The aim of this study is to characterise the structure of refrozen cracks, and to deduce the details of their formation. Surveys and experiments are conducted on straight-sided, linear, refrozen cracks of width 80 mm to 340 mm in land-fast first-year sea ice in McMurdo Sound, Antarctica. Refreezing of cracks is simulated analytically, and with a numerical fluid dynamics model of brine movement in the porous sea ice and in the ocean. Systematic arch-shaped patterns of inclusions, upstream-growing crystals, and two-dimensional variations in salinity are identified in completely and partially refrozen, natural cracks, and in artificial cracks. Using a two-dimensional thermistor array, a relationship between the development of the sea ice structure and the temperature records is found, which identifies the transition from the porous, skeletal layer to consolidated ice in artificial cracks. A two-dimensional analytical model is developed that predicts the measured thickness of consolidated ice in refreezing cracks for this study and for the studies of others. From a heat balance within the refreezing cracks, it is concluded that some of the experiments were conducted in the presence of a negative ocean heat flux. A two-dimensional thermistor array beneath the ice-water interface of a refreezing crack provides evidence for sporadic, cold temperature, advective events at night. A two-dimensional, numerical fluid dynamics model based on the finite volume method is developed to simulate desalination and fluid flow in refreezing cracks. This requires a permeability-porosity relationship for sea ice, which is deduced from data of other groups, combined with the numerical model. To make comparisons among data sets, an analytical approximation is derived for the relationship between connected pore space and total pore space of a random porous medium, based on a Monte Carlo model that is adapted to the crystal structure of sea ice. The permeability-porosity relationship derived in this study is in good agreement with permeability functions published recently. The refreezing of cracks simulated with the numerical fluid dynamics model is consistent with experiments and with the analytical model. In addition, the numerical model simulates the high porosity, arch-shaped freezing front and inclusion structure. Supercooling of the liquid is found to cause excessive heat loss in the simulation. Since a large oceanic heat flux was not observed in the experimental heat balance of refreezing slots, it is suggested that this indicates platelet ice formation or frazil ice formation at the vertical crack interface in Antarctic experiments.

A marginal ice zone (MIZ) is characterised by distinct ice floes and its direct exposure to the open ocean. Sea ice is typically described as a continuous material but this description can be inappropriate in an MIZ due to the granular nature of the ice cover and the scale of processes acting on the ice floes. In this thesis, the kinematic behaviour of sea ice in an MIZ modelled as a granular material is investigated with an emphasis on the influence of ocean waves. The kinematic behaviour of a set of ice floes subject to ocean wave forcing was recorded in an experiment conducted in the Ross Sea. Kinematic data were recorded from each ice floe using a GPS receiver, tri-axial accelerometer, and compass. The data show (1) the influence of wave forcing and (2) collisions between neighbouring ice floes. It was also discovered that the GPS receivers were able to resolve the effects of ocean wave forcing despite their poor absolute accuracy. The number density and normalised structure factor (NSF) are introduced to describe the spatial structure of a set of ice floes. Four idealised distributions (in 1D and 2D) are analysed to gain insight into the way that different factors determine the shape of the NSF. It is shown that (1) a significant sinusoidal deviation causes a peak in the NSF, (2) ordered structure dominates low spatial frequencies, and (3) disorder dominates high spatial frequencies. A comparison of the contributions from these different factors is used to estimate the significance of a sinusoidal deviation in the positions of the ice floes. A granular model of an MIZ is developed using a novel set of equations of motion to examine the effect of ocean wave forcing. The equations of motion are derived for small ice floes and allows forcing by multiple waves. These equations predict a transient, wave-induced torque, which can be sustained by the application of a second force to the ice floe. Torque induced by the interaction of two forces on an ice floe may be a general feature of sea ice motion. The number density and NSF are used to analyse the distribution of ice floes in the granular model. At low solids-fractions the number density is correlated at the frequency of the wave forcing. As the solids-fraction is increased this correlation is destroyed by collisions between the ice floes and new correlations are created that are related to the packing structure of the ice floes. When the number density is weighted by the velocity of the ice floes, the correlations between floes are related to the convolution of the wave velocity field and the number density. These correlations may be incorporated into the thickness distribution of large-scale models using the maximum entropy method. The granular model was also examined as a percolating network of contacts and it was found that percolation was more likely to occur along the crest of a wave than in the direction of propagation.

Spaceborne Synthetic Aperture Radar (SAR) is commonly considered a powerful sensor to detect sea ice. Unfortunately, the sea-ice types in SAR images are difficult to be interpreted due to speckle noise. SAR image denoising therefore becomes a critical step of SAR sea-ice image processing and analysis. In this study, a two-phase approach is designed and implemented for SAR sea-ice image segmentation. In the first phase, a Gamma-based bilateral filter is introduced and applied for SAR image denoising in the local domain. It not only perfectly inherits the conventional bilateral filter with the capacity of smoothing SAR sea-ice imagery while preserving edges, but also enhances it based on the homogeneity in local areas and Gamma distribution of speckle noise. The Gamma-based bilateral filter outperforms other widely used filters, such as Frost filter and the conventional bilateral filter. In the second phase, the K-means clustering algorithm, whose initial centroids are optimized, is adopted in order to obtain better segmentation results. The proposed approach is tested using both simulated and real SAR images, compared with several existing algorithms including K-means, K-means based on the Frost filtered images, and K-means based on the conventional bilateral filtered images. The F1 scores of the simulated results demonstrate the effectiveness and robustness of the proposed approach whose overall accuracies maintain higher than 90% as variances of noise range from 0.1 to 0.5. For the real SAR images, the proposed approach outperforms others with average overall accuracy of 95%.

