scholarly journals On the Predictability of the Winter Euro-Atlantic Climate: Lagged Influence of Autumn Arctic Sea Ice

2015 ◽  
Vol 28 (13) ◽  
pp. 5195-5216 ◽  
Author(s):  
J. García-Serrano ◽  
C. Frankignoul ◽  
G. Gastineau ◽  
A. de la Cámara
Keyword(s):  
Sea Ice ◽  
North Atlantic ◽  
Wave Train ◽  
Surface Air Temperature ◽  
Arctic Sea Ice ◽  
Prediction Skill ◽  
Sea Ice Concentration ◽  
Atlantic Sector ◽  
Empirical Prediction ◽  
The North

Abstract Satellite-derived sea ice concentration (SIC) and reanalyzed atmospheric data are used to explore the predictability of the winter Euro-Atlantic climate resulting from autumn SIC variability over the Barents–Kara Seas region (SIC/BK). The period of study is 1979/80–2012/13. Maximum covariance analyses show that the leading predictand is indistinguishable from the North Atlantic Oscillation (NAO). The leading covariability mode between September SIC/BK and winter North Atlantic–European sea level pressure (SLP) is not significant, indicating that no empirical prediction skill can be achieved. The leading covariability mode with either October or November SIC/BK is moderately significant (significance levels <10%), and both predictor fields yield a cross-validated NAO correlation of 0.3, suggesting some empirical prediction skill of the winter NAO index, with sea ice reduction in the Barents–Kara Seas being accompanied by a negative NAO phase in winter. However, only November SIC/BK provides significant cross-validated skill of winter SLP, surface air temperature, and precipitation anomalies over the Euro-Atlantic sector, namely in southwestern Europe. Statistical analysis suggests that November SIC/BK anomalies are associated with a Rossby wave train–like anomaly across Eurasia that affects vertical wave activity modulating the stratospheric vortex strength, which is then followed by downward propagation of anomalies that impact transient-eddy activity in the upper troposphere, helping to settle and maintain the NAO-like pattern at surface. This stratospheric pathway is not detected when using October SIC/BK anomalies. Hence, only November SIC/BK, with a one-month lead time, could be considered as a potential source of regional predictability.

Gridded Arctic sea ice concentration reconstruction for the first half of the 20th century based on different proxy data

2021 ◽  
Author(s):  
Vladimir Semenov ◽  
Tatiana Matveeva
Keyword(s):  
Sea Ice ◽  
20Th Century ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
The North ◽  
Arctic Sea ◽  
Ice Concentration

<p>Global warming in the recent decades has been accompanied by a rapid recline of the Arctic sea ice area most pronounced in summer (10% per decade). To understand the relative contribution of external forcing and natural variability to the modern and future sea ice area changes, it is necessary to evaluate a range of long-term variations of the Arctic sea ice area in the period before a significant increase in anthropogenic emissions of greenhouse gases into the atmosphere. Available observational data on the spatiotemporal dynamics of Arctic sea ice until 1950s are characterized by significant gaps and uncertainties. In the recent years, there have appeared several reconstructions of the early 20<sup>th</sup> century Arctic sea ice area that filled the gaps by analogue methods or utilized combined empirical data and climate model’s output. All of them resulted in a stronger that earlier believed negative sea ice area anomaly in the 1940s concurrent with the early 20<sup>th</sup> century warming (ETCW) peak. In this study, we reconstruct the monthly average gridded sea ice concentration (SIC) in the first half of the 20th century using the relationship between the spatiotemporal features of SIC variability, surface air temperature over the Northern Hemisphere extratropical continents, sea surface temperature in the North Atlantic and North Pacific, and sea level pressure. In agreement with a few previous results, our reconstructed data also show a significant negative anomaly of the Arctic sea ice area in the middle of the 20th century, however with some 15% to 30% stronger amplitude, about 1.5 million km<sup>2</sup> in September and 0.7 million km<sup>2</sup> in March. The reconstruction demonstrates a good agreement with regional Arctic sea ice area data when available and suggests that ETWC in the Arctic has been accompanied by a concurrent sea ice area decline of a magnitude that have been exceeded only in the beginning of the 21<sup>st</sup> century.</p>

scholarly journals Ural Blocking as an Amplifier of the Arctic Sea Ice Decline in Winter

