Influence of Arctic Sea ice concentration on extended-range prediction of strong and Long-lasting ural blocking events in Winter ...

<!--!introduction!--> It is traditionally considered that the predictability of atmosphere reaches approximately 2 weeks due to its chaotic features. Considering boundary conditions, the lead prediction time can exceed 2 weeks in certain cases. We find that the Arctic sea ice concentration (SI...

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Main Authors: Mu, Mu, Dai, Guokun, Ma, Xueying
Format: Conference Object
Language:unknown
Published: GFZ German Research Centre for Geosciences 2023
Subjects:
Online Access:https://dx.doi.org/10.57757/iugg23-0708
https://gfzpublic.gfz-potsdam.de/pubman/item/item_5016779
id ftdatacite:10.57757/iugg23-0708
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spelling ftdatacite:10.57757/iugg23-0708 2023-06-11T04:08:59+02:00 Influence of Arctic Sea ice concentration on extended-range prediction of strong and Long-lasting ural blocking events in Winter ... Mu, Mu Dai, Guokun Ma, Xueying 2023 https://dx.doi.org/10.57757/iugg23-0708 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5016779 unknown GFZ German Research Centre for Geosciences Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 ConferencePaper Oral Article 2023 ftdatacite https://doi.org/10.57757/iugg23-0708 2023-06-01T11:08:45Z <!--!introduction!--> It is traditionally considered that the predictability of atmosphere reaches approximately 2 weeks due to its chaotic features. Considering boundary conditions, the lead prediction time can exceed 2 weeks in certain cases. We find that the Arctic sea ice concentration (SIC) is crucial for extended-range prediction of strong and long-lasting Ural blocking (UB) formation. By applying the rotated empirical orthogonal function-based particle swarm optimization algorithm, the conditional nonlinear optimal perturbation is calculated with the Community Atmosphere Model, version 4, to identify the optimally growing boundary errors in extended-range prediction of strong and long-lasting UB formation. It is found that SIC perturbations in the Greenland Sea (GS), Barents Sea (BS), and Okhotsk Sea (OKS) are important for strong and long-lasting UB formation prediction in four pentads. Further analysis reveals that the SIC perturbations in these areas first influence the local temperature ... : The 28th IUGG General Assembly (IUGG2023) (Berlin 2023) ... Conference Object Arctic Barents Sea Greenland Greenland Sea okhotsk sea Sea ice DataCite Metadata Store (German National Library of Science and Technology) Arctic Barents Sea Greenland Okhotsk
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
description <!--!introduction!--> It is traditionally considered that the predictability of atmosphere reaches approximately 2 weeks due to its chaotic features. Considering boundary conditions, the lead prediction time can exceed 2 weeks in certain cases. We find that the Arctic sea ice concentration (SIC) is crucial for extended-range prediction of strong and long-lasting Ural blocking (UB) formation. By applying the rotated empirical orthogonal function-based particle swarm optimization algorithm, the conditional nonlinear optimal perturbation is calculated with the Community Atmosphere Model, version 4, to identify the optimally growing boundary errors in extended-range prediction of strong and long-lasting UB formation. It is found that SIC perturbations in the Greenland Sea (GS), Barents Sea (BS), and Okhotsk Sea (OKS) are important for strong and long-lasting UB formation prediction in four pentads. Further analysis reveals that the SIC perturbations in these areas first influence the local temperature ... : The 28th IUGG General Assembly (IUGG2023) (Berlin 2023) ...
format Conference Object
author Mu, Mu
Dai, Guokun
Ma, Xueying
spellingShingle Mu, Mu
Dai, Guokun
Ma, Xueying
Influence of Arctic Sea ice concentration on extended-range prediction of strong and Long-lasting ural blocking events in Winter ...
author_facet Mu, Mu
Dai, Guokun
Ma, Xueying
author_sort Mu, Mu
title Influence of Arctic Sea ice concentration on extended-range prediction of strong and Long-lasting ural blocking events in Winter ...
title_short Influence of Arctic Sea ice concentration on extended-range prediction of strong and Long-lasting ural blocking events in Winter ...
title_full Influence of Arctic Sea ice concentration on extended-range prediction of strong and Long-lasting ural blocking events in Winter ...
title_fullStr Influence of Arctic Sea ice concentration on extended-range prediction of strong and Long-lasting ural blocking events in Winter ...
title_full_unstemmed Influence of Arctic Sea ice concentration on extended-range prediction of strong and Long-lasting ural blocking events in Winter ...
title_sort influence of arctic sea ice concentration on extended-range prediction of strong and long-lasting ural blocking events in winter ...
publisher GFZ German Research Centre for Geosciences
publishDate 2023
url https://dx.doi.org/10.57757/iugg23-0708
https://gfzpublic.gfz-potsdam.de/pubman/item/item_5016779
geographic Arctic
Barents Sea
Greenland
Okhotsk
geographic_facet Arctic
Barents Sea
Greenland
Okhotsk
genre Arctic
Barents Sea
Greenland
Greenland Sea
okhotsk sea
Sea ice
genre_facet Arctic
Barents Sea
Greenland
Greenland Sea
okhotsk sea
Sea ice
op_rights Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
op_doi https://doi.org/10.57757/iugg23-0708
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