Spatial intensity variation introduced by illumination changes is a challenging problem for image segmentation and classification. Many techniques have been proposed which focus on removing this illumination variation by estimating or modelling it. There is limited research on developing an illumination invariant classification technique which does not use any preprocessing. A major focus of this research is on automatically classifying synthetic aperture radar (SAR) images. These are large satellite images which pose many challenges for image classification including the incidence angle effect which is a strong illumination variation across the image. Mapping of full scene satellite images of sea-ice is important for navigational purposes for ships and also for climate research. The images obtained from the RADARSAT-2 satellite are dual band, high quality images. Currently, sea ice chart are produced manually by ice analysts at the Canadian Ice Service. However, this process can be automated to reduce processing time and obtain more detailed pixel-level ice maps. An automated classification algorithm to achieve sea ice and open water separation will greatly help the ice analyst by providing sufficient guidance in the initial stages of creating an ice map. It would also help the analyst to improve the accuracy while finding ice concentrations and remove subjective bias. The existing Iterative Region Growing by Semantics (IRGS) algorithm is not effective for full scene segmentation because of the incidence angle effect. This research proposes a "glocal" (global as well as local) approach to solve this problem. The image is divided in a rectangular grid and each rectangle is segmented using IRGS. This is viewed as an over-segmentation of the original image. Finally, IRGS is used globally to glue together the over-segmented regions. This method yields acceptable results with the denoised images. The proposed technique can also be used for general image classification purposes. Extensive testing was done to investigate the best set of parameters for the proposed approach. Images were simulated with the SAR illumination variation and multiplicative speckle noise. The technique was effective for general classification and attained accurate results for full scene SAR segmentation.

This dissertation discusses a linkage between the Southern Ocean (SO) winds and the global ocean circulation in the framework of a coarse-resolution global ocean general circulation model coupled to a sea-ice model. In addition to reexamination of the conventional linkage that begins with northward Ekman transport and extends to the North Atlantic (NA) overturning, the author investigates a new linkage that begins with the Southern Hemisphere (SH) sea-ice – ocean interaction perturbed by the anomalous SO winds and extends to the SH overturning, the response of the NA overturning, and the long-term baroclinic adjustment of the Antarctic Circumpolar Current (ACC). How the above two linkages will interact with each other in a warming world is also investigated. An interactive momentum flux forcing, allowing for the strength of momentum flux between atmosphere and sea ice to vary in response to the simulated sea-ice conditions, enhances wind-driven ice divergence to increase the fraction of leads and polynyas, which increases dense water formation, and thus intensifies convection. Within three experimental frameworks, this increased dense water consistently increases the Antarctic Bottom Water formation, which directly intensifies the SH overturning and indirectly weakens the NA overturning. As a result of the hemispheric change in overturning circulations, the meridional density gradient across the ACC appears to increase, ultimately increasing the baroclinic part of the ACC via an enhanced thermal wind shear. Subsequently, impacts of the poleward shifted and intensified SH subpolar westerly winds (SWWs) on the global ocean circulation are investigated in phases. When the SWWs are only shifted poleward, the effect of the anomalous winds is transmitted to the northern NA, decreasing both the NA overturning and the North Atlantic Deep Water (NADW) outflow. However, when the SWWs are shifted poleward and intensified, this effect is cut off by the intensified Deacon cell overturning, and is not transmitted to the northern NA, and instead increases the NADW outflow substantially. To sum up, with respect to the SO winds perturbed by the global warming, the SH overturning cell and the NADW outflow increase, leading to an increase in the volume transport of the ACC.

Thesis (M.Eng.)--Memorial University of Newfoundland, 2002. / Bibliography: leaves 105-114.

Thesis (M.Eng.)--Memorial University of Newfoundland, 2002. / Bibliography: leaves 95-100.

Microwave scattering from sea ice ridges is poorly understood. This thesis aims to improve the current knowledge on in situ C-band microwave scattering from first-year sea ice (FYI) pressure ridges during winter, and how C-band backscatter can vary with changes to radar and target parameters. Remotely sensed data of ridged ice were collected at a sea ice mesocosm using a LiDAR laser scanner and a fully-polarimetric C-band scatterometer. Thesis results indicate that using an incidence angle between 30 and 50° and HV polarization will best enable distinguishing between smooth and ridged ice, while using an incidence angle of 40° and HV or HH polarization will best enable detecting variations in ridge height. Overall results indicate that a significant proportion of the variance in FYI snow-free ridge C-band backscatter can be explained by incidence angle, polarization, and ridge height, with almost 88% of the variability in backscatter attributed to ridge height.

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