Research article 24 Jun 2020
Research article | 24 Jun 2020
Spectral attenuation of ocean waves in pack ice and its application in calibrating viscoelastic wave-in-ice models
Sukun Cheng et al.
Related authors
Agnieszka Herman, Sukun Cheng, and Hayley H. Shen
The Cryosphere, 13, 2901–2914, https://doi.org/10.5194/tc-13-2901-2019, https://doi.org/10.5194/tc-13-2901-2019, 2019
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Sea ice interactions with waves are extensively studied in recent years, but mechanisms leading to wave energy attenuation in sea ice remain poorly understood. One of the reasons limiting progress in modelling is a lack of observational data for model validation. The paper presents an analysis of laboratory observations of waves propagating in colliding ice floes. We show that wave attenuation is sensitive to floe size and wave period. A numerical model is calibrated to reproduce this behaviour.
Agnieszka Herman, Sukun Cheng, and Hayley H. Shen
The Cryosphere, 13, 2887–2900, https://doi.org/10.5194/tc-13-2887-2019, https://doi.org/10.5194/tc-13-2887-2019, 2019
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Sea ice interactions with waves are extensively studied in recent years, but mechanisms leading to wave energy attenuation in sea ice remain poorly understood. Close to the ice edge, processes contributing to dissipation include collisions between ice floes and turbulence generated under the ice due to velocity differences between ice and water. This paper analyses details of those processes both theoretically and by means of a numerical model.
Guillaume Dodet, Jean-François Piolle, Yves Quilfen, Saleh Abdalla, Mickaël Accensi, Fabrice Ardhuin, Ellis Ash, Jean-Raymond Bidlot, Christine Gommenginger, Gwendal Marechal, Marcello Passaro, Graham Quartly, Justin Stopa, Ben Timmermans, Ian Young, Paolo Cipollini, and Craig Donlon
Earth Syst. Sci. Data, 12, 1929–1951, https://doi.org/10.5194/essd-12-1929-2020, https://doi.org/10.5194/essd-12-1929-2020, 2020
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Sea state data are of major importance for climate studies, marine engineering, safety at sea and coastal management. However, long-term sea state datasets are sparse and not always consistent. The CCI is a program of the European Space Agency, whose objective is to realize the full potential of global Earth Observation archives in order to contribute to the ECV database. This paper presents the implementation of the first release of the Sea State CCI dataset.
Agnieszka Herman, Sukun Cheng, and Hayley H. Shen
The Cryosphere, 13, 2901–2914, https://doi.org/10.5194/tc-13-2901-2019, https://doi.org/10.5194/tc-13-2901-2019, 2019
Short summary
Short summary
Sea ice interactions with waves are extensively studied in recent years, but mechanisms leading to wave energy attenuation in sea ice remain poorly understood. One of the reasons limiting progress in modelling is a lack of observational data for model validation. The paper presents an analysis of laboratory observations of waves propagating in colliding ice floes. We show that wave attenuation is sensitive to floe size and wave period. A numerical model is calibrated to reproduce this behaviour.
Agnieszka Herman, Sukun Cheng, and Hayley H. Shen
The Cryosphere, 13, 2887–2900, https://doi.org/10.5194/tc-13-2887-2019, https://doi.org/10.5194/tc-13-2887-2019, 2019
Short summary
Short summary
Sea ice interactions with waves are extensively studied in recent years, but mechanisms leading to wave energy attenuation in sea ice remain poorly understood. Close to the ice edge, processes contributing to dissipation include collisions between ice floes and turbulence generated under the ice due to velocity differences between ice and water. This paper analyses details of those processes both theoretically and by means of a numerical model.
Related subject area
Discipline: Sea ice | Subject: Arctic (e.g. Greenland)
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Beena Balan-Sarojini, Steffen Tietsche, Michael Mayer, Magdalena Balmaseda, Hao Zuo, Patricia de Rosnay, Tim Stockdale, and Frederic Vitart
The Cryosphere, 15, 325–344, https://doi.org/10.5194/tc-15-325-2021, https://doi.org/10.5194/tc-15-325-2021, 2021
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Our study for the first time shows the impact of measured sea ice thickness (SIT) on seasonal forecasts of all the seasons. We prove that the long-term memory present in the Arctic winter SIT is helpful to improve summer sea ice forecasts. Our findings show that realistic SIT initial conditions to start a forecast are useful in (1) improving seasonal forecasts, (2) understanding errors in the forecast model, and (3) recognizing the need for continuous monitoring of world's ice-covered oceans.
