Artykuły w czasopismach: „Sea ice”

1

Sukhorukov, Sergiy, i Sveinung Løset. "Friction of sea ice on sea ice". Cold Regions Science and Technology 94 (październik 2013): 1–12. http://dx.doi.org/10.1016/j.coldregions.2013.06.005.

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Mikolajewicz, Uwe, Dmitry V. Sein, Daniela Jacob, Torben Königk, Ralf Podzun i Tido Semmler. "Simulating Arctic sea ice variability with a coupled regional atmosphere-ocean-sea ice model". Meteorologische Zeitschrift 14, nr 6 (19.12.2005): 793–800. http://dx.doi.org/10.1127/0941-2948/2005/0083.

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Timco, Garry W. "Sea ice". Cold Regions Science and Technology 60, nr 2 (luty 2010): 105–6. http://dx.doi.org/10.1016/j.coldregions.2009.11.001.

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4

Hoppmann, Mario, Marcel Nicolaus, Stephan Paul, Priska A. Hunkeler, Günther Heinemann, Sascha Willmes, Ralph Timmermann i in. "Ice platelets below Weddell Sea landfast sea ice". Annals of Glaciology 56, nr 69 (2015): 175–90. http://dx.doi.org/10.3189/2015aog69a678.

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AbstractBasal melt of ice shelves may lead to an accumulation of disc-shaped ice platelets underneath nearby sea ice, to form a sub-ice platelet layer. Here we present the seasonal cycle of sea ice attached to the Ekström Ice Shelf, Antarctica, and the underlying platelet layer in 2012. Ice platelets emerged from the cavity and interacted with the fast-ice cover of Atka Bay as early as June. Episodic accumulations throughout winter and spring led to an average platelet-layer thickness of 4 m by December 2012, with local maxima of up to 10 m. The additional buoyancy partly prevented surface flooding and snow-ice formation, despite a thick snow cover. Subsequent thinning of the platelet layer from December onwards was associated with an inflow of warm surface water. The combination of model studies with observed fast-ice thickness revealed an average ice-volume fraction in the platelet layer of 0.25 ± 0.1. We found that nearly half of the combined solid sea-ice and ice-platelet volume in this area is generated by heat transfer to the ocean rather than to the atmosphere. The total ice-platelet volume underlying Atka Bay fast ice was equivalent to more than one-fifth of the annual basal melt volume under the Ekström Ice Shelf.

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5

Sayag, Roiy, Eli Tziperman i Michael Ghil. "Rapid switch-like sea ice growth and land ice-sea ice hysteresis". Paleoceanography 19, nr 1 (marzec 2004): n/a. http://dx.doi.org/10.1029/2003pa000946.

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6

Golden, Kenneth M., Luke G. Bennetts, Elena Cherkaev, Ian Eisenman, Daniel Feltham, Christopher Horvat, Elizabeth Hunke i in. "Modeling Sea Ice". Notices of the American Mathematical Society 67, nr 10 (1.11.2020): 1. http://dx.doi.org/10.1090/noti2171.

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7

Newton, Alicia. "Sea-ice effects". Nature Geoscience 6, nr 7 (27.06.2013): 513. http://dx.doi.org/10.1038/ngeo1881.

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8

Ray, G. Carleton, Gary L. Hufford, Igor I. Krupnik i James E. Overland. "Diminishing Sea Ice". Science 321, nr 5895 (12.09.2008): 1443.3–1445. http://dx.doi.org/10.1126/science.321.5895.1443c.

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9

Arrigo, Kevin R. "Sea Ice Ecosystems". Annual Review of Marine Science 6, nr 1 (3.01.2014): 439–67. http://dx.doi.org/10.1146/annurev-marine-010213-135103.

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10

Feltham, Daniel L. "Sea Ice Rheology". Annual Review of Fluid Mechanics 40, nr 1 (styczeń 2008): 91–112. http://dx.doi.org/10.1146/annurev.fluid.40.111406.102151.

