Late Winter First-Year Ice Floe Thickness Variability, Seawater Flooding and Snow Ice Formation in the Amundsen and Ross Seas

Jeffries, Martin O.; Li, S.; Jaña, Ricardo; Krouse, H. R.; Hurst-Cushing, Barbara

doi:10.1029/ar074p0069

Cited by 23 publications

(22 citation statements)

References 25 publications

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“…Surface flooding and subsequent snow ice formation are estimated to affect large parts of the Antarctic ice pack [Wadhams et al, 1987;Sturm and Massom, 2017], and snow ice is considered to contribute a significant proportion to the total Antarctic sea ice volume [Jeffries et al, 1998;Maksym and Markus, 2008]. The flooding water may originate from sea ice brines, if the ice is permeable [Golden et al, 1998;Jutras et al, 2016], or can be seawater moving laterally from ice floe edges and cracks [Massom et al, 2001].…”

Section: 1002/2017gl074346mentioning

confidence: 99%

Antarctic pack ice algal distribution: Floe‐scale spatial variability and predictability from physical parameters

Meiners

Arndt

Bestley

et al. 2017

Geophysical Research Letters

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Antarctic pack ice serves as habitat for microalgae which contribute to Southern Ocean primary production and serve as important food source for pelagic herbivores. Ice algal biomass is highly patchy and remains severely undersampled by classical methods such as spatially restricted ice coring surveys. Here we provide an unprecedented view of ice algal biomass distribution, mapped (as chlorophyll a) in a 100 m by 100 m area of a Weddell Sea pack ice floe, using under‐ice irradiance measurements taken with an instrumented remotely operated vehicle. We identified significant correlations (p < 0.001) between algal biomass and concomitant in situ surface measurements of snow depth, ice thickness, and estimated sea ice freeboard levels using a statistical model. The model's explanatory power (r2 = 0.30) indicates that these parameters alone may provide a first basis for spatial prediction of ice algal biomass, but parameterization of additional determinants is needed to inform more robust upscaling efforts.

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Section: 1002/2017gl074346mentioning

confidence: 99%

Antarctic pack ice algal distribution: Floe‐scale spatial variability and predictability from physical parameters

Meiners

Arndt

Bestley

et al. 2017

Geophysical Research Letters

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“…Techniques used include visual observations (ASPeCt protocol; Worby et al, 2008a), drilling transects (e.g., Jeffries et al, 1998), and electromagnetic sounding from the surface, ships, or helicopters (e.g., Haas, 1998) (Laxon et al, 2003) and the ICESat laser altimeter (Kwok et al, 2009). In the Antarctic, however, the thick snow cover shields the ice below from direct measurement (Giles et al, 2008;Zwally et al, 2008;Yi et al, 2011), requiring independent information on snow thickness (and density) to determine ice thickness.…”

Section: Modulating the Response To Changementioning

confidence: 99%

Antarctic Sea Ice—A Polar Opposite?

Maksym¹,

Stammerjohn²,

Ackley³

et al. 2012

oceanog

106

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“…Snow has a higher albedo and a lower thermal conductivity than sea ice, with marked effects on the internal energy balance. In winter, the snow cover can limit the thermodynamic growth of the ice [e.g., Maykut and Untersteiner, 1971;Ledley, 1993;Powell et al, 2005], especially in the Antarctic where deep snow accumulations and high ocean heat flux can lead to basal melting [e.g., Jeffries et al, 1998;Lewis et al, 2011]. In the Artic, the spatial distribution of snow has been shown to influence the evolution of melt ponds [Petrich et al, 2012;Polashenski et al, 2012], which in consequence affects the surface albedo [Perovich et al, 1998.…”

Section: Introductionmentioning

confidence: 99%

“…In the Artic, the spatial distribution of snow has been shown to influence the evolution of melt ponds [Petrich et al, 2012;Polashenski et al, 2012], which in consequence affects the surface albedo [Perovich et al, 1998. Similarly, snow accumulation can lead to isostatic adjustment allowing flooding of sea ice surfaces with ocean water, which enhances the formation of snow ice [e.g., Eicken et al, 1995;Jeffries et al, 1998;Maksym and Markus, 2008].events are often accompanied by strong winds, and direct measurement of snowfall amounts and separation of snowfall as opposed to blowing snow have proven to be difficult. At larger scales, estimation of snowfall amounts on sea ice have been inferred from atmospheric reanalysis products [e.g., Bromwich et al, 1995;Maksym and Markus, 2008], which have not been directly validated over sea ice.…”

Section: Introductionmentioning

confidence: 99%

Changes in snow distribution and surface topography following a snowstorm on Antarctic sea ice

et al. 2016

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Snow distribution over sea ice is an important control on sea ice physical and biological processes. We combine measurements of the atmospheric boundary layer and blowing snow on an Antarctic sea ice floe with terrestrial laser scanning to characterize a typical storm and its influence on the spatial patterns of snow distribution at resolutions of 1–10 cm over an area of 100 m × 100 m. The pre‐storm surface exhibits multidirectional elongated snow dunes formed behind aerodynamic obstacles. Newly deposited dunes are elongated parallel to the predominant wind direction during the storm. Snow erosion and deposition occur over 62% and 38% of the area, respectively. Snow deposition volume is more than twice that of erosion (351 m3 versus 158 m3), resulting in a modest increase of 2 ± 1 cm in mean snow depth, indicating a small net mass gain despite large mass relocation. Despite significant local snow depth changes due to deposition and erosion, the statistical distributions of elevation and the two‐dimensional correlation functions remain similar to those of the pre‐storm surface. Pre‐storm and post‐storm surfaces also exhibit spectral power law relationships with little change in spectral exponents. These observations suggest that for sea ice floes with mature snow cover features under conditions similar to those observed in this study, spatial statistics and scaling properties of snow surface morphology may be relatively invariant. Such an observation, if confirmed for other ice types and conditions, may be a useful tool for model parameterizations of the subgrid variability of sea ice surfaces.

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Late Winter First-Year Ice Floe Thickness Variability, Seawater Flooding and Snow Ice Formation in the Amundsen and Ross Seas

Cited by 23 publications

References 25 publications

Antarctic pack ice algal distribution: Floe‐scale spatial variability and predictability from physical parameters

Antarctic pack ice algal distribution: Floe‐scale spatial variability and predictability from physical parameters

Antarctic Sea Ice—A Polar Opposite?

Changes in snow distribution and surface topography following a snowstorm on Antarctic sea ice

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