Chao Min, Qinghua Yang, Longjiang Mu, Frank Kauker, and Robert Ricker
The Cryosphere, 15, 169–181, https://doi.org/10.5194/tc-15-169-2021, https://doi.org/10.5194/tc-15-169-2021, 2021
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An ensemble of four estimates of the sea-ice volume (SIV) variations in Baffin Bay from 2011 to 2016 is generated from the locally merged satellite observations, three modeled sea ice thickness sources (CMST, NAOSIM, and PIOMAS) and NSIDC ice drift data (V4). Results show that the net increase of the ensemble mean SIV occurs from October to April with the largest SIV increase in December, and the reduction occurs from May to September with the largest SIV decline in July.
Mohammed E. Shokr, Zihan Wang, and Tingting Liu
The Cryosphere, 14, 3611–3627, https://doi.org/10.5194/tc-14-3611-2020, https://doi.org/10.5194/tc-14-3611-2020, 2020
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Guillian Van Achter, Leandro Ponsoni, François Massonnet, Thierry Fichefet, and Vincent Legat
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We document the spatio-temporal internal variability of Arctic sea ice thickness and its changes under anthropogenic forcing, which is key to understanding, and eventually predicting, the evolution of sea ice in response to climate change.
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Abigail Smith, Alexandra Jahn, and Muyin Wang
The Cryosphere, 14, 2977–2997, https://doi.org/10.5194/tc-14-2977-2020, https://doi.org/10.5194/tc-14-2977-2020, 2020
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Michael Kern, Robert Cullen, Bruno Berruti, Jerome Bouffard, Tania Casal, Mark R. Drinkwater, Antonio Gabriele, Arnaud Lecuyot, Michael Ludwig, Rolv Midthassel, Ignacio Navas Traver, Tommaso Parrinello, Gerhard Ressler, Erik Andersson, Cristina Martin-Puig, Ole Andersen, Annett Bartsch, Sinead Farrell, Sara Fleury, Simon Gascoin, Amandine Guillot, Angelika Humbert, Eero Rinne, Andrew Shepherd, Michiel R. van den Broeke, and John Yackel
The Cryosphere, 14, 2235–2251, https://doi.org/10.5194/tc-14-2235-2020, https://doi.org/10.5194/tc-14-2235-2020, 2020
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Thomas Krumpen, Florent Birrien, Frank Kauker, Thomas Rackow, Luisa von Albedyll, Michael Angelopoulos, H. Jakob Belter, Vladimir Bessonov, Ellen Damm, Klaus Dethloff, Jari Haapala, Christian Haas, Carolynn Harris, Stefan Hendricks, Jens Hoelemann, Mario Hoppmann, Lars Kaleschke, Michael Karcher, Nikolai Kolabutin, Ruibo Lei, Josefine Lenz, Anne Morgenstern, Marcel Nicolaus, Uwe Nixdorf, Tomash Petrovsky, Benjamin Rabe, Lasse Rabenstein, Markus Rex, Robert Ricker, Jan Rohde, Egor Shimanchuk, Suman Singha, Vasily Smolyanitsky, Vladimir Sokolov, Tim Stanton, Anna Timofeeva, Michel Tsamados, and Daniel Watkins
The Cryosphere, 14, 2173–2187, https://doi.org/10.5194/tc-14-2173-2020, https://doi.org/10.5194/tc-14-2173-2020, 2020
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In October 2019 the research vessel Polarstern was moored to an ice floe in order to travel with it on the 1-year-long MOSAiC journey through the Arctic. Here we provide historical context of the floe's evolution and initial state for upcoming studies. We show that the ice encountered on site was exceptionally thin and was formed on the shallow Siberian shelf. The analyses presented provide the initial state for the analysis and interpretation of upcoming biogeochemical and ecological studies.
Jutta E. Wollenburg, Morten Iversen, Christian Katlein, Thomas Krumpen, Marcel Nicolaus, Giulia Castellani, Ilka Peeken, and Hauke Flores
The Cryosphere, 14, 1795–1808, https://doi.org/10.5194/tc-14-1795-2020, https://doi.org/10.5194/tc-14-1795-2020, 2020
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Based on an observed omnipresence of gypsum crystals, we concluded that their release from melting sea ice is a general feature in the Arctic Ocean. Individual gypsum crystals sank at more than 7000 m d−1, suggesting that they are an important ballast mineral. Previous observations found gypsum inside phytoplankton aggregates at 2000 m depth, supporting gypsum as an important driver for pelagic-benthic coupling in the ice-covered Arctic Ocean.
