOPAZ4) was released from 2014 to 2018. Apart from assimilating sea-ice concentration and oceanic variables, TOPAZ4 further assimilates CS2SMOS SIT. In this study, the 5-year reanalysis is compared with CS2SMOS, the Pan-Arctic Ice-Ocean Modeling and Assimilating System (PIOMAS) and the Combined Model and Satellite Thickness (CMST). Moreover, we evaluate TOPAZ4 SIT with field observations from upward-looking sonar (ULS), ice mass-balance buoys, Operation IceBridge Quicklook and Sea State Ship-borne Observations. The results indicate TOPAZ4 well reproduces the spatial characteristics of the Arctic SIT distributions, with large differences with CS2SMOS/PIOMAS/CMST mainly restricted to the Atlantic Sector and to the month of September. TOPAZ4 shows thinner ice in March and April, especially to the north of the Canadian Arctic Archipelago with a mean bias of −0.30 m when compared to IceBridge. Besides, TOPAZ4 simulates thicker ice in the Beaufort Sea when compared to ULS, with a mean bias of 0.11 m all year round. The benefit from assimilating SIT data in TOPAZ4 is reflected in a 34% improvement in root mean square deviation.
format Article in Journal/Newspaper
author Xiu, Yongwu
Min, Chao
Xie, Jiping
Mu, Longjiang
Han, Bo
Yang, Qinghua
spellingShingle Xiu, Yongwu
Min, Chao
Xie, Jiping
Mu, Longjiang
Han, Bo
Yang, Qinghua
Evaluation of sea-ice thickness reanalysis data from the coupled ocean-sea-ice data assimilation system TOPAZ4
author_facet Xiu, Yongwu
Min, Chao
Xie, Jiping
Mu, Longjiang
Han, Bo
Yang, Qinghua
author_sort Xiu, Yongwu
title Evaluation of sea-ice thickness reanalysis data from the coupled ocean-sea-ice data assimilation system TOPAZ4
title_short Evaluation of sea-ice thickness reanalysis data from the coupled ocean-sea-ice data assimilation system TOPAZ4
title_full Evaluation of sea-ice thickness reanalysis data from the coupled ocean-sea-ice data assimilation system TOPAZ4
title_fullStr Evaluation of sea-ice thickness reanalysis data from the coupled ocean-sea-ice data assimilation system TOPAZ4
title_full_unstemmed Evaluation of sea-ice thickness reanalysis data from the coupled ocean-sea-ice data assimilation system TOPAZ4
title_sort evaluation of sea-ice thickness reanalysis data from the coupled ocean-sea-ice data assimilation system topaz4
publisher Cambridge University Press (CUP)
publishDate 2021
url http://dx.doi.org/10.1017/jog.2020.110
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143020001100
genre Arctic Archipelago
Arctic
Beaufort Sea
Canadian Arctic Archipelago
Journal of Glaciology
North Atlantic
Sea ice
genre_facet Arctic Archipelago
Arctic
Beaufort Sea
Canadian Arctic Archipelago
Journal of Glaciology
North Atlantic
Sea ice
op_source Journal of Glaciology
volume 67, issue 262, page 353-365
ISSN 0022-1430 1727-5652
op_rights http://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.1017/jog.2020.110
container_title Journal of Glaciology
container_volume 67
container_issue 262
container_start_page 353
op_container_end_page 365
_version_ 1799471719797227520