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Maaß, Nina; Kaleschke, Lars (2010)
Publisher: Co-Action Publishing
Journal: Tellus A
Languages: English
Types: Article
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 involvedmicrowave 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.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Bellerby, T., Taberner, M., Wilmshurst, A., Beaumont, M., Barrett, E., and co-authors. 1998. Retrieval of land and sea brightness temperatures from mixed coastal pixels in passive mircowave Data. IEEE Trans. Geosci. Remote Sens. 36, 1844-1851.
    • Bennartz, R. 1999. On the use of SSM/I measurements in coastal regions. J. Atmos. Oceanic Technol. 16, 417-431.
    • CAL/VAL 1998. DMSP Special Sensor Microwave/Imager Calibration/ Validation, NRL Final Report 2, Naval Research Laboratory, Washington, DC, 453 pp.
    • Cavalieri, D. J., Crawford, J. P., Drinkwater, M. R., Eppler, D. T., Farmer, L. D. and co-authors. 1991. Aircraft active and passive microwave validation of sea ice concentration from the Defense Meteorological Satellite Program Special Sensor Microwave Imager. J. Geophys. Res.-Oceans 96(C12), 21 989-22 008.
    • Cavalieri, D. J., St. Germain, K. M. and Swift, C. T. 1995. Reduction of weather effects in the calculation of sea-ice concentration with DMSP SSM/I. J. Glaciol. 41(139), 455-464.
    • Drusch, M. 2006. Sea ice concentration analyses for the Baltic Sea and their impact on numerical weather prediction. J. Appl. Meteorol. Climatol. 45, No. 7, American Meteorological Society, 982-994.
    • Drusch, M., Wood, E. F. and Lindau, R. 1999. The impact of the SSM/I antenna gain function on land surface parameter retrieval. Geophys. Res. Lett. 26, 3481-3484.
    • Gloersen, P. and Cavalieri, D. J. 1986. Reduction of weather effects in the calculation of sea ice concentration from microwave radiances. J. Geophys. Res. 136(C3), 3913-3919.
    • Grandell, J. and Hallikainen, M. 1994. Modeling and retrieval of snow and sea ice characteristics in the frequency range 6 to 90 GHz. Final report. Report 21, Laboratory of Space Technology, Helsinki University of Technology, Finland.
    • Hollinger, J. P. 1990. DMSP Special Sensor Microwave/Imager Calibration/Validation. Final Report, Vol. I., Naval Research Laboratory, Washington, DC.
    • Kaleschke, L., Lu¨pkes, C., Vihma, T., Haarpaintner, J., Bochert, A. and co-authors. 2001. SSM/I sea ice remote sensing for mesoscale ocean-atmosphere interaction analysis. Can. J. Remote Sens. 27(5), 526-537.
    • Leppa¨ranta, M. and Myrberg, K. 2009. Physical Oceanography of the Baltic Sea. Springer-Verlag, Berlin, Germany.
    • Markus, T. and Cavalieri, D. J. 2000. An enhancement of the NASA Team sea ice algorithm. IEEE Trans. Geosci. Remote Sens. 38, 1387-1398.
    • Maslanik, J. A., Serreze, M. C. and Barry, R. G. 1996. Recent decreases in Arctic summer ice cover and linkages to atmospheric circulation anomalies. Geophys. Res. Lett. 23, 1677-1680.
    • NSIDC. 1996. Investigating mixed errors in SSM/I data processed with the AES/York sea ice concentration algorithm. NSIDC Notes Issue 18.
    • Parkinson, C., Comiso, J., Zwally, H., Cavalieri, D., Gloersen, P. and coauthors. 1987. Arctic sea ice, 1973-1976: Satellite passive-microwave observations, NASA SP-489, National Aeronautics and Space Administration, Washington, DC.
    • Shokr, M., Asmus, K. and Agnew, T. A. 2009. Microwave emission observations from artificial thin sea ice: the ice-tank experiment. IEEE Trans. Geosci. Remote Sens. 47(47), 325-338.
    • Spreen, G., Kaleschke, L. and Heygster, G. 2008. Sea ice remote sensing using AMSR-E 89-GHz channels. J. Geophys. Res. 113, 3481-3484.
    • Steffen, K. and Schweiger, A. 1991. NASA Team algorithm for sea ice concentration retrieval from DMSP SSM/I: Comparison with Landsat satellite imagery. J. Geophys. Res. 96, 21 971-21 987.
    • Swift, C. T., Cavalieri and D. J. 1985. Passive microwave remote sensing for sea ice research. EOS. 66(49), 1210-1212.
    • Wessel, P. and Smith, W. H. F. 1996. A global, self-consistent, hierarchical, high-resolution shoreline database. J. Geophys. Res.-Solid Earth 101(B4).
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