East Antarctic sea ice: Albedo, thickness distribution, and snow cover

1993 ◽  
Vol 98 (C7) ◽  
pp. 12417 ◽  
Author(s):  
Ian Allison ◽  
Richard E. Brandt ◽  
Stephen G. Warren
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Thickness Distribution ◽  
Antarctic Sea Ice

scholarly journals East Antarctic sea ice: observations and modelling

1998 ◽  
Vol 27 ◽  
pp. 427-432 ◽  
Author(s):  
Anthony P. Worby ◽  
Xingren Wu
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Numerical Models ◽  
Global Climate ◽  
Thickness Distribution ◽  
Ice Thickness ◽  
Antarctic Sea Ice ◽  
Pack Ice ◽  
Concentration Sensitivity ◽  
Sensitivity Studies

The importance of monitoring sea ice for studies of global climate has been well noted for several decades. Observations have shown that sea ice exhibits large seasonal variability in extent, concentration and thickness. These changes have a significant impact on climate, and the potential nature of many of these connections has been revealed in studies with numerical models. An accurate representation of the sea-ice distribution (including ice extent, concentration and thickness) in climate models is therefore important for modelling global climate change. This work presents an overview of the observed sea-ice characteristics in the East Antarctic pack ice (60-150° E) and outlines possible improvements to the simulation of sea ice over this region by modifying the ice-thickness parameterisation in a coupled sea-ice-atmosphere model, using observational data of ice thickness and concentration. Sensitivity studies indicate that the simulation of East Antarctic sea ice can be improved by modifying both the “lead parameterisation” and “rafting scheme” to be ice-thickness dependent. The modelled results are currently out of phase with the observed data, and the addition of a multilevel ice-thickness distribution would improve the simulation significantly.

Estimating the thickness of ridged sea ice from ship observations in the Ross Sea

2003 ◽  
Vol 15 (1) ◽  
pp. 47-54 ◽  
Author(s):  
TINA TIN ◽  
MARTIN O. JEFFRIES ◽  
MIKKO LENSU ◽  
JUKKA TUHKURI
Keyword(s):  
Sea Ice ◽  
Ross Sea ◽  
Low Cost ◽  
Thickness Distribution ◽  
Ice Thickness ◽  
Equivalent Thickness ◽  
Sea Ice Thickness ◽  
Antarctic Sea Ice ◽  
Using Data ◽  
Original Formula

Ship-based observations of sea ice thickness using the Antarctic Sea Ice Processes and Climate (ASPeCt) protocol provide information on ice thickness distribution at relatively low cost. This protocol uses a simple formula to calculate the mass of ice in ridges based on surface observations. We present two new formulae and compare these with results from the “Original” formula using data obtained in the Ross Sea in autumn and winter. The new “r-star” formula uses a more realistic ratio of sail and keel areas to transform dimensions of sails to estimates of mean keel areas. As a result, estimates of “equivalent thickness” (i.e. mean thickness of ice in ridged areas) increased by over 200%. The new “Probability” formula goes one step further, by incorporating the probability that a sail is associated with a keel underwater, and the probability that keels may be found under level surfaces. This resulted in estimates of equivalent thickness comparable with the Original formula. Estimates of equivalent thickness at one or two degree latitude resolution are sufficiently accurate for validating sea ice models. Although ridges are small features in the Ross Sea, we have shown that they constitute a significant fraction of the total ice mass.

scholarly journals Winter snow cover variability on East Antarctic sea ice

1998 ◽  
Vol 103 (C11) ◽  
pp. 24837-24855 ◽  
Author(s):  
R. A. Massom ◽  
V. I. Lytle ◽  
A. P. Worby ◽  
I. Allison
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Antarctic Sea Ice ◽  
Winter Snow

scholarly journals Radiometrie measurements of sea-ice surface temperature in East Antarctica

1998 ◽  
Vol 27 ◽  
pp. 466-470
Author(s):  
Kelvin J. Michael ◽  
Clemente S. Hungria ◽  
R. A. Massom
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Snow Cover ◽  
Open Water ◽  
Thermal Infrared ◽  
Near Surface ◽  
Video Footage ◽  
Antarctic Sea Ice ◽  
Ice Surface ◽  
Ice Conditions

This paper presents surface temperature data collected over East Antarctic sea ice by two thermal infrared radiometers mounted on the RSV Aurora Australis in March-May 1993. Operating at wavelengths equivalent to those utilised by channels 4 and 5 of AVHRR and similar channels of ATSR, the radiometers provided high-reso-lution data on surface (skin) temperature along the ship track. Additional information on the sea-ice conditions was obtained from hourly observations made from The ship's bridge, video footage and direct measurements made at ice stations. Following calibration, time series of temperatures from each of the radiometers were compared wi th ice-surface and near-surface air temperatures. Observed changes in the surface temperature are related to different snow and ice conditions. For a given air temperature, the surface temperature depends upon the thickness of ice and its snow cover. While open water areas (leads) have temperatures near -2.0°C, thick ice is characterised by surface temperatures which approximate those of the air. Taken as a whole, the along-track profile of surface temperature provides a proxy estimate of The proportion of open water and thin ice with in the pack. The presence of a snow cover has a significant effect on the surface temperature. It is anticipated that the results will be of use in the validation of sea-ice models and satellite thermal infrared data.

