Journal of Oceanography

, Volume 69, Issue 2, pp 215–227 | Cite as

Dual-polarized ratio algorithm for retrieving Arctic sea ice concentration from passive microwave brightness temperature

  • Shugang Zhang
  • Jinping Zhao
  • Karen Frey
  • Jie Su
Original Article


We present a new algorithm for retrieving sea ice concentration from the AMSR-E data, the dual-polarized ratio (DPR) algorithm. The DPR algorithm is developed using vertically and horizontally polarized brightness temperatures at the same channel of 36.5 GHz. It depends on the ratio of dual-polarized emissivity, α, which is determined empirically at about 0.92 by remotely sensed brightness temperature in winter and used for the other seasons as well. The ice concentration retrieved by the DPR is compared with those by the NT2 and ABA algorithms. Since the main difference among these algorithms takes place in marginal ice zones, 17 marginal ice zones are chosen. The retrieved ice concentrations in these zones are examined by the ice concentration obtained by the MODIS data. The mean error, root-mean-square error and mean absolute error of the DPR algorithm are relatively better than those from the other two algorithms. The results of this study illustrate that the DPR algorithm is a more accurate algorithm for retrieving sea ice concentration from the AMSR-E brightness temperature, and can be used for operational purposes.


Arctic Ice concentration AMSR-E Brightness temperature Dual-polarized ratio algorithm 



This study is supported by the Global Change Research Program (2010CB951403) and the Hi-tech Program of China (2008AA121701).


