Dependence of the Arctic Ocean ice thickness distribution on the poleward energy flux in the atmosphere

2002 ◽  
Vol 107 (C10) ◽  
Author(s):  
Göran Björk
Keyword(s):  
Arctic Ocean ◽  
Energy Flux ◽  
Thickness Distribution ◽  
The Arctic ◽  
Ice Thickness ◽  
The Arctic Ocean

scholarly journals Arctic Sea Ice Retreat in 2007 Follows Thinning Trend

2009 ◽  
Vol 22 (1) ◽  
pp. 165-176 ◽  
Author(s):  
R. W. Lindsay ◽  
J. Zhang ◽  
A. Schweiger ◽  
M. Steele ◽  
H. Stern
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Ocean Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Extent ◽  
Pacific Side ◽  
Arctic Sea ◽  
The Arctic Ocean

Abstract The minimum of Arctic sea ice extent in the summer of 2007 was unprecedented in the historical record. A coupled ice–ocean model is used to determine the state of the ice and ocean over the past 29 yr to investigate the causes of this ice extent minimum within a historical perspective. It is found that even though the 2007 ice extent was strongly anomalous, the loss in total ice mass was not. Rather, the 2007 ice mass loss is largely consistent with a steady decrease in ice thickness that began in 1987. Since then, the simulated mean September ice thickness within the Arctic Ocean has declined from 3.7 to 2.6 m at a rate of −0.57 m decade−1. Both the area coverage of thin ice at the beginning of the melt season and the total volume of ice lost in the summer have been steadily increasing. The combined impact of these two trends caused a large reduction in the September mean ice concentration in the Arctic Ocean. This created conditions during the summer of 2007 that allowed persistent winds to push the remaining ice from the Pacific side to the Atlantic side of the basin and more than usual into the Greenland Sea. This exposed large areas of open water, resulting in the record ice extent anomaly.

scholarly journals Simulation of Snow on Arctic Sea Ice Using a Coupled Snow–Ice Model

2010 ◽  
Vol 11 (1) ◽  
pp. 199-210 ◽  
Author(s):  
Yi-Ching Chung ◽  
Stéphane Bélair ◽  
Jocelyn Mailhot
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Snow Depth ◽  
Single Layer ◽  
Coupled System ◽  
The Arctic ◽  
Ice Thickness ◽  
The Arctic Ocean ◽  
Snow Model ◽  
Ice Model

Abstract The new Recherche Prévision Numérique (NEW-RPN) model, a coupled system including a multilayer snow thermal model (SNTHERM) and the sea ice model currently used in the Meteorological Service of Canada (MSC) operational forecasting system, was evaluated in a one-dimensional mode using meteorological observations from the Surface Heat Budget of the Arctic Ocean (SHEBA)’s Pittsburgh site in the Arctic Ocean collected during 1997/98. Two parameters simulated by NEW-RPN (i.e., snow depth and ice thickness) are compared with SHEBA’s observations and with simulations from RPN, MSC’s current coupled system (the same sea ice model and a single-layer snow model). Results show that NEW-RPN exhibits better agreement for the timing of snow depletion and for ice thickness. The profiles of snow thermal conductivity in NEW-RPN show considerable variability across the snow layers, but the mean value (0.39 W m−1 K−1) is within the range of reported observations for SHEBA. This value is larger than 0.31 W m−1 K−1, which is commonly used in single-layer snow models. Of particular interest in NEW-RPN’s simulation is the strong temperature stratification of the snowpack, which indicates that a multilayer snow model is needed in the SHEBA scenario. A sensitivity analysis indicates that snow compaction is also a crucial process for a realistic representation of the snowpack within the snow/sea ice system. NEW-RPN’s overestimation of snow depth may be related to other processes not included in the study, such as small-scale horizontal variability of snow depth and blowing snow processes.

scholarly journals Arctic sea-ice area and volume production:1996/97 versus 1997/98

2002 ◽  
Vol 34 ◽  
pp. 447-453 ◽  
Author(s):  
Ron Kwok
Keyword(s):  
Arctic Ocean ◽  
Large Scale ◽  
Heat Budget ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Thickness ◽  
The Arctic Ocean ◽  
Volume Production ◽  
Area And Volume

