Patterns of sea ice drift and polar bear (Ursus maritimus) movement in Hudson Bay

2020 ◽  
Vol 641 ◽  
pp. 227-240
Author(s):  
NJ Klappstein ◽  
RR Togunov ◽  
JR Reimer ◽  
NJ Lunn ◽  
AE Derocher
Keyword(s):  
Energy Expenditure ◽  
Sea Ice ◽  
Body Condition ◽  
Polar Bear ◽  
Ursus Maritimus ◽  
The Arctic ◽  
Hudson Bay ◽  
Drift Speed ◽  
Ice Drift ◽  
Sea Ice Drift

Sea ice habitats are highly dynamic, and ice drift may affect the energy expenditure of travelling animals. Several studies in the high Arctic have reported increased ice drift speeds, and consequently, polar bears Ursus maritimus in these areas expended more energy on counter-ice movement for station-keeping. However, little is known about the spatiotemporal dynamics of ice drift in Hudson Bay (HB) and its implications for the declining Western Hudson Bay (WH) polar bear subpopulation. Using sea ice drift data from 1987-2015 and polar bear satellite telemetry location data from 2004-2015, we examined trends in drift speeds in HB, polar bear movement relative to drift, and assessed annual and individual variation. In contrast to other areas of the Arctic, we did not find an increase in ice drift speed over the period examined. However, variability in ice drift speed increased over time, which suggests reduced habitat predictability. Polar bear movement direction was not strongly counter to ice drift in any month, and ice drift speed and direction had little effect on bear movement rates and, thus, energy expenditure. On an annual scale, we found individuals varied in their exposure and response to ice drift, which may contribute to variability in body condition. However, the lack of a long-term increase in ice drift speed suggests this is unlikely to be the main factor affecting the body condition decline observed in the WH subpopulation. Our results contrast findings in other subpopulations and demonstrate the need for subpopulation-specific research and risk evaluation.

scholarly journals Arctic sea ice drift-strength feedback modelled by NEMO-LIM3.6

2017 ◽  
Author(s):  
David Docquier ◽  
François Massonnet ◽  
Neil F. Tandon ◽  
Olivier Lecomte ◽  
Thierry Fichefet
Keyword(s):  
Sea Ice ◽  
Positive Feedback ◽  
Seasonal Cycle ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Drift Speed ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
Ice Strength

Abstract. Sea ice cover and thickness have substantially decreased in the Arctic Ocean since the beginning of the satellite era. As a result, sea ice strength has been reduced, allowing more deformation and fracturing and leading to increased sea ice drift speed. The resulting increased sea ice export is thought to further lower sea ice concentration and thickness. We use the global ocean-sea ice NEMO-LIM3.6 model (Nucleus for European Modelling of the Ocean coupled to the Louvain-la-Neuve sea Ice Model), satellite and buoy observations, as well as reanalysis data over the period from 1979 to 2013 to study this positive feedback for the first time in such detail. Overall, the model agrees well with observations in terms of sea ice extent, concentration and thickness. Although the seasonal cycle of sea ice drift speed is reasonably well reproduced by the model, the recent positive trend in drift speed is weaker than observations in summer. NEMO-LIM3.6 is able to capture the relationships between sea ice drift speed, concentration and thickness in terms of seasonal cycle, with higher drift speed for both lower concentration and lower thickness, in agreement with observations. Sensitivity experiments are carried out by varying the initial ice strength and show that higher values of ice strength lead to lower sea ice thickness. We demonstrate that higher ice strength results in a more uniform sea ice thickness distribution, leading to lower heat conduction fluxes, which provide lower ice production, and thus lower ice thickness. This shows that the positive feedback between sea ice drift speed and strength is more than just dynamic, more complex than originally thought and that other processes are at play. The methodology proposed in this analysis provides a benchmark for a further model intercomparison related to the interactions between sea ice drift speed and strength.

scholarly journals Relationships between Arctic sea ice drift and strength modelled by NEMO-LIM3.6

2017 ◽  
Vol 11 (6) ◽  
pp. 2829-2846 ◽  
Author(s):  
David Docquier ◽  
François Massonnet ◽  
Antoine Barthélemy ◽  
Neil F. Tandon ◽  
Olivier Lecomte ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Global Ocean ◽  
Model Intercomparison ◽  
Drift Speed ◽  
Ice Drift ◽  
Arctic Sea ◽  
Sea Ice Drift ◽  
Ice Strength

