Articles | Volume 14, issue 2
https://doi.org/10.5194/tc-14-709-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-14-709-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Mar 2020
Research article |
| 02 Mar 2020
Towards a coupled model to investigate wave–sea ice interactions in the Arctic marginal ice zone
Guillaume Boutin
CORRESPONDING AUTHOR
Laboratoire d’Océanographie Physique et Spatiale, Université de Bretagne Occidentale, CNRS, IRD, Ifremer, IUEM, Brest, France
Camille Lique
Laboratoire d’Océanographie Physique et Spatiale, Université de Bretagne Occidentale, CNRS, IRD, Ifremer, IUEM, Brest, France
Fabrice Ardhuin
Laboratoire d’Océanographie Physique et Spatiale, Université de Bretagne Occidentale, CNRS, IRD, Ifremer, IUEM, Brest, France
Clément Rousset
LOCEAN-IPSL, Sorbonne Université, CNRS/IRD/UPMC/MNHN, Paris, France
Claude Talandier
Laboratoire d’Océanographie Physique et Spatiale, Université de Bretagne Occidentale, CNRS, IRD, Ifremer, IUEM, Brest, France
Mickael Accensi
Laboratoire d’Océanographie Physique et Spatiale, Université de Bretagne Occidentale, CNRS, IRD, Ifremer, IUEM, Brest, France
Fanny Girard-Ardhuin
Laboratoire d’Océanographie Physique et Spatiale, Université de Bretagne Occidentale, CNRS, IRD, Ifremer, IUEM, Brest, France
Related authors
Heather Regan, Pierre Rampal, Einar Ólason, Guillaume Boutin, and Anton Korosov
The Cryosphere, 17, 1873–1893, https://doi.org/10.5194/tc-17-1873-2023, https://doi.org/10.5194/tc-17-1873-2023, 2023
Short summary
Short summary
Multiyear ice (MYI), sea ice that survives the summer, is more resistant to changes than younger ice in the Arctic, so it is a good indicator of sea ice resilience. We use a model with a new way of tracking MYI to assess the contribution of different processes affecting MYI. We find two important years for MYI decline: 2007, when dynamics are important, and 2012, when melt is important. These affect MYI volume and area in different ways, which is important for the interpretation of observations.
Guillaume Boutin, Einar Ólason, Pierre Rampal, Heather Regan, Camille Lique, Claude Talandier, Laurent Brodeau, and Robert Ricker
The Cryosphere, 17, 617–638, https://doi.org/10.5194/tc-17-617-2023, https://doi.org/10.5194/tc-17-617-2023, 2023
Short summary
Short summary
Sea ice cover in the Arctic is full of cracks, which we call leads. We suspect that these leads play a role for atmosphere–ocean interactions in polar regions, but their importance remains challenging to estimate. We use a new ocean–sea ice model with an original way of representing sea ice dynamics to estimate their impact on winter sea ice production. This model successfully represents sea ice evolution from 2000 to 2018, and we find that about 30 % of ice production takes place in leads.
Guillaume Boutin, Timothy Williams, Pierre Rampal, Einar Olason, and Camille Lique
The Cryosphere, 15, 431–457, https://doi.org/10.5194/tc-15-431-2021, https://doi.org/10.5194/tc-15-431-2021, 2021
Short summary
Short summary
In this study, we investigate the interactions of surface ocean waves with sea ice. We focus on the evolution of sea ice after it has been fragmented by the waves. Fragmented sea ice is expected to experience less resistance to deformation. We reproduce this evolution using a new coupling framework between a wave model and the recently developed sea ice model neXtSIM. We find that waves can significantly increase the mobility of compact sea ice over wide areas in the wake of storm events.
Pierre L'Hégaret, Xavier Carton, Stephanie Louazel, and Guillaume Boutin
Ocean Sci., 12, 687–701, https://doi.org/10.5194/os-12-687-2016, https://doi.org/10.5194/os-12-687-2016, 2016
Short summary
Short summary
The Persian Gulf produces high-salinity water spreading in the Indian Ocean through the Arabian Sea. Using measurements from the Phys-Indien 2011 experiments and satellite observations, the objective of this study is to follow the pathway and evolution of the salty water outflow in the northwestern Indian Ocean. It is shown that the outflow is strongly influenced by energetic eddies, shredding the water vein into filaments or lenses, and advecting them at their peripheries or in their cores.
Anne Marie Treguier, Clement de Boyer Montégut, Alexandra Bozec, Eric P. Chassignet, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Julien Le Sommer, Yiwen Li, Pengfei Lin, Camille Lique, Hailong Liu, Guillaume Serazin, Dmitry Sidorenko, Qiang Wang, Xiaobio Xu, and Steve Yeager
Geosci. Model Dev., 16, 3849–3872, https://doi.org/10.5194/gmd-16-3849-2023, https://doi.org/10.5194/gmd-16-3849-2023, 2023
Short summary
Short summary
The ocean mixed layer is the interface between the ocean interior and the atmosphere and plays a key role in climate variability. We evaluate the performance of the new generation of ocean models for climate studies, designed to resolve
ocean eddies, which are the largest source of ocean variability and modulate the mixed-layer properties. We find that the mixed-layer depth is better represented in eddy-rich models but, unfortunately, not uniformly across the globe and not in all models.
Heather Regan, Pierre Rampal, Einar Ólason, Guillaume Boutin, and Anton Korosov
The Cryosphere, 17, 1873–1893, https://doi.org/10.5194/tc-17-1873-2023, https://doi.org/10.5194/tc-17-1873-2023, 2023
Short summary
Short summary
Multiyear ice (MYI), sea ice that survives the summer, is more resistant to changes than younger ice in the Arctic, so it is a good indicator of sea ice resilience. We use a model with a new way of tracking MYI to assess the contribution of different processes affecting MYI. We find two important years for MYI decline: 2007, when dynamics are important, and 2012, when melt is important. These affect MYI volume and area in different ways, which is important for the interpretation of observations.
