Articles | Volume 15, issue 12
https://doi.org/10.5194/tc-15-5623-2021
© Author(s) 2021. 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-15-5623-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Dec 2021
Research article |
| 10 Dec 2021
| 10 Dec 2021
A generalized stress correction scheme for the Maxwell elasto-brittle rheology: impact on the fracture angles and deformations
Mathieu Plante
CORRESPONDING AUTHOR
Department of Atmospheric and Oceanic Sciences, McGill University, Montréal, Québec, Canada
L. Bruno Tremblay
Department of Atmospheric and Oceanic Sciences, McGill University, Montréal, Québec, Canada
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The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-100, https://doi.org/10.5194/tc-2023-100, 2023
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Brinicles are ice tubular structures that grow under the sea ice in cold regions. This happens because the salty water going downwards from the sea ice is colder than the sea water. We have recreated succesfully an analogue of these structures in our laboratory. Three methods were used, producing different results. In this paper we explain how to use these methods, study the behaviour of the brinicles created when changing the flow of water, as well as their importance for natural brinicles.
Katarzyna Bradtke and Agnieszka Herman
The Cryosphere, 17, 2073–2094, https://doi.org/10.5194/tc-17-2073-2023, https://doi.org/10.5194/tc-17-2073-2023, 2023
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The frazil streaks are one of the visible signs of complex interactions between the mixed-layer dynamics and the forming sea ice. Using high-resolution visible satellite imagery we characterize their spatial properties, relationship with the meteorological forcing, and role in modifying wind-wave growth in the Terra Nova Bay Polynya. We provide a simple statistical tool for estimating the extent and ice coverage of the region of high ice production under given wind speed and air temperature.
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
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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.
Nikolas O. Aksamit, Randall K. Scharien, Jennifer K. Hutchings, and Jennifer V. Lukovich
The Cryosphere, 17, 1545–1566, https://doi.org/10.5194/tc-17-1545-2023, https://doi.org/10.5194/tc-17-1545-2023, 2023
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Coherent flow patterns in sea ice have a significant influence on sea ice fracture and refreezing. We can better understand the state of sea ice, and its influence on the atmosphere and ocean, if we understand these structures. By adapting recent developments in chaotic dynamical systems, we are able to approximate ice stretching surrounding individual ice buoys. This illuminates the state of sea ice at much higher resolution and allows us to see previously invisible ice deformation patterns.
Robert Ricker, Steven Fons, Arttu Jutila, Nils Hutter, Kyle Duncan, Sinead L. Farrell, Nathan T. Kurtz, and Renée Mie Fredensborg Hansen
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Information on sea ice surface topography is important for studies of sea ice as well as for ship navigation through ice. The ICESat-2 satellite senses the sea ice surface with six laser beams. To examine the accuracy of these measurements, we carried out a temporally coincident helicopter flight along the same ground track as the satellite and measured the sea ice surface topography with a laser scanner. This showed that ICESat-2 can see even bumps of only few meters in the sea ice cover.
Ludovic Moreau, Léonard Seydoux, Jérôme Weiss, and Michel Campillo
The Cryosphere, 17, 1327–1341, https://doi.org/10.5194/tc-17-1327-2023, https://doi.org/10.5194/tc-17-1327-2023, 2023
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In the perspective of an upcoming seasonally ice-free Arctic, understanding the dynamics of sea ice in the changing climate is a major challenge in oceanography and climatology. It is therefore essential to monitor sea ice properties with fine temporal and spatial resolution. In this paper, we show that icequakes recorded on sea ice can be processed with artificial intelligence to produce accurate maps of sea ice thickness with high temporal and spatial resolutions.
Sasan Tavakoli and Alexander V. Babanin
The Cryosphere, 17, 939–958, https://doi.org/10.5194/tc-17-939-2023, https://doi.org/10.5194/tc-17-939-2023, 2023
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We have tried to develop some new wave–ice interaction models by considering two different types of forces, one of which emerges in the ice and the other of which emerges in the water. We have checked the ability of the models in the reconstruction of wave–ice interaction in a step-wise manner. The accuracy level of the models is acceptable, and it will be interesting to check whether they can be used in wave climate models or not.
