Predictability of Arctic sea ice on weather time scales
The field of Arctic sea ice prediction on “weather time scales” is still in its infancy with little existing understanding of the limits of predictability. This is especially true for sea ice deformation along so-called Linear Kinematic Features (LKFs) including leads that are relevant for marine op...
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ftpubmed:oai:pubmedcentral.nih.gov:5916911 2023-05-15T14:52:37+02:00 Predictability of Arctic sea ice on weather time scales Mohammadi-Aragh, M. Goessling, H. F. Losch, M. Hutter, N. Jung, T. 2018-04-25 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5916911/ http://www.ncbi.nlm.nih.gov/pubmed/29695814 https://doi.org/10.1038/s41598-018-24660-0 en eng Nature Publishing Group UK http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5916911/ http://www.ncbi.nlm.nih.gov/pubmed/29695814 http://dx.doi.org/10.1038/s41598-018-24660-0 © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. CC-BY Article Text 2018 ftpubmed https://doi.org/10.1038/s41598-018-24660-0 2018-05-06T00:32:23Z The field of Arctic sea ice prediction on “weather time scales” is still in its infancy with little existing understanding of the limits of predictability. This is especially true for sea ice deformation along so-called Linear Kinematic Features (LKFs) including leads that are relevant for marine operations. Here the potential predictability of the sea ice pack in the wintertime Arctic up to ten days ahead is determined, exploiting the fact that sea ice-ocean models start to show skill at representing sea ice deformation at high spatial resolutions. Results are based on ensemble simulations with a high-resolution sea ice-ocean model driven by atmospheric ensemble forecasts. The predictability of LKFs as measured by different metrics drops quickly, with predictability being almost completely lost after 4–8 days. In contrast, quantities such as sea ice concentration or the location of the ice edge retain high levels of predictability throughout the full 10-day forecast period. It is argued that the rapid error growth for LKFs is mainly due to the chaotic behaviour of the atmosphere associated with the low predictability of near surface wind divergence and vorticity; initial condition uncertainty for ice thickness is found to be of minor importance as long as LKFs are initialized at the right locations. Text Arctic ice pack Sea ice PubMed Central (PMC) Arctic Scientific Reports 8 1 |
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Article Mohammadi-Aragh, M. Goessling, H. F. Losch, M. Hutter, N. Jung, T. Predictability of Arctic sea ice on weather time scales |
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The field of Arctic sea ice prediction on “weather time scales” is still in its infancy with little existing understanding of the limits of predictability. This is especially true for sea ice deformation along so-called Linear Kinematic Features (LKFs) including leads that are relevant for marine operations. Here the potential predictability of the sea ice pack in the wintertime Arctic up to ten days ahead is determined, exploiting the fact that sea ice-ocean models start to show skill at representing sea ice deformation at high spatial resolutions. Results are based on ensemble simulations with a high-resolution sea ice-ocean model driven by atmospheric ensemble forecasts. The predictability of LKFs as measured by different metrics drops quickly, with predictability being almost completely lost after 4–8 days. In contrast, quantities such as sea ice concentration or the location of the ice edge retain high levels of predictability throughout the full 10-day forecast period. It is argued that the rapid error growth for LKFs is mainly due to the chaotic behaviour of the atmosphere associated with the low predictability of near surface wind divergence and vorticity; initial condition uncertainty for ice thickness is found to be of minor importance as long as LKFs are initialized at the right locations. |
format |
Text |
author |
Mohammadi-Aragh, M. Goessling, H. F. Losch, M. Hutter, N. Jung, T. |
author_facet |
Mohammadi-Aragh, M. Goessling, H. F. Losch, M. Hutter, N. Jung, T. |
author_sort |
Mohammadi-Aragh, M. |
title |
Predictability of Arctic sea ice on weather time scales |
title_short |
Predictability of Arctic sea ice on weather time scales |
title_full |
Predictability of Arctic sea ice on weather time scales |
title_fullStr |
Predictability of Arctic sea ice on weather time scales |
title_full_unstemmed |
Predictability of Arctic sea ice on weather time scales |
title_sort |
predictability of arctic sea ice on weather time scales |
publisher |
Nature Publishing Group UK |
publishDate |
2018 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5916911/ http://www.ncbi.nlm.nih.gov/pubmed/29695814 https://doi.org/10.1038/s41598-018-24660-0 |
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Arctic |
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Arctic |
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Arctic ice pack Sea ice |
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Arctic ice pack Sea ice |
op_relation |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5916911/ http://www.ncbi.nlm.nih.gov/pubmed/29695814 http://dx.doi.org/10.1038/s41598-018-24660-0 |
op_rights |
© The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
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CC-BY |
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https://doi.org/10.1038/s41598-018-24660-0 |
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Scientific Reports |
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8 |
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