Seasonal Relationships between Large-Scale Climate Variability and Antarctic Sea Ice Concentration

2012 ◽  
Vol 25 (16) ◽  
pp. 5451-5469 ◽  
Author(s):  
Graham R. Simpkins ◽  
Laura M. Ciasto ◽  
David. W. J. Thompson ◽  
Matthew H. England
Keyword(s):  
Climate Variability ◽  
Sea Ice ◽  
Large Scale ◽  
Southern Oscillation ◽  
Principal Component ◽  
Southern Annular Mode ◽  
Enso Cycle ◽  
Sea Ice Concentration ◽  
Antarctic Sea Ice ◽  
Ice Concentration

Abstract The observed relationships between anomalous Antarctic sea ice concentration (SIC) and the leading patterns of Southern Hemisphere (SH) large-scale climate variability are examined as a function of season over 1980–2008. Particular emphasis is placed on 1) the interactions between SIC, the southern annular mode (SAM), and El Niño–Southern Oscillation (ENSO); and 2) the contribution of these two leading modes to the 29-yr trends in sea ice. Regression, composite, and principal component analyses highlight a seasonality in SH sea ice–atmosphere interactions, whereby Antarctic sea ice variability exhibits the strongest linkages to the SAM and ENSO during the austral cold season months. As noted in previous work, a dipole in SIC anomalies emerges in relation to the SAM, characterized by centers of action located near the Bellingshausen/Weddell and Amundsen/eastern Ross Seas. The structure and magnitude of this SIC dipole is found to vary considerably as a function of season, consistent with the seasonality of the overlying atmospheric circulation anomalies. Relative to the SAM, the pattern of sea ice anomalies linked to ENSO exhibits a similar seasonality but tends to be weaker in amplitude and more diffuse in structure. The relationships between ENSO and sea ice also exhibit a substantial nonlinear component, highlighting the need to consider both season and phase of the ENSO cycle when diagnosing ENSO–SIC linkages. Trends in SIC over 1980–2008 are not significantly related to trends in either the SAM or ENSO during any season, including austral summer when the trend in the SAM is most pronounced.

scholarly journals Aspects of intraseasonal variability of Antarctic sea ice in austral winter related to ENSO and SAM events

2017 ◽  
Vol 63 (241) ◽  
pp. 838-846 ◽  
Author(s):  
KENJI BABA ◽  
JAMES RENWICK
Keyword(s):  
Sea Ice ◽  
El Nino ◽  
Intraseasonal Variability ◽  
Southern Annular Mode ◽  
Wave Number ◽  
Austral Winter ◽  
Sea Ice Concentration ◽  
Annular Mode ◽  
Antarctic Sea Ice ◽  
Ice Concentration

ABSTRACTWe performed an Empirical Orthogonal Function (EOF) analysis to assess the intraseasonal variability of 5–60 day band-pass filtered Antarctic sea-ice concentration in austral winter using a 20-year daily dataset from 1995 to 2014. Zonal wave number 3 dominated in the Antarctic, especially so across the west Antarctic. Results showed the coexistence of stationary and propagating wave components. A spectral analysis of the first two principal components (PCs) showed a similar structure for periods up to 15 days but generally more power in PC1 at longer periods. Regression analysis upon atmospheric fields using the first two PCs of sea-ice concentration showed a coherent wave number 3 pattern. The spatial phase delay between the sea-ice and mean sea-level pressure patterns suggests that meridional flow and associated temperature advection are important for modulating the sea-ice field. EOF analyses carried out separately for El Niño, La Niña and neutral years, and for Southern Annular Mode positive, negative and neutral periods, suggest that the spatial patterns of wave number 3 shift between subsets. The results also indicate that El Niño-Southern Oscillation and Southern Annular Mode affect stationary wave interactions between sea-ice and atmospheric fields on intraseasonal timescales.

scholarly journals Antarctic Sea Ice Climatology, Variability, and Late Twentieth-Century Change in CCSM4