Xiaoyong Yu, Annette Rinke, Wolfgang Dorn, Gunnar Spreen, Christof Lüpkes, Hiroshi Sumata, and Vladimir M. Gryanik
The Cryosphere, 14, 1727–1746, https://doi.org/10.5194/tc-14-1727-2020, https://doi.org/10.5194/tc-14-1727-2020, 2020
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Yinghui Liu, Jeffrey R. Key, Xuanji Wang, and Mark Tschudi
The Cryosphere, 14, 1325–1345, https://doi.org/10.5194/tc-14-1325-2020, https://doi.org/10.5194/tc-14-1325-2020, 2020
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Alice K. DuVivier, Patricia DeRepentigny, Marika M. Holland, Melinda Webster, Jennifer E. Kay, and Donald Perovich
The Cryosphere, 14, 1259–1271, https://doi.org/10.5194/tc-14-1259-2020, https://doi.org/10.5194/tc-14-1259-2020, 2020
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In autumn 2019, a ship will be frozen into the Arctic sea ice for a year to study system changes. We analyze climate model data from a group of experiments and follow virtual sea ice floes throughout a year. The modeled sea ice conditions along possible tracks are highly variable. Observations that sample a wide range of sea ice conditions and represent the variety and diversity in possible conditions are necessary for improving climate model parameterizations over all types of sea ice.
Xiao-Yi Yang, Guihua Wang, and Noel Keenlyside
The Cryosphere, 14, 693–708, https://doi.org/10.5194/tc-14-693-2020, https://doi.org/10.5194/tc-14-693-2020, 2020
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The post-2007 Arctic sea ice cover is characterized by a remarkable increase in annual cycle amplitude, which is attributed to multiyear variability in spring Bering sea ice extent. We demonstrated that changes of NPGO mode, by anomalous wind stress curl and Ekman pumping, trigger subsurface variability in the Bering basin. This accounts for the significant decadal oscillation of spring Bering sea ice after 2007. The study helps us to better understand the recent Arctic climate regime shift.
Adam W. Bateson, Daniel L. Feltham, David Schröder, Lucia Hosekova, Jeff K. Ridley, and Yevgeny Aksenov
The Cryosphere, 14, 403–428, https://doi.org/10.5194/tc-14-403-2020, https://doi.org/10.5194/tc-14-403-2020, 2020
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The Arctic sea ice cover has been observed to be decreasing, particularly in summer. We use numerical models to gain insight into processes controlling its seasonal and decadal evolution. Sea ice is made of pieces of ice called floes. Previous models have set these floes to be the same size, which is not supported by observations. In this study we show that accounting for variable floe size reveals the importance of sea ice regions close to the open ocean in driving seasonal retreat of sea ice.
Alex West, Mat Collins, Ed Blockley, Jeff Ridley, and Alejandro Bodas-Salcedo
The Cryosphere, 13, 2001–2022, https://doi.org/10.5194/tc-13-2001-2019, https://doi.org/10.5194/tc-13-2001-2019, 2019
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This study presents a framework for examining the causes of model errors in Arctic sea ice volume, using HadGEM2-ES as a case study. Simple models are used to estimate how much of the error in energy arriving at the ice surface is due to error in key Arctic climate variables. The method quantifies how each variable affects sea ice volume balance and shows that for HadGEM2-ES an annual mean low bias in ice thickness is likely due to errors in surface melt onset.
Caixin Wang, Robert M. Graham, Keguang Wang, Sebastian Gerland, and Mats A. Granskog
The Cryosphere, 13, 1661–1679, https://doi.org/10.5194/tc-13-1661-2019, https://doi.org/10.5194/tc-13-1661-2019, 2019
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A warm bias and higher total precipitation and snowfall were found in ERA5 compared with ERA-Interim (ERA-I) over Arctic sea ice. The warm bias in ERA5 was larger in the cold season when 2 m air temperature was < −25 °C and smaller in the warm season than in ERA-I. Substantial anomalous Arctic rainfall in ERA-I was reduced in ERA5, particularly in summer and autumn. When using ERA5 and ERA-I to force a 1-D sea ice model, the effects on ice growth are very small (cm) during the freezing period.
