1980s drafts were composed largely of ice exceeding 3.5 m, while the early 1990s drafts contained more ice in thinner categories. The differences in drafts between the two periods appear to be related largely to ice dynamics effects associated with the presence and strength of the Beaufort Gyre, which weakened considerably in the early 1990s.

During March 1988 a series of coordinated special sensor microwave imager (SSM/I) underflights were carried out with NASA and Navy aircraft over portions of the Bering, Beaufort, and Chukchi seas as part of the NASA Defense Meteorological Satellite Program SSM/I Sea Ice Validation Program. The two Navy research aircraft, a Naval Research Laboratory P‐3 with the NOARL Ka band radiometric mapping system operating at 33.6 GHz and a Naval Air Development Center (NADC) P‐3 with the NADC‐Environmental Research Institute of Michigan (ERIM) C band synthetic aperture radar (SAR), provided wide‐swath, high‐resolution microwave imagery for direct comparison with sea ice concentrations calculated from SSM/I radiances using the NASA sea ice algorithm. Coincident measurements made with the Jet Propulsion Laboratory (JPL) C band SAR and the Goddard Space Flight Center (GSFC) aircraft multifrequency microwave radiometers (AMMR) on the NASA DC‐8 airborne laboratory provided additional verification of the algorithm. NASA DC‐8 AMMR data from Bering Sea ice edge crossings were used to verify that the ice edge location, defined as the position of the initial ice bands encountered by the aircraft, corresponds to an SSM/I ice concentration of 15%. Direct comparison of SSM/I and aircraft ice concentrations for regions having at least 80% aircraft coverage reveals that the SSM/I total ice concentration is lower on average by 2.4%±2.4%. For multiyear ice, NASA and Navy flights across the Beaufort and Chukchi seas show that the SSM/I algorithm correctly maps the large‐scale distribution of multiyear ice: the zone of first‐year ice off the Alaskan coast, the large areas of mixed first‐year and multiyear ice, and the region of predominantly multiyear ice north of the Canadian archipelago. Quantitative comparisons show that the SSM/I algorithm overestimates multiyear ice concentration by 12%±11% on average in the Chukchi and Beaufort seas. Excluding data for a day which gave anomalously large positive biases, the multiyear ice concentration difference reduces to 5%±4%, also indicating a positive SSM/I bias. Anomalously low SSM/I concentrations were found in the coastal zone north of Ellesmere Island. Differences between multiyear ice concentrations estimated from the JPL C band SAR imagery and from the GSFC AMMR radiances using an SSM/I type algorithm show that the AMMR concentrations are smaller on average by 6%±14%. Sea ice conditions are described, and possible causes of the observed differences are discussed.

No abstract

We investigate observationally and theoretically the response of polarimetric backscattering at 24-cm wavelength to the thickness of Arctic sea ice in leads and first-year ice features. We employ backscattering data acquired by the Jet Propulsion Laboratory airborne synthetic aperture radar (SAR) during March 1988 in the Beaufort Sea, together with nearly simultaneous passive microwave imagery acquired by the U.S. Navy Ka band radiometric mapping system. We find that 24-cm copolar ratios and copolar phases vary strongly with apparent ice thickness. We observe copolar phase shifts between -10 ø and -50 ø (relative to multiyear ice phases) for new ice features in the imagery, as well as positive copolar phases in a first-year ice feature. Copolar ratios also vary with apparent thickness, from values larger than those expected theoretically for seawater to values slightly lower than those expected for thick ice. We derive a signature model based on scattering from a rough air/sea ice interface with realistic vertical profiles of brine volume and relative permittivity beneath. Model predictions for copolar ratios and phases show ice thickness-dependent variations consistent with those observed. We present simulation results showing that plausible ice thickness variations between pixels in a multilook average diminish, but do not eliminate, the signature response to thickness. This suggests that direct thickness estimation of sea ice in leads may be possible using polarimetric SAR at wavelengths of 24 cm or longer. IntroductionConcerns related to global geoscience and climate change motivate special interest in features of sea ice known as leads. Leads are cracks in the sea ice cover produced by differential wind stress in which seawater is exposed to the atmosphere. Except during the summer, the difference in temperatures between the boundary layer of the atmosphere and seawater at its Copyright 1995 by the American Geophysical Union. Paper number 94RS02313. 0048-6604/95/94RS-02313508.00 freezing point is large. Thick sea ice effectively insulates the two fluids, whereas new, thin ice in leads permits large heat fluxes [Maykut, 1986]. Thus the regionally averaged heat flux between the ocean and atmosphere depends strongly on the regional abundances of open water and thin ice (thickness •< 0.8 m) and on the distribution of thicknesses of the latter [Lindsay and Rothrock, 1994]. New sea ice forms rapidly in leads causing a flux of salinity, and thus negative buoyancy, into the Arctic seas; these fluxes play key roles in determining circulation in the world ocean, and therefore influence the global climate [Aagaard et al., 1981, 1985, 1994]'. Regional thin ice 373 374 WINEBRENNER ET AL.: RESPONSE OF RADAR SIGNATURES TO SEA ICE abundances also influence sea ice rheology, and thus motion, in response to winds [Hibler, 1986]. The logistic difficulties involved in measurement in the Arctic strongly motivate development of remote sensing, and in particular microwave remote sensing, methods to estimate ice thickness in leads....

During March 1983 extensive high‐quality airborne passive Ka band (33.6 GHz) microwave imagery and coincident high‐resolution aerial photography were obtained of ice along a 378‐km flight line in the Beaufort Sea. Analysis of these data suggests that four classes of winter surfaces can be distinguished solely on the basis of 33.6‐GHz brightness temperature: open water, frazil, old ice, and young/first‐year ice. New ice (excluding frazil) and nilas display brightness temperatures that overlap the range of temperatures characteristic of old ice and, to a lesser extent, young/first‐year ice. Scenes in which a new ice or nilas are present in appreciable amounts are subject to substantial errors in classification if static measures of Ka band radiometric brightness temperature alone are considered. Textural characteristics of nilas and new ice, however, differ significantly from textural features characteristic of other ice types and probably can be used with brightness temperature data to classify ice type in high‐resolution single‐band microwave images. In any case, open water is radiometrically the coldest surface observed in any scene. Lack of overlap between brightness temperatures characteristic of other surfaces indicates that estimates of the areal extent of open water based on only 33.6‐GHz brightness temperatures are accurate.