2012 ◽  
Vol 25 (14) ◽  
pp. 4817-4838 ◽  
Author(s):  
Laura Landrum ◽  
Marika M. Holland ◽  
David P. Schneider ◽  
Elizabeth Hunke
Keyword(s):  
Twentieth Century ◽  
Sea Ice ◽  
Southern Oscillation ◽  
Austral Summer ◽  
Southern Annular Mode ◽  
Cold Bias ◽  
Sea Ice Concentration ◽  
Climate System Model ◽  
Modes Of Variability ◽  
Antarctic Sea Ice

Abstract A preindustrial control run and an ensemble of twentieth-century integrations of the Community Climate System Model, version 4 (CCSM4), are evaluated for Antarctic sea ice climatology, modes of variability, trends, and covariance with related physical variables such as surface temperature and sea level pressure. Compared to observations, the mean ice cover is too extensive in all months. This is in part related to excessively strong westerly winds over ~50°–60°S, which drive a large equatorward meridional ice transport and enhanced ice growth near the continent and also connected with a cold bias in the Southern Ocean. In spite of these biases in the climatology, the model’s sea ice variability compares well to observations. The leading mode of austral winter sea ice concentration exhibits a dipole structure with anomalies of opposite sign in the Atlantic and Pacific sectors. Both the El Niño–Southern Oscillation and the southern annular mode (SAM) project onto this mode. In twentieth-century integrations, Antarctic sea ice area exhibits significant decreasing annual trends in all six ensemble members from 1950 to 2005, in apparent contrast to observations that suggest a modest ice area increase since 1979. Two ensemble members show insignificant changes when restricted to 1979–2005. The ensemble mean shows a significant increase in the austral summer SAM index over 1960–2005 and 1979–2005 that compares well with the observed SAM trend. However, Antarctic warming and sea ice loss in the model are closely connected to each other and not to the trend in the SAM.

scholarly journals Sea ice and large-scale atmospheric variability around East Antarctica

2021 ◽  
Author(s):  
◽  
Florence Isaacs
Keyword(s):  
Indian Ocean ◽  
Climate Variability ◽  
Sea Ice ◽  
Large Scale ◽  
Wave Train ◽  
East Antarctica ◽  
Sea Ice Concentration ◽  
Atmospheric Wave ◽  
Ice Concentration ◽  
Dronning Maud Land

<p><b>​​Antarctica’s sea ice cover is an important component in the global climate system. The variability and recent trends of sea ice concentration are, however, not accurately reproduced by models. Evaluating model performance is hampered because the processes that determine sea ice distribution are not yet well understood, particularly in the East Antarctic region. Here I explore the relationships between recent climate variability and sea ice around East Antarctica, the spatial variability in these relationships, and the impacts that these may have on other aspects of the climate and cryosphere. To achieve this, I analysed satellite-derived HadlSST sea ice concentration (SIC) alongside ERA5 atmospheric reanalysis data for the period between 1979-2018.</b></p> <p>I found that variability in sea ice coverage around East Antarctica was affected by El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), the Southern Annular Mode (SAM), and Zonal Wave 3 (ZW3). Additionally, I found that the influence of each of these modes varied spatially and temporally, and that sea ice variability affected how regional scale climate responded to changes in large-scale circulation. Summer and autumn SIC around Dronning Maud Land between 10°E and 70°E exhibited a statistically significant negative correlation with the Niño 3.4 index. Analysis of ERA5 data suggests that a southward‐propagating atmospheric wave train triggered by SST anomalies in the tropical Pacific extends into Dronning Maud Land and alters sea ice concentration by encouraging meridional airflow. Shifts in meridional flow in Dronning Maud Land affected sea ice thermodynamically, by altering local heat transport and in turn altering sea ice formation and melt. </p> <p>Sea ice around the Western Pacific sector (WPS) of East Antarctica showed a significant association with variability in the IOD and the SAM. The IOD was correlated with SIC in all seasons but summer. The IOD-SIC relationship is likely driven by an IOD-associated atmospheric wave-train which propagates polewards from the tropical Indian Ocean to Wilkes Land, altering regional circulation and in turn affecting SIC through changes to local climate and sea ice transport. The correlation between WPS SIC and the SAM shifts from positive in summer and autumn to negative in winter and spring, and is likely due to the influence of the SAM on katabatic winds and coastal polynyas, which in turn affect SIC. </p> <p>A significant correlation was observed between SIC variability around East Antarctica and precipitation variability across the continent and the near-coastal Southern Ocean. Further analysis showed that SIC affected how continental precipitation responded to large-scale atmospheric circulation, including modes such as ZW3 and the SAM. Specifically, increased southward moisture flux was only associated with increased precipitation in the inland coastal regions of the continent when SIC was anomalously low. These findings suggest that any future decrease in sea ice may result in greater coupling of climate variability with continental precipitation.</p>