John E. Walsh, J. Scott Stewart, and Florence Fetterer
The Cryosphere, 13, 1073–1088, https://doi.org/10.5194/tc-13-1073-2019, https://doi.org/10.5194/tc-13-1073-2019, 2019
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Persistence-based statistical forecasts of a Beaufort Sea ice severity index as well as September pan-Arctic ice extent show significant statistical skill out to several seasons when the data include the trend. However, this apparent skill largely vanishes when the trends are removed from the data. This finding is consistent with the notion of a springtime “predictability barrier” that has been found in sea ice forecasts based on more sophisticated methods.
Leandro Ponsoni, François Massonnet, Thierry Fichefet, Matthieu Chevallier, and David Docquier
The Cryosphere, 13, 521–543, https://doi.org/10.5194/tc-13-521-2019, https://doi.org/10.5194/tc-13-521-2019, 2019
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The Arctic is a main component of the Earth's climate system. It is fundamental to understand the behavior of Arctic sea ice coverage over time and in space due to many factors, e.g., shipping lanes, the travel and tourism industry, hunting and fishing activities, mineral resource extraction, and the potential impact on the weather in midlatitude regions. In this work we use observations and results from models to understand how variations in the sea ice thickness change over time and in space.
John R. Mioduszewski, Stephen Vavrus, Muyin Wang, Marika Holland, and Laura Landrum
The Cryosphere, 13, 113–124, https://doi.org/10.5194/tc-13-113-2019, https://doi.org/10.5194/tc-13-113-2019, 2019
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Arctic sea ice is projected to thin substantially in every season by the end of the 21st century with a corresponding increase in its interannual variability as the rate of ice loss peaks. This typically occurs when the mean ice thickness falls between 0.2 and 0.6 m. The high variability in both growth and melt processes is the primary factor resulting in increased ice variability. This study emphasizes the importance of short-term variations in ice cover within the mean downward trend.
Marion Lebrun, Martin Vancoppenolle, Gurvan Madec, and François Massonnet
The Cryosphere, 13, 79–96, https://doi.org/10.5194/tc-13-79-2019, https://doi.org/10.5194/tc-13-79-2019, 2019
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The present analysis shows that the increase in the Arctic ice-free season duration will be asymmetrical, with later autumn freeze-up contributing about twice as much as earlier spring retreat. This feature is robustly found in a hierarchy of climate models and is consistent with a simple mechanism: solar energy is absorbed more efficiently than it can be released in non-solar form and should emerge out of variability within the next few decades.
Abigail Smith and Alexandra Jahn
The Cryosphere, 13, 1–20, https://doi.org/10.5194/tc-13-1-2019, https://doi.org/10.5194/tc-13-1-2019, 2019
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Here we assessed how natural climate variations and different definitions impact the diagnosed and projected Arctic sea ice melt season length using model simulations. Irrespective of the definition or natural variability, the sea ice melt season is projected to lengthen, potentially by as much as 4–5 months by 2100 under the business as usual scenario. We also find that different definitions have a bigger impact on melt onset, while natural variations have a bigger impact on freeze onset.
Yuanyuan Zhang, Xiao Cheng, Jiping Liu, and Fengming Hui
The Cryosphere, 12, 3747–3757, https://doi.org/10.5194/tc-12-3747-2018, https://doi.org/10.5194/tc-12-3747-2018, 2018
Aaron Letterly, Jeffrey Key, and Yinghui Liu
The Cryosphere, 12, 3373–3382, https://doi.org/10.5194/tc-12-3373-2018, https://doi.org/10.5194/tc-12-3373-2018, 2018
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Significant reductions in Arctic sea ice and snow cover on Arctic land have led to increases in absorbed solar energy by the surface. Does one play a more important role in Arctic climate change? Using 34 years of satellite data we found that solar energy absorption increased by 10 % over the ocean, which was 3 times greater than over land. Therefore, the decreasing sea ice cover, not changes in terrestrial snow cover, has been the dominant feedback mechanism over the last few decades.
