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.

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.

The quantity of seasonal snow stored in the Lake Pukaki catchment, New Zealand has a significant impact on the country's economy through its influence on hydroelectricity generation, tourism, agriculture and conservation. SnowSim is a snow storage model developed for New Zealand conditions that may be used to quantify the catchment's frozen water resource and the melt water derived from that resource. Through implementation on a geographic information system, SnowSim has been applied and optimised to the Lake Pukaki catchment. The optimal parameters found were: temperature-elevation lapse rate of 0.005 ℃ m⁻¹, snow/rain temperature threshold of 2.5 ℃, and a melt to temperature relationship factor ranging from 1 to 6 mm ℃⁻¹ d⁻¹. The melt to temperature relationship factor is significantly reduced from that previously used for a New Zealand wide application of SnowSim. Use of a daily measured lapse rate was found to provide no improvement to the model, considered to be because of the spatial variability of lapse rates. Inclusion of a radiation component also provided no improvement in the model. This is contrary to the experience found in similar model applications in other regions of the world. The lower relative importance of radiation melt (with regard to total melt) in the region compared to continental l℃ations may explain this result. The use of a new precipitation distribution system did improve model results. Daily precipitation measurements were related to a new annual average precipitation surface prior to interpolating them across the region, without any elevation to precipitation relationship. Model free water results required an offset adjustment to bring them into line with measured lake inflows limiting the application of the model to estimation of seasonal variation, relative magnitudes and event frequencies of snow storage. Over four years of data a model output quality criterion of 0.61 (where a value of 1 is a perfect model) was returned. This increased to 0.76 for monthly values indicating a high quality of output at the seasonal scale. Model parameters and output quality are in line with those found using comparable models for various applications around the world. The variety of outputs available from the model provide a valuable resource for applications in the electricity, tourism, conservation and agriculture industries as well as for climate, glacier, snow and mountain research.

Thesis (M.S. - Renewable Natural Resources)--University of Arizona, 1988. / Includes bibliographical references (leaves 23-24).

Thesis (M.S. - Watershed Management)--University of Arizona. / Includes bibliographical references.

Thesis (M.S. - Renewable Natural Resources)--University of Arizona. / Includes bibliographical references.

Thesis (M.S. - Hydrology and Water Resources)--University of Arizona. / Includes bibliographical references.

Thesis (M.S. - Renewable Natural Resources)--University of Arizona, 1980. / Includes bibliographical references.

Diss. Linköping : Linköpings universitet, 2006.