Abstract. Sea ice cover and thickness have substantially decreased in the Arctic Ocean since the beginning of the satellite era. As a result, sea ice strength has been reduced, allowing more deformation and fracturing and leading to increased sea ice drift speed. We use the version 3.6 of the global ocean–sea ice NEMO-LIM model (Nucleus for European Modelling of the Ocean coupled to the Louvain-la-Neuve sea Ice Model), satellite, buoy and submarine observations, as well as reanalysis data over the period from 1979 to 2013 to study these relationships. Overall, the model agrees well with observations in terms of sea ice extent, concentration and thickness. The seasonal cycle of sea ice drift speed is reasonably well reproduced by the model. NEMO-LIM3.6 is able to capture the relationships between the seasonal cycles of sea ice drift speed, concentration and thickness, with higher drift speed for both lower concentration and lower thickness, in agreement with observations. Model experiments are carried out to test the sensitivity of Arctic sea ice drift speed, thickness and concentration to changes in sea ice strength parameter P*. These show that higher values of P* generally lead to lower sea ice deformation and lower sea ice thickness, and that no single value of P* is the best option for reproducing the observed drift speed and thickness. The methodology proposed in this analysis provides a benchmark for a further model intercomparison related to the relationships between sea ice drift speed and strength, which is especially relevant in the context of the upcoming Coupled Model Intercomparison Project 6 (CMIP6).

scholarly journals Trends in body condition in polar bears (Ursus maritimus) from the Southern Hudson Bay subpopulation in relation to changes in sea ice

2016 ◽  
Vol 2 (1) ◽  
pp. 15-32 ◽  
Author(s):  
M.E. Obbard ◽  
M.R.L. Cattet ◽  
E.J. Howe ◽  
K.R. Middel ◽  
E.J. Newton ◽  
...  
Keyword(s):  
Sea Ice ◽  
Body Condition ◽  
Survival Rates ◽  
Ursus Maritimus ◽  
Social Classes ◽  
The Arctic ◽  
Hudson Bay ◽  
Polar Bears ◽  
Western Hudson Bay ◽  
Break Up

Sea ice is declining over much of the Arctic. In Hudson Bay the ice melts completely each summer, and advances in break-up have resulted in longer ice-free seasons. Consequently, earlier break-up is implicated in declines in body condition, survival, and abundance of polar bears (Ursus maritimus Phipps, 1774) in the Western Hudson Bay (WH) subpopulation. We hypothesised that similar patterns would be evident in the neighbouring Southern Hudson Bay (SH) subpopulation. We examined trends 1980–2012 in break-up and freeze-up dates within the entire SH management unit and within smaller coastal break-up and freeze-up zones. We examined trends in body condition for 900 bears captured during 1984–1986, 2000–2005, and 2007–2009 and hypothesised that body condition would be correlated with duration of sea ice. The ice-free season in SH increased by about 30 days from 1980 to 2012. Body condition declined in all age and sex classes, but the decline was less for cubs than for other social classes. If trends towards a longer ice-free season continue in the future, further declines in body condition and survival rates are likely, and ultimately declines in abundance will occur in the SH subpopulation.

scholarly journals Opportunistic evaluation of modelled sea ice drift using passively drifting telemetry collars in Hudson Bay, Canada

2020 ◽  
Author(s):  
Ron R. Togunov ◽  
Natasha J. Klappstein ◽  
Andrew E. Derocher ◽  
Nicholas J. Lunn ◽  
Marie Auger-Méthé
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
The Arctic ◽  
Hudson Bay ◽  
Gps Telemetry ◽  
In Situ Data ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
Drift Direction

Abstract. Sea ice drift plays a central role in the Arctic climate and ecology through its effects on the ice cover, thermodynamics, and energetics of northern marine ecosystems. Due to the challenges of accessing the Arctic, remote sensing has been used to obtain large-scale longitudinal data. These data are often associated with errors and biases that must be considered when incorporated into research. However, obtaining reference data for validation is often prohibitively expensive or practically unfeasible. We used the motion of 20 passively drifting high-accuracy GPS telemetry collars originally deployed on polar bears, Ursus maritimus, in western Hudson Bay, Canada to validate a widely used sea ice drift dataset produced by the National Snow and Ice Data Centre (NSIDC). Our results showed that the NSIDC model tended to underestimate the horizontal and vertical (i.e. u and v) components of drift. Consequently, the NSIDC model underestimated magnitude of drift, particularly at high ice speeds. Modelled drift direction was unbiased, however was less precise at lower drift speeds. Research using these drift data should consider integrating these biases into their analyses, particularly where absolute ground speed or direction is necessary. Further investigation is required into the sources of error, particularly in under-examined areas without in situ data.

