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http://dx.doi.org/10.7780/kjrs.2014.30.5.12

Analysis of Sea Route to the Jangbogo Antarctic Research Station by using Passive Microwave Sea Ice Concentration Data  

Kim, Yeonchun (Department of Geophysics, Kangwon National University)
Ji, Yeonghun (Department of Geophysics, Kangwon National University)
Han, Hyangsun (Department of Geophysics, Kangwon National University)
Lee, Joohan (Technical Support & Polar Safety Team, Korea Polar Research Institute)
Lee, Hoonyol (Department of Geophysics, Kangwon National University)
Publication Information
Korean Journal of Remote Sensing / v.30, no.5, 2014 , pp. 677-686 More about this Journal
Abstract
Sea ice covers wide area in Terra Nova Bay in East Antarctica where the Jangbogo Antarctic Research Station was built in 2014, which affects greatly on the sailing of an icebreaker research vessel. In this study, we analyzed the optimum sea route and sailable period of the icebreaker to visit the Jangbogo Antarctic Research Station by using sea ice concentration data observed by passive microwave sensors such as Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager/Sounder (SSMIS) for the last decade, and by using sea route of the Araon, an icebreaker of Republic of Korea, from 2010 to 2012. It is found that Araon sailed in the route of sea ice concentration up to 78%. Sailing speed of the Araon decreased due to increasing sea ice concentration. However, Araon maintained the speed close to the average speed for the entire sailing period (~11 kn) in the route of sea ice concentration up to 70%. Therefore, we confirm that the Araon can sail typically in the route which shows sea ice concentration below 70%. We derived annually available sailing period in recent 10 years for the sea route of the Araon in 2010, 2011 and 2012, which is defined as the period showing sea ice concentration below 70% through the route. Maximum sailable period was analyzed to be 61 and 62 days for the route of the Araon in 2010 and 2011, respectively. However, the typical sailing in the routes was unavailable in some years because sea ice concentration was higher than 70% through the routes. Meanwhile, the sailable period for the routes of the Araon in 2012 was observed in every year, which was a minimum of 15 days and is a maximum of 89 days. Therefore, we could suggest that optimum route of icebreaker to visit the Jangbogo Antarctic Research Station is the route of the Araon in 2012. High resolution images from SAR or optical sensors are necessary to investigate sea ice condition near shoreline of Jangbogo research station due to several kilometers of low resolution of sea ice concentration.
Keywords
sea ice concentration; sea route; passive microwave sensor; Terra Nova Bay; Jangbogo Antarctic Research Station; SSM/I; SSMIS;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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1 Han, H. and H. Lee, 2007. Comparative study of KOMPSAT-1 EOC images and SSM/I NASA Team sea ice concentration of the Arctic, Korean Journal of Remote Sensing, 23(6): 507-520 (in Korean with English abstract).   과학기술학회마을   DOI
2 Han, H. and H. Lee, 2011a. Analysis of surface displacement of glaciers and sea ice around Canisteo Peninsula, West Antarctica, by using 4-pass DInSAR technique, Korean Journal of Remote Sensing, 27(5): 535-542 (in Korean with English abstract).   과학기술학회마을   DOI
3 Han, H. and H. Lee, 2011b. Microwave radiation characteristics of glacial ice in the AMSR-E NASA Team2 algorithm, Korean Journal of Remote Sensing, 27(5): 543-553 (in Korean with English abstract).   과학기술학회마을   DOI
4 Ivanova, N., O.M. Johannessen, L.T. Pedersen, and R.T. Tonboe, 2014. Retrieval of Arctic sea ice parameters by satellite passive microwave sensors: A comparison of eleven sea ice concentration algorithms, IEEE Transactions on Geoscience and Remote Sensing, 52(11): 7233-7246.   DOI
5 Lee, H. and H. Han, 2008. Evaluation of SSM/I and AMSR-E sea ice concentrations in the Antarctic spring using KOMPSAT-1 EOC images, IEEE Transactions on Geoscience and Remote Sensing, 46(7): 1905-1912.   DOI
6 Parkinson, C.L., 2004. Southern Ocean sea ice and its wider linkages: insights revealed from models and observations, Antarctic Science, 16(4): 387-400.   DOI
7 Parkinson, C.L. and D.J. Cavalieri, 2012. Antarctic sea ice variability and trends, 1979-2010, The Cryosphere, 6: 931-956.   DOI
8 Tamura, T., K.I. Ohshima, T. Markus, D.J. Cavalieri, S. Nihashi, and N. Hirasawa, 2007. Estimation of thin ice thickness and detection of fast ice from SSM/I data in the Antarctic Ocean, Journal of Atmospheric and Oceanic Technology, 24(10): 1757-1772.   DOI
9 Thomas, D.N. and G.S. Dieckmann, 2003. Sea ice: An Introduction to Its Physics, Chemistry, Biology, and Geology, Blackwell Science, Oxford, UK.
10 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.   DOI
11 Cavalieri, D.J., P. Gloersen, and W.J. Campbell, 1984. Determination of sea ice parameters with the NIMBUS 7 SMMR, Journal of Geophysical Research, 89(D4): 5355-5369.   DOI
12 Aulicino, G., G. Fusco, S. Kern, and G. Budillon, 2014. Estimation of sea-ice thickness in Ross and Weddell Seas from SSM/I brightness temperatures, IEEE Transactions on Geoscience and Remote Sensing, 52(7): 4122-4140.   DOI
13 Cavalieri, D.J., J.P. Crawford, M.R. Drinkwater, D.T. Eppler, L.D. Farmer, R.R. Jentz, and C.C. Wackerman, 1991. Aircraft active and passive microwave validation of sea ice concentration from the Defense Meteorological Satellite Program special sensor microwave imager, Journal of Geophysical Research, 96(C12): 21989-22008.   DOI
14 Bell, W., B. Candy, N. Atkinson, F. Hilton, N. Baker, N. Bormann, G. Kelly, M. Kazumori, W.F. Campbell, and S.D. Swadley, 2008. The assimilation of SSMIS radiances in numerical weather prediction models, IEEE Transactions on Geoscience and Remote Sensing, 46(4): 884-900.   DOI
15 Bjorgo, E., O.M. Johannessen, and M.W. Miles, 1997. Analysis of merged SMMR-SSM/I time series Arctic and Antarctic sea ice parameters 1978-1995, Geophysical Research Letters, 24(4): 413-416.   DOI   ScienceOn
16 Carsey, F.D., 1992. Microwave Remote Sensing of Sea Ice, American Geophysical Union, Washington, USA.
17 Clausi, D.A., 2001. Comparison and fusion of cooccurrence, Gabor and MRF texture features for classification of SAR sea-ice imagery, Atmosphere-Ocean, 39(3): 183-194.   DOI   ScienceOn
18 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.   DOI   ScienceOn
19 Comiso, J.C., R. Kwok, S. Martin, and A.L. Gordon, 2011. Variability and trends in sea ice extent and ice production in the Ross Sea, Journal of Geophysical Research, 116, C04021.
20 Haverkamp, D., L.K. Soh, and C. Tsatsoulis, 1995. A comprehensive, automated approach to determining sea ice thickness from SAR data, IEEE Transactions on Geoscience and Remote Sensing, 33(1): 46-57.   DOI
21 Stroeve, J., J. Maslanik, and L. Xiaoming, 1998. An intercomparison of DMSP F11- and F13-Derived Sea Ice Products, Remote Sensing of Environment, 64(2): 132-152.   DOI
22 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.   DOI