Guillaume Boutin, Einar Ólason, Pierre Rampal, Heather Regan, Camille Lique, Claude Talandier, Laurent Brodeau, and Robert Ricker
The Cryosphere, 17, 617–638, https://doi.org/10.5194/tc-17-617-2023, https://doi.org/10.5194/tc-17-617-2023, 2023
Short summary
Short summary
Sea ice cover in the Arctic is full of cracks, which we call leads. We suspect that these leads play a role for atmosphere–ocean interactions in polar regions, but their importance remains challenging to estimate. We use a new ocean–sea ice model with an original way of representing sea ice dynamics to estimate their impact on winter sea ice production. This model successfully represents sea ice evolution from 2000 to 2018, and we find that about 30 % of ice production takes place in leads.
Yufang Ye, Yanbing Luo, Yan Sun, Mohammed Shokr, Signe Aaboe, Fanny Girard-Ardhuin, Fengming Hui, Xiao Cheng, and Zhuoqi Chen
The Cryosphere, 17, 279–308, https://doi.org/10.5194/tc-17-279-2023, https://doi.org/10.5194/tc-17-279-2023, 2023
Short summary
Short summary
Arctic sea ice type (SITY) variation is a sensitive indicator of climate change. This study gives a systematic inter-comparison and evaluation of eight SITY products. Main results include differences in SITY products being significant, with average Arctic multiyear ice extent up to 1.8×106 km2; Ku-band scatterometer SITY products generally performing better; and factors such as satellite inputs, classification methods, training datasets and post-processing highly impacting their performance.
Matias Alday, Fabrice Ardhuin, Guillaume Dodet, and Mickael Accensi
Ocean Sci., 18, 1665–1689, https://doi.org/10.5194/os-18-1665-2022, https://doi.org/10.5194/os-18-1665-2022, 2022
Short summary
Short summary
Obtaining accurate results from wave models in coastal regions is typically more difficult. This is due to the complex interactions between waves and the local environment characteristics like complex shorelines, sea bottom topography, the presence of strong currents, and other processes that include wave growth and decay. In the present study we analyze which elements can be adjusted and/or included in order to reduce errors in the modeled output.
Ralf Döscher, Mario Acosta, Andrea Alessandri, Peter Anthoni, Thomas Arsouze, Tommi Bergman, Raffaele Bernardello, Souhail Boussetta, Louis-Philippe Caron, Glenn Carver, Miguel Castrillo, Franco Catalano, Ivana Cvijanovic, Paolo Davini, Evelien Dekker, Francisco J. Doblas-Reyes, David Docquier, Pablo Echevarria, Uwe Fladrich, Ramon Fuentes-Franco, Matthias Gröger, Jost v. Hardenberg, Jenny Hieronymus, M. Pasha Karami, Jukka-Pekka Keskinen, Torben Koenigk, Risto Makkonen, François Massonnet, Martin Ménégoz, Paul A. Miller, Eduardo Moreno-Chamarro, Lars Nieradzik, Twan van Noije, Paul Nolan, Declan O'Donnell, Pirkka Ollinaho, Gijs van den Oord, Pablo Ortega, Oriol Tintó Prims, Arthur Ramos, Thomas Reerink, Clement Rousset, Yohan Ruprich-Robert, Philippe Le Sager, Torben Schmith, Roland Schrödner, Federico Serva, Valentina Sicardi, Marianne Sloth Madsen, Benjamin Smith, Tian Tian, Etienne Tourigny, Petteri Uotila, Martin Vancoppenolle, Shiyu Wang, David Wårlind, Ulrika Willén, Klaus Wyser, Shuting Yang, Xavier Yepes-Arbós, and Qiong Zhang
Geosci. Model Dev., 15, 2973–3020, https://doi.org/10.5194/gmd-15-2973-2022, https://doi.org/10.5194/gmd-15-2973-2022, 2022
Short summary
Short summary
The Earth system model EC-Earth3 is documented here. Key performance metrics show physical behavior and biases well within the frame known from recent models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
Guillaume Boutin, Timothy Williams, Pierre Rampal, Einar Olason, and Camille Lique
The Cryosphere, 15, 431–457, https://doi.org/10.5194/tc-15-431-2021, https://doi.org/10.5194/tc-15-431-2021, 2021
Short summary
Short summary
In this study, we investigate the interactions of surface ocean waves with sea ice. We focus on the evolution of sea ice after it has been fragmented by the waves. Fragmented sea ice is expected to experience less resistance to deformation. We reproduce this evolution using a new coupling framework between a wave model and the recently developed sea ice model neXtSIM. We find that waves can significantly increase the mobility of compact sea ice over wide areas in the wake of storm events.
Louis Marié, Fabrice Collard, Frédéric Nouguier, Lucia Pineau-Guillou, Danièle Hauser, François Boy, Stéphane Méric, Peter Sutherland, Charles Peureux, Goulven Monnier, Bertrand Chapron, Adrien Martin, Pierre Dubois, Craig Donlon, Tania Casal, and Fabrice Ardhuin
Ocean Sci., 16, 1399–1429, https://doi.org/10.5194/os-16-1399-2020, https://doi.org/10.5194/os-16-1399-2020, 2020
Short summary
Short summary
With present-day techniques, ocean surface currents are poorly known near the Equator and globally for spatial scales under 200 km and timescales under 30 d. Wide-swath radar Doppler measurements are an alternative technique. Such direct surface current measurements are, however, affected by platform motions and waves. These contributions are analyzed in data collected during the DRIFT4SKIM airborne and in situ experiment, demonstrating the possibility of measuring currents from space globally.
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
Short summary
Short summary
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.
Yurui Zhang, Thierry Huck, Camille Lique, Yannick Donnadieu, Jean-Baptiste Ladant, Marina Rabineau, and Daniel Aslanian
Clim. Past, 16, 1263–1283, https://doi.org/10.5194/cp-16-1263-2020, https://doi.org/10.5194/cp-16-1263-2020, 2020
Short summary
Short summary
The early Eocene (~ 55 Ma) was an extreme warm period accompanied by a high atmospheric CO2 level. We explore the relationships between ocean dynamics and this warm climate with the aid of the IPSL climate model. Our results show that the Eocene was characterized by a strong overturning circulation associated with deepwater formation in the Southern Ocean, which is analogous to the present-day North Atlantic. Consequently, poleward ocean heat transport was strongly enhanced.