scholarly journals Opportunistic evaluation of modelled sea ice drift using passively drifting telemetry collars in Hudson Bay, Canada

2020 ◽  
Vol 14 (6) ◽  
pp. 1937-1950
Author(s):  
Ron R. Togunov ◽  
Natasha J. Klappstein ◽  
Nicholas J. Lunn ◽  
Andrew E. Derocher ◽  
Marie Auger-Méthé
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
The Arctic ◽  
Hudson Bay ◽  
Gps Telemetry ◽  
In Situ Data ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
Drift Direction

Abstract. Sea ice drift plays a central role in the Arctic climate and ecology through its effects on the ice cover, thermodynamics, and energetics of northern marine ecosystems. Due to the challenges of accessing the Arctic, remote sensing has been used to obtain large-scale longitudinal data. These data are often associated with errors and biases that must be considered when incorporated into research. However, obtaining reference data for validation is often prohibitively expensive or practically unfeasible. We used the motion of 20 passively drifting high-accuracy GPS telemetry collars originally deployed on polar bears, Ursus maritimus, in western Hudson Bay, Canada, to validate a widely used sea ice drift dataset produced by the National Snow and Ice Data Center (NSIDC). Our results showed that the NSIDC model tended to underestimate the horizontal and vertical (i.e., u and v) components of drift. Consequently, the NSIDC model underestimated magnitude of drift, particularly at high ice speeds. Modelled drift direction was unbiased; however, it was less precise at lower drift speeds. Research using these drift data should consider integrating these biases into their analyses, particularly where absolute ground speed or direction is necessary. Further investigation is required into the sources of error, particularly in under-examined areas without in situ data.

Oceanic eddy signature on SAR-derived sea ice drift and vorticity

2021 ◽  
Author(s):  
Angelina Cassianides ◽  
Camillie Lique ◽  
Anton Korosov
Keyword(s):  
Sea Ice ◽  
Surface Current ◽  
Satellite Observation ◽  
The Arctic ◽  
Global Ocean ◽  
Sar Images ◽  
Surface Ocean ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
Oceanic Eddy

<p>In the global ocean, mesoscale eddies are routinely observed from satellite observation. In the Arctic Ocean, however, their observation is impeded by the presence of sea ice, although there is a growing recognition that eddy may be important for the evolution of the sea ice cover. In this talk, we will present a new method of surface ocean eddy detection based on their signature in sea ice vorticity retrieved from Synthetic Aperture Radar (SAR) images. A combination of Feature Tracking and Pattern Matching algorithm is used to compute the sea ice drift from pairs of SAR images. We will mostly focus on the case of one eddy in October 2017 in the marginal ice zone of the Canadian Basin, which was sampled by mooring observations, allowing a detailed description of its characteristics. Although the eddy could not be identified by visual inspection of the SAR images, its signature is revealed as a dipole anomaly in sea ice vorticity, which suggests that the eddy is a dipole composed of a cyclone and an anticyclone, with a horizontal scale of 80-100 km and persisted over a week. We will also discuss the relative contributions of the wind and the surface current to the sea ice vorticity. We anticipate that the robustness of our method will allow us to detect more eddies as more SAR observations become available in the future.</p>

scholarly journals Sea ice drift in the Southern Ocean: Regional patterns, variability, and trends

Elem Sci Anth ◽  
2017 ◽  
Vol 5 ◽  
Author(s):  
Ron Kwok ◽  
Shirley S. Pang ◽  
Sahra Kacimi
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Sea Level ◽  
Ice Cover ◽  
The Arctic ◽  
Positive Trend ◽  
Amundsen Sea ◽  
Regional Patterns ◽  
Ice Drift ◽  
Sea Ice Drift