Thomas Kaminski, Frank Kauker, Leif Toudal Pedersen, Michael Voßbeck, Helmuth Haak, Laura Niederdrenk, Stefan Hendricks, Robert Ricker, Michael Karcher, Hajo Eicken, and Ola Gråbak
The Cryosphere, 12, 2569–2594, https://doi.org/10.5194/tc-12-2569-2018, https://doi.org/10.5194/tc-12-2569-2018, 2018
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We present mathematically rigorous assessments of the observation impact (added value) of remote-sensing products and in terms of the uncertainty reduction in a 4-week forecast of sea ice volume and snow volume for three regions along the Northern Sea Route by a coupled model of the sea-ice–ocean system. We quantify the difference in impact between rawer (freeboard) and higher-level (sea ice thickness) products, and the impact of adding a snow depth product.
Steffen Tietsche, Magdalena Alonso-Balmaseda, Patricia Rosnay, Hao Zuo, Xiangshan Tian-Kunze, and Lars Kaleschke
The Cryosphere, 12, 2051–2072, https://doi.org/10.5194/tc-12-2051-2018, https://doi.org/10.5194/tc-12-2051-2018, 2018
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We compare Arctic sea-ice thickness from L-band microwave satellite observations and an ocean–sea ice reanalysis. There is good agreement for some regions and times but systematic discrepancy in others. Errors in both the reanalysis and observational products contribute to these discrepancies. Thus, we recommend proceeding with caution when using these observations for model validation or data assimilation. At the same time we emphasise their unique value for improving sea-ice forecast models.
Elena V. Shalina and Stein Sandven
The Cryosphere, 12, 1867–1886, https://doi.org/10.5194/tc-12-1867-2018, https://doi.org/10.5194/tc-12-1867-2018, 2018
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In this paper we analyze snow data from Soviet airborne expeditions, Sever, which operated in late winter 1959-1986, in the Arctic and made snow measurements on the ice around plane landing sites. The snow measurements were made on the multiyear ice in the central Arctic and on the first-year ice in the Eurasian seas in the areas for which snow characteristics are poorly described in the literature. The main goal of this study is to produce an improved data set of snow depth on the sea ice.
Rebecca J. Rolph, Andrew R. Mahoney, John Walsh, and Philip A. Loring
The Cryosphere, 12, 1779–1790, https://doi.org/10.5194/tc-12-1779-2018, https://doi.org/10.5194/tc-12-1779-2018, 2018
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Using thresholds of physical climate variables developed from community observations, together with two large-scale datasets, we have produced local indices directly relevant to the impacts of a reduced sea ice cover on Alaska coastal communities. We demonstrate how community observations can inform use of large-scale datasets to derive these locally relevant indices.
Xianmin Hu, Jingfan Sun, Ting On Chan, and Paul G. Myers
The Cryosphere, 12, 1233–1247, https://doi.org/10.5194/tc-12-1233-2018, https://doi.org/10.5194/tc-12-1233-2018, 2018
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We evaluated the sea ice thickness simulation in the Canadian Arctic Archipelago region using 1/4 and 1/12 degree NEMO LIM2 configurations. Model resolution dose not play a significant role. Relatively smaller thermodynamic contribution in the winter season is found in the thick ice covered areas, with larger contributions in the thin ice covered regions. No significant trend in winter maximum ice volume is found in the northern CAA and Baffin Bay but a decline is simulated within Parry Channel.
Cited articles
Ardhuin, F., Stopa, J., Chapron, B., Collard, F., Smith, M., Thomson, J.,
Doble, M., Blomquist, B., Persson, O., Collins III, C. O., and Wadhams P.:
Measuring ocean waves in sea ice using SAR imagery: A quasi-deterministic
approach evaluated with Sentinel-1 and in situ data, Remote Sens.
Environ., 189, 211–222, 2017.
Ardhuin, F., Boutin, G., Stopa, J., Girard-Ardhuin, F., Melsheimer, C.,
Thomson, J., Kohout, A., Doble, M., and Wadhams, P.: Wave attenuation
through an Arctic marginal ice zone on 12 October 2015: 2. Numerical
modeling of waves and associated ice breakup, J. Geophys.
Res.-Oceans, 123, 5652–5668, 2018.
Bennetts, L. G. and Squire, V. A.: Model sensitivity analysis of
scattering-induced attenuation of ice-coupled waves, Ocean Model., 45,
1–13, 2012.
Bennetts, L. G. and Williams, T. D.: Water wave transmission by an array of
floating discs, P. Roy. Soc. A, 471, 20140698, https://doi.org/10.1098/rspa.2014.0698, 2015.
Bonjean, F. and Lagerloef, G. S. E.: Diagnostic model and analysis of the surface currents in the tropical Pacific Ocean, J. Phys. Oceanogr., 32, 2938–2954, https://doi.org/10.1175/1520-0485(2002)032<2938:DMAAOT>2.0.CO;2, 2002.
