A regime shift in seasonal total Antarctic sea ice extent in the twentieth century

<div><span>Climatic changes induce many significant changes to long standing weather patterns. These mechanisms interact to drive consequences that may not be immediately obvious. One such connection involves the apparent relationship between polar sea ice extent and mid-latitude precipitation timing and location. This correlation, its mechanisms, and possible influences on weather are decently understood with respect to the Northern Hemisphere. However, the analogous relation for the Southern Hemisphere has been less studied. This provides an opportunity to examine connections between polar conditions and mid-latitude weather.</span></div><div>&#160;</div><div><span>We explore the teleconnection between sea ice extent and lower latitude precipitation over the Southern Hemisphere. We investigate this relationship through observations of sea ice coverage using ICESat and ICESat-2 compared with reanalysis data via MERRA-2 in order to understand the variability of sea ice extent and its impact on midlatitude precipitation over the Southern Hemisphere. This study particularly examines the importance of seasonality and regional variations of the relationship.</span></div>

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

Journal of Climate ◽

10.1175/jcli-d-11-00201.1 ◽

2012 ◽

Vol 25 (5) ◽

pp. 1431-1452 ◽

Cited By ~ 82

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.

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Decadal decrease of Antarctic sea ice extent inferred from whaling records revisited on the basis of historical and modern sea ice records

Polar Research ◽

10.3402/polar.v22i1.6439 ◽

2003 ◽

Vol 22 (1) ◽

pp. 19-25 ◽

Cited By ~ 14

Author(s):

Stephen Ackley ◽

Peter Wadhams ◽

Josefino C. Comiso ◽

Anthony P. Worby

Keyword(s):

Sea Ice ◽

Sea Ice Extent ◽

Antarctic Sea Ice

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Conditions leading to the unprecedented low Antarctic sea ice extent during the 2016 austral spring season

Geophysical Research Letters ◽

10.1002/2017gl074691 ◽

2017 ◽

Vol 44 (17) ◽

pp. 9008-9019 ◽

Cited By ~ 57

Author(s):

Malte F. Stuecker ◽

Cecilia M. Bitz ◽

Kyle C. Armour

Keyword(s):

Sea Ice ◽

Spring Season ◽

Austral Spring ◽

Sea Ice Extent ◽

Antarctic Sea Ice

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Brief communication: lack of agreement in remote sensing detection of cyclonic drift caused by Atlantic weather in Antarctic sea ice

10.5194/tc-2021-144 ◽

2021 ◽

Author(s):

Wayne de Jager ◽

Marcello Vichi

Keyword(s):

Remote Sensing ◽

Sea Ice ◽

Alternative Methods ◽

Polar Regions ◽

Sea Ice Concentration ◽

Sea Ice Extent ◽

Ice Dynamics ◽

Antarctic Sea Ice ◽

Ice Drift ◽

The Impact

Abstract. Sea-ice extent variability, a measure based on satellite-derived sea ice concentration measurements, has traditionally been used as an essential climate variable to evaluate the impact of climate change on polar regions. However, concentration- based measurements of ice variability do not allow to discriminate the relative contributions made by thermodynamic and dynamic processes, prompting the need to use sea-ice drift products and develop alternative methods to quantify changes in sea ice dynamics that would indicate trends in Antarctic ice characteristics. Here, we present a new method to automate the detection of rotational drift features in Antarctic sea ice at daily timescales using currently available remote sensing ice motion products from EUMETSAT OSI SAF. Results show that there is a large discrepancy in the detection of cyclonic drift features between products, both in terms of intensity and year-to-year distributions, thus diminishing the confidence at which ice drift variability can be further analysed. Product comparisons showed that there was good agreement in detecting anticyclonic drift, and cyclonic drift features were measured to be 1.5–2.2 times more intense than anticyclonic features. The most intense features were detected by the merged product, suggesting that the processing chain used for this product could be injecting additional rotational momentum into the resultant drift vectors. We conclude that it is therefore necessary to better understand why the products lack agreement before further trend analysis of these drift features and their climatic significance can be assessed.

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Last Glacial Maximum Antarctic sea ice linked with global mean ocean temperature: evidence from PMIP3, PMIP4 and MIROC-4m simulations

10.5194/egusphere-egu21-3550 ◽

2021 ◽

Author(s):

Tristan Vadsaria ◽

Sam Sherriff-Tadano ◽

Ayako Abe-Ouchi ◽

Takashi Obase ◽

Wing-Le Chan ◽

...

Keyword(s):

Southern Ocean ◽

Sea Ice ◽

Last Glacial Maximum ◽

Ocean Circulation ◽

Glacial Maximum ◽

Ocean Temperature ◽

Sea Ice Extent ◽

Last Glacial ◽

Antarctic Sea Ice ◽

The Antarctic

<p>Southern Ocean sea ice and oceanic fronts are known to play an important role on the climate system, carbon cycles, bottom ocean circulation, and Antarctic ice sheet. However, many models of the previous Past-climate Model Intercomparison Project (PMIP) underestimated sea-ice extent (SIE) for the Last Glacial Maximum (LGM)(Roche et al., 2012; Marzocchi and Jensen, 2017), mainly because of surface bias (Flato et al., 2013) that may have an impact on mean ocean temperature (MOT). Indeed, recent studies further suggest an important link between Southern Ocean sea ice and mean ocean temperature (Ferrari et al., 2014; Bereiter et al., 2018 among others). Misrepresent the Antarctic sea-ice extent could highly impact deep ocean circulation, the heat transport and thus the MOT. In this study, we will stress the relationship between the distribution of Antarctic sea-ice extent and the MOT through the analysis of the PMIP3 and PMIP4 exercise and by using a set of MIROC models. To date, the latest version of MIROC improve its representation of the LGM Antarctic sea-ice extent, affecting the deep circulation and the MOT distribution (Sherriff-Tadano et al., under review).</p><p>Our results show that available PMIP4 models have an overall improvement in term of LGM sea-ice extent compared to PMIP3, associated to colder deep and bottom ocean temperature. Focusing on MIROC (4m) models, we show that models accounting for Southern Ocean sea-surface temperature (SST) bias correction reproduce an Antarctic sea-ice extent, 2D-distribution, and seasonal amplitude in good agreement with proxy-based data. Finally, using PMIP-MIROC analyze, we show that it exists a relationship between the maximum SIE and the MOT, modulated by the Antarctic intermediate and bottom waters.</p>

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