Understanding long-term changes in large-scale sea ice drift in the Southern Ocean is of considerable interest given its contribution to ice extent, to ice production in open waters, with associated dense water formation and heat flux to the atmosphere, and thus to the climate system. In this paper, we examine the trends and variability of this ice drift in a 34-year record (1982–2015) derived from satellite observations. Uncertainties in drift (~3 to 4 km day–1) were assessed with higher resolution observations. In a linear model, drift speeds were ~1.4% of the geostrophic wind from reanalyzed sea-level pressure, nearly 50% higher than that of the Arctic. This result suggests an ice cover in the Southern Ocean that is thinner, weaker, and less compact. Geostrophic winds explained all but ~40% of the variance in ice drift. Three spatially distinct drift patterns were shown to be controlled by the location and depth of atmospheric lows centered over the Amundsen, Riiser-Larsen, and Davis seas. Positively correlated changes in sea-level pressures at the three centers (up to 0.64) suggest correlated changes in the wind-driven drift patterns. Seasonal trends in ice edge are linked to trends in meridional winds and also to on-ice/off-ice trends in zonal winds, due to zonal asymmetry of the Antarctic ice cover. Sea ice area export at flux gates that parallel the 1000-m isobath were extended to cover the 34-year record. Interannual variability in ice export in the Ross and Weddell seas linked to the depth and location of the Amundsen Sea and Riiser-Larsen Sea lows to their east. Compared to shorter records, where there was a significant positive trend in Ross Sea ice area flux, the longer 34-year trends of outflow from both seas are now statistically insignificant.

scholarly journals neXtSIM: a new Lagrangian sea ice model

2016 ◽  
Vol 10 (3) ◽  
pp. 1055-1073 ◽  
Author(s):  
Pierre Rampal ◽  
Sylvain Bouillon ◽  
Einar Ólason ◽  
Mathieu Morlighem
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Dynamical Response ◽  
Ice Dynamics ◽  
Ice Drift ◽  
Wide Range ◽  
Arctic Sea ◽  
Sea Ice Drift ◽  
Ice Model

Abstract. The Arctic sea ice cover has changed drastically over the last decades. Associated with these changes is a shift in dynamical regime seen by an increase of extreme fracturing events and an acceleration of sea ice drift. The highly non-linear dynamical response of sea ice to external forcing makes modelling these changes and the future evolution of Arctic sea ice a challenge for current models. It is, however, increasingly important that this challenge be better met, both because of the important role of sea ice in the climate system and because of the steady increase of industrial operations in the Arctic. In this paper we present a new dynamical/thermodynamical sea ice model called neXtSIM that is designed to address this challenge. neXtSIM is a continuous and fully Lagrangian model, whose momentum equation is discretised with the finite-element method. In this model, sea ice physics are driven by the combination of two core components: a model for sea ice dynamics built on a mechanical framework using an elasto-brittle rheology, and a model for sea ice thermodynamics providing damage healing for the mechanical framework. The evaluation of the model performance for the Arctic is presented for the period September 2007 to October 2008 and shows that observed multi-scale statistical properties of sea ice drift and deformation are well captured as well as the seasonal cycles of ice volume, area, and extent. These results show that neXtSIM is an appropriate tool for simulating sea ice over a wide range of spatial and temporal scales.

scholarly journals Modeling M2 tidal variability in Arctic Sea-ice drift and deformation

2006 ◽  
Vol 44 ◽  
pp. 418-428 ◽  
Author(s):  
W.D. Hibler ◽  
A. Roberts ◽  
P. Heil ◽  
A.Y. Proshutinsky ◽  
H.L. Simmons ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Basin ◽  
Ocean Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ocean Coupling ◽  
Ice Drift ◽  
Arctic Sea ◽  
Sea Ice Drift ◽  
Tidal Variability

AbstractSemi-diurnal oscillations are a ubiquitous feature of polar Sea-ice motion. Over much of the Arctic basin, inertial and Semi-diurnal tidal variability have Similar frequencies So that periodicity alone is inadequate to determine the Source of oscillations. We investigate the relative roles of tidal and inertial variability in Arctic Sea ice using a barotropic ice–ocean model with Sea ice embedded in an upper boundary layer. Results from this model are compared with ‘levitated’ ice–ocean coupling used in many models. In levitated models the mechanical buoyancy effect of Sea ice is neglected So that convergence of ice, for example, does not affect the oceanic Ekman flux. We use rotary Spectral analysis to compare Simulated and observed results. This helps to interpret the rotation Sense of Sea-ice drift and deformation at the Semi-diurnal period and is a useful discriminator between tidal and inertial effects. Results indicate that the levitated model generates an artificial inertial resonance in the presence of tidal and wind forcing, contrary to the embedded Sea-ice model. We conclude that Sea-ice mechanics can cause the rotational response of ice motion to change Sign even in the presence of Strong and opposing local tidal forcing when a physically consistent dynamic ice–ocean coupling is employed.

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