scholarly journals Predictability of Arctic Annual Minimum Sea Ice Patterns

2016 ◽  
Vol 29 (19) ◽  
pp. 7065-7088 ◽  
Author(s):  
GARY GRUNSEICH ◽  
BIN WANG
Keyword(s):  
Climate Variability ◽  
Sea Ice ◽  
Southern Oscillation ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Circulation Patterns ◽  
Melting Period ◽  
Ice Concentration ◽  
The Arctic Oscillation ◽  
Natural Climate

Abstract Prediction of the arctic annual sea ice minimum extent and melting patterns draws interest from numerous industries and government agencies but has been an ongoing challenge for forecasters and climate scientists using statistical and dynamical models. Using the dominant independent modes of interannual sea ice concentration (SIC) variability during September–October, a new approach combining statistical analysis with physically derived links to natural climate variability sources is used to predict each mode and the total anomaly pattern. Sea ice patterns associated with each mode are predominantly shaped by the wind-driven advective convergence, forced by circulation anomalies associated with local and remote forms of naturally occurring climate variability. The impacts of the Arctic Oscillation, beginning from the preceding winter, control the leading mode of SIC variability during the annual minimum. In the three final months of the melting period, the broad impacts of the Indian and East Asian summer monsoons produce unique SIC impacts along the arctic periphery, displayed as the second and third modes, respectively. El Niño–Southern Oscillation (ENSO) largely shapes the fourth SIC mode patterns through influencing variability early in the melting period. Using physically meaningful and statistically significant predictors, physical–empirical (P–E) models are developed for each SIC mode. Some predictors directly account for the circulation patterns driving anomalous sea ice, while the monsoon-related predictors convey early season sources of monsoonal variability, which subsequently influences the Arctic. The combined SIC predictions of the P–E models exhibit great skill in matching the observed magnitude and temporal variability along the arctic margins during the annual minimum.

scholarly journals Southern Hemisphere Synoptic Behavior in Extreme Phases of SAM, ENSO, Sea Ice Extent, and Southern Australia Rainfall

2008 ◽  
Vol 21 (21) ◽  
pp. 5566-5584 ◽  
Author(s):  
Alexandre Bernardes Pezza ◽  
Tom Durrant ◽  
Ian Simmonds ◽  
Ian Smith
Keyword(s):  
Sea Ice ◽  
Southern Hemisphere ◽  
High Latitude ◽  
Large Scale ◽  
Southern Oscillation ◽  
Southern Annular Mode ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
Rainfall Anomalies ◽  
Western Side