scholarly journals Snow Depth and Air Temperature Seasonality on Sea Ice Derived From Snow Buoy Measurements

2021 ◽  
Vol 8 ◽  
Author(s):  
Marcel Nicolaus ◽  
Mario Hoppmann ◽  
Stefanie Arndt ◽  
Stefan Hendricks ◽  
Christian Katlein ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Air Temperature ◽  
Snow Depth ◽  
Snow Accumulation ◽  
Arctic Sea Ice ◽  
Weddell Sea ◽  
The Arctic ◽  
Validation Data ◽  
Antarctic Sea Ice

Snow depth on sea ice is an essential state variable of the polar climate system and yet one of the least known and most difficult to characterize parameters of the Arctic and Antarctic sea ice systems. Here, we present a new type of autonomous platform to measure snow depth, air temperature, and barometric pressure on drifting Arctic and Antarctic sea ice. “Snow Buoys” are designed to withstand the harshest environmental conditions and to deliver high and consistent data quality with minimal impact on the surface. Our current dataset consists of 79 time series (47 Arctic, 32 Antarctic) since 2013, many of which cover entire seasonal cycles and with individual observation periods of up to 3 years. In addition to a detailed introduction of the platform itself, we describe the processing of the publicly available (near real time) data and discuss limitations. First scientific results reveal characteristic regional differences in the annual cycle of snow depth: in the Weddell Sea, annual net snow accumulation ranged from 0.2 to 0.9 m (mean 0.34 m) with some regions accumulating snow in all months. On Arctic sea ice, the seasonal cycle was more pronounced, showing accumulation from synoptic events mostly between August and April and maxima in autumn. Strongest ablation was observed in June and July, and consistently the entire snow cover melted during summer. Arctic air temperature measurements revealed several above-freezing temperature events in winter that likely impacted snow stratigraphy and thus preconditioned the subsequent spring snow cover. The ongoing Snow Buoy program will be the basis of many future studies and is expected to significantly advance our understanding of snow on sea ice, also providing invaluable in situ validation data for numerical simulations and remote sensing techniques.

scholarly journals Physical and biological properties of early winter Antarctic sea ice in the Ross Sea

2020 ◽  
pp. 1-19
Author(s):  
Jean-Louis Tison ◽  
Ted Maksym ◽  
Alexander D. Fraser ◽  
Matthew Corkill ◽  
Noriaki Kimura ◽  
...  
Keyword(s):  
Sea Ice ◽  
Ross Sea ◽  
Thickness Distribution ◽  
Biological Properties ◽  
Weddell Sea ◽  
Algal Community ◽  
Early Winter ◽  
Ice Growth ◽  
Antarctic Sea Ice ◽  
Spatial Differences

Abstract This work presents the results of physical and biological investigations at 27 biogeochemical stations of early winter sea ice in the Ross Sea during the 2017 PIPERS cruise. Only two similar cruises occurred in the past, in 1995 and 1998. The year 2017 was a specific year, in that ice growth in the Central Ross Sea was considerably delayed, compared to previous years. These conditions resulted in lower ice thicknesses and Chl-a burdens, as compared to those observed during the previous cruises. It also resulted in a different structure of the sympagic algal community, unusually dominated by Phaeocystis rather than diatoms. Compared to autumn-winter sea ice in the Weddell Sea (AWECS cruise), the 2017 Ross Sea pack ice displayed similar thickness distribution, but much lower snow cover and therefore nearly no flooding conditions. It is shown that contrasted dynamics of autumnal-winter sea-ice growth between the Weddell Sea and the Ross Sea impacted the development of the sympagic community. Mean/median ice Chl-a concentrations were 3–5 times lower at PIPERS, and the community status there appeared to be more mature (decaying?), based on Phaeopigments/Chl-a ratios. These contrasts are discussed in the light of temporal and spatial differences between the two cruises.

scholarly journals Effects of the snow cover on Antarctic sea ice and potential modulation of its response to climate change

1995 ◽  
Vol 21 ◽  
pp. 369-376 ◽  
Author(s):  
Hajo Eicken ◽  
Holger Fischer ◽  
Peter Lemke
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Snow Cover ◽  
Field Data ◽  
Sea Water ◽  
Weddell Sea ◽  
Ice Formation ◽  
Average Thickness ◽  
One Dimensional ◽  
Antarctic Sea Ice

Based on presented field data, it is shown that snow contributes roughly 8% to the total mass of ice in the Weddell Sea. Snow depth averages 0.16 m on first-year ice (average thickness 0.75 m) and 0.53 m on second-year ice (average thickness 1.70 m). Due to snow loading, sea ice is depressed below water level and flooded by sea water. As a result of flooding, snow ice forms through congelation of sea water and brine in a matrix of meteoric ice (i.e. snow). Sea-ice growth has been simulated with a one-dimensional model, treating the evolution of salinity, porosity and thermal properties of the ice. Simulations demonstrate that in the presence of a snow cover, ice growth is significantly reduced. Brine volumes increase by a factor of 1.5–2, affecting properties such as ice strength. Snow-ice formation depends on the evolution of freeboard and ice permeability. Effects of accumulation-rate changes have been assessed, for the Weddell Sea with a large-scale sea-ice model accounting for snow-ice formation. Results for different scenarios are presented and compared with field data and one-dimensional simulations. The role of snow in modulating the response of Antarctic sea ice to climate change is discussed.

