Sea-ice concentration retrieval in the Antarctic based on the SSM/ I 85.5 GHz polarization

Abstract Using data from the 85 GHz channels of the Special Sensor Microwave/ Imager (SSM/I) allows a resolution improvement by at least a factor of four compared to the other channels. Consequently higher-resolution sea-ice concentration data can be obtained which in turn can be used to improve the results of numerical weather-prediction (NWP) and global circulation models. The proposed new sea-ice concentration retrieval algorithm (SEA LION algorithm) uses the polarization at 85 GHz (p). Emission from atmospheric water and scattering at the wind-roughened sea surface (weather effect) decrease p and cause an overestimate of the sea-ice concentration. We quantify the weather effect with a radiative transfer model and atmospheric data obtained from NWP models and the other SSM/I channels, and correct p for this effect. Tie points of open water and sea ice are determined for each month separately from daily gridded 85 GHz SSM/I brightness temperatures. Sea-ice concentrations are calculated with the new algorithm for the entire Southern Ocean for each day of the period 1992−98 with a spatial resolution of 12.5 × 12.5 km2. Comparisons of these ice concentrations with Operational Linescan System visible images reveal convincing results concerning the monitoring of coastal polynyas and the break-up of the pack ice in spring. SEA LION sea-ice extents and areas, and comparisons between SEA LION sea-ice concentrations and ship observations, agree with those obtained by the NASA Team and the Bootstrap algorithms:

[1]  G. Maykut.  Energy exchange over young sea ice in the central Arctic , 1978 .

[2]  E. Svendsen,et al.  A model for retrieving total sea ice concentration from a spaceborne dual-polarized passive microwave instrument operating near 90 GHz , 1987 .

[3]  C. C. Wackerman,et al.  Aircraft active and passive microwave validation of sea ice concentration from the Defense Meteorological Satellite Program special sensor microwave imager , 1991 .

[4]  Clemens Simmer,et al.  Remote sensing of cloud liquid water , 1994 .

[5]  Hajo Eicken,et al.  Passive microwave observations of the Weddell Sea during austral winter and early spring , 1994 .

[6]  Dan Lubin,et al.  The potential for interpreting total and multiyear ice concentrations in SSM/I 85.5 GHz imagery , 1995 .

[7]  D. Lubin,et al.  Total sea ice concentration retrieval from the SSM/I 85.5 GHz channels during the arctic summer , 1997 .

[8]  K. Walsh.  Antarctic Meteorology and Climatology , 1998 .

[9]  C. Simmer,et al.  A combined radiative transfer model for sea ice, open ocean, and atmosphere , 1998 .

[10]  Son V. Nghiem,et al.  Evolution of Electromagnetic-Signatures of Sea Ice From Initial Formation Through the Establishment of Thick First-Year Ice , 2000 .

[11]  Matthew Sturm,et al.  The Winter Snow Cover of the West Antarctic Pack Ice: Its Spatial and Temporal Variability , 2013 .

[12]  Martin O. Jeffries,et al.  Antarctic sea ice : physical processes, interactions, and variability , 1998 .

[13]  Ian Allison,et al.  Winter snow cover variability on East Antarctic sea ice , 1998 .

[14]  Jungang Miao,et al.  Signature of clouds over Antarctic sea ice detected by the Special Sensor Microwave/Imager , 2000, IEEE Trans. Geosci. Remote. Sens..