Christian Melsheimer, Gunnar Spreen, Yufang Ye, and Mohammed Shokr
The Cryosphere, 17, 105–126, https://doi.org/10.5194/tc-17-105-2023, https://doi.org/10.5194/tc-17-105-2023, 2023
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It is necessary to know the type of Antarctic sea ice present – first-year ice (grown in one season) or multiyear ice (survived one summer melt) – to understand and model its evolution, as the ice types behave and react differently. We have adapted and extended an existing method (originally for the Arctic), and now, for the first time, daily maps of Antarctic sea ice types can be derived from microwave satellite data. This will allow a new data set from 2002 well into the future to be built.
Nazanin Asadi, Philippe Lamontagne, Matthew King, Martin Richard, and K. Andrea Scott
The Cryosphere, 16, 3753–3773, https://doi.org/10.5194/tc-16-3753-2022, https://doi.org/10.5194/tc-16-3753-2022, 2022
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Machine learning approaches are deployed to provide accurate daily spatial maps of sea ice presence probability based on ERA5 data as input. Predictions are capable of predicting freeze-up/breakup dates within a 7 d period at specific locations of interest to shipping operators and communities. Forecasts of the proposed method during the breakup season have skills comparing to Climate Normal and sea ice concentration forecasts from a leading subseasonal-to-seasonal forecasting system.
Simon Felix Reifenberg and Helge Friedrich Goessling
The Cryosphere, 16, 2927–2946, https://doi.org/10.5194/tc-16-2927-2022, https://doi.org/10.5194/tc-16-2927-2022, 2022
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Using model simulations, we analyze the impact of chaotic error growth on Arctic sea ice drift predictions. Regarding forecast uncertainty, our results suggest that it matters in which season and where ice drift forecasts are initialized and that both factors vary with the model in use. We find ice velocities to be slightly more predictable than near-surface wind, a main driver of ice drift. This is relevant for future developments of ice drift forecasting systems.
Agathe Serripierri, Ludovic Moreau, Pierre Boue, Jérôme Weiss, and Philippe Roux
The Cryosphere, 16, 2527–2543, https://doi.org/10.5194/tc-16-2527-2022, https://doi.org/10.5194/tc-16-2527-2022, 2022
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As a result of global warming, the sea ice is disappearing at a much faster rate than predicted by climate models. To better understand and predict its ongoing decline, we deployed 247 geophones on the fast ice in Van Mijen Fjord in Svalbard, Norway, in March 2019. The analysis of these data provided a precise daily evolution of the sea-ice parameters at this location with high spatial and temporal resolution and accuracy. The results obtained are consistent with the observations made in situ.
Laura L. Landrum and Marika M. Holland
The Cryosphere, 16, 1483–1495, https://doi.org/10.5194/tc-16-1483-2022, https://doi.org/10.5194/tc-16-1483-2022, 2022
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High-latitude Arctic wintertime sea ice and snow insulate the relatively warmer ocean from the colder atmosphere. As the climate warms, wintertime Arctic conductive heat fluxes increase even when the sea ice concentrations remain high. Simulations from the Community Earth System Model Large Ensemble (CESM1-LE) show how sea ice and snow thicknesses, as well as the distribution of these thicknesses, significantly impact large-scale calculations of wintertime surface heat budgets in the Arctic.
Yunhe Wang, Xiaojun Yuan, Haibo Bi, Mitchell Bushuk, Yu Liang, Cuihua Li, and Haijun Huang
The Cryosphere, 16, 1141–1156, https://doi.org/10.5194/tc-16-1141-2022, https://doi.org/10.5194/tc-16-1141-2022, 2022
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Charles Brunette, L. Bruno Tremblay, and Robert Newton
The Cryosphere, 16, 533–557, https://doi.org/10.5194/tc-16-533-2022, https://doi.org/10.5194/tc-16-533-2022, 2022
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Sea ice motion is a versatile parameter for monitoring the Arctic climate system. In this contribution, we use data from drifting buoys, winds, and ice thickness to parameterize the motion of sea ice in a free drift regime – i.e., flowing freely in response to the forcing from the winds and ocean currents. We show that including a dependence on sea ice thickness and taking into account a climatology of the surface ocean circulation significantly improves the accuracy of sea ice motion estimates.
