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Can we extend local sea-ice measurements to satellite scale? An example from the N-ICE2015 expedition

  • Anja Rösel (a1), Jennifer King (a1), Anthony P. Doulgeris (a2), Penelope M. Wagner (a3), A. Malin Johansson (a2) and Sebastian Gerland (a1)...
Abstract

Knowledge of Arctic sea-ice conditions is of great interest for Arctic residents, as well as for commercial usage, and to study the effects of climate change. Information gained from analysis of satellite data contributes to this understanding. In the course of using in situ data in combination with remotely sensed data, the question of how representative local scale measurements are of a wider region may arise. We compare in situ total sea-ice thickness measurements from the Norwegian young sea ICE expedition in the area north of Svalbard with airborne-derived total sea-ice thickness from electromagnetic soundings. A segmented and classified synthetic aperture radar (SAR) quad-pol ALOS-2 Palsar-2 satellite scene was grouped into three simplified ice classes. The area fractions of the three classes are: 11.2% ‘thin’, 74.4% ‘level’, and 14.4% ‘deformed’. The area fractions of the simplified classes from ground- and helicopter-based measurements are comparable with those achieved from the SAR data. Thus, this study shows that there is potential for a stepwise upscaling from in situ, to airborne, to satellite data, which allow us to assess whether in situ data collected are representative of a wider region as observed by satellites.

