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Accumulation of dynamic and thermodynamic forces in the Arctic are decreasing the extent of thin annual sea ice which polar bear rely on for survival. It is imperative that we identify the preferred habitat of polar bears to fully understand their future requirements. In this thesis, surveys of polar bear tracks and the surrounding sea ice variables, at various scales, were recorded. Sea ice roughness was measured through surveys of the sample area in situ, with an electromagnetic induction (EM) system (IcePIC) mounted to a helicopter, and analyzed through advanced synthetic aperture radar (ASAR) images of the study area. In situ Polar bear tracks provided a limited association with the EM sea ice roughness and a negative association to ASAR sea ice roughness. Results indicate a significant association between EM mean values and ASAR brightness means. In addition, EM statistics and ASAR texture statistics were correlated through a best fit regression model. These associations display a remote method to identify preferred polar bear habitat and provide a potential linkage between the regional (EM) and remotely sensed (ASAR) assessment of sea ice roughness. / October 2008

An evaluation of the global water storage contribution to the Chandler wobble has never been undertaken because: (1) the hydrological data necessary for the reconstruction of an extended monthly time series have not been available; and (2) the water storage contribution has traditionally been regarded as relatively unimportant because of its minor role in the excitation of the annual wobble. However, a crude approximation of the global water storage series is possible using worldwide records of monthly precipitation and temperature, accumulating precipitation at individual locations whenever temperatures are at 0° Celsius or below. Comparison of this modeled series with a previous estimate of the annual component of the global water balance, and with the observed monthly polar motion series, indicates good agreement with the former, and a significant correlation with the latter near the Chandler frequency. / text

No description available.

Accumulation of dynamic and thermodynamic forces in the Arctic are decreasing the extent of thin annual sea ice which polar bear rely on for survival. It is imperative that we identify the preferred habitat of polar bears to fully understand their future requirements. In this thesis, surveys of polar bear tracks and the surrounding sea ice variables, at various scales, were recorded. Sea ice roughness was measured through surveys of the sample area in situ, with an electromagnetic induction (EM) system (IcePIC) mounted to a helicopter, and analyzed through advanced synthetic aperture radar (ASAR) images of the study area. In situ Polar bear tracks provided a limited association with the EM sea ice roughness and a negative association to ASAR sea ice roughness. Results indicate a significant association between EM mean values and ASAR brightness means. In addition, EM statistics and ASAR texture statistics were correlated through a best fit regression model. These associations display a remote method to identify preferred polar bear habitat and provide a potential linkage between the regional (EM) and remotely sensed (ASAR) assessment of sea ice roughness.

This dissertation attempts to improve the understanding of spatial distribution and evolution of snow-covered sea ice as related to polar bear habitat. This will be accomplished at both the local (i.e. 1m spatial resolution) and regional scales (i.e. 100 km spatial resolution) for various types of first-year sea ice (FYI) through four primary objectives. The first primary objective (i.e. Chapter 3) examines the observed and modeled temporal evolution of snow over smooth FYI, as well as the estimation of on-ice meteorological conditions. Results suggest that increases in observed snowdrifts and changes to the orientation of the drifts are related to snowfall and drifting events. Modeling these changes over time using a spatially distributed snow model is not able to accurately estimate the snow distribution. As well, only the on-ice temperature and humidity can be estimated from land-based station data, limiting the modeling of snow over sea ice. The second primary objective (i.e. Chapter 4) extends this research to rough FYI types, more relevant to polar bear habitat. More specifically this objective studies the spatial pattern of snow distribution over rough ice and ridges and the relationship between ice roughness and meteorological conditions. Results suggest that ice roughness influences the magnitude of snow depth, while the wind direction during periods of snow deposition and/or blowing snow events will impact the spatial pattern. The third primary objective (i.e. Chapter 5) focuses on developing a more feasible method of deriving surface roughness. This objective attempts to use satellite imagery and texture analysis to derive surface roughness for snow-covered sea ice. Results suggest that a Gamma speckle reduction filter, coupled with a grey-level co-occurrence matrix texture measure (Entropy or Angular Second Moment) is able to account for more than 88% of the variability in the surface roughness. The final primary objective (i.e. Chapter 6) examines the temporal evolution and factors controlling the changes in sea ice characteristics over regional scale for a period from 1978 to 2002. Observed anomalies in sea ice characteristics within some of the polar bear subpopulations may be explained by thermodynamic and/or dynamic factors. Results suggest that published reduction in polar bear population and condition within the subpopulations co-occur with these observed changes in sea ice characteristics.

No description available.

Accumulation of dynamic and thermodynamic forces in the Arctic are decreasing the extent of thin annual sea ice which polar bear rely on for survival. It is imperative that we identify the preferred habitat of polar bears to fully understand their future requirements. In this thesis, surveys of polar bear tracks and the surrounding sea ice variables, at various scales, were recorded. Sea ice roughness was measured through surveys of the sample area in situ, with an electromagnetic induction (EM) system (IcePIC) mounted to a helicopter, and analyzed through advanced synthetic aperture radar (ASAR) images of the study area. In situ Polar bear tracks provided a limited association with the EM sea ice roughness and a negative association to ASAR sea ice roughness. Results indicate a significant association between EM mean values and ASAR brightness means. In addition, EM statistics and ASAR texture statistics were correlated through a best fit regression model. These associations display a remote method to identify preferred polar bear habitat and provide a potential linkage between the regional (EM) and remotely sensed (ASAR) assessment of sea ice roughness.