scholarly journals Regional Arctic sea ice variations as predictor for winter climate conditions

2015 ◽  
Vol 46 (1-2) ◽  
pp. 317-337 ◽  
Author(s):  
Torben Koenigk ◽  
Mihaela Caian ◽  
Grigory Nikulin ◽  
Semjon Schimanke
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
Winter Climate ◽  
Climate Conditions ◽  
Arctic Sea

scholarly journals Evaluating Impacts of Recent Arctic Sea Ice Loss on the Northern Hemisphere Winter Climate Change

2018 ◽  
Vol 45 (7) ◽  
pp. 3255-3263 ◽  
Author(s):  
Fumiaki Ogawa ◽  
Noel Keenlyside ◽  
Yongqi Gao ◽  
Torben Koenigk ◽  
Shuting Yang ◽  
...  
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Northern Hemisphere ◽  
Arctic Sea Ice ◽  
Winter Climate ◽  
Winter Climate Change ◽  
Arctic Sea ◽  
Hemisphere Winter ◽  
Arctic Sea Ice Loss ◽  
Northern Hemisphere Winter

Observed statistical connections overestimate the causal effects of Arctic sea-ice changes on midlatitude winter climate

2021 ◽  
pp. 1-46
Author(s):  
Russell Blackport ◽  
James A. Screen
Keyword(s):  
Climate Variability ◽  
Sea Ice ◽  
Surface Temperature ◽  
Kara Sea ◽  
Arctic Sea Ice ◽  
Causal Effects ◽  
Coupled Models ◽  
Stratospheric Polar Vortex ◽  
Winter Climate ◽  
Arctic Sea

AbstractDisentangling the contribution of changing Arctic sea ice to midlatitude winter climate variability remains challenging because of the large internal climate variability in midlatitudes, difficulties separating cause from effect, methodological differences, and uncertainty around whether models adequately simulate connections between Arctic sea ice and midlatitude climate. We use regression analysis to quantify the links between Arctic sea ice and midlatitude winter climate in observations and large initial-condition ensembles of multiple climate models, in both coupled configurations and so-called atmospheric model intercomparison project (AMIP) configurations, where observed sea ice and/or sea surface temperatures are prescribed. The coupled models capture the observed links in interannual variability between winter Barents-Kara sea ice and Eurasian surface temperature, and between winter Chukchi-Bering sea ice and North American surface temperature. The coupled models also capture the delayed connection between reduced November-December Barents-Kara sea ice, a weakened winter stratospheric polar vortex, and a shift towards the negative phase of the North Atlantic Oscillation in late winter, although this downward impact is weaker than observed. The strength and sign of the connections both vary considerably between individual 35-year-long ensemble members, highlighting the need for large ensembles to separate robust connections from internal variability. All the aforementioned links are either absent, or substantially weaker, in the AMIP experiments prescribed with only observed sea ice variability. We conclude that the causal effects of sea ice variability on midlatitude winter climate are much weaker than suggested by statistical associations, evident in observations and coupled models, because the statistics are inflated by the effects of atmospheric circulation variability on sea ice.

scholarly journals Improvement in simulation of Eurasian winter climate variability with a realistic Arctic sea ice condition in an atmospheric GCM

2012 ◽  
Vol 7 (4) ◽  
pp. 044041 ◽  
Author(s):  
Young-Kwon Lim ◽  
Yoo-Geun Ham ◽  
Jee-Hoon Jeong ◽  
Jong-Seong Kug
Keyword(s):  
Climate Variability ◽  
Sea Ice ◽  
Arctic Sea Ice ◽  
Winter Climate ◽  
Arctic Sea

Patterns of Asian Winter Climate Variability and Links to Arctic Sea Ice

2015 ◽  
Vol 28 (17) ◽  
pp. 6841-6858 ◽  
Author(s):  
Bingyi Wu ◽  
Jingzhi Su ◽  
Rosanne D’Arrigo
Keyword(s):  
Sea Ice ◽  
East Asia ◽  
Barents Sea ◽  
Winter Precipitation ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Atmospheric Variability ◽  
Winter Climate ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss

Abstract This paper describes two dominant patterns of Asian winter climate variability: the Siberian high (SH) pattern and the Asia–Arctic (AA) pattern. The former depicts atmospheric variability closely associated with the intensity of the Siberian high, and the latter characterizes the teleconnection pattern of atmospheric variability between Asia and the Arctic, which is distinct from the Arctic Oscillation (AO). The AA pattern plays more important roles in regulating winter precipitation and the 850-hPa meridional wind component over East Asia than the SH pattern, which controls surface air temperature variability over East Asia. In the Arctic Ocean and its marginal seas, sea ice loss in both autumn and winter could bring the positive phase of the SH pattern or cause the negative phase of the AA pattern. The latter corresponds to a weakened East Asian winter monsoon (EAWM) and enhanced winter precipitation in the midlatitudes of the Asian continent and East Asia. For the SH pattern, sea ice loss in the prior autumn emerges in the Siberian marginal seas, and winter loss mainly occurs in the Barents Sea, Labrador Sea, and Davis Strait. For the AA pattern, sea ice loss in the prior autumn is observed in the Barents–Kara Seas, the western Laptev Sea, and the Beaufort Sea, and winter loss only occurs in some areas of the Barents Sea, the Labrador Sea, and Davis Strait. Simulation experiments with observed sea ice forcing also support that Arctic sea ice loss may favor frequent occurrence of the negative phase of the AA pattern. The results also imply that the relationship between Arctic sea ice loss and winter atmospheric variability over East Asia is unstable, which is a challenge for predicting the EAWM based on Arctic sea ice loss.