2017 ◽  
Vol 30 (7) ◽  
pp. 2639-2654 ◽  
Author(s):  
Tingting Gong ◽  
Dehai Luo
Keyword(s):  
Sea Ice ◽  
North Atlantic ◽  
Wave Train ◽  
Surface Air Temperature ◽  
Moisture Flux ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Decline ◽  
Arctic Sea ◽  
Sea Ice Reduction

In this paper, the lead–lag relationship between the Arctic sea ice variability over the Barents–Kara Sea (BKS) and Ural blocking (UB) in winter (DJF) ranging from 1979/80 to 2011/12 is examined. It is found that in a regressed DJF-mean field an increased UB frequency (days) corresponds to an enhanced sea ice decline over the BKS, while the high sea surface temperature over the BKS is accompanied by a significant Arctic sea ice reduction. Lagged daily regression and correlation reveal that the growth and maintenance of the UB that is related to the positive North Atlantic Oscillation (NAO+) through the negative east Atlantic/west Russia (EA/WR−) wave train is accompanied by an intensified negative BKS sea ice anomaly, and the BKS sea ice reduction lags the UB pattern by about four days. Because the intensified UB pattern occurs together with enhanced downward infrared radiation (IR) associated with the intensified moisture flux convergence and total column water over the BKS, the UB pattern contributes significantly to the BKS sea ice decrease on a time scale of weeks through intensified positive surface air temperature (SAT) anomalies resulting from enhanced downward IR. It is also found that the BKS sea ice decline can persistently maintain even when the UB has disappeared, thus indicating that the UB pattern is an important amplifier of the BKS sea ice reduction. Moreover, it is demonstrated that the EA/WR− wave train formed by the combined NAO+ and UB patterns is closely related to the amplified warming over the BKS through the strengthening (weakening) of mid-to-high-latitude westerly wind in the North Atlantic (Eurasia).

scholarly journals Modulations of North American and European Weather Variability and Extremes by Interdecadal Variability of the Atmospheric Circulation over the North Atlantic Sector

2020 ◽  
Vol 33 (18) ◽  
pp. 8125-8146
Author(s):  
Patrick Martineau ◽  
Hisashi Nakamura ◽  
Yu Kosaka ◽  
Bunmei Taguchi ◽  
Masato Mori
Keyword(s):  
North Atlantic ◽  
Wave Train ◽  
Surface Air Temperature ◽  
Reanalysis Data ◽  
Dominant Mode ◽  
Negative Phase ◽  
Eastern United States ◽  
Atlantic Sector ◽  
The North ◽  
The North Atlantic

AbstractThe dominant mode of wintertime interdecadal covariability between subseasonal surface air temperature (SAT) variability and midtropospheric circulation over the North Atlantic sector is identified through maximum covariance analysis applied to century-long reanalysis data. This mode highlights a tendency for subseasonal temperature variability over Europe and eastern North America to be enhanced during decades when the negative phase of the North Atlantic Oscillation (NAO) prevails. This interdecadal NAO is characterized by a stationary Rossby wave train that originates from the subtropical Atlantic, propagates northward into the subpolar Atlantic, and finally refracts toward Europe and the Middle East. A decadal increase in precipitation in the subtropics under the enhanced supply of heat and moisture from the Gulf Stream and its surroundings appears to act as a source for this wave train. The influence of the interdecadal NAO on subseasonal SAT variability is explained primarily by the modulated efficiency of baroclinic conversion of available potential energy from the background atmospheric flow to subseasonal eddies. The combination of enhanced subseasonal variability and low winter-mean temperature anomalies associated with the negative phase of the interdecadal NAO increases the frequency of cold extremes affecting Europe and the eastern United States.

