Publication Date:
2007-01-01
Description:
This paper synthesizes 10-years' worth of interannual time-series space-borne ERS-1 and RADARSAT-1 synthetic aperture radar (SAR) data collected coincident with daily measurement of snow-covered, land-fast first-year sea ice (FYI) geophysical and surface radiation data collected from the Seasonal Sea Ice Monitoring and Modeling Site, Collaborative-Interdisciplinary Cryospheric Experiment and 1998 North Water Polynya study over the period 1992 to 2002. The objectives are to investigate the seasonal co-relationship of the SAR time-series dataset with selected surface mass (bulk snow thickness) and climate state variables (surface temperature and albedo) measured in situ for the purpose of measuring the interannual variability of sea ice spring melt transitions and validating a time-series SAR methodology for sea ice surface mass and climate state parameter estimation. We begin with a review of the salient processes required for our interpretation of time-series microwave backscatter from land-fast FYI. Our results suggest that time-series SAR data can reliably measure the timing and duration of surface albedo transitions at daily to weekly time-scales and at a spatial scales that are on the order of hundreds of metres. Snow thickness on FYI immediately prior to melt onset explains a statistically significant portion of the variability in timing of SAR-detected melt onset to pond onset for SAR time-series that are made up of more than 25 images. Our results also show that the funicular regime of snowmelt, resolved in time-series SAR data at a temporal resolution of approximately 2-5 images per week, is not detectable for snow covers less than 25 cm in thickness. Copyright © 2007 John Wiley & Sons, Ltd.
Print ISSN:
0885-6087
Electronic ISSN:
1099-1085
Topics:
Architecture, Civil Engineering, Surveying
,
Geography
Permalink