scholarly journals Linear Additive Impacts of Arctic Sea Ice Reduction and La Niña on the Northern Hemisphere Winter Climate

2016 ◽  
Vol 29 (15) ◽  
pp. 5513-5532 ◽  
Author(s):  
Zhe Han ◽  
Shuanglin Li ◽  
Jiping Liu ◽  
Yongqi Gao ◽  
Ping Zhao
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
General Circulation ◽  
Arctic Sea Ice ◽  
La Niña ◽  
Winter Climate ◽  
La Nina ◽  
Arctic Sea ◽  
Hemisphere Winter ◽  
Northern Hemisphere Winter

Abstract Both Arctic sea ice loss and La Niña events can result in cold conditions in midlatitude Eurasia in winter. Since the two forcings sometimes occur simultaneously, determining whether they are independent of each other is undertaken first. The result suggests an overall independence. Considering possible interactions between them, their coordinated impacts on the Northern Hemisphere winter climate are then investigated based on observational data analyses, historical simulation analyses from one coupled model (MPI-ESM-LR) contributing to CMIP5, and atmospheric general circulation model sensitive experiments in ECHAM5. The results show that the impacts of the two forcings are overall linearly accumulated. In comparison with one single forcing, there is intensified cooling response in midlatitude Eurasia along with northern warmer–southern cooler dipolar temperature responses over North America. Despite the additive linearity, additive nonlinearity between the two forcings is identifiable. The nonlinearity causes midlatitude Eurasian cooling weakened by one-tenth to one-fifth as much as their individual impacts in combination. The underlying mechanisms for the weak additive nonlinearity are finally explored by transient adjustment AGCM runs with one single forcing or both the forcings switched on suddenly. The day-to-day evolution of responses suggests that the additive nonlinearity may arise initially from the forced wave dynamics and then be amplified because of the involvement of transient eddy feedbacks.

Prévoir les variations saisonnières de la glace de mer arctique et leurs impacts sur le climat

2020 ◽  
pp. 024
Author(s):  
Rym Msadek ◽  
Gilles Garric ◽  
Sara Fleury ◽  
Florent Garnier ◽  
Lauriane Batté ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
Climate Impacts ◽  
The Arctic ◽  
Recent Effort ◽  
Sea Ice Thickness ◽  
Arctic Sea ◽  
Ice Conditions ◽  
Upper Level

L'Arctique est la région du globe qui s'est réchauffée le plus vite au cours des trente dernières années, avec une augmentation de la température de surface environ deux fois plus rapide que pour la moyenne globale. Le déclin de la banquise arctique observé depuis le début de l'ère satellitaire et attribué principalement à l'augmentation de la concentration des gaz à effet de serre aurait joué un rôle important dans cette amplification des températures au pôle. Cette fonte importante des glaces arctiques, qui devrait s'accélérer dans les décennies à venir, pourrait modifier les vents en haute altitude et potentiellement avoir un impact sur le climat des moyennes latitudes. L'étendue de la banquise arctique varie considérablement d'une saison à l'autre, d'une année à l'autre, d'une décennie à l'autre. Améliorer notre capacité à prévoir ces variations nécessite de comprendre, observer et modéliser les interactions entre la banquise et les autres composantes du système Terre, telles que l'océan, l'atmosphère ou la biosphère, à différentes échelles de temps. La réalisation de prévisions saisonnières de la banquise arctique est très récente comparée aux prévisions du temps ou aux prévisions saisonnières de paramètres météorologiques (température, précipitation). Les résultats ayant émergé au cours des dix dernières années mettent en évidence l'importance des observations de l'épaisseur de la glace de mer pour prévoir l'évolution de la banquise estivale plusieurs mois à l'avance. Surface temperatures over the Arctic region have been increasing twice as fast as global mean temperatures, a phenomenon known as arctic amplification. One main contributor to this polar warming is the large decline of Arctic sea ice observed since the beginning of satellite observations, which has been attributed to the increase of greenhouse gases. The acceleration of Arctic sea ice loss that is projected for the coming decades could modify the upper level atmospheric circulation yielding climate impacts up to the mid-latitudes. There is considerable variability in the spatial extent of ice cover on seasonal, interannual and decadal time scales. Better understanding, observing and modelling the interactions between sea ice and the other components of the climate system is key for improved predictions of Arctic sea ice in the future. Running operational-like seasonal predictions of Arctic sea ice is a quite recent effort compared to weather predictions or seasonal predictions of atmospheric fields like temperature or precipitation. Recent results stress the importance of sea ice thickness observations to improve seasonal predictions of Arctic sea ice conditions during summer.

Eastern-Western Arctic Sea Ice Analysis: 1988

1988 ◽  
Author(s):  
NAVAL POLAR OCEANOGRAPHY CENTER WASHINGTON DC
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
Arctic Sea ◽  
Western Arctic
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