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  • 2020-2024
  • 2020-2023  (2)
  • 2020-2022  (4)
  • 2000-2004
  • 2020  (6)
  • 2020  (6)
  • 2020  (6)
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  • 2020-2024
  • 2020-2023  (2)
  • 2020-2022  (4)
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  • 1
    Publication Date: 2020-10-22
    Description: This study uses 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 (BS) during the following spring. The September-October Arctic Pacific sea-ice dipole variations are highly correlated with the subsequent April-May BS 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 BS sea-ice prediction at 7-month lead time. A cross-validated linear regression prediction model using the Arctic Pacific sea-ice dipole with 7-month lead time is demonstrated to have significant prediction skills with 0.54-0.85 anomaly correlation coefficients. The autumn sea-ice dipole, manifested as sea-ice retreat in the Beaufort-Chukchi Seas and expansion in the East Siberian-Laptev Seas, is primarily forced by preceding atmospheric shortwave anomalies from late spring to early autumn. The spring BS sea-ice increases are mostly driven by an ocean-to-sea ice heat flux reduction in preceding months, associated with reduced horizontal ocean heat transport into the BS. The dynamical linkage between the two regional sea-ice anomalies is suggested to involve positive stratospheric polar cap anomalies during autumn and winter, with its center slowly moving toward Greenland. The migration of the stratospheric anomalies is followed in mid-winter by a negative North Atlantic Oscillation-like pattern in the troposphere, leading to reduced ocean heat transport into the BS and sea-ice extent increase.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 2
  • 3
    Publication Date: 2020-04-06
    Description: The direct response of the cold-season atmospheric circulation to the Arctic sea ice loss is estimated from observed sea ice concentration (SIC) and an atmospheric reanalysis, assuming that the atmospheric response to the long-term sea ice loss is the same as that to interannual pan-Arctic SIC fluctuations with identical spatial patterns. No large-scale relationship with previous interannual SIC fluctuations is found in October and November, but a negative North Atlantic Oscillation (NAO)/Arctic Oscillation follows the pan-Arctic SIC fluctuations from December to March. The signal is field significant in the stratosphere in December, and in the troposphere and tropopause thereafter. However, multiple regressions indicate that the stratospheric December signal is largely due to concomitant Siberian snow-cover anomalies. On the other hand, the tropospheric January–March NAO signals can be unambiguously attributed to SIC variability, with an Iceland high approaching 45 m at 500 hPa, a 2°C surface air warming in northeastern Canada, and a modulation of blocking activity in the North Atlantic sector. In March, a 1°C northern Europe cooling is also attributed to SIC. An SIC impact on the warm Arctic–cold Eurasia pattern is only found in February in relation to January SIC. Extrapolating the most robust results suggests that, in the absence of other forcings, the SIC loss between 1979 and 2016 would have induced a 2°–3°C decade−1 winter warming in northeastern North America and a 40–60 m decade−1 increase in the height of the Iceland high, if linearity and perpetual winter conditions could be assumed.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 4
    Publication Date: 2020-01-20
    Description: ©2019. The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
    Description: A coordinated set of large ensemble atmosphere‐only simulations is used to investigatethe impacts of observed Arctic sea ice‐driven variability (SIDV) on the atmospheric circulation during1979–2014. The experimental protocol permits separating Arctic SIDV from internal variability andvariability driven by other forcings including sea surface temperature and greenhouse gases. The geographicpattern of SIDV is consistent across seven participating models, but its magnitude strongly depends onensemble size. Based on 130 members, winter SIDV is ~0.18 hPa2for Arctic‐averaged sea level pressure(~1.5% of the total variance), and ~0.35 K2for surface air temperature (~21%) at interannual and longertimescales. The results suggest that more than 100 (40) members are needed to separate Arctic SIDV fromother components for dynamical (thermodynamical) variables, and insufficient ensemble size always leadsto overestimation of SIDV. Nevertheless, SIDV is 0.75–1.5 times as large as the variability driven by otherforcings over northern Eurasia and Arctic.