Xavier Couvelard, Florian Lemarié, Guillaume Samson, Jean-Luc Redelsperger, Fabrice Ardhuin, Rachid Benshila, and Gurvan Madec
Geosci. Model Dev., 13, 3067–3090, https://doi.org/10.5194/gmd-13-3067-2020, https://doi.org/10.5194/gmd-13-3067-2020, 2020
Short summary
Short summary
Within the framework of the Copernicus Marine Environment Monitoring Service (CMEMS), an objective is to demonstrate the contribution of coupling the high-resolution analysis and forecasting system with a wave model. This study describes the necessary steps and discusses the various choices made for coupling a wave model and an oceanic model for global-scale applications.
Thomas Holding, Ian G. Ashton, Jamie D. Shutler, Peter E. Land, Philip D. Nightingale, Andrew P. Rees, Ian Brown, Jean-Francois Piolle, Annette Kock, Hermann W. Bange, David K. Woolf, Lonneke Goddijn-Murphy, Ryan Pereira, Frederic Paul, Fanny Girard-Ardhuin, Bertrand Chapron, Gregor Rehder, Fabrice Ardhuin, and Craig J. Donlon
Ocean Sci., 15, 1707–1728, https://doi.org/10.5194/os-15-1707-2019, https://doi.org/10.5194/os-15-1707-2019, 2019
Short summary
Short summary
FluxEngine is an open-source software toolbox designed to allow for the easy and accurate calculation of air–sea gas fluxes. This article describes new functionality and capabilities, which include the ability to calculate fluxes for nitrous oxide and methane, optimisation for running FluxEngine on a stand-alone desktop computer, and extensive new features to support the in situ measurement community. Four research case studies are used to demonstrate these new features.
Yufang Ye, Mohammed Shokr, Signe Aaboe, Wiebke Aldenhoff, Leif E. B. Eriksson, Georg Heygster, Christian Melsheimer, and Fanny Girard-Ardhuin
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-200, https://doi.org/10.5194/tc-2019-200, 2019
Revised manuscript not accepted
Short summary
Short summary
Sea ice has been monitored with microwave satellite observations since the late 1970s. However, the question remains as to which sea ice type concentration (SITC) method is most appropriate for ice type distribution and hence climate monitoring. This paper presents key results of inter-comparison and evaluation for eight SITC methods. The SITC methods were inter-compared with sea ice age and sea ice type products. Their performances were evaluated quantitatively and qualitatively.
François Massonnet, Antoine Barthélemy, Koffi Worou, Thierry Fichefet, Martin Vancoppenolle, Clément Rousset, and Eduardo Moreno-Chamarro
Geosci. Model Dev., 12, 3745–3758, https://doi.org/10.5194/gmd-12-3745-2019, https://doi.org/10.5194/gmd-12-3745-2019, 2019
Short summary
Short summary
Sea ice thickness varies considerably on spatial scales of several meters. However, contemporary climate models cannot resolve such scales yet. This is why sea ice models used in climate models include an ice thickness distribution (ITD) to account for this unresolved variability. Here, we explore with the ocean–sea ice model NEMO3.6-LIM3 the sensitivity of simulated mean Arctic and Antarctic sea ice states to the way the ITD is discretized.
Pedro Veras Guimarães, Fabrice Ardhuin, Peter Sutherland, Mickael Accensi, Michel Hamon, Yves Pérignon, Jim Thomson, Alvise Benetazzo, and Pierre Ferrant
Ocean Sci., 14, 1449–1460, https://doi.org/10.5194/os-14-1449-2018, https://doi.org/10.5194/os-14-1449-2018, 2018
Short summary
Short summary
This paper introduces a new design of drifting buoy. The "surface kinematics buoy'' (SKIB) is particularly optimized for measuring wave–current interactions, including relatively short wave components, from 0.09 to 1 Hz, that are important for air–sea interactions and remote-sensing applications. The capability of this instrument is compared to other sensors, and the ability to measure current-induced wave variations is illustrated with data acquired in a macro-tidal coastal environment.
Robert Ricker, Fanny Girard-Ardhuin, Thomas Krumpen, and Camille Lique
The Cryosphere, 12, 3017–3032, https://doi.org/10.5194/tc-12-3017-2018, https://doi.org/10.5194/tc-12-3017-2018, 2018
Short summary
Short summary
We present ice volume flux estimates through the Fram Strait using CryoSat-2 ice thickness data. This study presents a detailed analysis of temporal and spatial variability of ice volume export through the Fram Strait and shows the impact of ice volume export on Arctic ice mass balance.
Anton Andreevich Korosov, Pierre Rampal, Leif Toudal Pedersen, Roberto Saldo, Yufang Ye, Georg Heygster, Thomas Lavergne, Signe Aaboe, and Fanny Girard-Ardhuin
The Cryosphere, 12, 2073–2085, https://doi.org/10.5194/tc-12-2073-2018, https://doi.org/10.5194/tc-12-2073-2018, 2018
Short summary
Short summary
A new algorithm for estimating sea ice age in the Arctic is presented. The algorithm accounts for motion, deformation, melting and freezing of sea ice and uses daily sea ice drift and sea ice concentration products. The major advantage of the new algorithm is the ability to generate individual ice age fractions in each pixel or, in other words, to provide a frequency distribution of the ice age. Multi-year ice concentration can be computed as a sum of all ice fractions older than 1 year.
