Sea Ice Classification During Freeze-Up Conditions With Multifrequency Scatterometer Data

Abstract

Helicopter-borne radar backscatter measurements are analyzed with respect to a multifrequency classification approach of sea ice. Measurements were carried out over the Arctic Ocean during August and September 2007 and represented unusually warm freeze-up conditions. Radar cross sections (RCSs) of totally ice-free wind-roughened water are used in combination with an ocean surface theoretical backscattering model for the calibration. The calibrated RCS σ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">°</sup> agrees within 1 dB with nearly simultaneous Envisat Advanced Synthetic Aperture Radar measurements and literature values. Sea ice was classified using a Bayesian maximum likelihood approach. By including information from simultaneous infrared and visible video imagery of sea ice, four different surface types of sea ice could be identified in the resulting σ°: old ice, gray ice, nilas, and open water. The most reliable classification was obtained through combination of copolarized C-, X-, and Ku-band data. The results degraded by only 7% in the case where the X-band information was dropped. On the other hand, a combination of the C- and X-bands or the X- and Ku-bands yielded a degradation of 13%. Given the remaining uncertainties in the approach, for sea ice classification during summer/fall conditions, our results suggest the complementary use of two of these three frequency bands instead of relying on just one frequency band.