scholarly journals North Atlantic Oscillation in winter is largely insensitive to autumn Barents-Kara sea ice variability

2021 ◽  
Vol 7 (31) ◽  
pp. eabg4893
Author(s):  
Peter Yu Feng Siew ◽  
Camille Li ◽  
Mingfang Ting ◽  
Stefan P. Sobolowski ◽  
Yutian Wu ◽  
...  
Keyword(s):  
Sea Ice ◽  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Climate Models ◽  
Internal Variability ◽  
Arctic Sea Ice ◽  
Sea Ice Extent ◽  
Large Spread ◽  
Arctic Sea ◽  
The Relationship

Arctic sea ice extent in autumn is significantly correlated with the winter North Atlantic Oscillation (NAO) in the satellite era. However, questions about the robustness and reproducibility of the relationship persist. Here, we show that climate models are able to simulate periods of strong ice-NAO correlation, albeit rarely. Furthermore, we show that the winter circulation signals during these periods are consistent with observations and not driven by sea ice. We do so by interrogating a multimodel ensemble for the specific time scale of interest, thereby illuminating the dynamics that produce large spread in the ice-NAO relationship. Our results support the importance of internal variability over sea ice but go further in showing that the mechanism behind strong ice-NAO correlations, when they occur, is similar in longer observational records and models. Rather than sea ice, circulation anomalies over the Urals emerge as a decisive precursor to the winter NAO signal.

scholarly journals Assessment and Ranking of Climate Models in Arctic Sea Ice Cover Simulation: From CMIP5 to CMIP6

2021 ◽  
Vol 34 (9) ◽  
pp. 3609-3627
Author(s):  
Zili Shen ◽  
Anmin Duan ◽  
Dongliang Li ◽  
Jinxiao Li
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Substantial Reduction ◽  
Coupled Model ◽  
Internal Variability ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea

AbstractThe capability of 36 models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6) and their 24 CMIP5 counterparts in simulating the mean state and variability of Arctic sea ice cover for the period 1979–2014 is evaluated. In addition, a sea ice cover performance score for each CMIP5 and CMIP6 model is provided that can be used to reduce the spread in sea ice projections through applying weighted averages based on the ability of models to reproduce the historical sea ice state. Results show that the seasonal cycle of the Arctic sea ice extent (SIE) in the multimodel ensemble (MME) mean of the CMIP6 simulations agrees well with observations, with a MME mean error of less than 15% in any given month relative to the observations. CMIP6 has a smaller intermodel spread in climatological SIE values during summer months than its CMIP5 counterpart. In terms of the monthly SIE trends, the CMIP6 MME mean shows a substantial reduction in the positive bias relative to the observations compared with that of CMIP5. The spread of September SIE trends is very large, not only across different models but also across different ensemble members of the same model, indicating a strong influence of internal variability on SIE evolution. Based on the assumptions that the simulations of CMIP6 models are from the same distribution and that models have no bias in response to external forcing, we can infer that internal variability contributes to approximately 22% ± 5% of the September SIE trend over the period 1979–2014.

Erratum to: An interannual link between Arctic sea-ice cover and the North Atlantic Oscillation

2017 ◽  
Vol 50 (1-2) ◽  
pp. 443-443 ◽  
Author(s):  
Mihaela Caian ◽  
Torben Koenigk ◽  
Ralf Döscher ◽  
Abhay Devasthale
Keyword(s):  
Sea Ice ◽  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The North ◽  
Arctic Sea ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

scholarly journals Late-Twentieth-Century Simulation of Arctic Sea Ice and Ocean Properties in the CCSM4

2012 ◽  
Vol 25 (5) ◽  
pp. 1431-1452 ◽  
Author(s):  
Alexandra Jahn ◽  
Kara Sterling ◽  
Marika M. Holland ◽  
Jennifer E. Kay ◽  
James A. Maslanik ◽  
...  
Keyword(s):  
Twentieth Century ◽  
Sea Ice ◽  
Internal Variability ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Motion Field ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Ensemble Mean

To establish how well the new Community Climate System Model, version 4 (CCSM4) simulates the properties of the Arctic sea ice and ocean, results from six CCSM4 twentieth-century ensemble simulations are compared here with the available data. It is found that the CCSM4 simulations capture most of the important climatological features of the Arctic sea ice and ocean state well, among them the sea ice thickness distribution, fraction of multiyear sea ice, and sea ice edge. The strongest bias exists in the simulated spring-to-fall sea ice motion field, the location of the Beaufort Gyre, and the temperature of the deep Arctic Ocean (below 250 m), which are caused by deficiencies in the simulation of the Arctic sea level pressure field and the lack of deep-water formation on the Arctic shelves. The observed decrease in the sea ice extent and the multiyear ice cover is well captured by the CCSM4. It is important to note, however, that the temporal evolution of the simulated Arctic sea ice cover over the satellite era is strongly influenced by internal variability. For example, while one ensemble member shows an even larger decrease in the sea ice extent over 1981–2005 than that observed, two ensemble members show no statistically significant trend over the same period. It is therefore important to compare the observed sea ice extent trend not just with the ensemble mean or a multimodel ensemble mean, but also with individual ensemble members, because of the strong imprint of internal variability on these relatively short trends.

scholarly journals Modeled Arctic sea ice evolution through 2300 in CMIP5 extended RCPs

