Calculation of Arrival Intensity of Ridges Accounting for the Relative Angle Between Ridge Direction and Ice Drift Direction

2009 ◽  
Author(s):  
Jenny Trumars ◽  
Sveinung Lo̸set
Keyword(s):  
Arrival Rate ◽  
Relative Angle ◽  
Design Load ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
Design Loads ◽  
A Site ◽  
Drift Direction ◽  
Load Conditions ◽  
Arrival Intensity

The purpose of the study is to investigate the effect of the relative angle between ice ridges and sea ice drift directions on the arrival rate of ridges. The arrival rate is of importance both for estimating the load conditions at a site and for possible ice management connected to the operation. If the number of encounters increases, the probability of encounter of an extreme ice feature and load increases. A Monte Carlo simulation has been made to calculate the ridge arrival intensity for input formulated as distributions. In probabilistic calculations of design loads today the average arrival intensity is used and the ridge directions are assumed to be uniformly distributed. The implications of accounting for the varying arrival intensity due to the distribution of the relative direction of ridges to velocity on the design load are discussed.

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.

scholarly journals Improving Multiyear Sea Ice Concentration Estimates with Sea Ice Drift

2016 ◽  
Vol 8 (5) ◽  
pp. 397 ◽  
Author(s):  
Yufang Ye ◽  
Mohammed Shokr ◽  
Georg Heygster ◽  
Gunnar Spreen
Keyword(s):  
Sea Ice ◽  
Sea Ice Concentration ◽  
Ice Drift ◽  
Ice Concentration ◽  
Sea Ice Drift

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 Operational SAR-based sea ice drift monitoring over the Baltic Sea

Ocean Science ◽  
2012 ◽  
Vol 8 (4) ◽  
pp. 473-483 ◽  
Author(s):  
J. Karvonen
Keyword(s):  
Sea Ice ◽  
Baltic Sea ◽  
Vector Fields ◽  
Phase Correlation ◽  
The Baltic Sea ◽  
Sar Images ◽  
Envisat Asar ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
The Baltic

Abstract. An algorithm for computing ice drift from pairs of synthetic aperture radar (SAR) images covering a common area has been developed at FMI. The algorithm has been developed based on the C-band SAR data over the Baltic Sea. It is based on phase correlation in two scales (coarse and fine) with some additional constraints. The algorithm has been running operationally in the Baltic Sea from the beginning of 2011, using Radarsat-1 ScanSAR wide mode and Envisat ASAR wide swath mode data. The resulting ice drift fields are publicly available as part of the MyOcean EC project. The SAR-based ice drift vectors have been compared to the drift vectors from drifter buoys in the Baltic Sea during the first operational season, and also these validation results are shown in this paper. Also some navigationally useful sea ice quantities, which can be derived from ice drift vector fields, are presented.

Arctic Offshore Loading Downtime Due to Variability in Ice Drift Direction

2005 ◽  
Vol 59 (1) ◽  
pp. 9-26
Author(s):  
Basile Bonnemaire
Keyword(s):  
Risk Analysis ◽  
Ice Drift ◽  
Ice Conditions ◽  
Qualitative Risk Analysis ◽  
Drift Direction

Four arctic offshore loading concepts are selected, loading from the corner of a platform, loading in the wake of a loading tower, Submerged Turret Loading (STL) and Single Anchor Loading (SAL). The influence of variations in the ice drift direction on the performance of these concepts is discussed and critical drift events are determined. Ice drift measurements from eight ARGOS/GPS buoys deployed in the Pechora Sea in winters 1995 and 1998 are analysed to estimate downtime rates of these loading systems due to ice drift heading changes. Depending on the location in the Pechora Sea and the chosen concept, downtime rates range from 6 to 72%. A discussion on how these rates will vary with different assumptions, different ice conditions or different ice management is given. Finally the loading concepts are compared through a qualitative risk analysis.

scholarly journals Method to characterize directional changes in Arctic sea ice drift and associated deformation due to synoptic atmospheric variations using Lagrangian dispersion statistics

2017 ◽  
Vol 11 (4) ◽  
pp. 1707-1731 ◽  
Author(s):  
Jennifer V. Lukovich ◽  
Cathleen A. Geiger ◽  
David G. Barber
Keyword(s):  
Sea Ice ◽  
Single Particle ◽  
Weather Forecasting ◽  
Particle Dispersion ◽  
Arctic Sea Ice ◽  
Maximum Pressure ◽  
Dynamical Regime ◽  
Scaling Exponent ◽  
Ice Drift ◽  
Sea Ice Drift

Abstract. A framework is developed to assess the directional changes in sea ice drift paths and associated deformation processes in response to atmospheric forcing. The framework is based on Lagrangian statistical analyses leveraging particle dispersion theory which tells us whether ice drift is in a subdiffusive, diffusive, ballistic, or superdiffusive dynamical regime using single-particle (absolute) dispersion statistics. In terms of sea ice deformation, the framework uses two- and three-particle dispersion to characterize along- and across-shear transport as well as differential kinematic parameters. The approach is tested with GPS beacons deployed in triplets on sea ice in the southern Beaufort Sea at varying distances from the coastline in fall of 2009 with eight individual events characterized. One transition in particular follows the sea level pressure (SLP) high on 8 October in 2009 while the sea ice drift was in a superdiffusive dynamic regime. In this case, the dispersion scaling exponent (which is a slope between single-particle absolute dispersion of sea ice drift and elapsed time) changed from superdiffusive (α ∼ 3) to ballistic (α ∼ 2) as the SLP was rounding its maximum pressure value. Following this shift between regimes, there was a loss in synchronicity between sea ice drift and atmospheric motion patterns. While this is only one case study, the outcomes suggest similar studies be conducted on more buoy arrays to test momentum transfer linkages between storms and sea ice responses as a function of dispersion regime states using scaling exponents. The tools and framework developed in this study provide a unique characterization technique to evaluate these states with respect to sea ice processes in general. Application of these techniques can aid ice hazard assessments and weather forecasting in support of marine transportation and indigenous use of near-shore Arctic areas.

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