A new method for medium-resolution sea ice analysis using weather-influence corrected Special Sensor Microwave/Imager 85 GHz data

Abstract

A detailed description of a new method for sea ice analysis using Special Sensor Microwave/Imager (SSM/I) brightness temperature measurements (SEA LION algorithm) is given. The SEA LION algorithm uses the normalized brightness temperature polarization difference at 85 GHz. This polarization difference is corrected for the change in brightness temperatures due to sea surface scattering and absorption/emission by atmospheric water (weather influence). This is achieved by taking low-frequency SSM/I data and Numerical Weather Prediction model data for radiative transfer calculations. Tie points are derived from 85 GHz SSM/I data over a period of at least 10 days/one month focused around the period of investigation. The difference between measured and modelled polarization difference is minimized by iteration to obtain the sea ice concentration. The SEA LION algorithm was applied to daily gridded and single overpass 85 GHz SSM/I data. Resulting 12.5 km612.5 km ice concentrations are compared to those of the NASA-Team and the COMISO-Bootstrap algorithms, to ship observations, and to space-borne visible/infrared (VIS/IR) and active microwave imagery. The SEA LION algorithm ice edge agrees within 10 km with VIS/IR imagery. The across ice-edge SEA LION algorithm iceconcentration gradient is considerably steeper than that of the NASA-Team and COMISO-Bootstrap algorithm ice concentration and agrees with active microwave imagery. Arctic SEA LION ice concentrations compare to those obtained from classified active microwave imagery with a correlation (regression) coefficient of 0.84 (0.77) and a difference of 24.4% (NASA-Team algorithm: 0.85 (0.57) and 28.5%).

A Comparison of Two 85-GHz SSM/I Ice Concentration Algorithms With AVHRR and ERS-2 SAR Imagery

“…A first quantitative comparison among NTA, CBA, and SLA ice concentrations, i.e., of ice concentrations obtained at a spatial resolution of 25 km 25 km (NTA, CBA, 19-and 37-GHz data) and of 12.5 km 12.5 km (SLA, 85-GHz data), with SAR ice concentrations was made for the Greenland Sea by Kern [17]. This was done in the same manner and for the same dates as in this study.…”

“…This has become necessary because , , and values derived from SSM/I data are more realistic over open water than NWP model data and thus improve the SLA sea ice analysis. More information about the SLA is given in [11] and [17].…”

Inter-comparison and evaluation of sea ice algorithms: towards further identification of challenges and optimal approach using passive microwave observations

“…However, it is difficult to define an OW point in this axis, since samples are now spread along a line. This "weather line" even intersects the ice line, illustrating that algorithms based purely in the (Tb85V, Tb85H)-space (like the ASI and N90 algorithms) have difficulties at discriminating open water from sea ice under certain atmospheric conditions (Kern, 2004).…”

“…4.4), and found that it is removing not only atmospheric effects but also ice itself, which we found to be unacceptable for a SIC algorithm. Therefore we chose not to use the open water/weather filters, but implement an alternative solution, following Andersen et al (2006) and Kern (2004). The suggested method consists of applying a more direct atmospheric correction methodology, where the input SSM/I Tbs in all the channels used by the algorithms are corrected with regard to atmospheric and surface effects using a radiative transfer model (RTM):…”

IceMap250—Automatic 250 m Sea Ice Extent Mapping Using MODIS Data

“…Many algorithms were developed to retrieve sea ice concentrations from passive microwave observations, as presented by Ivanova et al [2]. From these algorithms, some use higher frequency bands to achieve finer grid resolution, such as the ARTIST Sea Ice Algorithm (ASI) from Kaleschke et al [14] and the SEA LION algorithm from Kern [15] at 12.5 km for use with SSM/I, the ASI applied to AMSR-E from Spreen et al [5] achieving a 6.25 km grid resolution and another application of the ASI to AMSR2, by Beitsch et al [16], achieving a 3.125 km grid resolution. It is important to note that the higher the frequency used in passive microwave, the more the signal is subject to weather influences.…”