scholarly journals Coastal complexity of the Antarctic continent

2021 ◽  
Vol 13 (7) ◽  
pp. 3103-3114
Author(s):  
Richard Porter-Smith ◽  
John McKinlay ◽  
Alexander D. Fraser ◽  
Robert A. Massom
Keyword(s):  
Low Complexity ◽  
Ecological Processes ◽  
Ice Shelves ◽  
Biological Studies ◽  
Coastal Margin ◽  
Terrestrial Environments ◽  
Antarctic Continent ◽  
The Antarctic ◽  
Unique Dataset

Abstract. The Antarctic outer coastal margin (i.e. the coastline itself or the terminus or front of ice shelves, whichever is adjacent to the ocean) is a key interface between the ice sheet and terrestrial environments and the Southern Ocean. Its physical configuration (including both length scale of variation, orientation, and aspect) has direct bearing on several closely associated cryospheric, biological, oceanographical, and ecological processes, yet no study has quantified the coastal complexity or orientation of Antarctica's coastal margin. This first-of-a-kind characterization of Antarctic coastal complexity aims to address this knowledge gap. We quantify and investigate the physical configuration and complexity of Antarctica's circumpolar outer coastal margin using a novel technique based on ∼ 40 000 random points selected along a vector coastline derived from the MODIS Mosaic of Antarctica dataset. At each point, a complexity metric is calculated at length scales from 1 to 256 km, giving a multiscale estimate of the magnitude and direction of undulation or complexity at each point location along the entire coastline. Using a cluster analysis to determine characteristic complexity “signatures” for random nodes, the coastline is found to comprise three basic groups or classes: (i) low complexity at all scales, (ii) most complexity at shorter scales, and (iii) most complexity at longer scales. These classes are somewhat heterogeneously distributed throughout the continent. We also consider bays and peninsulas separately and characterize their multiscale orientation. This unique dataset and its summary analysis have numerous applications for both geophysical and biological studies. All these data are referenced by https://doi.org/10.26179/5d1af0ba45c03 (Porter-Smith et al., 2019) and are available free of charge at http://data.antarctica.gov.au (last access: 7 June 2021).

scholarly journals Coastal complexity of the Antarctic continent

2019 ◽  
Author(s):  
Richard Porter-Smith ◽  
John McKinlay ◽  
Alex Fraser ◽  
Robert Massom
Keyword(s):  
Low Complexity ◽  
Quantitative Information ◽  
Ecological Processes ◽  
Ice Shelves ◽  
Multi Scale ◽  
Biological Studies ◽  
Coastal Margin ◽  
Terrestrial Environments ◽  
Antarctic Continent ◽  
The Antarctic

Abstract. The Antarctic outer coastal margin (i.e., the coastline itself, or the terminus/front of ice shelves, whichever is adjacent to the ocean) is a key interface between the ice-sheet and terrestrial environments and the Southern Ocean. Its physical configuration (including both length scale of variation and orientation/aspect) has direct bearing on several closely associated cryospheric, biological, oceanographical and ecological processes, yet no study has quantified the coastal complexity or orientation of Antarctica’s coastal margin. This first-of-a-kind characterisation of Antarctic coastal complexity aims to address this knowledge gap. We quantify and investigate the physical configuration and complexity of Antarctica’s circumpolar outer coastal margin using a novel, technique based on ∼ 40,000 random points selected along a vector coastline derived from the MODIS Mosaic of Antarctica dataset. At each point, a complexity metric is calculated at length scales from 1 to 256 km, giving a multiscale estimate of the magnitude and direction of undulation or complexity at each point location along the entire coastline. Using a cluster analysis to determine characteristic complexity ‘signatures’ for random nodes, the coastline is found to comprise three basic groups or classes: (i) low complexity at all scales; (ii) most complexity at shorter scales; and (iii) most complexity at longer scales. These classes are somewhat heterogeneously distributed throughout the continent. We also consider bays and peninsulas separately and characterise their multi-scale orientation. This unique dataset and its summary analysis have numerous applications for both geophysical and biological studies and will contribute to Antarctic research requiring quantitative information on, and related to, coastal complexity and configuration. All these data are referenced by https://doi.org/10.26179/5d1af0ba45c03 and are available free of charge at https://data.antarctica.gov.au.

scholarly journals Continent-wide estimates of Antarctic strain rates from Landsat 8-derived velocity grids

