Aircraft active and passive microwave validation of sea ice concentration from the Defense Meteorological Satellite Program special sensor microwave imager

Abstract

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.

Cryosphere applications of NSCAT data

“…The RL algorithm sea-ice extent closely matches the SSM/Iderived NASA Team Algorithm [8], [9] 30% ice concentration ice extent [54]. Fig.…”

Objective analyses of sea‐surface temperature and marine meteorological variables for the 20th century using ICOADS and the Kobe Collection

“…SIC in this study is derived each day on a 1°× 1°grid based on brightness temperatures from the Nimbus-5 scanning multichannel microwave radiometer (SMMR; October 1978 to July 1987) and the special sensor microwave imager (SSM/I; August 1987 to December 2000) using NASA-team algorithms (Cavalieri et al, 1984(Cavalieri et al, , 1991. Corrections proposed by Cavalieri et al (1999) are applied to SMMR data to mediate the discontinuity in SIC observations between SMMR and SSM/I data, and to data from both satellites to remove measurement errors.…”

Automatic Detection of the Ice Edge in SAR Imagery Using Curvelet Transform and Active Contour

“…However, due to the relatively coarse spatial resolution of ice concentration from passive microwave sensors (≈5 km-25 km), these products may tend to underestimate the ice concentration when the floe size is small or ice cover is sparse, which can happen in the vicinity of the ice edge, when the MIZ is diffuse. In addition, passive microwave estimates of sea ice concentration are biased low when the ice is thin and when there are melt ponds or water on the surface of the ice, leading regions with a high concentration of ice in these situation to appear as having a lower ice concentration [10][11][12]. In these situations, the use of ice concentration may result in an underestimate of the ice edge location.…”