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|Title: ||Spatial and temporal evolution of snow-covered sea ice, with reference to polar bear habitat|
|Authors: ||Iacozza, John|
|Supervisor: ||Barber, David G. (Environment and Geography)|
|Examining Committee: ||Ferguson, Steve (Environment and Geography)
Prinsenberg, Simon (Environment and Geography)
Riewe, Rick (Biological Sciences)
Hammill, Michael (Fisheries and Oceans Canada)|
|Graduation Date: ||May 2011|
|Issue Date: ||7-Apr-2011|
|Citation: ||Iacozza J. and D.G. Barber (2010). An examination of snow redistribution over smooth land-fast sea ice. Hydrological Processes, 24:850–865, doi: 10.1002/hyp.7526|
|Abstract: ||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.|
|Appears in Collections:||FGS - Electronic Theses & Dissertations (Public)|
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