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...
| Main Authors: | , |
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| Format: | Dataset |
| Language: | English |
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NSF Arctic Data Center
2022
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| Online Access: | https://dx.doi.org/10.18739/a2vd6p609 https://arcticdata.io/catalog/view/doi:10.18739/A2VD6P609 |
| Summary: | 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. |
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