2014 ◽  
Vol 8 (1) ◽  
pp. 1383-1406 ◽  
Author(s):  
P. J. Hezel ◽  
T. Fichefet ◽  
F. Massonnet
Keyword(s):  
Sea Ice ◽  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Arctic Sea Ice Extent

Abstract. Almost all global climate models and Earth system models that participated in the Coupled Model Intercomparison Project 5 (CMIP5) show strong declines in Arctic sea ice extent and volume under the highest forcing scenario of the Radiative Concentration Pathways (RCPs) through 2100, including a transition from perennial to seasonal ice cover. Extended RCP simulations through 2300 were completed for a~subset of models, and here we examine the time evolution of Arctic sea ice in these simulations. In RCP2.6, the summer Arctic sea ice extent increases compared to its minimum following the peak radiative forcing in 2044 in all 9 models. RCP4.5 demonstrates continued summer Arctic sea ice decline due to continued warming on longer time scales. These two scenarios imply that summer sea ice extent could begin to recover if and when radiative forcing from greenhouse gas concentrations were to decrease. In RCP8.5 the Arctic Ocean reaches annually ice-free conditions in 7 of 9 models. The ensemble of simulations completed under the extended RCPs provide insight into the global temperature increase at which sea ice disappears in the Arctic and reversibility of declines in seasonal sea ice extent.

scholarly journals A 120 000-year record of sea ice in the North Atlantic?

2019 ◽  
Vol 15 (6) ◽  
pp. 2031-2051 ◽  
Author(s):  
Niccolò Maffezzoli ◽  
Paul Vallelonga ◽  
Ross Edwards ◽  
Alfonso Saiz-Lopez ◽  
Clara Turetta ◽  
...  
Keyword(s):  
Sea Ice ◽  
North Atlantic ◽  
Ice Core ◽  
Arctic Sea Ice ◽  
First Year ◽  
Sea Ice Extent ◽  
Nordic Seas ◽  
The North ◽  
Arctic Sea ◽  
The North Atlantic

Abstract. Although it has been demonstrated that the speed and magnitude of the recent Arctic sea ice decline is unprecedented for the past 1450 years, few records are available to provide a paleoclimate context for Arctic sea ice extent. Bromine enrichment in ice cores has been suggested to indicate the extent of newly formed sea ice areas. Despite the similarities among sea ice indicators and ice core bromine enrichment records, uncertainties still exist regarding the quantitative linkages between bromine reactive chemistry and the first-year sea ice surfaces. Here we present a 120 000-year record of bromine enrichment from the RECAP (REnland ice CAP) ice core, coastal east Greenland, and interpret it as a record of first-year sea ice. We compare it to existing sea ice records from marine cores and tentatively reconstruct past sea ice conditions in the North Atlantic as far north as the Fram Strait (50–85∘ N). Our interpretation implies that during the last deglaciation, the transition from multi-year to first-year sea ice started at ∼17.5 ka, synchronously with sea ice reductions observed in the eastern Nordic Seas and with the increase in North Atlantic ocean temperature. First-year sea ice reached its maximum at 12.4–11.8 ka during the Younger Dryas, after which open-water conditions started to dominate, consistent with sea ice records from the eastern Nordic Seas and the North Icelandic shelf. Our results show that over the last 120 000 years, multi-year sea ice extent was greatest during Marine Isotope Stage (MIS) 2 and possibly during MIS 4, with more extended first-year sea ice during MIS 3 and MIS 5. Sea ice extent during the Holocene (MIS 1) has been less than at any time in the last 120 000 years.

scholarly journals Statistical indicators of Arctic sea-ice stability – prospects and limitations

2016 ◽  
Vol 10 (4) ◽  
pp. 1631-1645 ◽  
Author(s):  
Sebastian Bathiany ◽  
Bregje van der Bolt ◽  
Mark S. Williamson ◽  
Timothy M. Lenton ◽  
Marten Scheffer ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Arctic Sea Ice ◽  
Ice Coverage ◽  
Arctic Sea ◽  
Complex Models ◽  
Large Heat ◽  
Annual Time Series ◽  
Arctic Sea Ice Loss ◽  
The Relationship

Abstract. We examine the relationship between the mean and the variability of Arctic sea-ice coverage and volume in a large range of climates from globally ice-covered to globally ice-free conditions. Using a hierarchy of two column models and several comprehensive Earth system models, we consolidate the results of earlier studies and show that mechanisms found in simple models also dominate the interannual variability of Arctic sea ice in complex models. In contrast to predictions based on very idealised dynamical systems, we find a consistent and robust decrease of variance and autocorrelation of sea-ice volume before summer sea ice is lost. We attribute this to the fact that thinner ice can adjust more quickly to perturbations. Thereafter, the autocorrelation increases, mainly because it becomes dominated by the ocean water's large heat capacity when the ice-free season becomes longer. We show that these changes are robust to the nature and origin of climate variability in the models and do not depend on whether Arctic sea-ice loss occurs abruptly or irreversibly. We also show that our climate is changing too rapidly to detect reliable changes in autocorrelation of annual time series. Based on these results, the prospects of detecting statistical early warning signals before an abrupt sea-ice loss at a "tipping point" seem very limited. However, the robust relation between state and variability can be useful to build simple stochastic climate models and to make inferences about past and future sea-ice variability from only short observations or reconstructions.

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