Madison M. Smith, Marika Holland, and Bonnie Light
The Cryosphere, 16, 419–434, https://doi.org/10.5194/tc-16-419-2022, https://doi.org/10.5194/tc-16-419-2022, 2022
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Climate models represent the atmosphere, ocean, sea ice, and land with equations of varying complexity and are important tools for understanding changes in global climate. Here, we explore how realistic variations in the equations describing how sea ice melt occurs at the edges (called lateral melting) impact ice and climate. We find that these changes impact the progression of the sea-ice–albedo feedback in the Arctic and so make significant changes to the predicted Arctic sea ice.
Arttu Jutila, Stefan Hendricks, Robert Ricker, Luisa von Albedyll, Thomas Krumpen, and Christian Haas
The Cryosphere, 16, 259–275, https://doi.org/10.5194/tc-16-259-2022, https://doi.org/10.5194/tc-16-259-2022, 2022
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Sea-ice thickness retrieval from satellite altimeters relies on assumed sea-ice density values because density cannot be measured from space. We derived bulk densities for different ice types using airborne laser, radar, and electromagnetic induction sounding measurements. Compared to previous studies, we found high bulk density values due to ice deformation and younger ice cover. Using sea-ice freeboard, we derived a sea-ice bulk density parameterisation that can be applied to satellite data.
Joey J. Voermans, Qingxiang Liu, Aleksey Marchenko, Jean Rabault, Kirill Filchuk, Ivan Ryzhov, Petra Heil, Takuji Waseda, Takehiko Nose, Tsubasa Kodaira, Jingkai Li, and Alexander V. Babanin
The Cryosphere, 15, 5557–5575, https://doi.org/10.5194/tc-15-5557-2021, https://doi.org/10.5194/tc-15-5557-2021, 2021
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We have shown through field experiments that the amount of wave energy dissipated in landfast ice, sea ice attached to land, is much larger than in broken ice. By comparing our measurements against predictions of contemporary wave–ice interaction models, we determined which models can explain our observations and which cannot. Our results will improve our understanding of how waves and ice interact and how we can model such interactions to better forecast waves and ice in the polar regions.
Marika M. Holland, David Clemens-Sewall, Laura Landrum, Bonnie Light, Donald Perovich, Chris Polashenski, Madison Smith, and Melinda Webster
The Cryosphere, 15, 4981–4998, https://doi.org/10.5194/tc-15-4981-2021, https://doi.org/10.5194/tc-15-4981-2021, 2021
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As the most reflective and most insulative natural material, snow has important climate effects. For snow on sea ice, its high reflectivity reduces ice melt. However, its high insulating capacity limits ice growth. These counteracting effects make its net influence on sea ice uncertain. We find that with increasing snow, sea ice in both hemispheres is thicker and more extensive. However, the drivers of this response are different in the two hemispheres due to different climate conditions.
Don Perovich, Madison Smith, Bonnie Light, and Melinda Webster
The Cryosphere, 15, 4517–4525, https://doi.org/10.5194/tc-15-4517-2021, https://doi.org/10.5194/tc-15-4517-2021, 2021
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During summer, Arctic sea ice melts on its surface and bottom and lateral edges. Some of this fresh meltwater is stored on the ice surface in features called melt ponds. The rest flows into the ocean. The meltwater flowing into the upper ocean affects ice growth and melt, upper ocean properties, and ocean ecosystems. Using field measurements, we found that the summer meltwater was equal to an 80 cm thick layer; 85 % of this meltwater flowed into the ocean and 15 % was stored in melt ponds.
Sönke Maus, Martin Schneebeli, and Andreas Wiegmann
The Cryosphere, 15, 4047–4072, https://doi.org/10.5194/tc-15-4047-2021, https://doi.org/10.5194/tc-15-4047-2021, 2021
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As the hydraulic permeability of sea ice is difficult to measure, observations are sparse. The present work presents numerical simulations of the permeability of young sea ice based on a large set of 3D X-ray tomographic images. It extends the relationship between permeability and porosity available so far down to brine porosities near the percolation threshold of a few per cent. Evaluation of pore scales and 3D connectivity provides novel insight into the percolation behaviour of sea ice.
