대한원격탐사학회지 (Korean Journal of Remote Sensing)

  • 제27권5호
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  • Pages.543-553
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  • 2011
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  • 1225-6161(pISSN)
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  • 2287-9307(eISSN)
대한원격탐사학회 (Korean Society of Remote Sensing)
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AMSR-E NASA Team2 알고리즘에서 빙하빙의 마이크로파 복사특성

Microwave Radiation Characteristics of Glacial Ice in the AMSR-E NASA Team2 Algorithm

  • 투고 : 2011.09.02
  • 심사 : 2011.09.27
  • 발행 : 2011.10.31
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초록

Aqua에 탑재된 AMSR-E는 NASA Team2 해빙 알고리즘을 사용하여 해밍 면적비를 계산하고 있으며, 이는 남극의 해빙 지역에서 매우 정확하다는 것이 증명되었다. 그러나 AMSR-E의 관측 영역 내에 빙산 및 빙붕과 같은 빙하빙이 많이 포함될 경우 해빙과는 다른 빙하빙의 복사특성 때문에 NASA Team2알고리즘으로부터 계산되는 얼음의 면적비는 그 정확성이 유지되지 않는다. 본 논문에서는 남극의 George V 해안이 촬영된 두 장의 ENVISAT ASAR 영상으로부터 해빙과 빙하빙의 면적비를 추출하였고, 이를 NASA Team2 해빙 면적비와 비교하였다. NASA Team2 알고리즘은 빙하빙에 대해 실제보다 작은 면적비를 계산하였다. 빙하빙에 대한 NASA Team2 알고리즘의 면적비 계산 오류를 해석하기 위해 PR(polarization ratio), GR(spectral gradient ratio), $PR_R$(rotated PR), 그리고 ${\Delta}GR$ 영역에서 빙하빙의 마이크로파 복사특성을 분석하였다. 빙하빙은 PR, GR, $PR_R$, ${\Delta}GR$ 영역에서 ice type A, B, C와 같은 남극의 해빙 및 open water와 구분되는 고유한 범위를 형성하였으며, 이는 빙하빙이 얼음의 새로운 종류로 AMSR-ENASA Team2 해빙 알고리즘에 추가될 수 있음을 의미한다.

Sea ice concentration calculated from the AMSR-E onboard Aqua satellite by using NASA Team2 sea ice algorithm has proven to be very accurate over sea ice in Antarctic Ocean. When glacial ice such as icebergs and ice shelves are dominant in an AMSR-E footprint, the accuracy of the ice concentration calculated from NASA Team2 algorithm is not well maintained due to the different microwave characteristics of the glacial ice from sea ice. We extracted the concentrations of sea ice and glacial ice from two ENVISAT ASAR images of George V coast in southern Antarctica, and compared them with NASA Team2 sea ice concentration. The result showed that the NASA Team2 algorithm underestimates the concentration of glacial ice. To interpret the large deviation of estimation over glacial ice, we analyzed the characteristics of microwave radiation of the glacial ice in PR(polarization ratio), GR(spectral gradient ratio), $PR_R$(rotated PR), and ${\Delta}GR$ domain. We found that glacial ice occupies a unique region in the PR, GR, $PR_R$, and ${\Delta}GR$ domain different from other types of ice such as ice type A, B, and C, and open water. This implies that glacial ice can be added as a new category of ice to the AMSR-E NASA Team2 sea ice algorithm.

