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.
| Identifer | oai:union.ndltd.org:MANITOBA/oai:mspace.lib.umanitoba.ca:1993/30225 |
| Date | January 2014 |
| Creators | Komarov, Alexander |
| Contributors | Shafai, Lotfollah (Electrical and Computer Engineering) Barber, David (Environment and Geography), Mojabi, Puyan (Electrical and Computer Engineering) Ehn, Jens (Environment and Geography) Dierking, Wolfgang (Alfred Wegener Institute for Polar and Marine Research) |
| Publisher | Institute of Electrical and Electronics Engineers, The Electromagnetics Academy |
| Source Sets | University of Manitoba Canada |
| Detected Language | English |
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