Improving passive microwave sea ice concentration algorithms for coastal areas: applications to the Baltic Sea

Sea ice concentration can be retrieved from passive microwave data using the NASA Team algorithm or the Artist Sea Ice (ASI) algorithm, for example. The brightness temperature measurements obtained from the Special Sensor Microwave Imager (SSM/I) instrument or the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) are commonly used for this purpose. Due to the coarse resolution of these instruments considerable systematic ice concentration errors in coastal regions occur. In the vicinity of the coast the instrument footprints usually contain both land and sea surfaces. Compared to sea surfaces, land surfaces are characterized by higher emissivities and lower polarization differences at the involved microwave channels. Thus, a systematic overestimation of coastal ice concentration is caused. In this paper, a method is developed to remove the land impact on the observed radiation. Combining a high-resolution data set for the shoreline and the antenna gain function the brightness temperature contribution originating from land surfaces can be identified. The brightness temperature related to the ocean fraction within the considered footprint can then be extracted. This separation technique is applied to SSM/I measurements in the Baltic Sea and the resulting ice concentration fields are compared to high-resolution satellite images. The highly complex shoreline of the Baltic Sea region provides an ideal area for testing the method. However, the presented approach can as well be applied to Arctic coastal regions. It is shown that the method considerably improves ice concentration retrieval in regions influenced by land surfaces without removing actually existing sea ice.

[1]  Thorsten Markus,et al.  An enhancement of the NASA Team sea ice algorithm , 2000, IEEE Trans. Geosci. Remote. Sens..

[2]  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 .

[3]  Mohammed Shokr,et al.  Microwave Emission Observations from Artificial Thin Sea Ice: The Ice-Tank Experiment , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[4]  Matthias Drusch,et al.  Sea Ice Concentration Analyses for the Baltic Sea and Their Impact on Numerical Weather Prediction , 2006 .

[5]  H. Zwally,et al.  Antarctic Sea Ice, 1973-1976: Satellite Passive-Microwave Observations , 1983 .

[6]  Walter H. F. Smith,et al.  A global, self‐consistent, hierarchical, high‐resolution shoreline database , 1996 .

[7]  Donald J. Cavalieri,et al.  Reduction of weather effects in the calculation of sea ice concentration from microwave radiances , 1986 .

[8]  John Scott,et al.  Retrieval of land and sea brightness temperatures from mixed coastal pixels in passive microwave data , 1998, IEEE Trans. Geosci. Remote. Sens..

[9]  K. Germain,et al.  Reduction of weather effects in the calculation of sea-ice concentration with the DMSP SSM/I , 1995 .

[10]  J. Haarpaintner,et al.  SSM/I Sea Ice Remote Sensing for Mesoscale Ocean-Atmosphere Interaction Analysis , 2001 .

[11]  Ralf Bennartz,et al.  On the Use of SSM/I Measurements in Coastal Regions , 1999 .

[12]  L. Kaleschke,et al.  Sea ice remote sensing using AMSR‐E 89‐GHz channels , 2008 .

[13]  Nasa,et al.  Passive microwave remote sensing for sea ice research , 2013 .

[14]  Konrad Steffen,et al.  NASA team algorithm for sea ice concentration retrieval from Defense Meteorological Satellite Program special sensor microwave imager: Comparison with Landsat satellite imagery , 1991 .

[15]  Roger G. Barry,et al.  Recent decreases in Arctic summer ice cover and linkages to atmospheric circulation anomalies , 1996 .

[16]  J P Hollinger,et al.  DMSP Special Sensor Microwave/Imager Calibration/Validation , 1991 .

[17]  Matthias Drusch,et al.  The impact of the SSM/I antenna gain function on land surface parameter retrieval , 1999 .