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11

Ye, Yufang, Mohammed Shokr, Georg Heygster i Gunnar Spreen. "Improving Multiyear Sea Ice Concentration Estimates with Sea Ice Drift". Remote Sensing 8, nr 5 (10.05.2016): 397. http://dx.doi.org/10.3390/rs8050397.

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12

Seo, Minji, Chang Suk Lee, Hyunji Kim, Morang Huh i Kyung-Soo Han. "Relationship between sea ice concentration and sea ice albedo over Antarctica". Korean Journal of Remote Sensing 31, nr 4 (31.08.2015): 347–51. http://dx.doi.org/10.7780/kjrs.2015.31.4.7.

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13

Bi, Haibo, Min Fu, Ke Sun, Yilin Liu, Xiuli Xu i Haijun Huang. "Arctic sea ice thickness changes in terms of sea ice age". Acta Oceanologica Sinica 35, nr 10 (październik 2016): 1–10. http://dx.doi.org/10.1007/s13131-016-0922-x.

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14

Itkin, Polona, i Thomas Krumpen. "Winter sea ice export from the Laptev Sea preconditions the local summer sea ice cover and fast ice decay". Cryosphere 11, nr 5 (23.10.2017): 2383–91. http://dx.doi.org/10.5194/tc-11-2383-2017.

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Abstract. Ice retreat in the eastern Eurasian Arctic is a consequence of atmospheric and oceanic processes and regional feedback mechanisms acting on the ice cover, both in winter and summer. A correct representation of these processes in numerical models is important, since it will improve predictions of sea ice anomalies along the Northeast Passage and beyond. In this study, we highlight the importance of winter ice dynamics for local summer sea ice anomalies in thickness, volume and extent. By means of airborne sea ice thickness surveys made over pack ice areas in the south-eastern Laptev Sea, we show that years of offshore-directed sea ice transport have a thinning effect on the late-winter sea ice cover. To confirm the preconditioning effect of enhanced offshore advection in late winter on the summer sea ice cover, we perform a sensitivity study using a numerical model. Results verify that the preconditioning effect plays a bigger role for the regional ice extent. Furthermore, they indicate an increase in volume export from the Laptev Sea as a consequence of enhanced offshore advection, which has far-reaching consequences for the entire Arctic sea ice mass balance. Moreover we show that ice dynamics in winter not only preconditions local summer ice extent, but also accelerate fast-ice decay.

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15

Bassett, Christopher, Andone C. Lavery, Ted Maksym, Jeremy Wilkinson, Dajun Tang i Scott Pegau. "Development of acoustic remote sensing techniques for sea ice, oil under sea ice, and oil encapsulated in sea ice". Journal of the Acoustical Society of America 138, nr 3 (wrzesień 2015): 1742. http://dx.doi.org/10.1121/1.4933490.

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16

Röthlisberger, Regine, i Nerilie Abram. "Sea-ice proxies in Antarctic ice cores". PAGES news 17, nr 1 (styczeń 2009): 24–26. http://dx.doi.org/10.22498/pages.17.1.24.

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17

Ledley, Tamara Shapiro. "Sea ice: Multiyear cycles and white ice". Journal of Geophysical Research 90, nr D3 (1985): 5676. http://dx.doi.org/10.1029/jd090id03p05676.

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18

Haas, C., i D. N. Thomas. "Glacial-ice fragments in Antarctic sea ice". Journal of Glaciology 41, nr 138 (1995): 432–35. http://dx.doi.org/10.1017/s0022143000016312.

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19

Fetterer, Florence, i Kenneth Knowles. "Sea ice index monitors polar ice extent". Eos, Transactions American Geophysical Union 85, nr 16 (20.04.2004): 163. http://dx.doi.org/10.1029/2004eo160007.

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20

Smith, I. J., P. J. Langhorne, R. D. Frew, R. Vennell i T. G. Haskell. "Sea ice growth rates near ice shelves". Cold Regions Science and Technology 83-84 (grudzień 2012): 57–70. http://dx.doi.org/10.1016/j.coldregions.2012.06.005.

