Contributions of growth and deformation to monthly variability in sea ice thickness north of the coasts of Greenland and the Canadian Arctic Archipelago

2016 ◽  
Vol 43 (15) ◽  
pp. 8097-8105 ◽  
Author(s):  
R. Kwok ◽  
G. F. Cunningham
Keyword(s):  
Sea Ice ◽  
Canadian Arctic ◽  
Ice Thickness ◽  
Canadian Arctic Archipelago ◽  
Sea Ice Thickness

scholarly journals Thermodynamic and Dynamic Ice Thickness Changes in the Canadian Arctic Archipelago in NEMO-LIM2 Numerical Simulations

2017 ◽  
Author(s):  
Xianmin Hu ◽  
Jingfan Sun ◽  
Ting On Chan ◽  
Paul G. Myers
Keyword(s):  
Spatial Distribution ◽  
Sea Ice ◽  
Numerical Simulations ◽  
Canadian Arctic ◽  
Horizontal Resolution ◽  
Ice Thickness ◽  
Canadian Arctic Archipelago ◽  
The West ◽  
Sea Ice Thickness ◽  
Frame Work

Abstract. Sea ice thickness evolution within the Canadian Arctic Archipelago (CAA) is of great interest. In this study, based on the NEMO numerical frame work including the LIM2 sea ice module, simulations at both 1/4° and 1/12° horizontal resolution were conducted from 2002 to 2016. The model captures well the general spatial distribution of ice thickness in the CAA region, with very thick sea ice (∼&rthinsp;4 m and thicker) in the northern CAA, thick sea ice (2.5 m to 3 m) in the west-central Parry Channel and M'Clintock Channel, and thin (

scholarly journals Thermodynamic and dynamic ice thickness contributions in the Canadian Arctic Archipelago in NEMO-LIM2 numerical simulations

2018 ◽  
Vol 12 (4) ◽  
pp. 1233-1247 ◽  
Author(s):  
Xianmin Hu ◽  
Jingfan Sun ◽  
Ting On Chan ◽  
Paul G. Myers
Keyword(s):  
Sea Ice ◽  
Canadian Arctic ◽  
Horizontal Resolution ◽  
Scale Model ◽  
Ice Thickness ◽  
Canadian Arctic Archipelago ◽  
High Concentration ◽  
Baffin Bay ◽  
Ice Growth ◽  
Ice Volume

Abstract. Sea ice thickness evolution within the Canadian Arctic Archipelago (CAA) is of great interest to science, as well as local communities and their economy. In this study, based on the NEMO numerical framework including the LIM2 sea ice module, simulations at both 1∕4 and 1/12∘ horizontal resolution were conducted from 2002 to 2016. The model captures well the general spatial distribution of ice thickness in the CAA region, with very thick sea ice (∼ 4 m and thicker) in the northern CAA, thick sea ice (2.5 to 3 m) in the west-central Parry Channel and M'Clintock Channel, and thin (<2 m) ice (in winter months) on the east side of CAA (e.g., eastern Parry Channel, Baffin Island coast) and in the channels in southern areas. Even though the configurations still have resolution limitations in resolving the exact observation sites, simulated ice thickness compares reasonably (seasonal cycle and amplitudes) with weekly Environment and Climate Change Canada (ECCC) New Ice Thickness Program data at first-year landfast ice sites except at the northern sites with high concentration of old ice. At 1∕4 to 1/12∘ scale, model resolution does not play a significant role in the sea ice simulation except to improve local dynamics because of better coastline representation. Sea ice growth is decomposed into thermodynamic and dynamic (including all non-thermodynamic processes in the model) contributions to study the ice thickness evolution. Relatively smaller thermodynamic contribution to ice growth between December and the following April is found in the thick and very thick ice regions, with larger contributions in the thin ice-covered region. No significant trend in winter maximum ice volume is found in the northern CAA and Baffin Bay while a decline (r2 ≈ 0.6, p < 0.01) is simulated in Parry Channel region. The two main contributors (thermodynamic growth and lateral transport) have high interannual variabilities which largely balance each other, so that maximum ice volume can vary interannually by ±12 % in the northern CAA, ±15 % in Parry Channel, and ±9 % in Baffin Bay. Further quantitative evaluation is required.

scholarly journals Sea ice thickness in the Eastern Canadian Arctic: Hudson Bay Complex & Baffin Bay

2017 ◽  
Vol 200 ◽  
pp. 281-294 ◽  
Author(s):  
Jack C. Landy ◽  
Jens K. Ehn ◽  
David G. Babb ◽  
Nathalie Thériault ◽  
David G. Barber
Keyword(s):  
Sea Ice ◽  
Canadian Arctic ◽  
Ice Thickness ◽  
Hudson Bay ◽  
Sea Ice Thickness ◽  
Baffin Bay ◽  
Eastern Canadian Arctic

scholarly journals Assimilating Copernicus SST Data into a Pan-Arctic Ice–Ocean Coupled Model with a Local SEIK Filter