Abstract The association between Southern Hemisphere cyclones and anticyclones and the El Niño–Southern Oscillation (ENSO), southern annular mode (SAM), Antarctic sea ice extent (SIE), and rainfall in Perth and Melbourne is explored. Those cities are, respectively, located in the southwestern and southeastern corners of Australia, where substantial decreasing rainfall trends have been observed over the last decades. The need for a more unified understanding of large-scale anomalies in storm indicators associated with the climate features itemized above has motivated this study. The main aim is to identify cyclone-anomalous areas that are potentially important in characterizing continental rainfall anomalies from a hemispheric perspective, focusing on midlatitude Australia. The study covers the “satellite era” from 1979 to 2003 and was conducted for the southern winter when midlatitude rainfall is predominantly baroclinic. The results indicate a well-organized hemispheric cyclone pattern associated with ENSO, SAM, SIE, and rainfall anomalies. There is a moderate large-scale, high-latitude resemblance between La Niña, negative SAM, and reduced SIE in some sectors. In particular, there is a suggestion that SIE anomalies over the Indian Ocean and Western Australia sectors are associated with a large-scale pattern of cyclone/anticyclone anomalies that is more pronounced over the longitudes of Australia and New Zealand. Spatial correlation analysis suggests a robust link between cyclone density over the sectors mentioned above and rainfall in Perth and Melbourne. Statistical analyses of rainfall and SIE show modest correlations for Perth and weak correlations for Melbourne, generally corroborating the above. It is proposed that SAM and SIE are part of a complex physical system that is best understood as a coupled mechanism, and that their impacts on the circulation can be seen as partially independent of ENSO. While SAM and SIE have greater influence on the circulation affecting rainfall in the western side of Australia, ENSO is the dominant influence on the eastern half of the country. A contraction of the sea ice seems to be accompanied by a southward shift of high-latitude cyclones, which is also hypothesized to increase downstream cyclone density at midlatitudes via conservation of mass, similarly to what is observed during the extreme positive phase of the SAM. These associations build on previous developments in the literature. They bring a more unified view on high-latitude climate features, and may also help to explain the declining trends in Australian rainfall.

scholarly journals Sea ice and large-scale atmospheric variability around East Antarctica

2021 ◽  
Author(s):  
◽  
Florence Isaacs
Keyword(s):  
Indian Ocean ◽  
Climate Variability ◽  
Sea Ice ◽  
Large Scale ◽  
Wave Train ◽  
East Antarctica ◽  
Sea Ice Concentration ◽  
Atmospheric Wave ◽  
Ice Concentration ◽  
Dronning Maud Land

<p><b>​​Antarctica’s sea ice cover is an important component in the global climate system. The variability and recent trends of sea ice concentration are, however, not accurately reproduced by models. Evaluating model performance is hampered because the processes that determine sea ice distribution are not yet well understood, particularly in the East Antarctic region. Here I explore the relationships between recent climate variability and sea ice around East Antarctica, the spatial variability in these relationships, and the impacts that these may have on other aspects of the climate and cryosphere. To achieve this, I analysed satellite-derived HadlSST sea ice concentration (SIC) alongside ERA5 atmospheric reanalysis data for the period between 1979-2018.</b></p> <p>I found that variability in sea ice coverage around East Antarctica was affected by El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), the Southern Annular Mode (SAM), and Zonal Wave 3 (ZW3). Additionally, I found that the influence of each of these modes varied spatially and temporally, and that sea ice variability affected how regional scale climate responded to changes in large-scale circulation. Summer and autumn SIC around Dronning Maud Land between 10°E and 70°E exhibited a statistically significant negative correlation with the Niño 3.4 index. Analysis of ERA5 data suggests that a southward‐propagating atmospheric wave train triggered by SST anomalies in the tropical Pacific extends into Dronning Maud Land and alters sea ice concentration by encouraging meridional airflow. Shifts in meridional flow in Dronning Maud Land affected sea ice thermodynamically, by altering local heat transport and in turn altering sea ice formation and melt. </p> <p>Sea ice around the Western Pacific sector (WPS) of East Antarctica showed a significant association with variability in the IOD and the SAM. The IOD was correlated with SIC in all seasons but summer. The IOD-SIC relationship is likely driven by an IOD-associated atmospheric wave-train which propagates polewards from the tropical Indian Ocean to Wilkes Land, altering regional circulation and in turn affecting SIC through changes to local climate and sea ice transport. The correlation between WPS SIC and the SAM shifts from positive in summer and autumn to negative in winter and spring, and is likely due to the influence of the SAM on katabatic winds and coastal polynyas, which in turn affect SIC. </p> <p>A significant correlation was observed between SIC variability around East Antarctica and precipitation variability across the continent and the near-coastal Southern Ocean. Further analysis showed that SIC affected how continental precipitation responded to large-scale atmospheric circulation, including modes such as ZW3 and the SAM. Specifically, increased southward moisture flux was only associated with increased precipitation in the inland coastal regions of the continent when SIC was anomalously low. These findings suggest that any future decrease in sea ice may result in greater coupling of climate variability with continental precipitation.</p>

