Improvements in September Arctic Sea Ice Predictions Via Assimilation of Summer CryoSat‐2 Sea Ice Thickness Observations

Abstract Because of a spring predictability barrier, the seasonal forecast skill of Arctic summer sea ice is limited by the availability of melt‐season sea ice thickness (SIT) observations. The first year‐round SIT observations, retrieved from CryoSat‐2 from 2011 to 2020, are assimilated into the GF...

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Published in:Geophysical Research Letters
Main Authors: Yong‐Fei Zhang, Mitchell Bushuk, Michael Winton, Bill Hurlin, William Gregory, Jack Landy, Liwei Jia
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2023
Subjects:
Online Access:https://doi.org/10.1029/2023GL105672
https://doaj.org/article/d339bbe64182499fbd312ebd78929ab7
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spelling ftdoajarticles:oai:doaj.org/article:d339bbe64182499fbd312ebd78929ab7 2024-09-15T18:01:59+00:00 Improvements in September Arctic Sea Ice Predictions Via Assimilation of Summer CryoSat‐2 Sea Ice Thickness Observations Yong‐Fei Zhang Mitchell Bushuk Michael Winton Bill Hurlin William Gregory Jack Landy Liwei Jia 2023-12-01T00:00:00Z https://doi.org/10.1029/2023GL105672 https://doaj.org/article/d339bbe64182499fbd312ebd78929ab7 EN eng Wiley https://doi.org/10.1029/2023GL105672 https://doaj.org/toc/0094-8276 https://doaj.org/toc/1944-8007 1944-8007 0094-8276 doi:10.1029/2023GL105672 https://doaj.org/article/d339bbe64182499fbd312ebd78929ab7 Geophysical Research Letters, Vol 50, Iss 24, Pp n/a-n/a (2023) Arctic sea ice thickness data assimilation seasonal prediction Geophysics. Cosmic physics QC801-809 article 2023 ftdoajarticles https://doi.org/10.1029/2023GL105672 2024-08-05T17:49:23Z Abstract Because of a spring predictability barrier, the seasonal forecast skill of Arctic summer sea ice is limited by the availability of melt‐season sea ice thickness (SIT) observations. The first year‐round SIT observations, retrieved from CryoSat‐2 from 2011 to 2020, are assimilated into the GFDL ocean–sea ice model. The model's SIT anomaly field is brought into significantly better agreement with the observations, particularly in the Central Arctic. Although the short observational period makes forecast assessment challenging, we find that the addition of May–August SIT assimilation improves September local sea ice concentration (SIC) and extent forecasts similarly to SIC‐only assimilation. Although most regional forecasts are improved by SIT assimilation, the Chukchi Sea forecasts are degraded. This degradation is likely due to the introduction of negative correlations between September SIC and earlier SIT introduced by SIT assimilation, contrary to the increased correlations found in other regions. Article in Journal/Newspaper Chukchi Chukchi Sea Sea ice Directory of Open Access Journals: DOAJ Articles Geophysical Research Letters 50 24
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Arctic
sea ice thickness
data assimilation
seasonal prediction
Geophysics. Cosmic physics
QC801-809
spellingShingle Arctic
sea ice thickness
data assimilation
seasonal prediction
Geophysics. Cosmic physics
QC801-809
Yong‐Fei Zhang
Mitchell Bushuk
Michael Winton
Bill Hurlin
William Gregory
Jack Landy
Liwei Jia
Improvements in September Arctic Sea Ice Predictions Via Assimilation of Summer CryoSat‐2 Sea Ice Thickness Observations
topic_facet Arctic
sea ice thickness
data assimilation
seasonal prediction
Geophysics. Cosmic physics
QC801-809
description Abstract Because of a spring predictability barrier, the seasonal forecast skill of Arctic summer sea ice is limited by the availability of melt‐season sea ice thickness (SIT) observations. The first year‐round SIT observations, retrieved from CryoSat‐2 from 2011 to 2020, are assimilated into the GFDL ocean–sea ice model. The model's SIT anomaly field is brought into significantly better agreement with the observations, particularly in the Central Arctic. Although the short observational period makes forecast assessment challenging, we find that the addition of May–August SIT assimilation improves September local sea ice concentration (SIC) and extent forecasts similarly to SIC‐only assimilation. Although most regional forecasts are improved by SIT assimilation, the Chukchi Sea forecasts are degraded. This degradation is likely due to the introduction of negative correlations between September SIC and earlier SIT introduced by SIT assimilation, contrary to the increased correlations found in other regions.
format Article in Journal/Newspaper
author Yong‐Fei Zhang
Mitchell Bushuk
Michael Winton
Bill Hurlin
William Gregory
Jack Landy
Liwei Jia
author_facet Yong‐Fei Zhang
Mitchell Bushuk
Michael Winton
Bill Hurlin
William Gregory
Jack Landy
Liwei Jia
author_sort Yong‐Fei Zhang
title Improvements in September Arctic Sea Ice Predictions Via Assimilation of Summer CryoSat‐2 Sea Ice Thickness Observations
title_short Improvements in September Arctic Sea Ice Predictions Via Assimilation of Summer CryoSat‐2 Sea Ice Thickness Observations
title_full Improvements in September Arctic Sea Ice Predictions Via Assimilation of Summer CryoSat‐2 Sea Ice Thickness Observations
title_fullStr Improvements in September Arctic Sea Ice Predictions Via Assimilation of Summer CryoSat‐2 Sea Ice Thickness Observations
title_full_unstemmed Improvements in September Arctic Sea Ice Predictions Via Assimilation of Summer CryoSat‐2 Sea Ice Thickness Observations
title_sort improvements in september arctic sea ice predictions via assimilation of summer cryosat‐2 sea ice thickness observations
publisher Wiley
publishDate 2023
url https://doi.org/10.1029/2023GL105672
https://doaj.org/article/d339bbe64182499fbd312ebd78929ab7
genre Chukchi
Chukchi Sea
Sea ice
genre_facet Chukchi
Chukchi Sea
Sea ice
op_source Geophysical Research Letters, Vol 50, Iss 24, Pp n/a-n/a (2023)
op_relation https://doi.org/10.1029/2023GL105672
https://doaj.org/toc/0094-8276
https://doaj.org/toc/1944-8007
1944-8007
0094-8276
doi:10.1029/2023GL105672
https://doaj.org/article/d339bbe64182499fbd312ebd78929ab7
op_doi https://doi.org/10.1029/2023GL105672
container_title Geophysical Research Letters
container_volume 50
container_issue 24
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