Cyril Palerme and Malte Müller
The Cryosphere, 15, 3989–4004, https://doi.org/10.5194/tc-15-3989-2021, https://doi.org/10.5194/tc-15-3989-2021, 2021
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Methods have been developed for calibrating sea ice drift forecasts from an operational prediction system using machine learning algorithms. These algorithms use predictors from sea ice concentration observations during the initialization of the forecasts, sea ice and wind forecasts, and some geographical information. Depending on the calibration method, the mean absolute error is reduced between 3.3 % and 8.0 % for the direction and between 2.5 % and 7.1 % for the speed of sea ice drift.
Dongyang Fu, Bei Liu, Yali Qi, Guo Yu, Haoen Huang, and Lilian Qu
The Cryosphere, 15, 3797–3811, https://doi.org/10.5194/tc-15-3797-2021, https://doi.org/10.5194/tc-15-3797-2021, 2021
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Our results show three main sea ice drift patterns have different multiscale variation characteristics. The oscillation period of the third sea ice transport pattern is longer than the other two, and the ocean environment has a more significant influence on it due to the different regulatory effects of the atmosphere and ocean environment on sea ice drift patterns on various scales. Our research can provide a basis for the study of Arctic sea ice dynamics parameterization in numerical models.
Andrii Murdza, Arttu Polojärvi, Erland M. Schulson, and Carl E. Renshaw
The Cryosphere, 15, 2957–2967, https://doi.org/10.5194/tc-15-2957-2021, https://doi.org/10.5194/tc-15-2957-2021, 2021
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The strength of refrozen floes or piles of ice rubble is an important factor in assessing ice-structure interactions, as well as the integrity of an ice cover itself. The results of this paper provide unique data on the tensile strength of freeze bonds and are the first measurements to be reported. The provided information can lead to a better understanding of the behavior of refrozen ice floes and better estimates of the strength of an ice rubble pile.
H. Jakob Belter, Thomas Krumpen, Luisa von Albedyll, Tatiana A. Alekseeva, Gerit Birnbaum, Sergei V. Frolov, Stefan Hendricks, Andreas Herber, Igor Polyakov, Ian Raphael, Robert Ricker, Sergei S. Serovetnikov, Melinda Webster, and Christian Haas
The Cryosphere, 15, 2575–2591, https://doi.org/10.5194/tc-15-2575-2021, https://doi.org/10.5194/tc-15-2575-2021, 2021
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Summer sea ice thickness observations based on electromagnetic induction measurements north of Fram Strait show a 20 % reduction in mean and modal ice thickness from 2001–2020. The observed variability is caused by changes in drift speeds and consequential variations in sea ice age and number of freezing-degree days. Increased ocean heat fluxes measured upstream in the source regions of Arctic ice seem to precondition ice thickness, which is potentially still measurable more than a year later.
Ann Keen, Ed Blockley, David A. Bailey, Jens Boldingh Debernard, Mitchell Bushuk, Steve Delhaye, David Docquier, Daniel Feltham, François Massonnet, Siobhan O'Farrell, Leandro Ponsoni, José M. Rodriguez, David Schroeder, Neil Swart, Takahiro Toyoda, Hiroyuki Tsujino, Martin Vancoppenolle, and Klaus Wyser
The Cryosphere, 15, 951–982, https://doi.org/10.5194/tc-15-951-2021, https://doi.org/10.5194/tc-15-951-2021, 2021
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We compare the mass budget of the Arctic sea ice in a number of the latest climate models. New output has been defined that allows us to compare the processes of sea ice growth and loss in a more detailed way than has previously been possible. We find that that the models are strikingly similar in terms of the major processes causing the annual growth and loss of Arctic sea ice and that the budget terms respond in a broadly consistent way as the climate warms during the 21st century.
Ron Kwok, Alek A. Petty, Marco Bagnardi, Nathan T. Kurtz, Glenn F. Cunningham, Alvaro Ivanoff, and Sahra Kacimi
The Cryosphere, 15, 821–833, https://doi.org/10.5194/tc-15-821-2021, https://doi.org/10.5194/tc-15-821-2021, 2021
Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Rasmus Tonboe, Stefan Hendricks, Robert Ricker, James Mead, Robbie Mallett, Marcus Huntemann, Polona Itkin, Martin Schneebeli, Daniela Krampe, Gunnar Spreen, Jeremy Wilkinson, Ilkka Matero, Mario Hoppmann, and Michel Tsamados
The Cryosphere, 14, 4405–4426, https://doi.org/10.5194/tc-14-4405-2020, https://doi.org/10.5194/tc-14-4405-2020, 2020
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This study provides a first look at the data collected by a new dual-frequency Ka- and Ku-band in situ radar over winter sea ice in the Arctic Ocean. The instrument shows potential for using both bands to retrieve snow depth over sea ice, as well as sensitivity of the measurements to changing snow and atmospheric conditions.
