September-October Arctic Pacific Sectior Sea-ice Dipole Index Time Series, 1980-2016

These are the September-October Arctic Pacific Sector Sea-ice Dipole Index and April-May Barents Sea average Sea-ice Index used in Liang et al. (2021). This study used observational and reanalysis datasets in 1980–2016 to show a close connection between a boreal autumn sea ice dipole in the Arctic P...

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Main Authors: Kwon, Young-Oh, Liang, Yu-Chiao
Format: Dataset
Language:English
Published: NSF Arctic Data Center 2022
Subjects:
Online Access:https://dx.doi.org/10.18739/a2w669948
https://arcticdata.io/catalog/view/doi:10.18739/A2W669948
id ftdatacite:10.18739/a2w669948
record_format openpolar
spelling ftdatacite:10.18739/a2w669948 2023-05-15T14:35:08+02:00 September-October Arctic Pacific Sectior Sea-ice Dipole Index Time Series, 1980-2016 Kwon, Young-Oh Liang, Yu-Chiao 2022 text/xml https://dx.doi.org/10.18739/a2w669948 https://arcticdata.io/catalog/view/doi:10.18739/A2W669948 en eng NSF Arctic Data Center Arctic Sea-Ice Seasonal Predictability Dataset dataset 2022 ftdatacite https://doi.org/10.18739/a2w669948 2022-04-01T18:11:03Z These are the September-October Arctic Pacific Sector Sea-ice Dipole Index and April-May Barents Sea average Sea-ice Index used in Liang et al. (2021). This study used observational and reanalysis datasets in 1980–2016 to show a close connection between a boreal autumn sea ice dipole in the Arctic Pacific sector and sea ice anomalies in the Barents Sea during the following spring. The autumn sea ice dipole index is calculated based on the difference between the sea-ice concentration anomalies averaged over as the Beaufort-Chukchi Seas and the East Siberian-Laptev Seas. The Barents Sea sea ice index is the sea-ice concentration averaged over the Barents Sea region. The September–October Arctic Pacific sea ice dipole variations are highly correlated with the subsequent April–May Barents Sea sea ice variations (r=0.71). The strong connection between the regional sea ice variabilities across the Arctic uncovers a new source of predictability for spring Barents Sea sea ice prediction at 7-month lead time. Please find the detail definition of the indices from Liang et al. (2021). Liang, Y.-C., Y.-O. Kwon, and C. Frankignoul, 2021: Autumn Arctic Pacific Sea-ice Dipole as a Source of Predictability for Subsequent Spring Barents-Kara Sea-ice Condition. J. Climate., 34, 787-804. https://doi.org/10.1175/JCLI-D-20-0172.1. Dataset Arctic Barents Sea Chukchi Kara Sea laptev Sea ice DataCite Metadata Store (German National Library of Science and Technology) Arctic Barents Sea Kara Sea Pacific
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic Arctic Sea-Ice
Seasonal Predictability
spellingShingle Arctic Sea-Ice
Seasonal Predictability
Kwon, Young-Oh
Liang, Yu-Chiao
September-October Arctic Pacific Sectior Sea-ice Dipole Index Time Series, 1980-2016
topic_facet Arctic Sea-Ice
Seasonal Predictability
description These are the September-October Arctic Pacific Sector Sea-ice Dipole Index and April-May Barents Sea average Sea-ice Index used in Liang et al. (2021). This study used observational and reanalysis datasets in 1980–2016 to show a close connection between a boreal autumn sea ice dipole in the Arctic Pacific sector and sea ice anomalies in the Barents Sea during the following spring. The autumn sea ice dipole index is calculated based on the difference between the sea-ice concentration anomalies averaged over as the Beaufort-Chukchi Seas and the East Siberian-Laptev Seas. The Barents Sea sea ice index is the sea-ice concentration averaged over the Barents Sea region. The September–October Arctic Pacific sea ice dipole variations are highly correlated with the subsequent April–May Barents Sea sea ice variations (r=0.71). The strong connection between the regional sea ice variabilities across the Arctic uncovers a new source of predictability for spring Barents Sea sea ice prediction at 7-month lead time. Please find the detail definition of the indices from Liang et al. (2021). Liang, Y.-C., Y.-O. Kwon, and C. Frankignoul, 2021: Autumn Arctic Pacific Sea-ice Dipole as a Source of Predictability for Subsequent Spring Barents-Kara Sea-ice Condition. J. Climate., 34, 787-804. https://doi.org/10.1175/JCLI-D-20-0172.1.
format Dataset
author Kwon, Young-Oh
Liang, Yu-Chiao
author_facet Kwon, Young-Oh
Liang, Yu-Chiao
author_sort Kwon, Young-Oh
title September-October Arctic Pacific Sectior Sea-ice Dipole Index Time Series, 1980-2016
title_short September-October Arctic Pacific Sectior Sea-ice Dipole Index Time Series, 1980-2016
title_full September-October Arctic Pacific Sectior Sea-ice Dipole Index Time Series, 1980-2016
title_fullStr September-October Arctic Pacific Sectior Sea-ice Dipole Index Time Series, 1980-2016
title_full_unstemmed September-October Arctic Pacific Sectior Sea-ice Dipole Index Time Series, 1980-2016
title_sort september-october arctic pacific sectior sea-ice dipole index time series, 1980-2016
publisher NSF Arctic Data Center
publishDate 2022
url https://dx.doi.org/10.18739/a2w669948
https://arcticdata.io/catalog/view/doi:10.18739/A2W669948
geographic Arctic
Barents Sea
Kara Sea
Pacific
geographic_facet Arctic
Barents Sea
Kara Sea
Pacific
genre Arctic
Barents Sea
Chukchi
Kara Sea
laptev
Sea ice
genre_facet Arctic
Barents Sea
Chukchi
Kara Sea
laptev
Sea ice
op_doi https://doi.org/10.18739/a2w669948
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