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21

Haas, C., i D. N. Thomas. "Glacial-ice fragments in Antarctic sea ice". Journal of Glaciology 41, nr 138 (1995): 432–35. http://dx.doi.org/10.3189/s0022143000016312.

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22

Prasad, Siva, Igor Zakharov, Peter McGuire, Desmond Power i Martin Richard. "Estimation of sea ice parameters from sea ice model with assimilated ice concentration and SST". Cryosphere 12, nr 12 (21.12.2018): 3949–65. http://dx.doi.org/10.5194/tc-12-3949-2018.

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Abstract. A multi-category numerical sea ice model CICE was used along with data assimilation to derive sea ice parameters in the region of Baffin Bay and Labrador Sea. The assimilation of ice concentration was performed using the data derived from the Advanced Microwave Scanning Radiometer (AMSR-E and AMSR2). The model uses a mixed-layer slab ocean parameterization to compute the sea surface temperature (SST) and thereby to compute the freezing and melting potential of ice. The data from Advanced Very High Resolution Radiometer (AVHRR-only optimum interpolation analysis) were used to assimilate SST. The modelled ice parameters including concentration, ice thickness, freeboard and keel depth were compared with parameters estimated from remote-sensing data. The ice thickness estimated from the model was compared with the measurements derived from Soil Moisture Ocean Salinity – Microwave Imaging Radiometer using Aperture Synthesis (SMOS–MIRAS). The model freeboard estimates were compared with the freeboard measurements derived from CryoSat2. The ice concentration, thickness and freeboard estimates from the model assimilated with both ice concentration and SST were found to be within the uncertainty in the observation except during March. The model-estimated draft was compared with the measurements from an upward-looking sonar (ULS) deployed in the Labrador Sea (near Makkovik Bank). The difference between modelled draft and ULS measurements estimated from the model was found to be within 10 cm. The keel depth measurements from the ULS instruments were compared to the estimates from the model to retrieve a relationship between the ridge height and keel depth.

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23

Macdonald, Grant J., Predrag Popović i David P. Mayer. "Formation of sea ice ponds from ice-shelf runoff, adjacent to the McMurdo Ice Shelf, Antarctica". Annals of Glaciology 61, nr 82 (11.03.2020): 73–77. http://dx.doi.org/10.1017/aog.2020.9.

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AbstractPonds that form on sea ice can cause it to thin or break-up, which can promote calving from an adjacent ice shelf. Studies of sea ice ponds have predominantly focused on Arctic ponds formed by in situ melting/ponding. Our study documents another mechanism for the formation of sea ice ponds. Using Landsat 8 and Sentinel-2 images from the 2015–16 to 2018–19 austral summers, we analyze the evolution of sea ice ponds that form adjacent to the McMurdo Ice Shelf, Antarctica. We find that each summer, meltwater flows from the ice shelf onto the sea ice and forms large (up to 9 km2) ponds. These ponds decrease the sea ice's albedo, thinning it. We suggest the added mass of runoff causes the ice to flex, potentially promoting sea-ice instability by the ice-shelf front. As surface melting on ice shelves increases, we suggest that ice-shelf surface hydrology will have a greater effect on sea-ice stability.

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24

Han, Lu, Haihua Chen, Lei Guan i Lele Li. "Multiple Sea Ice Type Retrieval Using the HaiYang-2B Scatterometer in the Arctic". Remote Sensing 15, nr 3 (23.01.2023): 678. http://dx.doi.org/10.3390/rs15030678.