2018 ◽  
Vol 64 (244) ◽  
pp. 321-332 ◽  
Author(s):  
KAREN E. ALLEY ◽  
TED A. SCAMBOS ◽  
ROBERT S. ANDERSON ◽  
HARIHAR RAJARAM ◽  
ALLEN POPE ◽  
...  
Keyword(s):  
Strain Rate ◽  
Mass Balance ◽  
Landsat 8 ◽  
Length Scale ◽  
Strain Rates ◽  
Rheological Models ◽  
Ice Shelves ◽  
Antarctic Continent ◽  
Ice Velocity ◽  
The Antarctic

ABSTRACTStrain rates are fundamental measures of ice flow and are used in a wide variety of glaciological applications including investigations of bed properties, calculations of basal mass balance on ice shelves, and constraints on ice rheological models. However, despite their extensive application, strain rates are calculated using a variety of methods and length scales and the details are often not specified. In this study, we compare the results of nominal and logarithmic strain-rate calculations based on a satellite-derived velocity field of the Antarctic ice sheet generated from Landsat 8 satellite data. Our comparison highlights the differences between the two common approaches in the glaciological literature. We evaluate the errors introduced by each approach and their impacts on the results. We also demonstrate the importance of choosing and specifying a length scale over which strain-rate calculations are made, which can strongly influence other derived quantities such as basal mass balance on ice shelves. Finally, we present strain-rate data products calculated using an approximate viscous length-scale with satellite observations of ice velocity for the Antarctic continent.

Antarctica, one continent or two?

Polar Record ◽  
1961 ◽  
Vol 10 (67) ◽  
pp. 335-348 ◽  
Author(s):  
Edward Thiel
Keyword(s):  
Ice Shelves ◽  
Antarctic Continent ◽  
The Antarctic ◽  
Two Sides

In outline, the Antarctic continent crudely resembles a pear. It is indented on two sides by arms of the ocean, the Ross and Weddell Seas. These indentations are even greater than an outline map would suggest, for the seas extend far toward the interior of the continent beneath the world's two largest floating ice shelves, bearing the names of their respective discoverers, the English sea captain, Ross, and the German explorer, Filchner.

scholarly journals Finding Antarctica’s Pole of Inaccessibility

Polar Record ◽  
2021 ◽  
Vol 57 ◽  
Author(s):  
Gareth Rees ◽  
Laura Gerrish ◽  
Adrian Fox ◽  
Richard Barnes
Keyword(s):  
Rate Of Change ◽  
Scientific Committee ◽  
Similar Magnitude ◽  
Ice Shelves ◽  
British Antarctic Survey ◽  
Digital Database ◽  
Antarctic Continent ◽  
The Antarctic

Abstract Antarctica’s Pole of Inaccessibility (Southern Pole of Inaccessibility (SPI)) is the point on the Antarctic continent farthest from its edge. Existing literature exhibits disagreement over its location. Using two revisions of the Scientific Committee on Antarctic Research’s Antarctic Digital Database, we calculate modern-day positions for the SPI around 10 years apart, based on the position of the “outer” Antarctic coastline, i.e. its boundary with the ocean. These show that the position of the SPI in the year 2010 was around 83° 54’ S, 64° 53’ E, shifting on the order of 1 km per year as a result of changes of a similar magnitude in the Amery, Ronne-Filchner and Ross Ice Shelves. Excepting a position of the SPI calculated by British Antarctic Survey in 2005, to which it is very close, our newly calculated position differs by 150–900 km from others reported in the literature. We also consider the “inner” SPI, defined by the coastline with floating ice removed. The position of this SPI in 2010 is estimated as 83°37’ S, 53° 43’ E, differing significantly from other reported positions. Earlier cartographic data are probably not sufficiently accurate to allow its rate of change to be calculated meaningfully.

Taxonomic characterization and identification of Saccharomyces cerevisiae D8 for brandy production from pineapple

2018 ◽  
Vol 39 (4) ◽  
pp. 474-482
Author(s):  
Hoang Thi Le Thuong ◽  
Nguyen Quang Hao ◽  
Tran Thi Thuy
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Low Ph ◽  
Yeast Strains ◽  
Biological Studies ◽  
Taxonomic Characterization

Eight yeast strains (denoted as D1 to D8) were isolated from samples of natural fermented pineapple. Strain D8 showed highest alcoholic production at low pH and special aroma of pineapple has been chosen for further study. Taxonomic characterization of strain D8 using morphological, biochemical and molecular biological studies confirmed that strain D8  belong to Saccharomycetaceae family, Saccharomycetales order and Saccharomyces cerevisiae species. Therefore, we named this strain as Saccharomyces cerevisiae D8 for further study on Brandy production from pineapple. Citation: Hoang Thi Le Thuong, Nguyen Quang Hao, Tran Thi Thuy, 2017. Taxonomic characterization and identification of Saccharomyces cerevisiae D8 for brandy production from pineapple. Tap chi Sinh hoc, 39(4): 474- 482. DOI: 10.15625/0866-7160/v39n4.10864.*Corresponding author: [email protected] Received 5 December 2016, accepted 12 August 2017