Fabrice Ardhuin, Yevgueny Aksenov, Alvise Benetazzo, Laurent Bertino, Peter Brandt, Eric Caubet, Bertrand Chapron, Fabrice Collard, Sophie Cravatte, Jean-Marc Delouis, Frederic Dias, Gérald Dibarboure, Lucile Gaultier, Johnny Johannessen, Anton Korosov, Georgy Manucharyan, Dimitris Menemenlis, Melisa Menendez, Goulven Monnier, Alexis Mouche, Frédéric Nouguier, George Nurser, Pierre Rampal, Ad Reniers, Ernesto Rodriguez, Justin Stopa, Céline Tison, Clément Ubelmann, Erik van Sebille, and Jiping Xie
Ocean Sci., 14, 337–354, https://doi.org/10.5194/os-14-337-2018, https://doi.org/10.5194/os-14-337-2018, 2018
Short summary
Short summary
The Sea surface KInematics Multiscale (SKIM) monitoring mission is a proposal for a future satellite that is designed to measure ocean currents and waves. Using a Doppler radar, the accurate measurement of currents requires the removal of the mean velocity due to ocean wave motions. This paper describes the main processing steps needed to produce currents and wave data from the radar measurements. With this technique, SKIM can provide unprecedented coverage and resolution, over the global ocean.
Charles Peureux, Alvise Benetazzo, and Fabrice Ardhuin
Ocean Sci., 14, 41–52, https://doi.org/10.5194/os-14-41-2018, https://doi.org/10.5194/os-14-41-2018, 2018
Short summary
Short summary
Little is known on the short ocean wave (1 to 20 m wave length typically) directional distribution. It has been measured from a platform in the Adriatic Sea using a three-dimensional reconstruction technique, used for the first time for this purpose. In this record, while longer waves propagate along the wind direction, shorter waves have been found to propagate mainly along two oblique directions, more and more separated towards smaller scales.
Aurore Voldoire, Bertrand Decharme, Joris Pianezze, Cindy Lebeaupin Brossier, Florence Sevault, Léo Seyfried, Valérie Garnier, Soline Bielli, Sophie Valcke, Antoinette Alias, Mickael Accensi, Fabrice Ardhuin, Marie-Noëlle Bouin, Véronique Ducrocq, Stéphanie Faroux, Hervé Giordani, Fabien Léger, Patrick Marsaleix, Romain Rainaud, Jean-Luc Redelsperger, Evelyne Richard, and Sébastien Riette
Geosci. Model Dev., 10, 4207–4227, https://doi.org/10.5194/gmd-10-4207-2017, https://doi.org/10.5194/gmd-10-4207-2017, 2017
Short summary
Short summary
This study presents the principles of the new coupling interface based on the SURFEX multi-surface model and the OASIS3-MCT coupler. As SURFEX can be plugged into several atmospheric models, it can be used in a wide range of applications. The objective of this development is to build and share a common structure for the atmosphere–surface coupling of all these applications, involving on the one hand atmospheric models and on the other hand ocean, ice, hydrology, and wave models.
Petteri Uotila, Doroteaciro Iovino, Martin Vancoppenolle, Mikko Lensu, and Clement Rousset
Geosci. Model Dev., 10, 1009–1031, https://doi.org/10.5194/gmd-10-1009-2017, https://doi.org/10.5194/gmd-10-1009-2017, 2017
Short summary
Short summary
We performed ocean model simulations with new and old sea-ice components. Sea ice improved in the new model compared to the earlier one due to better model physics. In the ocean, the largest differences are confined close to the surface within and near the sea-ice zone. The global ocean circulation slowly deviates between the simulations due to dissimilar sea ice in the deep water formation regions, such as the North Atlantic and Antarctic.
Justin E. Stopa, Fabrice Ardhuin, and Fanny Girard-Ardhuin
The Cryosphere, 10, 1605–1629, https://doi.org/10.5194/tc-10-1605-2016, https://doi.org/10.5194/tc-10-1605-2016, 2016
Short summary
Short summary
Satellite observations show the Arctic sea ice has decreased the last 30 years. From our wave model hindcast and satellite altimeter datasets we observe profound increasing wave heights, which are caused by the loss of sea ice and not the driving winds. If ice-free conditions persist later into fall, then regions like the Beaufort–Chukchi Sea will be prone to developing larger waves since the driving winds are strong this time of year.
Pierre L'Hégaret, Xavier Carton, Stephanie Louazel, and Guillaume Boutin
Ocean Sci., 12, 687–701, https://doi.org/10.5194/os-12-687-2016, https://doi.org/10.5194/os-12-687-2016, 2016
Short summary
Short summary
The Persian Gulf produces high-salinity water spreading in the Indian Ocean through the Arabian Sea. Using measurements from the Phys-Indien 2011 experiments and satellite observations, the objective of this study is to follow the pathway and evolution of the salty water outflow in the northwestern Indian Ocean. It is shown that the outflow is strongly influenced by energetic eddies, shredding the water vein into filaments or lenses, and advecting them at their peripheries or in their cores.
C. Rousset, M. Vancoppenolle, G. Madec, T. Fichefet, S. Flavoni, A. Barthélemy, R. Benshila, J. Chanut, C. Levy, S. Masson, and F. Vivier
Geosci. Model Dev., 8, 2991–3005, https://doi.org/10.5194/gmd-8-2991-2015, https://doi.org/10.5194/gmd-8-2991-2015, 2015
Short summary
Short summary
LIM3.6 presented in this paper is the last release of the Louvain-la-Neuve sea ice model, and will be used for the next climate model intercomparison project (CMIP6). The model's robustness, versatility and sophistication have been improved.