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Sea ice type classification is of great significance for the exploration of waterways, fisheries, and offshore operations in the Arctic. However, to date, there is no multiple remote sensing method to detect sea ice type in the Arctic. This study develops a multiple sea ice type algorithm using the HaiYang-2B Scatterometer (HY-2B SCA). First, the parameters most applicable to classify sea ice type are selected through feature extraction, and a stacking model is established for the first time, which integrates decision tree and image segmentation algorithms. Finally, multiple sea ice types are classified in the Arctic, comprising Nilas, Young Ice, First Year Ice, Old Ice, and Fast Ice. Comparing the results with the Ocean and Sea Ice Satellite Application Facility (OSI-SAF) Sea Ice Type dataset (SIT) indicates that the sea ice type classified by HY-2B SCA (Stacking-HY2B) is similar to OSI-SAF SIT with regard to the changing trends in extent of sea ice. We use the Copernicus Marine Environment Monitoring Service (CMEMS) high-resolution sea ice type data and EM-Bird ice thickness data to validate the result, and accuracies of 87% and 88% are obtained, respectively. This indicates that the algorithm in this work is comparable with the performance of OSI-SAF dataset, while providing information of multiple sea ice types.

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25

Lange, M. A., S. F. Ackley, P. Wadhams, G. S. Dieckmann i H. Eicken. "Development of Sea Ice in the Weddell Sea". Annals of Glaciology 12 (1989): 92–96. http://dx.doi.org/10.3189/s0260305500007023.

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We report on the development and physical properties of sea ice in the central and eastern Weddell Sea. The investigations were part of the Winter Weddell Sea Project 1986, which extended over the months of July through December. Major elements of the glaciological part of this study included continuous shipborne observations of sea-ice conditions and occasional helicopter reconnaissance flights, extensive measurements of snow and ice thicknesses at daily ice stations, and detailed analyses of sampled ice cores from each ice station. Textural investigations of the sampled ice revealed the dominance of frazil ice in the central Weddell Sea and the occurrence of an additional ice class, called platelet ice, together with the commonly known frazil and congelation ice in the coastal region of the eastern Weddell Sea. These results, in combination with the visual ice observations, reveal two major mechanisms for sea-ice generation in the Antarctic, which were not sufficiently well accounted for in previous investigations. In the central Weddell Sea, a cycle of pancake-ice formation and its growth into consolidated floes seems to be the dominant process of the advancing sea-ice edge. In the coastal waters, the growing sea-ice cover consists, to a considerable degree, of ice platelets which are formed in the underlying water column in front of the ice-shelf edges. Thus, congelation-ice growth, which is mainly controlled by atmospheric, thermodynamic forcing, seems to be of less importance in the central and south-eastern Weddell Sea than, for example, in the Arctic Basin.

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26

Lange, M. A., S. F. Ackley, P. Wadhams, G. S. Dieckmann i H. Eicken. "Development of Sea Ice in the Weddell Sea". Annals of Glaciology 12 (1989): 92–96. http://dx.doi.org/10.1017/s0260305500007023.

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We report on the development and physical properties of sea ice in the central and eastern Weddell Sea. The investigations were part of the Winter Weddell Sea Project 1986, which extended over the months of July through December. Major elements of the glaciological part of this study included continuous shipborne observations of sea-ice conditions and occasional helicopter reconnaissance flights, extensive measurements of snow and ice thicknesses at daily ice stations, and detailed analyses of sampled ice cores from each ice station. Textural investigations of the sampled ice revealed the dominance of frazil ice in the central Weddell Sea and the occurrence of an additional ice class, called platelet ice, together with the commonly known frazil and congelation ice in the coastal region of the eastern Weddell Sea. These results, in combination with the visual ice observations, reveal two major mechanisms for sea-ice generation in the Antarctic, which were not sufficiently well accounted for in previous investigations. In the central Weddell Sea, a cycle of pancake-ice formation and its growth into consolidated floes seems to be the dominant process of the advancing sea-ice edge. In the coastal waters, the growing sea-ice cover consists, to a considerable degree, of ice platelets which are formed in the underlying water column in front of the ice-shelf edges. Thus, congelation-ice growth, which is mainly controlled by atmospheric, thermodynamic forcing, seems to be of less importance in the central and south-eastern Weddell Sea than, for example, in the Arctic Basin.

