Field Data for Sea Ice and Iceberg Drift Offshore Newfoundland and Labrador

2015 ◽  
Author(s):  
Rocky Taylor ◽  
Ian Turnbull ◽  
Aaron Slaney
Keyword(s):  
Sea Ice ◽  
Newfoundland And Labrador ◽  
Field Data ◽  
Iceberg Drift

Sea Ice, Seals, and Settlement

2019 ◽  
pp. 16-43
Author(s):  
Christopher B. Wolff ◽  
Donald H. Holly ◽  
Victor D. Thompson
Keyword(s):  
Sea Ice ◽  
Cultural History ◽  
Newfoundland And Labrador ◽  
Atlantic Cod ◽  
Social Conditions ◽  
Marine Ecology ◽  
Subarctic Region ◽  
Hunter Gatherers ◽  
Subsistence Economies ◽  
History Of

The cultural history of Newfoundland and Labrador is linked with the sea. The European occupation of this subarctic region was dependent on the abundance of Atlantic cod and other marine resources, such as seals, walrus, and whales. Precontact indigenous hunter gatherers of the region also relied heavily on marine ecology for their livelihood; yet, at various times in the region’s significant history, dynamic environmental and social conditions acted to change subsistence economies, cultures, and the course of its occupation. In this chapter, we examine archaeological, historical, and paleoecological evidence to assess the relative roles that environmental and social processes played in these critical transformations.

Parameterization of an Iceberg Drift Model in the Barents Sea

2009 ◽  
Vol 26 (10) ◽  
pp. 2216-2227 ◽  
Author(s):  
Intissar Keghouche ◽  
Laurent Bertino ◽  
Knut Arild Lisæter
Keyword(s):  
Sea Ice ◽  
Barents Sea ◽  
Reanalysis Data ◽  
Ocean Model ◽  
Form Drag ◽  
Drag Coefficients ◽  
Drag Forces ◽  
Drift Model ◽  
The Barents Sea ◽  
Iceberg Drift

Abstract The problem of parameter estimation is examined for an iceberg drift model of the Barents Sea. The model is forced by atmospheric reanalysis data from ECMWF and ocean and sea ice variables from the Hybrid Coordinate Ocean Model (HYCOM). The model is compared with four observed iceberg trajectories from April to July 1990. The first part of the study focuses on the forces that have the strongest impact on the iceberg trajectories, namely, the oceanic, atmospheric, and Coriolis forces. The oceanic and atmospheric form drag coefficients are optimized for three different iceberg geometries. As the iceberg mass increases, the optimal form drag coefficients increase linearly. A simple balance between the drag forces and the Coriolis force explains this behavior. The ratio between the oceanic and atmospheric form drag coefficients is similar in all experiments, although there are large uncertainties on the iceberg geometries. Two iceberg trajectory simulations have precisions better than 20 km during two months of drift. The trajectory error for the two other simulations is less than 25 km during the first month of drift but increases rapidly to over 70 km afterward. The second part of the study focuses on the sea ice parameterization. The sea ice conditions east of Svalbard in winter 1990 were too mild to exhibit any sensitivity to the sea ice parameters.

scholarly journals Direct helicopter EM — Sea-ice thickness inversion assessed with synthetic and field data

Geophysics ◽  
2007 ◽  
Vol 72 (4) ◽  
pp. F127-F137 ◽  
Author(s):  
Andreas Pfaffling ◽  
Christian Haas ◽  
James E. Reid
Keyword(s):  
Sea Ice ◽  
Field Data ◽  
Flying Height ◽  
Small Scale ◽  
Ice Thickness ◽  
Systematic Bias ◽  
Sea Ice Thickness ◽  
Instrumental Noise ◽  
Precision And Accuracy ◽  
Better Than

Accuracy and precision of helicopter electromagnetic (HEM) sounding are the essential parameters for HEM sea-ice thickness profiling. For sea-ice thickness research, the quality of HEM ice thickness estimates must be better than [Formula: see text] to detect potential climatologic thickness changes. We introduce and assess a direct, 1D HEM data inversion algorithm for estimating sea-ice thickness. For synthetic quality assessment, an analytically determined HEM sea-ice thickness sensitivity is used to derive precision and accuracy. Precision is related directly to random, instrumental noise, although accuracy is defined by systematic bias arising from the data processing algorithm. For the in-phase component of the HEM response, sensitivity increases with frequency and coil spacing, but decreases with flying height. For small-scale HEM instruments used in sea-ice thickness surveys, instrumental noise must not exceed [Formula: see text] to reach ice thickness precision of [Formula: see text] at 15-m nominal flying height. Comparable precision is yielded at 30-m height for conventional exploration HEM systems with bigger coil spacings. Accuracy losses caused by approximations made for the direct inversion are negligible for brackish water and remain better than [Formula: see text] for saline water. Synthetic precision and accuracy estimates are verified with drill-hole validated field data from East Antarctica, where HEM-derived level-ice thickness agrees with drilling results to within 4%, or [Formula: see text].