Cheng, S., Rogers, W. E., Thomson, J., Smith, M., Doble, M. J., Wadhams, P.,
Kohout, A. L., Lund, B., Persson, O. P., Collins III, C. O., Ackley, C. F.,
Montiel F., and Shen H. H.: Calibrating a viscoelastic sea ice model for
wave propagation in the Arctic fall marginal ice zone, J.
Geophys. Res.-Oceans, 122, 8770–8793, 2017.
Collins III, C. O., Rogers, W. E., Marchenko, A., and Babanin, A. V.: In
situ measurements of an energetic wave event in the Arctic marginal ice
zone, Geophys. Res. Lett., 42, 1863–1870, 2015.
Collins III, C. O., Doble, M., Lund, B., and Smith, M.: Observations of
surface wave dispersion in the marginal ice zone, J. Geophys.
Res.-Oceans, 123, 3336–3354, 2018.
Comiso, J. C., Parkinson, C. L., Gersten, R., and Stock, L.: Accelerated
decline in the Arctic sea ice cover, Geophys. Res. Lett., 35, L01703, https://doi.org/10.1029/2007GL031972, 2008.
De Carolis, G., Olla, P., and Pignagnoli, L.: Effective viscosity of grease
ice in linearized gravity waves, J. Fluid Mech., 535, 369–381,
2005.
ESR: OSCAR third degree resolution ocean surface currents, Ver. 1. PO.DAAC, CA, USA, https://doi.org/10.5067/OSCAR-03D01, 2009.
Fox, C. and Haskell, T. G.: Ocean wave speed in the Antarctic marginal ice
zone, Ann. Glaciol., 33, 350–354, 2001.
Hasselmann, S. and Hasselmann, K.: Computations and parameterizations of
the nonlinear energy transfer in a gravity-wave spectrum. Part I: A new
method for efficient computations of the exact nonlinear transfer integral,
J. Phys. Oceanogr., 15, 1369–1377, 1985.
Hasselmann, S., Hasselmann, K., Allender, J. H., and Barnett, T. P.:
Computations and parameterizations of the nonlinear energy transfer in a
gravity-wave spectrum. Part II: Parameterizations of the nonlinear energy
transfer for application in wave models, J. Phys. Oceanogr.,
15, 1378–1391, 1985.
Herman, A., Cheng, S., and Shen, H. H.: Wave energy attenuation in fields of colliding ice floes – Part 1: Discrete-element modelling of dissipation due to ice–water drag, The Cryosphere, 13, 2887–2900, https://doi.org/10.5194/tc-13-2887-2019, 2019a.
Herman, A., Cheng, S., and Shen, H. H.: Wave energy attenuation in fields of colliding ice floes – Part 2: A laboratory case study, The Cryosphere, 13, 2901–2914, https://doi.org/10.5194/tc-13-2901-2019, 2019b.
Huntemann, M., Heygster, G., Kaleschke, L., Krumpen, T., Mäkynen, M., and Drusch, M.: Empirical sea ice thickness retrieval during the freeze-up period from SMOS high incident angle observations, The Cryosphere, 8, 439–451, https://doi.org/10.5194/tc-8-439-2014, 2014.
Johnsen, H. and Collard, F.: Sentinel-1 ocean swell wave spectra (OSW) algorithm definition, Sentinel-1 IPF Development (Project No.: 355) Report., 2009.
Keller, J. B.: Gravity waves on ice-covered water, J. Geophys.
Res.-Oceans, 103, 7663–7669, 1998.
Kohout, A. L. and Williams, M. J. M.: Waves-in-ice observations made during the SIPEX II voyage of the Aurora Australis, 2012, Australian Antarctic Data Centre, 2013.
Kohout, A. L., Williams, M. J. M., Toyota, T., Lieser, J., and Hutchings,
J.: In situ observations of wave-induced sea ice breakup, Deep-Sea Res.
Pt. II, 131, 22–27, 2016.
Komen, G., Hasselmann, K., and Hasselmann, K.: On the existence of a fully
developed wind-sea spectrum, J. Phys. Oceanogr., 14,
1271–1285, 1984.