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27

Schröder, David, Danny L. Feltham, Michel Tsamados, Andy Ridout i Rachel Tilling. "New insight from CryoSat-2 sea ice thickness for sea ice modelling". Cryosphere 13, nr 1 (14.01.2019): 125–39. http://dx.doi.org/10.5194/tc-13-125-2019.

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Abstract. Estimates of Arctic sea ice thickness have been available from the CryoSat-2 (CS2) radar altimetry mission during ice growth seasons since 2010. We derive the sub-grid-scale ice thickness distribution (ITD) with respect to five ice thickness categories used in a sea ice component (Community Ice CodE, CICE) of climate simulations. This allows us to initialize the ITD in stand-alone simulations with CICE and to verify the simulated cycle of ice thickness. We find that a default CICE simulation strongly underestimates ice thickness, despite reproducing the inter-annual variability of summer sea ice extent. We can identify the underestimation of winter ice growth as being responsible and show that increasing the ice conductive flux for lower temperatures (bubbly brine scheme) and accounting for the loss of drifting snow results in the simulated sea ice growth being more realistic. Sensitivity studies provide insight into the impact of initial and atmospheric conditions and, thus, on the role of positive and negative feedback processes. During summer, atmospheric conditions are responsible for 50 % of September sea ice thickness variability through the positive sea ice and melt pond albedo feedback. However, atmospheric winter conditions have little impact on winter ice growth due to the dominating negative conductive feedback process: the thinner the ice and snow in autumn, the stronger the ice growth in winter. We conclude that the fate of Arctic summer sea ice is largely controlled by atmospheric conditions during the melting season rather than by winter temperature. Our optimal model configuration does not only improve the simulated sea ice thickness, but also summer sea ice concentration, melt pond fraction, and length of the melt season. It is the first time CS2 sea ice thickness data have been applied successfully to improve sea ice model physics.

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28

Wolff, Eric W., R. Gersonde i A. de Vernal. "Reconstructing past sea ice". Past Global Changes Magazine 22, nr 1 (kwiecień 2014): 50. http://dx.doi.org/10.22498/pages.22.1.50.

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29

KOZLOV, A. I., i A. I. LOGVIN. "Radiopolarimetry of Sea Ice". Turkish Journal of Physics 20, nr 4 (1.01.1996): 308–12. http://dx.doi.org/10.55730/1300-0101.2568.

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30

Nehiem, Son, i G. Neumann. "Arctic sea ice change". IOP Conference Series: Earth and Environmental Science 6, nr 1 (1.01.2009): 012012. http://dx.doi.org/10.1088/1755-1307/6/1/012012.

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31

GARRISON, DAVID L. "Antarctic Sea Ice Biota". American Zoologist 31, nr 1 (luty 1991): 17–34. http://dx.doi.org/10.1093/icb/31.1.17.

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32

Stickley, Catherine E. "The sea ice thickens". Nature Geoscience 7, nr 3 (26.01.2014): 165–66. http://dx.doi.org/10.1038/ngeo2080.

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33

Goldin, Tamara. "Bobbing for sea ice". Nature Geoscience 7, nr 4 (28.03.2014): 249. http://dx.doi.org/10.1038/ngeo2132.

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34

Nørgaard-Pedersen, Niels. "Tracking ancient sea ice". Nature Geoscience 2, nr 11 (listopad 2009): 743–44. http://dx.doi.org/10.1038/ngeo676.

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35

Francois, Robert E., Gerald R. Garrison i Timothy Wen. "Reflectivity of sea ice". Journal of the Acoustical Society of America 83, S1 (maj 1988): S46—S47. http://dx.doi.org/10.1121/1.2025365.

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36

Simpkins, Graham. "Sediment-laden sea ice". Nature Reviews Earth & Environment 1, nr 1 (18.12.2019): 9. http://dx.doi.org/10.1038/s43017-019-0014-5.

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37

Schulson, Erland M. "Friction of sea ice". Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 376, nr 2129 (20.08.2018): 20170336. http://dx.doi.org/10.1098/rsta.2017.0336.