    Description: Published
    Description: e2019GL085397
    Description: 5A. Ricerche polari e paleoclima
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 5
    Publication Date: 2022-05-26
    Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Liang, Y., Kwon, Y., Frankignoul, C., Danabasoglu, G., Yeager, S., Cherchi, A., Gao, Y., Gastineau, G., Ghosh, R., Matei, D., Mecking, J., V., Peano, D., Suo, L., & Tian, T. Quantification of the arctic sea ice-driven atmospheric circulation variability in coordinated large ensemble simulations. Geophysical Research Letters, 47(1), (2020): e2019GL085397, doi:10.1029/2019GL085397.
    Description: A coordinated set of large ensemble atmosphere‐only simulations is used to investigate the impacts of observed Arctic sea ice‐driven variability (SIDV) on the atmospheric circulation during 1979–2014. The experimental protocol permits separating Arctic SIDV from internal variability and variability driven by other forcings including sea surface temperature and greenhouse gases. The geographic pattern of SIDV is consistent across seven participating models, but its magnitude strongly depends on ensemble size. Based on 130 members, winter SIDV is ~0.18 hPa2 for Arctic‐averaged sea level pressure (~1.5% of the total variance), and ~0.35 K2 for surface air temperature (~21%) at interannual and longer timescales. The results suggest that more than 100 (40) members are needed to separate Arctic SIDV from other components for dynamical (thermodynamical) variables, and insufficient ensemble size always leads to overestimation of SIDV. Nevertheless, SIDV is 0.75–1.5 times as large as the variability driven by other forcings over northern Eurasia and Arctic.
    Description: The authors thank Editor Christina Patricola and two anonymous reviewers for their comprehensive and insightful comments, which have led to improved presentation of this manuscript. We acknowledge support by the Blue‐Action Project (European Union's Horizon 2020 research and innovation program, 727852, http://www.blue‐action.eu/index.php?id = 3498). The WHOI‐NCAR group is also supported by the US National Science Foundation (NSF) Office of Polar Programs Grants 1736738 and 1737377, and their computing and data storage resources, including the Cheyenne supercomputer (doi:10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory at NCAR. NCAR is a major facility sponsored by the U.S. NSF under Cooperative Agreement 1852977. The LOCEAN‐IPSL group was granted access to the HPC resources of TGCC under the Allocation A5‐017403 made by GENCI. The SST and SIC data were downloaded from the U.K. Met Office Hadley Centre Observations Datasets (http://www.metoffice.gov.uk/hadobs/hadisst).
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 6
    Publication Date: 2022-05-26
    Description: Author Posting. © American Meteorological Society, 2020. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 33(9), (2020): 3863-3882, doi:10.1175/JCLI-D-19-0687.1.
    Description: The direct response of the cold-season atmospheric circulation to the Arctic sea ice loss is estimated from observed sea ice concentration (SIC) and an atmospheric reanalysis, assuming that the atmospheric response to the long-term sea ice loss is the same as that to interannual pan-Arctic SIC fluctuations with identical spatial patterns. No large-scale relationship with previous interannual SIC fluctuations is found in October and November, but a negative North Atlantic Oscillation (NAO)/Arctic Oscillation follows the pan-Arctic SIC fluctuations from December to March. The signal is field significant in the stratosphere in December, and in the troposphere and tropopause thereafter. However, multiple regressions indicate that the stratospheric December signal is largely due to concomitant Siberian snow-cover anomalies. On the other hand, the tropospheric January–March NAO signals can be unambiguously attributed to SIC variability, with an Iceland high approaching 45 m at 500 hPa, a 2°C surface air warming in northeastern Canada, and a modulation of blocking activity in the North Atlantic sector. In March, a 1°C northern Europe cooling is also attributed to SIC. An SIC impact on the warm Arctic–cold Eurasia pattern is only found in February in relation to January SIC. Extrapolating the most robust results suggests that, in the absence of other forcings, the SIC loss between 1979 and 2016 would have induced a 2°–3°C decade−1 winter warming in northeastern North America and a 40–60 m decade−1 increase in the height of the Iceland high, if linearity and perpetual winter conditions could be assumed.
    Description: This research was supported by the Blue-Action project (European Union’s Horizon 2020 research and innovation program, Grant 727852) and by the National Science Foundation (OPP 1736738).
    Description: 2020-10-06
    Keywords: Atmosphere-ocean interaction ; Climate change ; Climate variability ; Ice loss/growth
    Repository Name: Woods Hole Open Access Server
    Type: Article
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