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참고문헌

  1. 한향선, 이훈열, 2007. 북극의 KOMPSAT-1 EOC 영상과 SSM/I NASA Team 해빙 면적비의 비교연구, 대한원격탐사학회지, 23(6): 507-520. https://doi.org/10.7780/kjrs.2007.23.6.507
  2. Andersen, S., L. Kaleschke, G. Heygster, and L.T. Pedersen, 2007. Intercomparison of passive microwave sea ice concentration retrievals over the high-concentration Arctic sea ice, Journal of Geophysical Research, 112, C08004, doi:10.1029/2006JC003543.
  3. Cavalieri, D.J., P. Gloersen, C.L. Parkinson, J.C. Comiso, and H.J. Zwally, 1997. Observed hemispheric asymmetry in global sea ice changes, Science, 278(5340): 1104-1106. https://doi.org/10.1126/science.278.5340.1104
  4. Cavalieri, D.J., T. Markus, D.K. Hall, A.J. Gasiewski, M. Klein, and A. Ivanoff, 2006. Assessment of EOS Aqua AMSR-E arctic sea ice concentration using Landsat-7 and airborne microwave imagery, IEEE Transactions on Geoscience and Remote Sensing, 44(11): 3057-3069. https://doi.org/10.1109/TGRS.2006.878445
  5. Comiso, J.C., D.J. Cavalieri, C.L. Parkinson, and P. Gloersen, 1997. Passive microwave algorithms for sea ice concentration: A comparison of two techniques, Remote Sensing of Environment, 60(3): 357-384. https://doi.org/10.1016/S0034-4257(96)00220-9
  6. Comiso, J.C., D.J. Cavalieri, and T. Markus, 2003. Sea ice concentration, ice temperature, and snow depth using AMSR-E data, IEEE Transactions on Geoscience and Remote Sensing, 41(2): 243-252. https://doi.org/10.1109/TGRS.2002.808317
  7. Fricker, H.A., N.W. Young, I. Allison, and R. Coleman, 2002. Iceberg calving from the Amery ice shelf, East Antarctica, Annals of Glaciology, 34(1): 241-246. https://doi.org/10.3189/172756402781817581
  8. Hanna, E., P. Huybrechts, K. Steffen, J. Cappelen, R. Huff, C. Shuman, T. Irvine-Fynn, S. Wise, and M. Griffiths, 2008. Increased runoff from melt from the Greenland ice sheet: A response to global warming, Journal of Climate, 21(2): 331-341. https://doi.org/10.1175/2007JCLI1964.1
  9. Hattermann, T. and A. Levermann, 2010. Response of Southern Ocean circulation to global warming may enhance basal ice shelf melting around Antarctica, Climate Dynamics, 35(5): 741-756. https://doi.org/10.1007/s00382-009-0643-3
  10. Jiang, L., J. Shi, S. Tjuatja, J. Dozier, K. Chen, and L. Zhang, 2007. A parameterized multiplescattering model for microwave emission from dry snow, Remote Sensing of Environment, 111(2-3): 357-366. https://doi.org/10.1016/j.rse.2007.02.034
  11. Kelly, R.E., A.T. Chang, L. Tsang, and J.L. Foster, 2003. A prototype AMSR-E global snow area and snow depth algorithm, IEEE Transactions on Geoscience and Remote Sensing, 41(2): 230-242. https://doi.org/10.1109/TGRS.2003.809118
  12. Lee. H., and H. Han, 2008. Evaluation of SSM/I and AMSR-E sea ice concentrations in the Antarctic spring using KOMPSAT-1 EOC imagery, IEEE Transactions on Geoscience and Remote Sensing, 46(7): 1905-1912. https://doi.org/10.1109/TGRS.2008.916479
  13. Luckman, A., L. Padman, and D. Jansen, 2009. Persistent iceberg groundings in the western Weddell Sea, Antarctica, Remote Sensing of Environment, 114(2): 385-391. https://doi.org/10.1016/j.rse.2009.09.009
  14. Magagi, R., and M. Bernier, 2003. Optimal condition for wet snow detection using RADARSAT SAR data, Remote Sensing of Environment, 84(2): 221-233. https://doi.org/10.1016/S0034-4257(02)00104-9
  15. Makynen, M.P., B. Cheng, M.H. Simila, T. Vihma, and M.T. Hallikainen, 2007. Comparisons between SAR backscattering coefficient and results of a thermodynamic snow/ice method for the Baltic Sea land-fast sea ice, IEEE Transactions on Geoscience and Remote Sensing, 45(5): 1131-1141. https://doi.org/10.1109/TGRS.2007.893735
  16. Markus, T., and D.J. Cavalieri, 2000. An enhancement of the NASA team sea ice algorithm, IEEE Transactions on Geoscience and Remote Sensing, 38(3): 1387-1398. https://doi.org/10.1109/36.843033
  17. Markus, T., D.J. Cavalieri, A.J. Gasiewski, M. Klein, J.A. Maslanik, D.C. Powell, B.B. Stankov, J.C. Stroeve, and M. Sturm, 2006. Microwave signatures of snow on sea ice: Observations, IEEE Transactions on Geoscience and Remote Sensing, 44(11): 3081-3090. https://doi.org/10.1109/TGRS.2006.883134
  18. Oppenheimer, M., 1998. Global warming and the stability of the West Antarctic Ice Sheet, Nature, 393: 325-332. https://doi.org/10.1038/30661
  19. Picard, G. and M. Fily, 2006. Surface melting observations in Antarctica by microwave radiometers: Correcting 26-year time series from changes in acquisition hours, Remote Sensing of Environment, 104(3): 325-336. https://doi.org/10.1016/j.rse.2006.05.010
  20. Powell, D.C., T. Markus, D.J. Cavalieri, A.J. Gasiewski, M. Klein, J.A. Maslanik, J.C. Strove, and M. Sturm, 2006. Microwave signatures of snow on sea ice: Modeling, IEEE Transactions on Geoscience and Remote Sensing, 44(11): 3091-3102. https://doi.org/10.1109/TGRS.2006.882139
  21. Rignot, E. and R.H. Thomas, 2002. Mass balance of polar ice sheets, Science, 297(5586): 1502-1506. https://doi.org/10.1126/science.1073888
  22. Tedesco, M., and J. Miller, 2007. Observations and statistical analysis of combined active-passive microwave space-borne data and snow depth at large spatial scales, Remote Sensing of Environment, 111(2-3): 382-397. https://doi.org/10.1016/j.rse.2007.04.019
  23. Velicogna, I., 2009. Increasing rates of ice mass loss from the Greenland and Antarctic ice sheets revealed by GRACE, Geophysical Research Letters, 36, L19503, doi:10.1029/2009GL040222.
  24. Vinnikov, K.Y., A. Robock, R.J. Stouffer, J.E. Walsh, C.L. Parkinson, D.J. Cavalieri, J.F.B. Mitchell, D. Garrett, and V.F. Zakharov, 1999. Global warming and northern hemisphere sea ice extent, Science, 286(5446): 1934-1937. https://doi.org/10.1126/science.286.5446.1934

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