scholarly journals Observed Atmospheric Response to Cold Season Sea Ice Variability in the Arctic

2014 ◽  
Vol 27 (3) ◽  
pp. 1243-1254 ◽  
Author(s):  
Claude Frankignoul ◽  
Nathalie Sennéchael ◽  
Pierre Cauchy
Keyword(s):  
Sea Ice ◽  
North Atlantic ◽  
North Pacific ◽  
Cold Season ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Atlantic Sector ◽  
The North ◽  
The North Atlantic ◽  
Sst Anomalies

Abstract The relation between weekly Arctic sea ice concentrations (SICs) from December to April and sea level pressure (SLP) during 1979–2007 is investigated using maximum covariance analysis (MCA). In the North Atlantic sector, the interaction between the North Atlantic Oscillation (NAO) and a SIC seesaw between the Labrador Sea and the Greenland–Barents Sea dominates. The NAO drives the seesaw and in return the seesaw precedes a midwinter/spring NAO-like signal of the opposite polarity but with a strengthened northern lobe, thus acting as a negative feedback, with maximum squared covariance at a lag of 6 weeks. Statistical significance decreases when SLP is considered in the whole Northern Hemisphere but it increases when North Pacific SIC is included in the analysis. The maximum squared covariance then occurs after 8 weeks, resembling a combination of the NAO response to the Atlantic SIC seesaw and the Aleutian–Icelandic low seesaw-like response to in-phase SIC changes in the Bering and Okhotsk Seas, which is found to lag the North Pacific SIC. Adding SST anomalies to the SIC anomalies in the MCA leads to a loss of significance when the MCA is limited to the North Atlantic sector and a slight degradation in the Pacific and hemispheric cases, suggesting that SIC is the driver of the midwinter/spring atmospheric signal. However, North Pacific cold season SST anomalies also precede a NAO/Arctic Oscillation (AO)-like SLP signal after a shorter delay of 3–4 weeks.

Drivers of Eurasian spring snow cover variability

2020 ◽  
pp. 1
Author(s):  
Taotao Zhang ◽  
Tao Wang ◽  
Yutong Zhao ◽  
Chaoyi Xu ◽  
Yingying Feng ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Wave Train ◽  
Surface Air Temperature ◽  
Temporal Variations ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Atmospheric Teleconnection ◽  
The North ◽  
Sst Anomalies

AbstractThe variability of spring snow cover over Eurasia can have notable impacts on the current and following season climate, but the causes of it are poorly understood. This study investigates the potential drivers and the associated physical processes for the first two empirical orthogonal function (EOF) modes of the Eurasian spring snow cover variability during 1967-2018, which are characterized by a continent-wide coherent pattern and a west-east dipole structure, respectively. Analyses show that the spring surface air temperature and snowfall are the direct factors influencing the two modes. We further examined the contributions to the snow cover variability of atmospheric teleconnection patterns, sea surface temperature (SST) anomalies, and variations of Arctic sea ice during spring. The results indicate that circulation anomalies associated with the Arctic Oscillation, Polar–Eurasia, and West Pacific patterns can partly explain the formation of the EOF1 mode, while the EOF2 mode has a close relationship with the East Atlantic–Western Russia pattern. In addition, a horseshoe like monopole structure of SST anomalies over the North Atlantic plays an important role in regulating the EOF2 mode, by inducing a wave train circulation. Moreover, the EOF2 mode is also affected by anomalous circulations induced by the sea ice anomalies in the Barents–Kara Seas. An empirical model using these drivers satisfactorily reproduced the temporal variations of the two EOF modes, implying that our results can substantially improve comprehension of the variability of Eurasian spring snow cover.

