The objective of this research is to explore the information content of repeat-pass cross-track Interferometric SAR (InSAR) with regard to snow, in particular Snow Water Equivalent (SWE) and snow depth. The study is an outgrowth of earlier snow cover modeling and radar interferometry experiments at Schefferville, Quebec, Canada and elsewhere which has shown that for reasons of loss of coherence repeat-pass InSAR is not useful for the purpose of snow cover mapping, even when used in differential InSAR mode. Repeat-pass cross-track InSAR would overcome this problem. As at radar wavelengths dry snow is transparent, the main reflection is at the snow/ground interface. The high refractive index of ice creates a phase delay which is linearly related to the water equivalent of the snow pack. When wet, the snow surface is the main reflector, and this enables measurement of snow depth. Algorithms are elaborated accordingly. Field experiments were conducted at two sites and employ two different types of digital elevation models (DEM) produced by means of cross track InSAR. One was from the Shuttle Radar Topography Mission digital elevation model (SRTM DEM), flown in February 2000. It was compared to the photogrammetrically produced Canadian Digital Elevation Model (CDEM) to examine snow-related effects at a site near Schefferville, where snow conditions are well known from half a century of snow and permafrost research. The second type of DEM was produced by means of airborne cross track InSAR (TOPSAR). Several missions were flown for this purpose in both summer and winter conditions during NASA's Cold Land Processes Experiment (CLPX) in Colorado, USA. Differences between these DEM's were compared to snow conditions that were well documented during the CLPX field campaigns. The results are not straightforward. As a result of automated correction routines employed in both SRTM and AIRSAR DEM extraction, the snow cover signal is contaminated. Fitting InSAR DEM's to known topography distorts the snow information, just as the snow cover distorts the topographic information. The analysis is therefore mostly qualitative, focusing on particular terrain situations. At Schefferville, where the SRTM was adjusted to known lake levels, the expected dry-snow signal is seen near such lakes. Mine pits and waste dumps not included in the CDEM are depicted and there is also a strong signal related to the spatial variations in SWE produced by wind redistribution of snow near lakes and on the alpine tundra. In Colorado, cross-sections across ploughed roads support the hypothesis that in dry snow the SWE is measurable by differential InSAR. They also support the hypothesis that snow depth may be measured when the snow cover is wet. Difference maps were also extracted for a 1 km2 Intensive Study Area (ISA) for which intensive ground truth was available. Initial comparison between estimated and observed snow properties yielded low correlations which improved after stratification of the data set.In conclusion, the study shows that snow-related signals are measurable. For operational applications satellite-borne cross-track InSAR would be necessary. The processing needs to be snow-specific with appropriate filtering routines to account for influences by terrain factors other than snow.

The Greenland ice sheet is an area of great interest to the scientific community due to its role as an important bellwether for the global climate. Satellite-borne scatterometers are particularly well-suited to studying temporal changes in the Greenland ice sheet because of their high spatial coverage, frequent sampling, and sensitivity to the presence of liquid water. The dry snow zone is the largest component of the Greenland ice sheet and is identified as the region that experiences negligible annual melt. Due to the lack of melt in the dry snow zone, backscatter was previously assumed to be relatively constant over time in this region. However, this thesis shows that a small seasonal variation in backscatter is present in QuikSCAT data in the dry snow zone. Understanding the cause of this seasonal variability is important to verify the accuracy of QuikSCAT measurements, to better understand the ice sheet conditions, and to improve future scatterometer calibration efforts that may use ice sheets as calibration targets.This thesis provides a study of the temporal behavior of backscatter in the dry snow zone of the Greenland ice sheet focusing on seasonal variation. Spatial averaging of backscatter and the Karhunen-Lo`eve transform are used to identify and study the dominant patterns in annual backscatter behavior. Several QuikSCAT instrumental parameters are tested as possible causes of seasonal variation in backscatter in the dry snow zone to verify the accuracy of QuikSCAT products. None of the tested parameters are found to be related to seasonal variation. Further evidence is given that suggests that the cause of the seasonal variation is geophysical and several geophysical factors are tested. Temperature is found to be highly related to dry snow backscatter and therefore may be driving the seasonal variation in backscatter in the dry snow zone.