Leandro Ponsoni, François Massonnet, David Docquier, Guillian Van Achter, and Thierry Fichefet
The Cryosphere, 14, 2409–2428, https://doi.org/10.5194/tc-14-2409-2020, https://doi.org/10.5194/tc-14-2409-2020, 2020
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The continuous melting of the Arctic sea ice observed in the last decades has a significant impact at global and regional scales. To understand the amplitude and consequences of this impact, the monitoring of the total sea ice volume is crucial. However, in situ monitoring in such a harsh environment is hard to perform and far too expensive. This study shows that four well-placed sampling locations are sufficient to explain about 70 % of the inter-annual changes in the pan-Arctic sea ice volume.
H. Jakob Belter, Thomas Krumpen, Stefan Hendricks, Jens Hoelemann, Markus A. Janout, Robert Ricker, and Christian Haas
The Cryosphere, 14, 2189–2203, https://doi.org/10.5194/tc-14-2189-2020, https://doi.org/10.5194/tc-14-2189-2020, 2020
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The validation of satellite sea ice thickness (SIT) climate data records with newly acquired moored sonar SIT data shows that satellite products provide modal rather than mean SIT in the Laptev Sea region. This tendency of satellite-based SIT products to underestimate mean SIT needs to be considered for investigations of sea ice volume transports. Validation of satellite SIT in the first-year-ice-dominated Laptev Sea will support algorithm development for more reliable SIT records in the Arctic.
Mark S. Handcock and Marilyn N. Raphael
The Cryosphere, 14, 2159–2172, https://doi.org/10.5194/tc-14-2159-2020, https://doi.org/10.5194/tc-14-2159-2020, 2020
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Traditional methods of calculating the annual cycle of sea ice extent disguise the variation of amplitude and timing (phase) of the advance and retreat of the ice. We present a multiscale model that explicitly allows them to vary, resulting in a much improved representation of the cycle. We show that phase is the dominant contributor to the variability in the cycle and that the anomalous decay of Antarctic sea ice in 2016 was due largely to a change of phase.
Rebecca J. Rolph, Daniel L. Feltham, and David Schröder
The Cryosphere, 14, 1971–1984, https://doi.org/10.5194/tc-14-1971-2020, https://doi.org/10.5194/tc-14-1971-2020, 2020
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It is well known that the Arctic sea ice extent is declining, and it is often assumed that the marginal ice zone (MIZ), the area of partial sea ice cover, is consequently increasing. However, we find no trend in the MIZ extent during the last 40 years from observations that is consistent with a widening of the MIZ as it moves northward. Differences of MIZ extent between different satellite retrievals are too large to provide a robust basis to verify model simulations of MIZ extent.
Mark A. Tschudi, Walter N. Meier, and J. Scott Stewart
The Cryosphere, 14, 1519–1536, https://doi.org/10.5194/tc-14-1519-2020, https://doi.org/10.5194/tc-14-1519-2020, 2020
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A new version of a set of data products that contain the velocity of sea ice and the age of this ice has been developed. We provide a history of the product development and discuss the improvements to the algorithms that create these products. We find that changes in sea ice motion and age show a significant shift in the Arctic ice cover, from a pack with a high concentration of older ice to a sea ice cover dominated by younger ice, which is more susceptible to summer melt.
Angela Cheng, Barbara Casati, Adrienne Tivy, Tom Zagon, Jean-François Lemieux, and L. Bruno Tremblay
The Cryosphere, 14, 1289–1310, https://doi.org/10.5194/tc-14-1289-2020, https://doi.org/10.5194/tc-14-1289-2020, 2020
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Sea ice charts by the Canadian Ice Service (CIS) contain visually estimated ice concentration produced by analysts. The accuracy of manually derived ice concentrations is not well understood. The subsequent uncertainty of ice charts results in downstream uncertainties for ice charts users, such as models and climatology studies, and when used as a verification source for automated sea ice classifiers. This study quantifies the level of accuracy and inter-analyst agreement for ice charts by CIS.