A. M. Treguier, J. Deshayes, J. Le Sommer, C. Lique, G. Madec, T. Penduff, J.-M. Molines, B. Barnier, R. Bourdalle-Badie, and C. Talandier
Ocean Sci., 10, 243–255, https://doi.org/10.5194/os-10-243-2014, https://doi.org/10.5194/os-10-243-2014, 2014
T. Krumpen, M. Janout, K. I. Hodges, R. Gerdes, F. Girard-Ardhuin, J. A. Hölemann, and S. Willmes
The Cryosphere, 7, 349–363, https://doi.org/10.5194/tc-7-349-2013, https://doi.org/10.5194/tc-7-349-2013, 2013
Related subject area
Discipline: Sea ice | Subject: Ocean Interactions
Underestimation of oceanic carbon uptake in the Arctic Ocean: ice melt as predictor of the sea ice carbon pump
Uncertainty analysis of single- and multiple-size-class frazil ice models
Wave–sea-ice interactions in a brittle rheological framework
Experimental evidence for a universal threshold characterizing wave-induced sea ice break-up
High-resolution simulations of interactions between surface ocean dynamics and frazil ice
Frazil ice growth and production during katabatic wind events in the Ross Sea, Antarctica
Wave energy attenuation in fields of colliding ice floes – Part 2: A laboratory case study
Responses of sub-ice platelet layer thickening rate and frazil-ice concentration to variations in ice-shelf water supercooling in McMurdo Sound, Antarctica
Benjamin Richaud, Katja Fennel, Eric C. J. Oliver, Michael D. DeGrandpre, Timothée Bourgeois, Xianmin Hu, and Youyu Lu
The Cryosphere, 17, 2665–2680, https://doi.org/10.5194/tc-17-2665-2023, https://doi.org/10.5194/tc-17-2665-2023, 2023
Short summary
Short summary
Sea ice is a dynamic carbon reservoir. Its seasonal growth and melt modify the carbonate chemistry in the upper ocean, with consequences for the Arctic Ocean carbon sink. Yet, the importance of this process is poorly quantified. Using two independent approaches, this study provides new methods to evaluate the error in air–sea carbon flux estimates due to the lack of biogeochemistry in ice in earth system models. Those errors range from 5 % to 30 %, depending on the model and climate projection.
Fabien Souillé, Cédric Goeury, and Rem-Sophia Mouradi
The Cryosphere, 17, 1645–1674, https://doi.org/10.5194/tc-17-1645-2023, https://doi.org/10.5194/tc-17-1645-2023, 2023
Short summary
Short summary
Models that can predict temperature and ice crystal formation (frazil) in water are important for river and coastal engineering. Indeed, frazil has direct impact on submerged structures and often precedes the formation of ice cover. In this paper, an uncertainty analysis of two mathematical models that simulate supercooling and frazil is carried out within a probabilistic framework. The presented methodology offers new insight into the models and their parameterization.
Guillaume Boutin, Timothy Williams, Pierre Rampal, Einar Olason, and Camille Lique
The Cryosphere, 15, 431–457, https://doi.org/10.5194/tc-15-431-2021, https://doi.org/10.5194/tc-15-431-2021, 2021
Short summary
Short summary
In this study, we investigate the interactions of surface ocean waves with sea ice. We focus on the evolution of sea ice after it has been fragmented by the waves. Fragmented sea ice is expected to experience less resistance to deformation. We reproduce this evolution using a new coupling framework between a wave model and the recently developed sea ice model neXtSIM. We find that waves can significantly increase the mobility of compact sea ice over wide areas in the wake of storm events.
Joey J. Voermans, Jean Rabault, Kirill Filchuk, Ivan Ryzhov, Petra Heil, Aleksey Marchenko, Clarence O. Collins III, Mohammed Dabboor, Graig Sutherland, and Alexander V. Babanin
The Cryosphere, 14, 4265–4278, https://doi.org/10.5194/tc-14-4265-2020, https://doi.org/10.5194/tc-14-4265-2020, 2020
Short summary
Short summary
In this work we demonstrate the existence of an observational threshold which identifies when waves are most likely to break sea ice. This threshold is based on information from two recent field campaigns, supplemented with existing observations of sea ice break-up. We show that both field and laboratory observations tend to converge to a single quantitative threshold at which the wave-induced sea ice break-up takes place, which opens a promising avenue for operational forecasting models.
Agnieszka Herman, Maciej Dojczman, and Kamila Świszcz
The Cryosphere, 14, 3707–3729, https://doi.org/10.5194/tc-14-3707-2020, https://doi.org/10.5194/tc-14-3707-2020, 2020
Short summary
Short summary
Under typical conditions favorable for sea ice formation in many regions (strong wind and waves, low air temperature), ice forms not at the sea surface but within the upper, turbulent layer of the ocean. Although interactions between ice and ocean dynamics are very important for the evolution of sea ice cover, many aspects of them are poorly understood. We use a numerical model to analyze three-dimensional water circulation and ice transport and show that ice strongly modifies that circulation.
Lisa Thompson, Madison Smith, Jim Thomson, Sharon Stammerjohn, Steve Ackley, and Brice Loose
The Cryosphere, 14, 3329–3347, https://doi.org/10.5194/tc-14-3329-2020, https://doi.org/10.5194/tc-14-3329-2020, 2020
Short summary
Short summary
The offshore winds around Antarctica can reach hurricane strength and produce intense cooling, causing the surface ocean to form a slurry of seawater and ice crystals. For the first time, we observed a buildup of heat and salt in the surface ocean, caused by loose ice crystal formation. We conclude that up to 1 m of ice was formed per day by the intense cooling, suggesting that unconsolidated crystals may be an important part of the total freezing that happens around Antarctica.
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.
Chen Cheng, Adrian Jenkins, Paul R. Holland, Zhaomin Wang, Chengyan Liu, and Ruibin Xia
The Cryosphere, 13, 265–280, https://doi.org/10.5194/tc-13-265-2019, https://doi.org/10.5194/tc-13-265-2019, 2019
Short summary
Short summary
The sub-ice platelet layer (SIPL) under fast ice is most prevalent in McMurdo Sound, Antarctica. Using a modified plume model, we investigated the responses of SIPL thickening rate and frazil concentration to variations in ice shelf water supercooling in McMurdo Sound. It would be key to parameterizing the relevant process in more complex three-dimensional, primitive equation ocean models, which relies on the knowledge of the suspended frazil size spectrum within the ice–ocean boundary layer.
Cited articles
Aksenov, Y., Popova, E. E., Yool, A., Nurser, A. G., Williams, T. D., Bertino, L., and Bergh, J.: On the future navigability of Arctic sea routes:
High-resolution projections of the Arctic Ocean and sea ice, Mar. Policy,
75, 300–317, 2017. a
Ardhuin, F., Sutherland, P., Doble, M., and Wadhams, P.: Ocean waves across the Arctic: attenuation due to dissipation dominates over scattering for
periods longer than 19 s, Geophys. Res. Lett., 43, 5775–5783,
https://doi.org/10.1002/2016GL068204, 2016. a
Ardhuin, F., Chapron, B., Collard, F., Smith, M., Stopa, J., Thomson, J.,
Doble, M., Wadhams, P., Blomquist, B., Persson, O., and Collins, III, C. O.:
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. a
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 October 12, 2015: 2.
