YU Qinglong, WANG Hui, WAN Liying, BI Haibo. Retrieving the antarctic sea-ice concentration based on AMSR-E 89 GHz data[J]. Acta Oceanologica Sinica, 2013, 32(9): 38-43. doi: 10.1007/s13131-013-0350-0
Citation: YU Qinglong, WANG Hui, WAN Liying, BI Haibo. Retrieving the antarctic sea-ice concentration based on AMSR-E 89 GHz data[J]. Acta Oceanologica Sinica, 2013, 32(9): 38-43. doi: 10.1007/s13131-013-0350-0

Retrieving the antarctic sea-ice concentration based on AMSR-E 89 GHz data

doi: 10.1007/s13131-013-0350-0
  • Received Date: 2012-03-02
  • Rev Recd Date: 2012-05-14
  • Sea-ice concentration is a key item in global climate change research. Recent progress in remotely sensed sea-ice concentration product has been stimulated by the use of a new sensor, advanced microwave scanning radiometer for EOS (AMSR-E), which offers a spatial resolution of 6 km×4 km at 89GHz. A new inversion algorithm named LASI (linear ASI) using AMSR-E 89GHz data was proposed and applied in the antarctic sea areas. And then comparisons between the LASI ice concentration products and those retrieved by the other two standard algorithms, ASI (arctic radiation and turbulence interaction study sea-ice algorithm) and bootstrap, were made. Both the spatial and temporal variability patterns of ice concentration differences, LASI minus ASI and LASI minus bootstrap, were investigated. Comparative data suggest a high result consistency, especially between LASI and ASI. On the other hand, in order to estimate the LASI ice concentration errors introduced by the tie-points uncertainties, a sensitivity analysis was carried out. Additionally an LASI algorithmerror estimation based on the field measurements was also completed. The errors suggest that themoderate to high ice concentration areas (>70%) are less affected (never exceeding 10%) than those in the low ice concentration. LASI and ASI consume 75 and 112 s respectively when processing the same AMSR-E time series thourghout the year 2010. To conclude, by using the LASI algorithm, not only the seaice concentration can be retrieved with at least an equal quality as that of the two extensively demonstrated operational algorithms, ASI and bootstrap, but also in a more efficient way than ASI.
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  • Cavalieri D J, St.Germain K M, Swift C T. 1995. Reduction of weather effects in the calculation of sea-ice concentration with DMSP SMM/I. J Glaciology, 41(139): 455-464 Comiso J C, Cavalieri D J, Parkinson C L. 1997. Passive microwave algorithms for sea ice concentration: a comparison of two techniques. Rem Sens Environ, 60(3): 357-384 Gloersen P, Cavalieri D J. 1986. Reduction of weather effects in the calculationj of sea ice concentration frommicrowave radiances. J Geophys Res, 91(C3): 3913-3919 Kaleschke L, Lupkes C, Vihma T. 2001. SSM/I sea ice remote sensing for mesoscale ocean-atmosphere interaction analysis. Can J Rem Sens, 27(5): 526-537
    Kern S. 2009. Wintertime antarctic coastal polynya area: 1992-2008. Geophys Res Lett, 36(L14501), doi: 10.1029/2009GL038062
    Kern S, Spreen G, Kaleschke L. 2007. Polynya signature simulation method polynya area in comparison on AMSR-E 89 GHz sea ice concentration in the Ross Sea and off Adelie coast, Antarctic, for 2002-2005: first results. Ann Glac, 46(1): 409-418
    Kern S, Kaleschke L, Clausi D A. 2003. A comparison of two 85 GHz SSM/I ice concentration algorithms with AVHRR and ERS-2 SAR imagery. IEEE Trans Geosci Rem Sens, 41(10): 2294-2306
    Mathew N, Heygster G,Melsheimer C. 2008. Surface emissivity of arctic sea ice at AMSU window frequencies. IEEE Trans Geosci Rem Sens, 46(8): 2298
    Parkinson C L, Rind D, Healy R J. 2001. The impact of sea ice concentration accuracies on climate model simulations with the GISS GCM. J Climate, 14(12): 2206-2631
    Serreze M. 2003. A record minimum arctic sea ice extent and area in 2002. Geophys Res Lett, 30(3): 1110
    Spreen G, Kaleschke L, Heygster G. 2005. Operational sea ice remote sensingwith AMSR-E 89GHz channels. IGARSS, 6(1): 4033-4036
    Spreen G, Kaleschke L, Heygster G. 2008. Sea ice remote sensing using AMSR-E 89 GHz channels. J Geophys Res, 113(2): C02S03
    Svendsen E, Matzler C, Grenfell T C. 1987. A model for retrieving total sea ice concentration from a spaceborne dual-polarized passive microwave instrument operating near 90 GHz. Int J Rem Sens, 8(10): 1479-1487
    Wang Huanghuang, Heygster G, Han Shouzong, et al. 2009. Arctic multiyear ice concentration retrieval based on AMSR-E 89GHz data. Chin J Polar Res, 21(3): 186-196
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