Young Jun Kim, Hyun-Cheol Kim, Daehyeon Han, Sanggyun Lee, and Jungho Im
The Cryosphere, 14, 1083–1104, https://doi.org/10.5194/tc-14-1083-2020, https://doi.org/10.5194/tc-14-1083-2020, 2020
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In this study, we proposed a novel 1-month sea ice concentration (SIC) prediction model with eight predictors using a deep-learning approach, convolutional neural networks (CNNs). The proposed CNN model was evaluated and compared with the two baseline approaches, random-forest and simple-regression models, resulting in better performance. This study also examined SIC predictions for two extreme cases in 2007 and 2012 in detail and the influencing factors through a sensitivity analysis.
Shiming Xu, Lu Zhou, and Bin Wang
The Cryosphere, 14, 751–767, https://doi.org/10.5194/tc-14-751-2020, https://doi.org/10.5194/tc-14-751-2020, 2020
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Sea ice thickness parameters are key to polar climate change studies and forecasts. Airborne and satellite measurements provide complementary observational capabilities. The study analyzes the variability in freeboard and snow depth measurements and its changes with scale in Operation IceBridge, CryoVEx, CryoSat-2 and ICESat. Consistency between airborne and satellite data is checked. Analysis calls for process-oriented attribution of variability and covariability features of these parameters.
Valeria Selyuzhenok, Igor Bashmachnikov, Robert Ricker, Anna Vesman, and Leonid Bobylev
The Cryosphere, 14, 477–495, https://doi.org/10.5194/tc-14-477-2020, https://doi.org/10.5194/tc-14-477-2020, 2020
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This study explores a link between the long-term variations in the integral sea ice volume in the Greenland Sea and oceanic processes. We link the changes in the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) regional sea ice volume with the mixed layer, depth and upper-ocean heat content derived using the ARMOR dataset.
Chao Min, Longjiang Mu, Qinghua Yang, Robert Ricker, Qian Shi, Bo Han, Renhao Wu, and Jiping Liu
The Cryosphere, 13, 3209–3224, https://doi.org/10.5194/tc-13-3209-2019, https://doi.org/10.5194/tc-13-3209-2019, 2019
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Sea ice volume export through the Fram Strait has been studied using varied methods, however, mostly in winter months. Here we report sea ice volume estimates that extend over summer seasons. A recent developed sea ice thickness dataset, in which CryoSat-2 and SMOS sea ice thickness together with SSMI/SSMIS sea ice concentration are assimilated, is used and evaluated in the paper. Results show our estimate is more reasonable than that calculated by satellite data only.
M. Jeffrey Mei, Ted Maksym, Blake Weissling, and Hanumant Singh
The Cryosphere, 13, 2915–2934, https://doi.org/10.5194/tc-13-2915-2019, https://doi.org/10.5194/tc-13-2915-2019, 2019
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Sea ice thickness is hard to measure directly, and current datasets are very limited to sporadically conducted drill lines. However, surface elevation is much easier to measure. Converting surface elevation to ice thickness requires making assumptions about snow depth and density, which leads to large errors (and may not generalize to new datasets). A deep learning method is presented that uses the surface morphology as a direct predictor of sea ice thickness, with testing errors of < 20 %.
Pierre Rampal, Véronique Dansereau, Einar Olason, Sylvain Bouillon, Timothy Williams, Anton Korosov, and Abdoulaye Samaké
The Cryosphere, 13, 2457–2474, https://doi.org/10.5194/tc-13-2457-2019, https://doi.org/10.5194/tc-13-2457-2019, 2019
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In this article, we look at how the Arctic sea ice cover, as a solid body, behaves on different temporal and spatial scales. We show that the numerical model neXtSIM uses a new approach to simulate the mechanics of sea ice and reproduce the characteristics of how sea ice deforms, as observed by satellite. We discuss the importance of this model performance in the context of simulating climate processes taking place in polar regions, like the exchange of energy between the ocean and atmosphere.