Numerical modeling of Waves and Associated Ice Break-Up, J. Geophys. Res.-Oceans, 123, 5652–5668, https://doi.org/10.1002/2018JC013784, 2018. a, b, c, d, e
Asplin, M. G., Galley, R., Barber, D. G., and Prinsenberg, S.: Fracture of
summer perennial sea ice by ocean swell as a result of Arctic storms, J.
Geophys. Res., 117, C06025, https://doi.org/10.1029/2011JC007221, 2012. a
Barnier, B., Madec, G., Penduff, T., Molines, J.-M., Treguier, A.-M., Sommer,
J. L., Beckmann, A., Biastoch, A., Böning, C., Dengg, J., Derval, C.,
Durand, E., Gulev, S., Remy, E., Talandier, C., Theetten, S., Maltrud, M.,
McClean, J., and Cuevas, B. D.: Impact of partial steps and momentum
advection schemes in a global ocean circulation model at eddy-permitting
resolution, Ocean Model., 56, 543–567, https://doi.org/10.1007/s10236-006-0082-1,
2006. a
Bateson, A. W., Feltham, D. L., Schröder, D., Hosekova, L., Ridley, J. K., and Aksenov, Y.: Impact of floe size distribution on seasonal fragmentation and melt of Arctic sea ice, The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-44, in review, 2019. a, b, c
Bennetts, L. G., O'Farrell, S., and Uotila, P.: Brief communication: Impacts of ocean-wave-induced breakup of Antarctic sea ice via thermodynamics in a stand-alone version of the CICE sea-ice model, The Cryosphere, 11, 1035–1040, https://doi.org/10.5194/tc-11-1035-2017, 2017. a, b
Bouillon, S., Fichefet, T., Legat, V., and Madec, G.: The
elastic–viscous–plastic method revisited, Ocean Model., 71, 2–12,
https://doi.org/10.1016/j.ocemod.2013.05.013, 2013. a
Boutin, G., Ardhuin, F., Dumont, D., Sévigny, C., Girard-Ardhuin, F., and
Accensi, M.: Floe Size Effect on Wave-Ice Interactions: Possible Effects,
Implementation in Wave Model, and Evaluation, J. Geophys. Res.-Oceans, 123, 4779–4805, https://doi.org/10.1029/2017JC013622, 2018. a, b, c, d, e, f, g, h
Boutin, G.: gboutin-lops/nemo_lim3_wave_ice_cpl: TC_code (Version v1.0), Zenodo, https://doi.org/10.5281/zenodo.3600149, 2020. a
Cheng, S., Rogers, W. E., Thomson, J., Smith, M., Doble, M. J., Wadhams, P.,
Kohout, A. L., Lund, B., Persson, O. P., Collins, C. O., Ackley, S. 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. a
Chevallier, M., Smith, G. C., Dupont, F., Lemieux, J.-F., Forget, G., Fujii,
Y., Hernandez, F., Msadek, R., Peterson, K. A., Storto, A., Toyoda, T., Valdivieso, M., Vernieres, G., Zuo, H., Balmaseda, M., Chang, Y.-S., Ferry, N., Garric, G., Haines, K., Keeley, S., Kovach, R. M., Kuragano, T., Masina, S., Tang, Y., Tsujino, H., and Wang, X.:
Intercomparison of the Arctic sea ice cover in global ocean–sea ice
reanalyses from the ORA-IP project, Climate Dynam., 49, 1107–1136, 2017. a, b
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, https://doi.org/10.1002/2015GL063063, 2015. a, b
Comiso, J. C., Meier, W. N., and Gersten, R.: Variability and trends in the
Arctic Sea ice cover: Results from different techniques, J. Geophys. Res.-Oceans, 122, 6883–6900, 2017. a
Couvelard, X., Lemarié, F., Samson, G., Redelsperger, J.-L., Ardhuin, F., Benshila, R., and Madec, G.: Development of a 2-way coupled ocean-wave model: assessment on a global NEMO(v3.6)-WW3(v6.02) coupled configuration, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-189, in review, 2019. a
Craig, A., Valcke, S., and Coquart, L.: Development and performance of a new version of the OASIS coupler, OASIS3-MCT_3.0, Geosci. Model Dev., 10, 3297–3308, https://doi.org/10.5194/gmd-10-3297-2017, 2017. a
Day, J. J. and Hodges, K. I.: Growing land-sea temperature contrast and the
intensification of Arctic cyclones, Geophys. Res. Lett., 45,
3673–3681, 2018. a
Day, J. J., Holland, M. M., and Hodges, K. I.: Seasonal differences in the
response of Arctic cyclones to climate change in CESM1, Clim. Dynam., 50,
3885–3903, 2018. a
Dupont, F., Higginson, S., Bourdallé-Badie, R., Lu, Y., Roy, F., Smith, G. C., Lemieux, J.-F., Garric, G., and Davidson, F.: A high-resolution ocean and sea-ice modelling system for the Arctic and North Atlantic oceans, Geosci. Model Dev., 8, 1577–1594, https://doi.org/10.5194/gmd-8-1577-2015, 2015. a
Feltham, D. L.: Granular flow in the marginal ice zone, Philos. T. R. Soc. Lond, 363, 1677–1700, 2005. a
Herman, A., Evers, K.-U., and Reimer, N.: Floe-size distributions in laboratory ice broken by waves, The Cryosphere, 12, 685–699, https://doi.org/10.5194/tc-12-685-2018, 2018. a, b
Hibler III, W. D.: A Dynamic Thermodynamic Sea Ice Model, J. Phys. Oceanogr., 9, 815–846,
https://doi.org/10.1175/1520-0485(1979)009<0815:ADTSIM>2.0.CO;2, 1979. a, b
Hunke, E. C. and Dukowicz, J. K.: An Elastic–Viscous–Plastic Model
for Sea Ice Dynamics, J. Phys. Oceanogr., 27, 1849–1867,
https://doi.org/10.1175/1520-0485(1997)027<1849:AEVPMF>2.0.CO;2, 1997. a
Inoue, J., Wakatsuchi, M., and Fujiyoshi, Y.: Ice floe distribution in the Sea of Okhotsk in the period when sea-ice extent is advancing, Geophys.