2017 ◽  
Vol 34 (9) ◽  
pp. 1985-1999 ◽  
Author(s):  
Xi Liang ◽  
Qinghua Yang ◽  
Lars Nerger ◽  
Svetlana N. Losa ◽  
Biao Zhao ◽  
...  
Keyword(s):  
Sea Ice ◽  
Canadian Arctic ◽  
Coupled Model ◽  
Arctic Basin ◽  
Beaufort Sea ◽  
Canadian Arctic Archipelago ◽  
Negative Effects ◽  
Sea Ice Concentration ◽  
Sea Ice Thickness ◽  
Arctic Ice

AbstractSea surface temperature (SST) data from the Copernicus Marine Environment Monitoring Service are assimilated into a pan-Arctic ice–ocean coupled model using the ensemble-based local singular evolutive interpolated Kalman (LSEIK) filter. This study found that the SST deviation between model hindcasts and independent SST observations is reduced by the assimilation. Compared with model results without data assimilation, the deviation between the model hindcasts and independent SST observations has decreased by up to 0.2°C at the end of summer. The strongest SST improvements are located in the Greenland Sea, the Beaufort Sea, and the Canadian Arctic Archipelago. The SST assimilation also changes the sea ice concentration (SIC). Improvements of the ice concentrations are found in the Canadian Arctic Archipelago, the Beaufort Sea, and the central Arctic basin, while negative effects occur in the west area of the eastern Siberian Sea and the Laptev Sea. Also, sea ice thickness (SIT) benefits from ensemble SST assimilation. A comparison with upward-looking sonar observations reveals that hindcasts of SIT are improved in the Beaufort Sea by assimilating reliable SST observations into light ice areas. This study illustrates the advantages of assimilating SST observations into an ice–ocean coupled model system and suggests that SST assimilation can improve SIT hindcasts regionally during the melting season.

In-situ automatic observations of ice thickness of seas

2012 ◽  
Vol 19 (3) ◽  
pp. 583-592 ◽  
Author(s):  
Yinke Dou ◽  
Xiaomin Chang
Keyword(s):  
Sea Ice ◽  
New Technologies ◽  
Capacitive Sensor ◽  
Automatic Monitoring ◽  
Ice Thickness ◽  
In Situ Observation ◽  
Glacier Surface ◽  
Sea Ice Thickness ◽  
Surface Ice

Abstract Ice thickness is one of the most critical physical indicators in the ice science and engineering. It is therefore very necessary to develop in-situ automatic observation technologies of ice thickness. This paper proposes the principle of three new technologies of in-situ automatic observations of sea ice thickness and provides the findings of laboratory applications. The results show that the in-situ observation accuracy of the monitor apparatus based on the Magnetostrictive Delay Line (MDL) principle can reach ±2 mm, which has solved the “bottleneck” problem of restricting the fine development of a sea ice thermodynamic model, and the resistance accuracy of monitor apparatus with temperature gradient can reach the centimeter level and research the ice and snow substance balance by automatically measuring the glacier surface ice and snow change. The measurement accuracy of the capacitive sensor for ice thickness can also reach ±4 mm and the capacitive sensor is of the potential for automatic monitoring the water level under the ice and the ice formation and development process in water. Such three new technologies can meet different needs of fixed-point ice thickness observation and realize the simultaneous measurement in order to accurately judge the ice thickness.

Assimilation of SMOS sea ice thickness in the regional ice prediction system

2021 ◽  
Vol 42 (12) ◽  
pp. 4583-4606
Author(s):  
Mukesh Gupta ◽  
Alain Caya ◽  
Mark Buehner
Keyword(s):  
Sea Ice ◽  
Ice Thickness ◽  
Prediction System ◽  
Sea Ice Thickness

scholarly journals Antarctic sea-ice thickness and volume estimates from ice charts between 1995 and 1998

2015 ◽  
Vol 56 (69) ◽  
pp. 383-393 ◽  
Author(s):  
E. Rachel Bernstein ◽  
Cathleen A. Geiger ◽  
Tracy L. Deliberty ◽  
Mary D. Lemcke-Stampone
Keyword(s):  
Sea Ice ◽  
Regional Scale ◽  
Weighted Average ◽  
Ice Thickness ◽  
Average Thickness ◽  
Sea Ice Thickness ◽  
Subjective Analysis ◽  
Stage Of Development ◽  
Volume Estimates ◽  
The Impact

AbstractThis work evaluates two distinct calculations of central tendency for sea-ice thickness and quantifies the impact such calculations have on ice volume for the Southern Ocean. The first calculation, area-weighted average thickness, is computed from polygonal ice features and then upscaled to regions. The second calculation, integrated thickness, is a measure of the central value of thickness categories tracked across different scales and subsequently summed to chosen regions. Both methods yield the same result from one scale to the next, but subsequent scales develop diverging solutions when distributions are strongly non-Gaussian. Data for this evaluation are sea-ice stage-of-development records from US National Ice Center ice charts from 1995 to 1998, as proxy records of ice thickness. Results show regionally integrated thickness exceeds area-weighted average thickness by as much as 60% in summer with as few as five bins in thickness distribution. Year-round, the difference between the two calculations yields volume differences consistently >10%. The largest discrepancies arise due to bimodal distributions which are common in ice charts based on current subjective-analysis protocols. We recommend that integrated distribution be used for regional-scale sea-ice thickness and volume estimates from ice charts and encourage similar testing of other large-scale thickness data archives.

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