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Static and kinetic friction play a fundamental role in sea-ice mechanics. The coefficient of static friction increases with hold time under normal load and is modelled in terms of creep and fracture of asperities in contact. The coefficient of kinetic friction exhibits velocity strengthening at lower speeds and velocity weakening at intermediate speeds. Strengthening is modelled in terms of asperity creep and hardness; weakening is modelled in terms of a progressive increase in the true area of contact wetted by meltwater produced through frictional heating. The concept is introduced of contact size distribution in which the smallest contacts melt first, leading to the onset of weakening; the largest melt last, leading to a third regime of kinetic friction and again to strengthening where hydrodynamics governs. Neither the static nor the kinetic coefficient is significantly affected by the presence of sea water. The paper closes with a few implications for sea-ice mechanics. The paper is based largely upon a critical review of the literature, but includes a more quantitative, physics-based analysis of velocity strengthening and a new analysis of velocity weakening that incorporates parameters that describe the (proposed) fractal character of the sliding interface. This article is part of the theme issue ‘Modelling of sea-ice phenomena’.

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38

Smith, H. J. "GEOLOGY: Sea Ice Amplification". Science 310, nr 5747 (21.10.2005): 409a. http://dx.doi.org/10.1126/science.310.5747.409a.

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39

Yang, Guojin. "Bohai Sea Ice Conditions". Journal of Cold Regions Engineering 14, nr 2 (czerwiec 2000): 54–67. http://dx.doi.org/10.1061/(asce)0887-381x(2000)14:2(54).

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40

Gray, J. M. N. T., i Peter D. Killworth. "Sea Ice Ridging Schemes". Journal of Physical Oceanography 26, nr 11 (listopad 1996): 2420–28. http://dx.doi.org/10.1175/1520-0485(1996)026<2420:sirs>2.0.co;2.

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41

Thorndike, A. S. "Diffusion of sea ice". Journal of Geophysical Research 91, nr C6 (1986): 7691. http://dx.doi.org/10.1029/jc091ic06p07691.

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42

MCGUINNESS, MARK J. "MODELLING SEA ICE GROWTH". ANZIAM Journal 50, nr 3 (styczeń 2009): 306–19. http://dx.doi.org/10.1017/s1446181109000029.

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AbstractThe freezing of water to ice is a classic problem in applied mathematics, involving the solution of a diffusion equation with a moving boundary. However, when the water is salty, the transport of salt rejected by ice introduces some interesting twists to the tale. A number of analytic models for the freezing of water are briefly reviewed, ranging from the famous work by Neumann and Stefan in the 1800s, to the mushy zone models coming out of Cambridge and Oxford since the 1980s. The successes and limitations of these models, and remaining modelling issues, are considered in the case of freezing sea-water in the Arctic and Antarctic Oceans. A new, simple model which includes turbulent transport of heat and salt between ice and ocean is introduced and solved analytically, in two different cases—one where turbulence is given by a constant friction velocity, and the other where turbulence is buoyancy-driven and hence depends on ice thickness. Salt is found to play an important role, lowering interface temperatures, increasing oceanic heat flux, and slowing ice growth.

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43

Dyer, Ira. "Fracture of sea ice". Journal of the Acoustical Society of America 94, nr 3 (wrzesień 1993): 1759. http://dx.doi.org/10.1121/1.408080.

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Saggiomo, Vincenzo, Olga Mangoni i Antonio Pusceddu. "Sea Ice, 2nd edn". Marine Ecology 32, nr 1 (1.02.2011): 132–33. http://dx.doi.org/10.1111/j.1439-0485.2010.00427.x.

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45

Wolff, E. W., R. Gersonde i Anne de Vernal. "Reconstructing Past Sea Ice". Eos, Transactions American Geophysical Union 94, nr 42 (15.10.2013): 376. http://dx.doi.org/10.1002/2013eo420004.