Liu, A. K. and Mollo-Christensen, E.: Wave propagation in a solid ice pack,
J. Phys. Oceanogr., 18, 1702–1712, 1988.
Marko, J. R.: Observations and analyses of an intense waves-in-ice event in
the Sea of Okhotsk, J. Geophys. Res.-Oceans, 108, 3296, https://doi.org/10.1029/2001JC001214, 2003.
MATLAB and Global Optimization Toolbox R2016a: The MathWorks Inc., Natick,
Massachusetts, United States, 2016.
Meier, W. N.: Losing Arctic sea ice: Observations of the recent decline and the long-term context, in: Sea Ice, Third Edition, edited by: Thomas, D. N., Hoboken, Wiley Blackwell, 290–303, 2017.
Meylan, M. H., Bennetts, L. G., and Kohout, A. L.: In situ measurements and
analysis of ocean waves in the Antarctic marginal ice zone, Geophys.
Res. Lett., 41, 5046–5051, 2014.
Meylan, M. H., Bennetts, L. G., Mosig, J. E., Rogers, W. E., Doble, M. J.,
and Peter, M. A.: Dispersion relations, power laws, and energy loss for
waves in the marginal ice zone, J. Geophys. Res.-Oceans,
123, 3322–3335, 2018.
Monteban, D., Johnsen, H., and Lubbad, R.: Spatiotemporal observations of
wave dispersion within sea ice using Sentinel-1 SAR TOPS mode, J.
Geophys. Res.-Oceans, 24, 8522–8537, https://doi.org/10.1029/2019JC015311, 2019.
Mosig, J. E., Montiel, F., and Squire, V. A.: Comparison of
viscoelastic-type models for ocean wave attenuation in ice-covered seas,
J. Geophys. Res.-Oceans, 120, 6072–6090, 2015.
Newyear, K. and Martin, S.: Comparison of laboratory data with a viscous
two-layer model of wave propagation in grease ice, J. Geophys.
Res.-Oceans, 104, 7837–7840, 1999.
Rabault, J., Sutherland, G., Gundersen, O., and Jensen, A.: Measurements of
wave damping by a grease ice slick in Svalbard using off-the-shelf sensors
and open-source electronics, J. Glaciol., 63, 372–381, 2017.
Rabault, J., Sutherland, G., Jensen, A., Christensen, K. H., and Marchenko,
A.: Experiments on wave propagation in grease ice: combined wave gauges and
particle image velocimetry measurements, J. Fluid Mech., 864,
876–898, 2019.
Robin, G. D. Q.: Wave propagation through fields of pack ice, Philos.
T. R. Soc. Lond. A, 255, 313–339, 1963.
Rogers, W. E., Thomson, J., Shen, H. H., Doble, M. J., Wadhams, P., and
Cheng, S.: Dissipation of wind waves by pancake and frazil ice in the autumn
Beaufort Sea, J. Geophys. Res.-Oceans, 121, 7991–8007,
2016.
Rosenblum, E. and Eisenman, I.: Sea ice trends in climate models only
accurate in runs with biased global warming, J. Climate, 30, 6265–6278, 2017.
Saha, S., Moorthi, S., Pan, H. L., Wu, X., Wang, J., Nadiga, S., Tripp, P.,
Kistler, R., Woollen, J., and Behringer, D.: The NCEP climate forecast
system reanalysis, B. Am. Meteorol. Soc., 91,
1015–1058, 2010.
Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., Tripp, P., Behringer, D., Hou Y. T., Chuang, H. Y., Iredell, M., and Ek, M.: NCEP climate forecast system version 2 (CFSv2) 6-hourly products, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, https://doi.org/10.5065/D61C1TXF, 2011.
Shen, H., Perrie, W., Hu, Y., and He, Y.: Remote sensing of waves
propagating in the marginal ice zone by SAR, J. Geophys.
Res.-Oceans, 123, 189–200, 2018.
Shen, H. H., Ackley, S. F., and Hopkins, M. A.: A conceptual model for
pancake-ice formation in a wave field, Ann. Glaciol., 33, 361–367,
2001.
Smith, M. and Thomson, J.: Ocean surface turbulence in newly formed
marginal ice zones, J. Geophys. Res.-Oceans, 124, 1382–1398,
2019.
Smith, M., Stammerjohn, S., Persson, O., Rainville, L., Liu, G., Perrie, W.,
Robertson, R., Jackson, J., and Thomson, J.: Episodic reversal of autumn ice
advance caused by release of ocean heat in the Beaufort Sea, J.