AbstractThe RADARSAT geophysical processor system (RGPS) produces measurements of ice motion and estimates of ice thickness using repeat synthetic aperture radar maps of the Arctic Ocean. From the RGPS products, we compute the net deformation and advection of the winter ice cover using the motion observations, and the seasonal ice area and volume production using the estimates of ice thickness. The results from the winters of 1996/97 and 1997/98 are compared. The second winter is of particular interest because it coincides with the Surface Heat Budget of the Arctic Ocean (SHEBA) field program. The character of the deformation of the ice cover from the two years is very different. Over a domain covering a large part of the western Arctic Ocean (~2.5 × 106 km2), the net divergence of that area during the 6 months of the first winter was 2.7% and for the second winter was 49.3%. In a subregion where the SHEBA camp was located, the net divergence was almost 38% compared to a net divergence of the same subregion of ~9% in 1996/97. The resulting deformation created a much larger volume of seasonal ice than in the earlier year. The net seasonal ice-volume production is 1.6 times (0.38 m vs 0.62 m) that of the first year. In addition to the larger divergence, this part of the ice cover advected a longer distance toward the Chukchi Sea over the same time-span. The total coverage of multi-year ice remained almost identical at ~2.08 × 106 km2, or 83% of the initial area of the domain. In this paper, we compare the behavior of the ice cover over the two winters and discuss these observations in the context of large-scale ice motion and atmospheric-pressure pattern.

Winter Arctic sea ice bottom evolution detected by thermistor string-based ice mass balance buoys (SIMBA)

2020 ◽  
Author(s):  
Bin Cheng ◽  
Timo Vihma ◽  
Zeling Liao ◽  
Ruibo Lei ◽  
Mario Hoppmann ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Mass Balance ◽  
Arctic Sea Ice ◽  
Heating Element ◽  
The Arctic ◽  
Ice Thickness ◽  
The Arctic Ocean ◽  
Ice Mass Balance ◽  
Snow And Ice

<p>A thermistor-string-based Snow and Ice Mass Balance Array (SIMBA) has been developed in recent years and used for monitoring snow and ice mass balance in the Arctic Ocean. SIMBA measures vertical environment temperature (ET) profiles through the air-snow-sea ice-ocean column using a thermistor string (5 m long, sensor spacing 2cm). Each thermistor sensor equipped with a small identical heating element. A small voltage was applied to the heating element so that the heat energy liberated in the vicinity of each sensor is the same. The heating time intervals lasted 60 s and 120 s, respectively. The heating temperatures (HT) after these two intervals were recorded. The ET was measured 4 times a day and once per day for the HT.</p><p>A total 15 SIMBA buoys have been deployed in the Arctic Ocean during the Chinese National Arctic Research Expedition (CHINARE) 2018 and the Nansen and Amundsen Basins Observational System (NABOS) 2018 field expeditions in late autumn. We applied a recently developed SIMBA algorithm to retrieve snow and ice thickness using SIMBA ET and HT temperature data. We focus particularly on sea ice bottom evolution during Arctic winter.</p><p>In mid-September 2018, 5 SIMBA buoys were deployed in the East Siberian Sea (NABOS2018) where snow was in practical zero cm and ice thickness ranged between 1.8 m – 2.6 m. By the end of May, those SIMBA buoys were drifted in the central Arctic where snow and ice thicknesses were around 0.05m - 0.2m and 2.6m – 3.2m, respectively. For those 10 SIMBA buoys deployed by the CHINARE2018 in the Chukchi Sea and Canadian Basin, the initial snow and ice thickness were ranged between 0.05m – 0.1cm and 1.5m – 2.5m, respectively.  By the end of May, those SIMBA buoys were drifted toward the north of Greenland where snow and ice thicknesses were around 0.2m - 0.3m and 2.0m – 3.5m, respectively. The ice bottom evolution derived by SIMBA algorithm agrees well with SIMBA HT identified ice-ocean interfaces. We also perform a preliminary investigation of sea ice bottom evolution measured by several SIMBA buoys deployed during the MOSAiC leg1 field campaign in winter 2019/2020.  </p>

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