Res. lett., 31, L20303, https://doi.org/10.1029/2004GL020809, 2004. a
Jackson, J., Carmack, E., McLaughlin, F., Allen, S. E., and Ingram, R.:
Identification, characterization, and change of the near-surface temperature
maximum in the Canada Basin, 1993–2008, J. Geophys. Res.-Oceans, 115, C05021, https://doi.org/10.1029/2009JC005265, 2010. a
Kohout, A. L., Williams, M. J. M., Dean, S. M., and Meylan, M. H.:
Storm-induced sea-ice breakup and the implications for ice extent, Nature,
509, 604–607, https://doi.org/10.1038/nature13262, 2014. a
Lemieux, J.-F., Lei, J., Dupont, F., Roy, F., Losch, M., Lique, C., and
Laliberté, F.: The Impact of Tides on Simulated Landfast Ice in a
Pan-Arctic Ice-Ocean Model, J. Geophys. Res.-Oceans, 123,
7747–7762, 2018. a
Lique, C., Holland, M. M., Dibike, Y. B., Lawrence, D. M., and Screen, J. A.:
Modeling the Arctic freshwater system and its integration in the global
system: Lessons learned and future challenges, J. Geophys.
Res.-Biogeo., 121, 540–566, 2016. a
Longuet-Higgins, M. S. and Stewart, R. W.: Radiation stresses and mass
transport in surface gravity waves with application to `surf beats', J. Fluid
Mech., 13, 481–504, 1962. a
Lüpkes, C., Gryanik, V. M., Hartmann, J., and Andreas, E. L.: A
parametrization, based on sea ice morphology, of the neutral atmospheric drag
coefficients for weather prediction and climate models, J.
Geophys. Res.-Atmos., 117, D13112, https://doi.org/10.1029/2012JD017630, 2012. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s
Madec, G.: NEMO ocean engine, Note du Pôle de modélisation, Institut
Pierre-Simon Laplace (IPSL), France, No. 27, ISSN: 1288-1619, 2008. a
Marcq, S. and Weiss, J.: Influence of sea ice lead-width distribution on turbulent heat transfer between the ocean and the atmosphere, The Cryosphere, 6, 143–156, https://doi.org/10.5194/tc-6-143-2012, 2012. a
Martin, S. and Kauffman, P.: A Field and Laboratory Study of Wave
Damping by Grease Ice, J. Glaciol., 27, 283–313,
https://doi.org/10.1017/S0022143000015392, 1981. a
Maykut, G. A. and Perovich, D. K.: The role of shortwave radiation in the
summer decay of a sea ice cover, J. Geophys. Res.-Oceans, 92,
7032–7044, 1987. a
Mellor, M.: Mechanical Behavior of Sea Ice, in: The Geophysics of SeaIce, edited by: Untersteiner, N., NATO ASI Series,
Springer US, 165–281, https://doi.org/10.1007/978-1-4899-5352-0_3, 1986. a
Montiel, F., Squire, V. A., and Bennetts, L. G.: Attenuation and directional
spreading of ocean wave spectra in the marginal ice zone, J. Fluid Mech.,
790, 492–522, https://doi.org/10.1017/jfm.2016.2, 2016. a
Perrie, W. and Hu, Y.: Air–ice–ocean momentum exchange – Part II: Ice drift,
J. Phys. Oceanogr., 27, 1976–1996, https://doi.org/10.1175/1520-0485(1997)027<1976:AIOMEP>2.0.CO;2, 1997. a
Rainville, L., Lee, C. M., and Woodgate, R. A.: Impact of wind-driven mixing in the Arctic Ocean, Oceanography, 24, 136–145, 2011. a
Rampal, P., Bouillon, S., Ólason, E., and Morlighem, M.: neXtSIM: a new Lagrangian sea ice model, The Cryosphere, 10, 1055–1073, https://doi.org/10.5194/tc-10-1055-2016, 2016. a, b
Roach, L. A., Dean, S. M., and Renwick, J. A.: Consistent biases in Antarctic sea ice concentration simulated by climate models, The Cryosphere, 12, 365–383, https://doi.org/10.5194/tc-12-365-2018, 2018a. a
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., 121, 7991–8007, https://doi.org/10.1002/2016JC012251, 2016. a
Rousset, C., Vancoppenolle, M., Madec, G., Fichefet, T., Flavoni, S., Barthélemy, A., Benshila, R., Chanut, J., Levy, C., Masson, S., and Vivier, F.: The Louvain-La-Neuve sea ice model LIM3.6: global and regional capabilities, Geosci. Model Dev., 8, 2991–3005, https://doi.org/10.5194/gmd-8-2991-2015, 2015. a, b
Shen, H. H. and Ackley, S. F.: A one-dimensional model for wave-induced
ice-floe collisions, Ann. Glaciol., 15, 87–95, 1991. a
Squire, V. A.: A fresh look at how ocean waves and sea ice interact, Phil.