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46

Garrison, DL, i AR Close. "Winter ecology of the sea ice biota in Weddell Sea pack ice". Marine Ecology Progress Series 96 (1993): 17–31. http://dx.doi.org/10.3354/meps096017.

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47

Bouillon, S., i P. Rampal. "On producing sea ice deformation dataset from SAR-derived sea ice motion". Cryosphere Discussions 8, nr 5 (10.10.2014): 5105–35. http://dx.doi.org/10.5194/tcd-8-5105-2014.

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Abstract. We propose a method to compute nearly noise-free sea ice deformation fields from SAR-derived motion and present the results of its application to RGPS sea ice trajectories. The method is based on two steps. The first step consists of using a triangulation of the positions taken from the sea ice trajectories to define a mesh on which a first estimate of sea ice deformation is computed. The second step consists of applying a specific smoother to the deformation field to reduce the artificial noise that arises along discontinuities in the sea ice motion field. From the comparison between unfiltered and filtered fields, we estimate that the artificial noise causes an overestimation of about 60% of opening and closing. The artificial noise also has a strong impact on the statistical distribution of the deformation and on the scaling exponents estimated with multi-fractal analysis. These findings may have serious implications for previous studies as the constant overestimation of the opening and closing could lead to a large overestimation of freezing in leads, salt rejection and sea ice ridging.

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48

Sallila, Heidi, Sinéad Louise Farrell, Joshua McCurry i Eero Rinne. "Assessment of contemporary satellite sea ice thickness products for Arctic sea ice". Cryosphere 13, nr 4 (12.04.2019): 1187–213. http://dx.doi.org/10.5194/tc-13-1187-2019.

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Abstract. Advances in remote sensing of sea ice over the past two decades have resulted in a wide variety of satellite-derived sea ice thickness data products becoming publicly available. Selecting the most appropriate product is challenging given end user objectives range from incorporating satellite-derived thickness information in operational activities, including sea ice forecasting, routing of maritime traffic and search and rescue, to climate change analysis, longer-term modelling, prediction and future planning. Depending on the use case, selecting the most suitable satellite data product can depend on the region of interest, data latency, and whether the data are provided routinely, for example via a climate or maritime service provider. Here we examine a suite of current sea ice thickness data products, collating key details of primary interest to end users. We assess 8 years of sea ice thickness observations derived from sensors on board the CryoSat-2 (CS2), Advanced Very-High-Resolution Radiometer (AVHRR) and Soil Moisture and Ocean Salinity (SMOS) satellites. We evaluate the satellite-only observations with independent ice draft and thickness measurements obtained from the Beaufort Gyre Exploration Project (BGEP) upward looking sonar (ULS) instruments and Operation IceBridge (OIB), respectively. We find a number of key differences among data products but find that products utilizing CS2-only measurements are reliable for sea ice thickness, particularly between ∼0.5 and 4 m. Among data compared, a blended CS2-SMOS product was the most reliable for thin ice. Ice thickness distributions at the end of winter appeared realistic when compared with independent ice draft measurements, with the exception of those derived from AVHRR. There is disagreement among the products in terms of the magnitude of the mean thickness trends, especially in spring 2017. Regional comparisons reveal noticeable differences in ice thickness between products, particularly in the marginal seas in areas of considerable ship traffic.

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Rhodes, Rachael H., Xin Yang i Eric W. Wolff. "Sea Ice Versus Storms: What Controls Sea Salt in Arctic Ice Cores?" Geophysical Research Letters 45, nr 11 (9.06.2018): 5572–80. http://dx.doi.org/10.1029/2018gl077403.

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Kaartokallio, Hermanni, Jaana Tuomainen, Harri Kuosa, Jorma Kuparinen, Pertti J. Martikainen i Kristina Servomaa. "Succession of sea-ice bacterial communities in the Baltic Sea fast ice". Polar Biology 31, nr 7 (2.02.2008): 783–93. http://dx.doi.org/10.1007/s00300-008-0416-1.

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