Passive microwave remote sensing of thin sea ice using principal component analysis
Article first published online: 20 SEP 2012
Copyright 1993 by the American Geophysical Union.
Journal of Geophysical Research: Oceans (1978–2012)
Volume 98, Issue C7, pages 12453–12468, 15 July 1993
How to Cite
1993), Passive microwave remote sensing of thin sea ice using principal component analysis, J. Geophys. Res., 98(C7), 12453–12468, doi:10.1029/93JC00939., , , and (
- Issue published online: 20 SEP 2012
- Article first published online: 20 SEP 2012
- Manuscript Accepted: 16 MAR 1993
- Manuscript Received: 17 AUG 1992
Time sequences of surface based measurements of passive microwave emission from growing saline ice reported by Wensnahan et al. (1993) are used to explore the possibility of developing a satellite based sea ice concentration algorithm which solves for the presence of thinner ice. It is shown that two classes of thinner ice can be distinguished from mixtures of open water (OW), first-year (FY) ice, and multiyear (MY) ice. The two classes do not necessarily correspond to specific World Meteorological Organization ice types; rather, newly formed ice represents a brief transition spectrum between OW and thin ice. Newly formed ice appears to be optically thick at 37 and 90 GHz and has a relatively dry surface. The thin ice spectrum occurs when the ice is greater than 4 cm thick and appears to result from the accumulation of brine at the surface of the ice. Thin ice has a relatively stable spectrum characterized by high brightness temperatures, a near-zero spectral gradient at vertical polarization, and a large difference between vertical and horizontal polarizations. Supervised principal component analysis (PCA) was done of laboratory data using 10 channels of passive data: vertical and horizontal polarization at 6.7, 10, 19, 37, and 90 GHz. Analyses were also done on subsets of the laboratory data at 6.7 to 37 GHz as well as 19 to 90 GHz, representing the scanning multichannel microwave radiometer (SMMR) and special sensor microwave imager (SSM/I) satellite frequencies, respectively. Using all of the channels or the SMMR subset makes it possible to solve for mixtures of OW and FY, MY, newly formed and thin ice but with large errors. However, any four of these scene types can be distinguished with reasonable accuracy. The SSM/I frequencies allow determination of at most four of these scene types but with moderate errors. PCA was used in a case study of SSM/I data from the Bering Sea for April 2, 1988. Winds from the north formed thin ice areas which the NASA Team algorithm interprets as large amounts of OW and MY ice. With PCA, these same areas are interpreted as 20–30% OW near the lee shores but otherwise as consisting almost entirely of thin ice. We conclude that thin ice can be detected using satellite data. However, questions remain as to how the thin ice spectrum varies with environmental conditions, how it evolves to that of FY, and how this evolution affects the predicted concentrations of thin ice.