Trans. R. Soc. A, 376, 20170342, https://doi.org/10.1098/rsta.2017.0342, 2018. a
Steele, K., Teng, C.-C., and Wang, D. W.-C.: Wave direction measurements using pitch and roll buoys, Ocean Eng., 19, 349–375, 1992. a
Steele, M.: Sea ice melting and floe geometry in a simple ice-ocean model,
J. Geophys. Res.-Oceans, 97, 17729–17738,
https://doi.org/10.1029/92JC01755, 1992. a
Steele, M., Morison, J. H., and Untersteiner, N.: The partition of
air-ice-ocean momentum exchange as a function of ice concentration, floe
size, and draft, J. Geophys. Res.-Oceans, 94,
12739–12750, 1989. a
Stopa, J. E., Ardhuin, F., and Girard-Ardhuin, F.: Wave climate in the Arctic 1992–2014: seasonality and trends, The Cryosphere, 10, 1605–1629, https://doi.org/10.5194/tc-10-1605-2016, 2016. a, b
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, 2018b. a
Stroeve, J., Hamilton, L. C., Bitz, C. M., and Blanchard-Wrigglesworth, E.:
Predicting September sea ice: Ensemble skill of the SEARCH Sea Ice Outlook
2008–2013, Geophys. Res. Lett., 41, 2411–2418, https://doi.org/10.1002/2014GL059388,
2014. a
Strong, C. and Rigor, I. G.: Arctic marginal ice zone trending wider in summer and narrower in winter, Geophys. Res. Lett., 40, 4864–4868,
https://doi.org/10.1002/grl.50928, 2013. a, b
Sutherland, P. and Dumont, D.: Marginal ice zone thickness and extent due to
wave radiation stress, J. Phys. Oceanogr., 48, 1885–1901, https://doi.org/10.1175/JPO-D-17-0167.1, 2018. a
Sutherland, P. and Melville, W. K.: Field measurements and scaling of ocean
surface wave-breaking statistics, Geophys. Res. Lett., 40, 3074–3079,
https://doi.org/10.1002/grl.50584, 2013. a
Thomson, J. and Rogers, W. E.: Swell and sea in the emerging Arctic Ocean, Geophys. Res. Lett., 41, 3136–3140, https://doi.org/10.1002/2014GL059983, 2014. a
Thomson, J., Ackley, S., Girard-Ardhuin, F., Ardhuin, F., Babanin, A., Bidlot, J., Boutin, G., Brozena, J., Cheng, S., Doble, M., Fairall, C.
Guest, P., Gebhardt, C., Gemmrich, J., Graber, H. C., Holt, B., Lehner, S., Lund, B., Meylan, M. H., Maksym, T., Montiel, F., Perrie, W., Persson, O., Rainville, L., Rogers, W. E., Shen, H., Shen, H., Squire,
V., Stammerjohn, S., Stopa, J., Smith, M. M., Sutherland,
P., and Wadhams P.: Overview of the arctic sea state and boundary layer physics program, J. Geophys. Res.-Oceans, 123, 8674–8687, 2018. a, b
Timmermans, M.-L.: The impact of stored solar heat on Arctic sea ice growth,
Geophys. Res. Lett., 42, 6399–6406, 2015. a
Tsamados, M., Feltham, D., Petty, A., Schroeder, D., and Flocco, D.: Processes controlling surface, bottom and lateral melt of Arctic sea ice in a state of the art sea ice model, Philos. T. R. Soc. Lond, 373, 20140167,
https://doi.org/10.1098/rsta.2014.0167, 2015. a
Uotila, P., Goosse, H., Haines, K., Chevallier, M., Barthélemy, A.,
Bricaud, C., Carton, J., Fučkar, N., Garric, G., Iovino, D., Kauker, F., Korhonen, M., Lien, V. S., Marnela, M., Massonnet, F., Mignac, D., Peterson, K. A., Sadikni, R., Shi, L., Tietsche, S., Toyoda, T., Xie, J., and Zhang, Z.: An
assessment of ten ocean reanalyses in the polar regions, Clim. Dynam.,
52, 1613–1650, 2018. a
Vancoppenolle, M., Fichefet, T., Goosse, H., Bouillon, S., Madec, G., and
Maqueda, M. A. M.: Simulating the mass balance and salinity of Arctic and
Antarctic sea ice. 1. Model description and validation, Ocean Model.,
27, 33–53, 2009. a
Wang, Q., Ilicak, M., Gerdes, R., Drange, H., Aksenov, Y., Bailey, D. A.,
Bentsen, M., Biastoch, A., Bozec, A., Böning, C., et al.: An assessment
of the Arctic Ocean in a suite of interannual CORE-II simulations. Part II:
Liquid freshwater, Ocean Model., 99, 86–109, 2016. a
Waseda, T., Webb, A., Sato, K., Inoue, J., Kohout, A., Penrose, B., and
Penrose, S.: Correlated Increase of High Ocean Waves and Winds in the
Ice-Free Waters of the Arctic Ocean, Sci. Rep., 8, 4489,
https://doi.org/10.1038/s41598-018-22500-9, 2018. a
WAVEWATCH III® Development Group:
User manual and system documentation of WAVEWATCH
III® version 5.16, Tech. Note 329,
NOAA/NWS/NCEP/MMAB, College Park, MD, USA, 326 pp. + Appendices,
2016. a
Williams, T. D., Bennetts, L. G., Squire, V. A., Dumont, D., and Bertino, L.:
Wave-ice interactions in the marginal ice zone. Part 2: Numerical
implementation and sensitivity studies along 1D transects of the ocean
surface, Ocean Model., 71, 92–101, https://doi.org/10.1016/j.ocemod.2013.05.011,
2013. a, b, c
WW3DG: The WAVEWATCH III Framework, available at: https://github.com/NOAA-EMC/WW3, last access: December, 2019.
a
Zhang, J., Schweiger, A., Steele, M., and Stern, H.: Sea ice floe size
distribution in the marginal ice zone: Theory and numerical experiments:
Modeling floe size distribution, J. Geophys. Res.-Oceans,
120, 3484–3498, https://doi.org/10.1002/2015JC010770, 2015. a, b, c, d, e, f, g, h, i, j, k, l, m, n
Zhang, J., Stern, H., Hwang, B., Schweiger, A., Steele, M., Stark, M., and
Graber, H. C.: Modeling the seasonal evolution of the Arctic sea ice floe
size distribution, Elementa, 4, 000126, https://doi.org/10.12952/journal.elementa.000126, 2016. a, b, c, d
Short summary
We investigate the interactions of surface ocean waves with sea ice taking place at the interface between the compact sea ice cover and the open ocean. We use a newly developed coupling framework between a wave and an ocean–sea ice numerical model. Our results show how the push on sea ice exerted by waves changes the amount and the location of sea ice melting, with a strong impact on the ocean surface properties close to the ice edge.
We investigate the interactions of surface ocean waves with sea ice taking place at the...