Alberto Alberello, Miguel Onorato, Luke Bennetts, Marcello Vichi, Clare Eayrs, Keith MacHutchon, and Alessandro Toffoli
The Cryosphere, 13, 41–48, https://doi.org/10.5194/tc-13-41-2019, https://doi.org/10.5194/tc-13-41-2019, 2019
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Existing observations do not provide quantitative descriptions of the floe size distribution for pancake ice floes. This is important during the Antarctic winter sea ice expansion, when hundreds of kilometres of ice cover around the Antarctic continent are composed of pancake floes (D = 0.3–3 m). Here, a new set of images from the Antarctic marginal ice zone is used to measure the shape of individual pancakes for the first time and to infer their size distribution.
Frédéric Laliberté, Stephen E. L. Howell, Jean-François Lemieux, Frédéric Dupont, and Ji Lei
The Cryosphere, 12, 3577–3588, https://doi.org/10.5194/tc-12-3577-2018, https://doi.org/10.5194/tc-12-3577-2018, 2018
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Ice that forms over marginal seas often gets anchored and becomes landfast. Landfast ice is fundamental to the local ecosystems, is of economic importance as it leads to hazardous seafaring conditions and is also a choice hunting ground for both the local population and large predators. Using observations and climate simulations, this study shows that, especially in the Canadian Arctic, landfast ice might be more resilient to climate change than is generally thought.
Iina Ronkainen, Jonni Lehtiranta, Mikko Lensu, Eero Rinne, Jari Haapala, and Christian Haas
The Cryosphere, 12, 3459–3476, https://doi.org/10.5194/tc-12-3459-2018, https://doi.org/10.5194/tc-12-3459-2018, 2018
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We quantify the sea ice thickness variability in the Bay of Bothnia using various observational data sets. For the first time we use helicopter and shipborne electromagnetic soundings to study changes in drift ice of the Bay of Bothnia. Our results show that the interannual variability of ice thickness is larger in the drift ice zone than in the fast ice zone. Furthermore, the mean thickness of heavily ridged ice near the coast can be several times larger than that of fast ice.
Edward W. Blockley and K. Andrew Peterson
The Cryosphere, 12, 3419–3438, https://doi.org/10.5194/tc-12-3419-2018, https://doi.org/10.5194/tc-12-3419-2018, 2018
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Arctic sea-ice prediction on seasonal time scales is becoming increasingly more relevant to society but the predictive capability of forecasting systems is low. Several studies suggest initialization of sea-ice thickness (SIT) could improve the skill of seasonal prediction systems. Here for the first time we test the impact of SIT initialization in the Met Office's GloSea coupled prediction system using CryoSat-2 data. We show significant improvements to Arctic extent and ice edge location.
Jeff K. Ridley and Edward W. Blockley
The Cryosphere, 12, 3355–3360, https://doi.org/10.5194/tc-12-3355-2018, https://doi.org/10.5194/tc-12-3355-2018, 2018
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The climate change conference held in Paris in 2016 made a commitment to limiting global-mean warming since the pre-industrial era to well below 2 °C and to pursue efforts to limit the warming to 1.5 °C. Since global warming is already at 1 °C, the 1.5 °C can only be achieved at considerable cost. It is thus important to assess the risks associated with the higher target. This paper shows that the decline of Arctic sea ice, and associated impacts, can only be halted with the 1.5 °C target.
Aleksey Malinka, Eleonora Zege, Larysa Istomina, Georg Heygster, Gunnar Spreen, Donald Perovich, and Chris Polashenski
The Cryosphere, 12, 1921–1937, https://doi.org/10.5194/tc-12-1921-2018, https://doi.org/10.5194/tc-12-1921-2018, 2018
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Melt ponds occupy a large part of the Arctic sea ice in summer and strongly affect the radiative budget of the atmosphere–ice–ocean system. The melt pond reflectance is modeled in the framework of the radiative transfer theory and validated with field observations. It improves understanding of melting sea ice and enables better parameterization of the surface in Arctic atmospheric remote sensing (clouds, aerosols, trace gases) and re-evaluating Arctic climatic feedbacks at a new accuracy level.