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This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
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Armstrong, T (1972) World Meteorological Organization. WMO sea-ice nomenclature. Terminology, codes and illustrated glossary. Edition 1970. Geneva, Secretariat of the World Meteorological Organization, 1970. [ix], 147 p. [including 175 photos] corrigenda slip. (WMO/OMM/BMO, No. 259, TP. 145.). Journal of Glaciology, 11(61), 148–149. doi:10.3189/S0022143000022577
Casey, JA, Howell, SE, Tivy, A and Haas, C (2016) Separability of sea ice types from wide swath C- and L-band synthetic aperture radar imagery acquired during the melt season. Remote Sens. Environ., 174, 314328 (doi: 10.1016/j.rse.2015.12.02)
Doulgeris, AP (2013) A simple and extendable segmentation method for multi-polarisation SAR scenes. In Proceedings of POLinSAR 2013, Frascati, Italy, 8 pp
Doulgeris, AP (2015) An automatic calU-distribution and Markov random field segmentation algorithm for PolSAR images. IEEE Trans. Geosci. Remote Sens., 53(4), 18191827 (doi: 10.1109/TGRS.2014.2349575)
Doulgeris, AP and Eltoft, T (2010) Scale mixture of Gaussian modelling of polarimetric SAR data. EURASIP J. Adv. Signal Process., 2010, 113 (doi: 10.1155/2010/874592)
Granskog, M and 5 others (2016) Arctic research on thin ice: consequences of arctic sea ice loss. Eos, Trans. Amer. Geophys. Union, 97 (doi: 10.1029/2016eo044097)
Granskog, MA and 6 others (2017) Snow contribution to first-year and second-year Arctic sea ice mass balance north of Svalbard. J. Geophys. Res.: Oceans, 122, 25392549 (doi: 10.1002/2016jc012398)
Haas, C, Gerland, S, Eicken, H and Miller, H (1997) Comparison of sea-ice thickness measurements under summer and winter conditions in the Arctic using a small electromagnetic induction device. Geophysics, 62(3), 749757 (doi: 10.1190/1.1444184)
Haas, C, Lobach, J, Hendricks, S, Rabenstein, L and Pfaffling, A (2009) Helicopter-borne measurements of sea ice thickness, using a small and lightweight, digital EM system. J. Appl. Geophys., 67(3), 234241 (doi: 10.1016/j.jappgeo.2008.05.005)
Hansen, E and 5 others (2014) Variability in categories of Arctic sea ice in Fram Strait. J. Geophys. Res.: Oceans, 119(10), 71757189 (doi: 10.1002/2014jc010048)
Hara, Y and 5 others (1995) Application of neural networks for sea ice classification in polarimetric SAR images. IEEE Trans. Geosci. Remote Sens, 33(3), 740748
Hughes, N and Wagner, P (2015) Knowledge and forecasts of seaice extent and icebergs – Barents Sea SE and Jan Mayen. In METReport, vol. 26/15. Norwegian Meteorological Institute, Oslo
Itkin, P and 10 others (2017) Thin ice and storms: sea ice deformation from buoy arrays deployed during N-ICE2015. J. Geophys. Res.: Oceans, 122, 46614674 (doi: 10.1002/2016JC012403)
Johannessen, OM and 10 others (2007) Remote sensing of sea ice in the Northern Sea Route: Studies and Applications. Springer-Praxis, Chichester, UK
Johansson, AM and 6 others (2017) Combined observations of Arctic sea ice with near-coincident co-located X, C and L-band SAR satellite remote sensing and helicopter-borne measurements. J. Geophys. Res.: Oceans, 122(1), 669691 (doi: 10.1002/2016JC012273)
Kaleschke, L and 5 others (2015) Improved retrieval of sea ice thickness from SMOS and CryoSat-2. In IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS) (doi: 10.1109/igarss.2015.7327014)
King, J, Gerland, S, Spreen, G and Bratrein, M (2016) [data set] N-ICE2015 sea-ice thickness measurements from helicopter-borne electromagnetic induction sounding (doi: 10.21334/npolar.2016.aa3a5232)
Kovacs, A and Morey, RM (1991) Sounding sea ice thickness using a portable electromagnetic induction instrument. Geophysics, 56(12), 19921998 (doi: 10.1190/1.1443011)
Kwok, R and Cunningham, GF (2015) Variability of Arctic sea ice thickness and volume from CryoSat-2. Philos. Trans. R. Soc.: Math, Phys Eng. Sci., 373 (doi: 10.1098/rsta.2014.0157)
Lindsay, R and Schweiger, A (2015) Arctic sea ice thickness loss determined using subsurface, aircraft, and satellite observations. Cryosphere, 9(1), 269283 (doi: 10.5194/tc-9-269-2015)
Mahoney, AR and 8 others (2015) Taking a look at both sides of the ice: comparison of ice thickness and drift speed as observed from moored, airborne and shore-based instruments near Barrow, Alaska. Ann. Glaciol., 56(69), 363372 (doi: 10.3189/2015aog69a565)
Meier, WN and 9 others (2014) Arctic sea ice in transformation: a review of recent observed changes and impacts on biology and human activity. Rev. Geophys., 52(3), 185217 (doi: 10.1002/2013rg000431)
Meteorological Service of Canada (2005) MANICE: manual of standard procedures for observing and reporting ice conditions. Environment Canada. http://publications.gc.ca/collections/collection_2013/ec/En56-175-2005-eng.pdf
Moen, MA, Anfinsen, S, Doulgeris, A, Renner, A and Gerland, S (2015) Assessing polarimetric SAR sea-ice classifications using consecutive day images. Ann. Glaciol., 56(69) (doi: 10.3189/2015AoG69A802)
Perovich, DK and 7 others (2016) Sea Ice [in Arctic Report Card 2016]. http://www.arctic.noaa.gov/reportcard
Pfaffhuber, AA, Hendricks, S and Kvistedal, YA (2012) Progressing from 1D to 2D and 3D near-surface airborne electromagnetic mapping with a multisensor, airborne sea-ice explorer. Geophysics, 77(4), WB109WB117 (doi: 10.1190/geo2011-0375.1)
Pope, A and 5 others (2017) Community review of southern ocean satellite data needs. Antarct. Sci., 29(2), 97138 (doi: 10.1017/S0954102016000390)
Ressel, R, Singha, S, Lehner, S, Rösel, A and Spreen, G (2016) Investigation into different polarimetric features for sea ice classification using X-band synthetic aperture radar. IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens., 9(7), 31313143 (doi: 10.1109/jstars.2016.2539501)
Ricker, R and 7 others (2017a) Satellite-observed drop of Arctic sea ice growth in winter 2015?2016. Geophys. Res. Lett., 44(7), 32363245, 2016GL072244 (doi: 10.1002/2016GL072244)
Ricker, R and 5 others (2017b) A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data. Cryosphere, 11, 16071623 (doi: 10.5194/tc-11-1607-2017)
Rösel, A and King, J (2017) [data set] N-ICE2015 ice thickness, snow thickness, and freeboard from thickness drillings (doi: 10.21334/npolar.2017.25f70db1)
Rösel, A and 18 others (2016a) [data set] N-ICE2015 total (snow and ice) thickness data from EM31 (doi: 10.21334/npolar.2016.70352512)
Rösel, A and 18 others (2016b) [data set] N-ICE2015 snow depth data with Magna Probe (doi: 10.21334/2016.3d72756d)
Shimada, M, Watanabe, M, Motooka, T, Kankaku, Y and Suzuki, S (2015) Calibration and validation of the PALSAR-2. In IEEE Int. Geoscience and Remote Sensing Symp., IGARS 2015, 26–31 July, Milan, Italy
Wakabayashi, H, Matsuoka, T, Nakamura, K and Nishiro, F (2004) Polarimetric characteristics of sea ice in the Sea of Okhotsk observed by airborne L-band SAR. IEEE Trans. Geosci. Remote Sens., 42(11), 24122425 (doi: 10.1109/TGRS.2004.836259)
Yu, QY and Clausi, DA (2007) SAR sea-ice image analysis based on iterative region growing using semantics. IEEE Trans. Geosci. Remote Sens., 45(12), 39193931
Zakhvatkina, NY, Alexandrov, VY, Johannessen, OM, Sandven, S and Frolov, IY (2013) Classification of sea ice types in ENVISAT synthetic aperture radar images. IEEE Trans. Geosci. Remote Sens., 51(5), 25872600 (doi: 10.1109/TGRS.2012.2212445)
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Annals of Glaciology
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