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Seasonal sea ice – ice which freezes in late fall and melts completely the following summer – is a central feature in the ecology, geomorphology, and climatology of the Bering Sea. In this region's coastal zones, sea ice becomes locked into a stationary position against the coastlines to become landfast ice, which influences bioegophysical processes in the region, as well as exchanges of energy and matter among land, ocean, and atmosphere. It provides a platform for human mobility and subsistence activities, habitat for certain marine mammals, regulates terregenous nutrient cycling into ocean environments, and modulates the effect of erosive wind/wave action against coastlines. However, a thorough understanding of how this stationary ice, known as landfast ice, affects biogeophysical processes in the Bering Sea is limited by a lack of data on its areal coverage and seasonal duration. This dissertation establishes a baseline set of observations of landfast ice conditions in the Bering Sea through the creation and analysis of continuous spatial datasets. Chapter 1 focuses on the landfast ice annual cycle in the Eastern Bering Sea, which spans from the western tip of the Seward Peninsula to the southernmost point on the Yukon-Kuskokwim River Deltas. Chapter 1 results in the creation of landfast ice spatial data in these areas ranging from 1996 – 2008. Results show the spatial distribution and seasonal duration of landfast ice vary regionally within our study area, does not generally reach water depths associated with stabilization of the landfast ice cover in other regions of the Arctic, and is shortening in seasonal duration by approximately 9 days. Chapter 2 focuses on the landfast ice annual cycle on St. Lawrence Island, an Alaska Island located in the northern Bering Sea. Chapter 2 results in the creation of landfast ice spatial data in these areas ranging from 1996 – 2019. Results show the spatial distribution of landfast ice to vary regionally on the island, based on the coastlines orientation towards prevailing winds that transport pack ice through the Bering Strait. We also observed a sharp decline in landfast ice cover from 2017-2019, which coincides with record-breaking declines in sea ice coverage for the entire Bearing Sea. We also found coastal morphology and orientation have limited explanatory power when modeling landfast ice widths – the distance between the landfast ice edge and coastline – suggesting the consideration of meteorological variables is needed to improve models. Chapter 3 uses the landfast ice data from Chapter 2 to create an explanatory logistic regression model of landfast ice cover on St. Lawrence Island, using a combination of geographic and meteorological predictor variables. Using these variables, the model was able to predict the location of landfast ice cover with 80-90% accuracy, depending on the region of St. Lawrence Island. The model outputs resulted in very low commission error, with high omission error, which may be improved in future studies with the additional predictor variables. Cumulatively, this dissertation is the most comprehensive analysis of landfast ice cover to date on Alaskan Bering Sea coastlines. Research findings advance scholarly understandings of coastal ice conditions in the Bering Sea, and the geographic as wellas meteorological factors that enable their presence. / Doctor of Philosophy / Landfast sea ice – sea ice that becomes locked into a stationary position against the coastline – is a central feature in the ecology, geomorphology, and climatology of the Bering Sea. However, a thorough understanding of how this stationary ice, known as landfast ice, affects human/environmental processes (e.g. climate regulation, sediment mixing in marine environments, wildlife habitat/behavior, human transportation) in the Bering Sea is limited by a lack of data on its areal coverage and seasonal duration. This dissertation establishes a baseline set of observations of landfast ice conditions in the Bering Sea through the creation and analysis of continuous spatial datasets. Cumulatively, this dissertation is the most comprehensive analysis of landfast ice cover to date on Alaskan Bering Sea coastlines. First, this dissertation creates and analyzes the landfast ice annual cycle from 1996 – 2008 on the Eastern Bering Sea. Second, this dissertation creates a similar dataset from 1996 – 2019 on St. Lawrence Island, finding significant declines in landfast ice coverage that match broader sea ice trends in the northern Bering Sea. Third, this dissertation uses the landfast ice data on St. Lawerence Island to create a model explaining outcomes in the location of landfast ice cover under certain geographic and meteorological conditions.

A sea ice model developed by W. D. Hibler (1979) was applied to the Lancaster Sound/Barrow Strait channel in an effort to simulate the observed ice environment. The simulation covered a ten month period, from October 1985 until August 1986. The impact of atmospheric and oceanographic forcing on the development of characteristic ice features that develop seasonally within the channel was examined. The importance of the ice interaction component of the model when simulating a restricted channel ice environment was also examined. The model was able to simulate regional scale processes and conditions within the channel. Small scale localised processes and conditions which control the spatial variability and complexity of the ice regime were not accurately reproduced. Simulation results provided insights into the effect and importance of both the model and geophysical variables examined. The study highlighted concerns that need be addressed in future modelling work in the Lancaster Sound/Barrow Strait channel.

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This dissertation presents new methods for detecting dynamic and thermodynamic characteristics of Arctic sea ice using radar remote sensing. A new technique for sea ice motion detection from sequential satellite synthetic aperture radar (SAR) images was developed and thoroughly validated. The accuracy of the system is 0.43 km obtained from a comparison between SAR-derived ice motion vectors and in-situ sea ice beacon trajectories. For the first time, we evaluated ice motion tracking results derived from co-polarization (HH) and cross-polarization (HV) channels of RADARSAT-2 ScanSAR imagery and formulated a condition where the HV channel is more reliable than the HH channel for ice motion tracking. Sea ice motion is substantially controlled by surface winds. Two new models for ocean surface wind speed retrieval from C-band SAR data have been developed and validated based on a large body of statistics on buoy observations collocated and coincided with RADARSAT-1 and -2 ScanSAR images. The proposed models without wind direction input demonstrated a better accuracy than conventionally used algorithms. As a combination of the developed methods we designed a wind speed-ice motion product which can be a useful tool for studying sea ice dynamics processes in the marginal ice zone. To effectively asses the thermodynamic properties of sea ice advanced tools for modeling electromagnetic (EM) wave scattering from rough natural surfaces are required. In this dissertation we present a new analytical formulation for EM wave scattering from rough boundaries interfacing inhomogeneous media based on the first-order approximation of the small perturbation method. Available solutions in the literature represent special cases of our general solution. The developed scattering theory was applied to experimental data collected at three stations (with different snow thicknesses) in the Beaufort Sea from the research icebreaker Amundsen during the Circumpolar Flaw Lead system study. Good agreement between the model and experimental data were observed for all three case studies. Both model and experimental radar backscatter coefficients were considerably higher for thin snow cover (4 cm) compared to the thick snow cover case (16 cm). Our findings suggest that, winter snow thickness retrieval may be possible from radar observations under particular scattering conditions.