scholarly journals On the influence of model physics on simulations of Arctic and Antarctic sea ice

2011 ◽  
Vol 5 (3) ◽  
pp. 687-699 ◽  
Author(s):  
F. Massonnet ◽  
T. Fichefet ◽  
H. Goosse ◽  
M. Vancoppenolle ◽  
P. Mathiot ◽  
...  
Keyword(s):  
Sea Ice ◽  
Interannual Variability ◽  
Initial Conditions ◽  
Thickness Distribution ◽  
Arctic Sea Ice ◽  
Global Ocean ◽  
Small Scale ◽  
Ice Thickness ◽  
Model Skill ◽  
Antarctic Sea Ice

Abstract. Two hindcast (1983–2007) simulations are performed with the global, ocean-sea ice models NEMO-LIM2 and NEMO-LIM3 driven by atmospheric reanalyses and climatologies. The two simulations differ only in their sea ice component, while all other elements of experimental design (resolution, initial conditions, atmospheric forcing) are kept identical. The main differences in the sea ice models lie in the formulation of the subgrid-scale ice thickness distribution, of the thermodynamic processes, of the sea ice salinity and of the sea ice rheology. To assess the differences in model skill over the period of investigation, we develop a set of metrics for both hemispheres, comparing the main sea ice variables (concentration, thickness and drift) to available observations and focusing on both mean state and seasonal to interannual variability. Based upon these metrics, we discuss the physical processes potentially responsible for the differences in model skill. In particular, we suggest that (i) a detailed representation of the ice thickness distribution increases the seasonal to interannual variability of ice extent, with spectacular improvement for the simulation of the recent observed summer Arctic sea ice retreats, (ii) the elastic-viscous-plastic rheology enhances the response of ice to wind stress, compared to the classical viscous-plastic approach, (iii) the grid formulation and the air-sea ice drag coefficient affect the simulated ice export through Fram Strait and the ice accumulation along the Canadian Archipelago, and (iv) both models show less skill in the Southern Ocean, probably due to the low quality of the reanalyses in this region and to the absence of important small-scale oceanic processes at the models' resolution (~1°).

The thickness distribution of sea ice and snow cover during late winter in the Bellingshausen and Amundsen Seas, Antarctica

1996 ◽  
Vol 101 (C12) ◽  
pp. 28441-28455 ◽  
Author(s):  
A. P. Worby ◽  
M. O. Jeffries ◽  
W. F. Weeks ◽  
K. Morris ◽  
R. Jaña
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Thickness Distribution ◽  
Late Winter

scholarly journals On the influence of model physics on simulations of Arctic and Antarctic sea ice

2011 ◽  
Vol 5 (2) ◽  
pp. 1167-1200 ◽  
Author(s):  
F. Massonnet ◽  
T. Fichefet ◽  
H. Goosse ◽  
M. Vancoppenolle ◽  
P. Mathiot ◽  
...  
Keyword(s):  
Sea Ice ◽  
Interannual Variability ◽  
Initial Conditions ◽  
Thickness Distribution ◽  
Arctic Sea Ice ◽  
Global Ocean ◽  
Small Scale ◽  
Ice Thickness ◽  
Model Skill ◽  
Antarctic Sea Ice

Abstract. Two hindcast (1983–2007) simulations are performed with the global, ocean-sea ice models NEMO-LIM2 and NEMO-LIM3 driven by atmospheric reanalyses and climatologies. The two simulations differ only in their sea ice component, while all other elements of experimental design (resolution, initial conditions, atmospheric forcing) are kept identical. The main differences in the sea ice models lie in the formulation of the subgrid-scale ice thickness distribution, of the thermodynamic processes, of the sea ice salinity and of the sea ice rheology. To assess the differences in model skill over the period of investigation, we develop a set of metrics for both hemispheres, comparing the main sea ice variables (concentration, thickness and drift) to available observations and focusing on both mean state and seasonal to interannual variability. Based upon these metrics, we discuss the physical processes potentially responsible for the differences in model skill. In particular, we suggest that (i) a detailed representation of the ice thickness distribution increases the seasonal to interannual variability of ice extent, with spectacular improvement for the simulation of the recent observed summer Arctic sea ice retreats, (ii) the elastic-viscous-plastic rheology enhances the response of ice to wind stress, compared to the classical viscous-plastic approach, (iii) the grid formulation and the air-sea ice drag coefficient affect the simulated ice export through Fram Strait and the ice accumulation along the Canadian Archipelago, and (iv) both models show less skill in the Southern Ocean, probably due to the low quality of the reanalyses in this region and to the absence of important small-scale oceanic processes at the models' resolution (~1°).

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