  1. Aagaard K, Coachaman LK, Mack EC (1981) On the halocline of the Arctic Ocean. Deep Sea Res 28:529–545CrossRefGoogle Scholar
  2. Andersen S, Tonboe RT, Kaleschke L, Heygster G, Pedersen LT (2007) Intercomparison of passive microwave sea ice concentration retrievals over the high-concentration Arctic sea ice. J Geophys Res 112:C08004. doi: 10.1029/2006JC003543 CrossRefGoogle Scholar
  3. Cavalieri DJ, Gloersen P, Campbell WJ (1984) Determination of sea ice parameters with the NIMBUS 7 SMMR. J Geophys Res 89(D4):5355–5369Google Scholar
  4. Cavalieri DJ, Martin S (1994) The contribution of Alaskan, Siberian, and Canadian coastal polynyas to the cold halocline layer of the Arctic Ocean. J Geophys Res 99(C9) 18: 343–18,362. doi: 10.1029/94JC01169
  5. Comiso JC (1986) Characteristics of Arctic Winter sea ice form satellite Multispectral microwave observations. J Geophys Res 91(C1):975–994Google Scholar
  6. Comiso JC (1995) SSM/I concentrations using the Bootstrap algorithm. NASA Spec Publ 1380:40Google Scholar
  7. Comiso JC, Sullivan CW (1986) Satellite microwave and in Situ observations of the Weddell sea ice cover and its marginal ice zone. J Geophys Res 91(C8):9663–9681Google Scholar
  8. Comiso JC, Zwally HJ (1982) Antarctic sea ice concentration inferred from Nimbus 5 ESMR and Landsat imagery. J Geophys Res 87:5836–5844CrossRefGoogle Scholar
  9. Comiso JC, Ackley SF, Gordon AL (1984) Antarctic sea ice microwave signatures and their correlation with in situ ice observations. J Geophys Res 89:662–672CrossRefGoogle Scholar
  10. Comiso JC, Cavalieri DJ, Parkinson CL, Gloersen P (1997) Passive microwave algorithms for sea ice concentration: a comparison of two techniques. Remote Sens Environ 60:357–384CrossRefGoogle Scholar
  11. Comiso JC, Member S, Cavalieri DJ, Markus T (2003) Sea ice concentration, ice temperature, and snow depth using AMSR-E data. IEEE Trans Geosci Remote Sens 41:243–252CrossRefGoogle Scholar
  12. Grenfell TC (1983) A theoretical model of the optical properties of sea ice in the visible and near infrared. J Geophys Res 88:9723–9735CrossRefGoogle Scholar
  13. Grenfell TC, Lohanick AW (1985) Temporal variations of the microwave signatures of sea ice during the late spring and early summer near Mould Bay NWT. J Geophys Res 90(C3):5063–5074Google Scholar
  14. Heinrichs JF, Cavalieri DJ, Markus T (2006) Assessment of the AMSR-E sea ice concentration product at the ice edge using RADARSAT-1 and MODIS imagery. IEEE Trans Geosci Remote Sens 44(11):3070–3080CrossRefGoogle Scholar
  15. Lemke P (1987) A coupled one-dimensional sea ice-mixed layer model. J Geophys Res 92(C12):13,164–13,172Google Scholar
  16. Liou KN (2002) An introduction to atmospheric radiation, chap 7, 2nd edn. Elsevier Science, Amsterdam, pp 414–419Google Scholar
  17. Lu P, Li ZJ, Cheng B, Lei RB, Zhang R (2010) Sea ice surface features in Arctic summer 2008: aerial observations. Remote Sens Environ 114:693–699CrossRefGoogle Scholar
  18. Markus T, Cavalieri DJ (2000) An enhancement of the NASA Team sea ice algorithm. IEEE Trans Geosci Remote Sens 38:1387–1398CrossRefGoogle Scholar
  19. Maykut GA (1978) Energy exchange over young sea ice in the central arctic. J Geophys Res 83(C7):3646–3658Google Scholar
  20. Perovich DK, Tucker WB III, Ligett KA (2002) Aerial observations of the evolution of ice surface conditions during summer. J Geophys Res. 107(C10):8048. doi: 10.1029/2000JC000449
  21. Smith DM (1996) Extraction of winter sea-ice concentration in the Greenland and Barents Seas from SSM/I data. Int J Remote Sens 17(13):2625–2646CrossRefGoogle Scholar
  22. Spreen G, Kaleschke L, Heygster G (2008) Sea ice remote sensing using AMSR-E 89 GHz channels. J Geophys Res. 113:C02S03. doi: 10.1029/2005JC003384
  23. Svendsen E, Kloster K, Farrelly B, Johannessen OM, Johannessen JA, Campbell WJ, Gloersen P, Cavalieri DJ, Matzler C (1983) Norwegian remote sensing experiment: evaluation of the nimbus 7 scanning multichannel microwave radiometer for sea ice research. J Geophys Res 88:2781–2792CrossRefGoogle Scholar
  24. Svendsen E, Matzler C, Grenfell TC (1987) A model for retrieving total sea ice concentration from spaceborne dual-polarized passive microwave instrument operating near 90 GHz. Int J Remote Sens 8(10):1479–1487CrossRefGoogle Scholar
  25. Wilheit TT (1980) Atmospheric corrections to microwave radiometer data. Boundary Layer Meteorol 18:65–77CrossRefGoogle Scholar
  26. Ye XX, Su J, Wang Y, Hao GH, Hou JQ (2011) Assessment of AMSR-E sea ice concentration in ice margin zone using MODIS data. In: Proceedings of the international conference on remote sensing environment and transportation engineering (RSETE) of IEEEGoogle Scholar
  27. Zhao JP, Ren JP (2000) From airlines digital image extraction method of arctic sea ice form parameters. J Remote Sens 4(4):271–278Google Scholar
  28. Zwally HJ, Comiso JC, Parkinson CL, Cavalieri DJ, Gloersen P (2002) Variability of Antarctic sea ice 1979–1998. J Geophys Res 107:3041. doi: 10.1029/2000JC000733 CrossRefGoogle Scholar
  29. Zwally HJ, Comiso JC, Parkinson CL, Campbell WJ, Carsey FD, Gloersen P (1983) Antarctic sea ice, 1973–1976: satellite passive microwave observations. Washington, DC. NASA SP-459Google Scholar

Copyright information

© The Oceanographic Society of Japan and Springer Japan 2013

Authors and Affiliations

  • Shugang Zhang
    • 1
  • Jinping Zhao
    • 1
  • Karen Frey
    • 2
  • Jie Su
    • 1
  1. 1.Ocean University of ChinaQingdaoPeople’s Republic of China
  2. 2.Clark UniversityWorcesterUSA

Personalised recommendations