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 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 A Nonlinear Theory of Atmospheric Blocking: An Application to Greenland Blocking Changes Linked to Winter Arctic Sea Ice Loss

2019 ◽  
Vol 77 (2) ◽  
pp. 723-751 ◽  
Author(s):  
Wenqi Zhang ◽  
Dehai Luo
Keyword(s):  
Sea Ice ◽  
Phase Speed ◽  
Arctic Sea Ice ◽  
Atmospheric Blocking ◽  
Energy Dispersion ◽  
Sea Ice Concentration ◽  
Zonal Scale ◽  
The North ◽  
Arctic Sea ◽  
The Impact

Abstract In this paper, the impact of winter Arctic sea ice concentration (SIC) decline over Baffin Bay, Davis Strait, and Labrador Sea (BDL) on Greenland blocking (GB) is first examined. It is found that the GB has a longer duration, a more notable westward movement, and a larger zonal scale in the low SIC winter than in the high SIC winter. In particular, the decay of GB may become slower than its growth in the low SIC winter, but the reverse is seen in the high SIC winter. The GB in the low SIC winter can have a more important impact on cold anomalies over North American midlatitudes than in the high SIC winter because of its slower decay and stronger retrogression. The influence of large BDL SIC loss on the GB mainly through reduced meridional potential vorticity gradient (PVy) related to reduced zonal winds over the North Atlantic mid- to high latitudes (NAMH) due to BDL warming is further examined by using the nonlinear phase speed and energy dispersion speed formula of blocking based on a nonlinear wave packet theory of atmospheric blocking. In this theory, the preexisting synoptic-scale eddies rather than the eddy straining or deformation is important for the blocking intensification and maintenance, which contradicts the eddy straining theory of Shutts. It is revealed from this theoretical model that under weaker NAMH zonal wind conditions the energy dispersion speed of GB may become smaller due to weaker PVy during its decaying phase than during the blocking growing phase, in addition to the GB having larger negative phase speed and stronger nonlinearity. The opposite is true when the PVy is larger. Thus, under a large SIC loss condition the GB shows notable retrogression, large zonal scales, and a long lifetime, which has a slower decay than its growth.

Arctic Sea Ice Reemergence: The Role of Large-Scale Oceanic and Atmospheric Variability*

2015 ◽  
Vol 28 (14) ◽  
pp. 5477-5509 ◽  
Author(s):  
Mitchell Bushuk ◽  
Dimitrios Giannakis ◽  
Andrew J. Majda
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Arctic Sea ◽  
Spring Sea Ice ◽  
Phase Relationships

Abstract Arctic sea ice reemergence is a phenomenon in which spring sea ice anomalies are positively correlated with fall anomalies, despite a loss of correlation over the intervening summer months. This work employs a novel data analysis algorithm for high-dimensional multivariate datasets, coupled nonlinear Laplacian spectral analysis (NLSA), to investigate the regional and temporal aspects of this reemergence phenomenon. Coupled NLSA modes of variability of sea ice concentration (SIC), sea surface temperature (SST), and sea level pressure (SLP) are studied in the Arctic sector of a comprehensive climate model and in observations. It is found that low-dimensional families of NLSA modes are able to efficiently reproduce the prominent lagged correlation features of the raw sea ice data. In both the model and observations, these families provide an SST–sea ice reemergence mechanism, in which melt season (spring) sea ice anomalies are imprinted as SST anomalies and stored over the summer months, allowing for sea ice anomalies of the same sign to reappear in the growth season (fall). The ice anomalies of each family exhibit clear phase relationships between the Barents–Kara Seas, the Labrador Sea, and the Bering Sea, three regions that compose the majority of Arctic sea ice variability. These regional phase relationships in sea ice have a natural explanation via the SLP patterns of each family, which closely resemble the Arctic Oscillation and the Arctic dipole anomaly. These SLP patterns, along with their associated geostrophic winds and surface air temperature advection, provide a large-scale teleconnection between different regions of sea ice variability. Moreover, the SLP patterns suggest another plausible ice reemergence mechanism, via their winter-to-winter regime persistence.

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