Lichens of the Oasis Molodyozhnyi and adjacent areas (Enderby Land, Antarctic)

2013 ◽  
Vol 47 ◽  
pp. 167-178 ◽  
Author(s):  
M. P. Andreev
Keyword(s):  
Liquid Water ◽  
Climate Conditions ◽  
Water Ice ◽  
Buellia Frigida ◽  
Antarctic Continent ◽  
Harsh Climate ◽  
The Antarctic ◽  
First Time ◽  
Lichen Flora

Lichen flora and vegetation in the vicinity of the Russian base «Molodyozhnaya» (Enderby Land, Antarctica) were investigated in 2010–2011 in details for the first time. About 500 specimens were collected in 100 localities in all available ecotopes. The lichen flora is the richest in the region and numbers 39 species (21 genera, 11 families). The studied vegetation is very poor and sparse, but typical for coastal oases of the Antarctic continent. The poorness is caused by the extremely harsh climate conditions, insufficient availability of liquid water, ice-free land, and high insolation levels. The dominant and most common lichens are Rinodina olivaceobrunnea, Amandinea punctata, Candelariella flava, Physcia caesia, Caloplaca tominii, Lecanora expectans, Caloplaca ammiospila, Lecidea cancriformis, Pseudephebe minuscula, Lecidella siplei, Umbilicaria decussata, Buellia frigida, Lecanora fuscobrunnea, Usnea sphacelata, Lepraria and Buellia spp.

Characterization of Alpine Snowpacks Using a Low Complexity Portable MIMO Radar System

2020 ◽  
Author(s):  
Lekhmissi Harkati ◽  
Ray Abdo ◽  
Stephane Avrillon ◽  
Laurent Ferro-Famil ◽  
Isabelle Gouttevin ◽  
...  
Keyword(s):  
Low Complexity ◽  
Mimo Radar ◽  
Radar System

scholarly journals Accuracy Analysis of International Reference Ionosphere 2016 and NeQuick2 in the Antarctic

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1551
Author(s):  
Zihuai Guo ◽  
Yibin Yao ◽  
Jian Kong ◽  
Gang Chen ◽  
Chen Zhou ◽  
...  
Keyword(s):  
Solar Radiation ◽  
International Reference Ionosphere ◽  
Electron Content ◽  
Observation Data ◽  
Dual Frequency ◽  
Total Electron ◽  
International Reference ◽  
Antarctic Continent ◽  
The Antarctic ◽  
Frequency Observation

Global navigation satellite system (GNSS) can provide dual-frequency observation data, which can be used to effectively calculate total electron content (TEC). Numerical studies have utilized GNSS-derived TEC to evaluate the accuracy of ionospheric empirical models, such as the International Reference Ionosphere model (IRI) and the NeQuick model. However, most studies have evaluated vertical TEC rather than slant TEC (STEC), which resulted in the introduction of projection error. Furthermore, since there are few GNSS observation stations available in the Antarctic region and most are concentrated in the Antarctic continent edge, it is difficult to evaluate modeling accuracy within the entire Antarctic range. Considering these problems, in this study, GNSS STEC was calculated using dual-frequency observation data from stations that almost covered the Antarctic continent. By comparison with GNSS STEC, the accuracy of IRI-2016 and NeQuick2 at different latitudes and different solar radiation was evaluated during 2016–2017. The numerical results showed the following. (1) Both IRI-2016 and NeQuick2 underestimated the STEC. Since IRI-2016 utilizes new models to represent the F2-peak height (hmF2) directly, the IRI-2016 STEC is closer to GNSS STEC than NeQuick2. This conclusion was also confirmed by the Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC) occultation data. (2) The differences in STEC of the two models are both normally distributed, and the NeQuick2 STEC is systematically biased as solar radiation increases. (3) The root mean square error (RMSE) of the IRI-2016 STEC is smaller than that of the NeQuick2 model, and the RMSE of the two modeling STEC increases with solar radiation intensity. Since IRI-2016 relies on new hmF2 models, it is more stable than NeQuick2.

Dimethysulfide concentrations in the ocean close to the antarctic continent

1988 ◽  
Vol 6 (3-4) ◽  
pp. 179-184 ◽  
Author(s):  
John A.E. Gibson ◽  
Russell C. Garrick ◽  
Harry R. Burton ◽  
Andrew R. McTaggart
Keyword(s):  
Antarctic Continent ◽  
The Antarctic
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