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  4. Impacts of Arctic Sea ice on cold season atmospheric variability and trends estimated from observations and a multimodel large ensemble
 
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Impacts of Arctic Sea ice on cold season atmospheric variability and trends estimated from observations and a multimodel large ensemble

Journal
Journal of Climate
Journal Volume
34
Journal Issue
20
Pages
8419-8443
Date Issued
2021
Author(s)
YU-CHIAO LIANG et al.  
DOI
10.1175/JCLI-D-20-0578.1
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116901064&doi=10.1175%2fJCLI-D-20-0578.1&partnerID=40&md5=10c710ac6078a0edbc10dd7dec7477ab
https://scholars.lib.ntu.edu.tw/handle/123456789/606340
Abstract
To examine the atmospheric responses to Arctic sea ice variability in the Northern Hemisphere cold season (from October to the following March), this study uses a coordinated set of large-ensemble experiments of nine atmospheric general circulation models (AGCMs) forced with observed daily varying sea ice, sea surface temperature, and radiative forcings prescribed during the 1979–2014 period, together with a parallel set of experiments where Arctic sea ice is substituted by its climatology. The simulations of the former set reproduce the near-surface temperature trends in reanalysis data, with similar amplitude, and their multimodel ensemble mean (MMEM) shows decreasing sea level pressure over much of the polar cap and Eurasia in boreal autumn. The MMEM difference between the two experiments allows isolating the effects of Arctic sea ice loss, which explain a large portion of the Arctic warming trends in the lower troposphere and drive a small but statistically significant weakening of the wintertime Arctic Oscillation. The observed interannual covariability between sea ice extent in the Barents–Kara Seas and lagged atmospheric circulation is distinguished from the effects of confounding factors based on multiple regression, and quantitatively compared to the covariability in MMEMs. The interannual sea ice decline followed by a negative North Atlantic Oscillation–like anomaly found in observations is also seen in the MMEM differences, with consistent spatial structure but much smaller amplitude. This result suggests that the sea ice impacts on trends and interannual atmospheric variability simulated by AGCMs could be underestimated, but caution is needed because internal atmospheric variability may have affected the observed relationship. ? 2021 American Meteorological Society.
Subjects
Arctic
Atmospheric circulation
Climate models
Sea ice
Atmospheric pressure
Atmospheric radiation
Atmospheric temperature
Climatology
Digital storage
Sea level
Submarine geophysics
Surface properties
Surface waters
Arctic sea ice
Atmospheric general circulation models
Atmospheric general-circulation model
Atmospheric trends
Atmospheric variability
Cold season
Interannual
Multi-model ensemble
air-sea interaction
annual variation
Arctic Oscillation
atmospheric circulation
atmospheric dynamics
atmospheric general circulation model
climate modeling
ensemble forecasting
estimation method
Northern Hemisphere
sea ice
trend analysis
troposphere
warming
SDGs

[SDGs]SDG13

[SDGs]SDG14

Type
journal article

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