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 The RADARSAT Constellation Mission Core Applications: First Results

2022 ◽  
Vol 14 (2) ◽  
pp. 301
Author(s):  
Mohammed Dabboor ◽  
Ian Olthof ◽  
Masoud Mahdianpari ◽  
Fariba Mohammadimanesh ◽  
Mohammed Shokr ◽  
...  
Keyword(s):  
Sea Ice ◽  
Newfoundland And Labrador ◽  
Visual Analysis ◽  
Flood Mapping ◽  
Wetland Classification ◽  
First Results ◽  
Dual Polarized ◽  
Sar Imagery ◽  
Operation Phase

The Canadian RADARSAT Constellation Mission (RCM) has passed its early operation phase with the performance evaluation being currently active. This evaluation aims to confirm that the innovative design of the mission’s synthetic aperture radar (SAR) meets the expectations of intended users. In this study, we provide an overview of initial results obtained for three high-priority applications; flood mapping, sea ice analysis, and wetland classification. In our study, the focus is on results obtained using not only linear polarization, but also the adopted Compact Polarimetric (CP) architecture in RCM. Our study shows a promising level of agreement between RCM and RADARSAT-2 performance in flood mapping using dual-polarized HH-HV SAR data over Red River, Manitoba, suggesting smooth continuity between the two satellite missions for operational flood mapping. Visual analysis of coincident RCM CP and RADARSAT-2 dual-polarized HH-HV SAR imagery over the Resolute Passage, Canadian Central Arctic, highlighted an improved contrast between sea ice classes in dry ice winter conditions. A statistical analysis using selected sea ice samples confirmed the increased contrast between thin and both rough and deformed ice in CP SAR. This finding is expected to enhance Canadian Ice Service’s (CIS) operational visual analysis of sea ice in RCM SAR imagery for ice chart production. Object-oriented classification of a wetland area in Newfoundland and Labrador by fusion of RCM dual-polarized VV-VH data and Sentinel-2 optical imagery revealed promising classification results, with an overall accuracy of 91.1% and a kappa coefficient of 0.87. Marsh presented the highest user’s and producer’s accuracies (87.77% and 82.08%, respectively) compared to fog, fen, and swamp.

scholarly journals Modeling giant-iceberg drift under the influence of sea ice in the Weddell Sea, Antarctica

2001 ◽  
Vol 47 (158) ◽  
pp. 452-460 ◽  
Author(s):  
Christoph Lichey ◽  
Hartmut H. Hellmer
Keyword(s):  
Sea Ice ◽  
Driving Forces ◽  
Weddell Sea ◽  
Coastal Current ◽  
Ice Shelf ◽  
Significant Discrepancy ◽  
Sea Ice Concentration ◽  
Iceberg Drift ◽  
Lock In ◽  
Ice Force

AbstractThe drift trajectory of giant iceberg C-7 traversing the Weddell Sea, Antarctica, for > 2 years was successfully simulated. Application of the “classical” driving forces like wind and ocean currents resulted in a significant discrepancy between modeled and observed iceberg velocities in the western Weddell Sea. The most realistic drift pattern in space and time was achieved by adding a sea-ice force which represents the ability of a dense sea-ice cover (≥90%) to lock in icebergs and collect the momentum of the wind over an area much larger than the area of the iceberg proper. This process was parameterized using a sea-ice strength P which depends on sea-ice concentration and thickness, both having highest values in winter and in the western Weddell Sea which is covered with multi-year sea ice. As a consequence of the sensitivity to sea ice, the timing of the iceberg drift becomes important, revealing the region off Brunt Ice Shelf (eastern Weddell Sea) as a location where bergs either continue westward with the coastal current or follow a southern branch onto the shallow continental shelf.

Modeling Iceberg Drift in the Barents Sea from Field Data

2018 ◽  
Vol 43 (5) ◽  
pp. 313-322 ◽  
Author(s):  
N. A. Diansky ◽  
A. V. Marchenko ◽  
I. I. Panasenkova ◽  
V. V. Fomin
Keyword(s):  
Field Data ◽  
Barents Sea ◽  
The Barents Sea ◽  
Iceberg Drift

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.

Sign in / Sign up

Export Citation Format

Share Document