Geophys. Res.-Oceans, 123, 3164–3185, 2018.
Snyder, R. L., Dobson, F. W., Elliott, J. A., and Long, R. B.: Array
measurements of atmospheric pressure fluctuations above surface gravity
waves, J. Fluid Mech., 102, 1–59, 1981.
Spreen, G., Kaleschke, L., and Heygster, G.: Sea ice remote sensing using AMSR-E 89 GHz channels, J. Geophys. Res., 113, C02S03, https://doi.org/10.1029/2005JC003384, 2008.
Squire, V. A., Dugan, J. P., Wadhams, P., Rottier, P. J., and Liu, A. K.: Of
ocean waves and sea ice, Annu. Rev. Fluid Mech., 27, 115–168,
1995.
Squire, V. A.: Of ocean waves and sea-ice revisited, Cold Reg. Sci.
Technol., 49, 110–133, 2007.
Squire, V. A.: A fresh look at how ocean waves and sea ice interact,
Philos. T. R. Soc. A, 376, 20170342, https://doi.org/10.1098/rsta.2017.0342, 2018.
Squire, V. A.: Ocean wave interactions with sea ice: a reappraisal, Annu. Rev.
Fluid Mech., 52, 37–60, https://doi.org/10.1146/annurev-fluid-010719-060301.
2020.
Stopa, J. E., Ardhuin, F., Chapron, B., and Collard, F.: Estimating wave
orbital velocity through the azimuth cutoff from space-borne satellites,
J. Geophys. Res.-Oceans, 120, 7616–7634, 2015.
Stopa, J. E., Sutherland, P., and Ardhuin, F.: Strong and highly variable
push of ocean waves on Southern Ocean sea ice, P. Natl. Acad. Sci. USA,
115, 5861–5865, https://doi.org/10.1073/pnas.1802011115, 2018a.
Stopa, J., Ardhuin, F., Thomson, J., Smith, M. M., Kohout, A., Doble, M.,
and Wadhams, P.: Wave attenuation through an Arctic marginal ice zone on 12
October 2015: 1. Measurement of wave spectra and ice features from Sentinel
1A, J. Geophys. Res.-Oceans, 123, 3619–3634, 2018b.
Stroeve, J. and Notz, D.: Changing state of Arctic sea ice across all
seasons, Environ. Res. Lett., 13, 10, https://doi.org/10.1088/1748-9326/aade56, 2018.
Thomson, J., Ackley, S., Girard-Ardhuin, F., Ardhuin, F., Babanin, A.,
Boutin, G., Brozena, J., Cheng, S., Collins, C., Doble, M.,
and Wadhams, P.: Overview of the arctic sea state and boundary layer physics
program, J. Geophys. Res.-Oceans, 123, 8674–8687, 2018.
Wang, R. and Shen, H. H.: Experimental study on surface wave propagating
through a grease–pancake ice mixture, Cold Reg. Sci. Technol.,
61, 90–96, 2010a.
Wang, R. and Shen, H. H.: Gravity waves propagating into an ice-covered
ocean: A viscoelastic model, J. Geophys. Res.-Oceans, 115, C06024, https://doi.org/10.1029/2009JC005591,
2010b.
WAVEWATCH III® Development Group (WW3DG): User manual and
system documentation of WAVEWATCH III® version 6.07. Tech.
Note 333, NOAA/NWS/NCEP/MMAB, College Park, MD, USA, 465 pp. +Appendices,
2019.
Weeks, W. F. and Assur, A.: The mechanical properties of sea ice, Cold
regions research and engineering lab, Hanover, NH, 1967.
Zhao, X. and Shen, H. H.: Wave propagation in frazil/pancake, pancake, and
fragmented ice covers, Cold Reg. Sci. Technol., 113, 71–80,
2015.
Zhao, X. and Shen, H. H.: A three-layer viscoelastic model with eddy
viscosity effect for flexural-gravity wave propagation through ice covers,
Ocean Model., 151, 15–23, 2018.
Short summary
Wave states in ice in polar oceans are mostly studied near the ice edge. However, observations in the internal ice field, where ice morphology is very different from the ice edge, are rare. Recently derived wave data from satellite imagery are easier and cheaper than field studies and provide large coverage. This work presents a way of using these data to have a close view of some key features in the wave propagation over hundreds of kilometers and calibrate models for predicting wave decay.
Wave states in ice in polar oceans are mostly studied near the ice edge. However, observations...