scholarly journals DASSO: a data assimilation system for the Southern Ocean that utilizes both sea-ice concentration and thickness observations

2021 ◽  
pp. 1-6
Author(s):  
Hao Luo ◽  
Qinghua Yang ◽  
Longjiang Mu ◽  
Xiangshan Tian-Kunze ◽  
Lars Nerger ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Southern Ocean ◽  
Sea Ice ◽  
Coupled Model ◽  
Sea Ice Concentration ◽  
Model Free ◽  
Antarctic Sea Ice ◽  
Ice Concentration ◽  
Data Assimilation System ◽  
Assimilation System

Abstract To improve Antarctic sea-ice simulations and estimations, an ensemble-based Data Assimilation System for the Southern Ocean (DASSO) was developed based on a regional sea ice–ocean coupled model, which assimilates sea-ice thickness (SIT) together with sea-ice concentration (SIC) derived from satellites. To validate the performance of DASSO, experiments were conducted from 15 April to 14 October 2016. Generally, assimilating SIC and SIT can suppress the overestimation of sea ice in the model-free run. Besides considering uncertainties in the operational atmospheric forcing data, a covariance inflation procedure in data assimilation further improves the simulation of Antarctic sea ice, especially SIT. The results demonstrate the effectiveness of assimilating sea-ice observations in reconstructing the state of Antarctic sea ice, but also highlight the necessity of more reasonable error estimation for the background as well as the observation.

scholarly journals Cryospheric Impacts of Soviet River Diversion Schemes

1984 ◽  
Vol 5 ◽  
pp. 61-68 ◽  
Author(s):  
T. Holt ◽  
P. M. Kelly ◽  
B. S. G. Cherry
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
River Discharge ◽  
Large Scale ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Ice Concentration ◽  
The Arctic Ocean ◽  
The Impact

Soviet plans to divert water from rivers flowing into the Arctic Ocean have led to research into the impact of a reduction in discharge on Arctic sea ice. We consider the mechanisms by which discharge reductions might affect sea-ice cover and then test various hypotheses related to these mechanisms. We find several large areas over which sea-ice concentration correlates significantly with variations in river discharge, supporting two particular hypotheses. The first hypothesis concerns the area where the initial impacts are likely to which is the Kara Sea. Reduced riverflow is associated occur, with decreased sea-ice concentration in October, at the time of ice formation. This is believed to be the result of decreased freshening of the surface layer. The second hypothesis concerns possible effects on the large-scale current system of the Arctic Ocean and, in particular, on the inflow of Atlantic and Pacific water. These effects occur as a result of changes in the strength of northward-flowing gradient currents associated with variations in river discharge. Although it is still not certain that substantial transfers of riverflow will take place, it is concluded that the possibility of significant cryospheric effects and, hence, large-scale climate impact should not be neglected.

scholarly journals Comparison between AMSR2 Sea Ice Concentration Products and Pseudo-Ship Observations of the Arctic and Antarctic Sea Ice Edge on Cloud-Free Days

2018 ◽  
Vol 10 (2) ◽  
pp. 317 ◽  
Author(s):  
Xiaoping Pang ◽  
Jian Pu ◽  
Xi Zhao ◽  
Qing Ji ◽  
Meng Qu ◽  
...  
Keyword(s):  
Sea Ice ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Antarctic Sea Ice ◽  
Ice Concentration ◽  
Ice Edge ◽  
Sea Ice Edge
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