Cited articles
Amitrano, D. and Helmstetter, A.:
Brittle creep, damage and time to failure in rocks,
J. Geophys. Res.-Sol. Ea.,
111, B11201, https://doi.org/10.1029/2005JB004252, 2006. a, b
Amitrano, D., Grasso, J.-R., and Hantz, D.:
From diffuse to localised damage through elastic interaction,
Geophys. Res. Lett.,
26, 2109–2112, 1999. a
Arthur, J. R. F., Dunstan, T., Al-Ani, Q. A. J. L., and Assadi, A.:
Plastic deformation and failure in granular media,
Géotechnique,
27, 53–74, https://doi.org/10.1680/geot.1977.27.1.53, 1977. a, b
Balendran, B. and Nemat-Nasser, S.:
Double sliding model for cyclic deformation of granular materials, including dilatancy effects,
J. Mech. Phys. Solids,
41, 573–612, https://doi.org/10.1016/0022-5096(93)90049-L, 1993. a, b, c
Bardet, J.:
Orientation of shear bands in frictional soils,
J. Eng. Mech.-ASCE,
117, 1466–1484, https://doi.org/10.1061/(ASCE)0733-9399(1991)117:7(1466), 1991. a, b
Bolton, M. D.:
The strength and dilatancy of sands,
Geotechnique,
36, 65–78, https://doi.org/10.1680/geot.1986.36.1.65, 1986. a
Bouchat, A. and Tremblay, B.:
Using sea-ice deformation fields to constrain the mechanical strength parameters of geophysical sea ice,
J. Geophys. Res.-Oceans,
122, 5802–5825, https://doi.org/10.1002/2017JC013020, 2017. a
Bouchat, A., Hutter, N. C., Chanut, J., Dupont, F., Dukhovskoy, D. S., Garric, G., Lee, Y. J., Lemieux, J.-F., Lique, C., Losch, M., Maslowski, W., Myers, P. G., Òlason, E. Ö., Rampal, P., Rasmussen, T. A. S., Talandier, C., Tremblay, B., and Wang, Q.:
Sea Ice Rheology Experiment (SIREx), Part I: Scaling and statistical properties of sea-ice deformation fields,
Earth and Space Science Open Archive,
p. 36, https://doi.org/10.1002/essoar.10507397.1, 2021. a, b, c
Bouillon, S. and Rampal, P.:
Presentation of the dynamical core of neXtSIM, a new sea ice model,
Ocean Model.,
91, 23–37, https://doi.org/10.1016/j.ocemod.2015.04.005, 2015. a
Carrier, A., Got, J.-L., Peltier, A., Ferrazzini, V., Staudacher, T., Kowalski, P., and Boissier, P.:
A damage model for volcanic edifices: Implications for edifice strength, magma pressure, and eruptive processes,
J. Geophys. Res.-Sol. Ea.,
120, 567–583, https://doi.org/10.1002/2014JB011485, 2015. a
Coon, M. D., Maykut, G. A., Pritchard, R. S., Rothrock, D. A., and Thorndike, A. S.:
Modeling the pack ice as an elastic-plastic material,
AIDJEX bulletin,
24, 1–105, https://doi.org/10.1017/CBO9781107415324.004, 1974. a, b
Coulomb, C.:
Test on the applications of the rules of maxima and minima to some problems of statics related to architecture,
Mem. Math. Phys.,
7, 343–382, 1773. a
Damsgaard, A., Adcroft, A., and Sergienko, O.:
Application of Discrete Element Methods to Approximate Sea Ice Dynamics,
J. Adv. Model. Earth Sy.,
10, 2228–2244, https://doi.org/10.1029/2018MS001299, 2018. a
Dansereau, V., Weiss, J., Saramito, P., Lattes, P., and Coche, E.: Ice bridges and ridges in the Maxwell-EB sea ice rheology, The Cryosphere, 11, 2033–2058, https://doi.org/10.5194/tc-11-2033-2017, 2017. a, b
Erlingsson, B.:
Two-Dimensional Deformation Patterns in Sea Ice,
J. Glaciol.,
34, 301–308, https://doi.org/10.3189/S0022143000007061, 1988. a
Girard, L., Bouillon, S., Weiss, J., Amitrano, D., Fichefet, T., and Legat, V.:
A new modeling framework for sea-ice mechanics based on elasto-brittle rheology,
Ann. Glaciol.,
52, 123–132, https://doi.org/10.3189/172756411795931499, 2011. a
Hata, Y. and Tremblay, L. B.:
Anisotropic internal thermal stress in sea ice from the Canadian Arctic Archipelago,
J. Geophys. Res.-Oceans,
120, 5457–5472, https://doi.org/10.1002/2015JC010819, 2015. a
Herman, A.: Discrete-Element bonded-particle Sea Ice model DESIgn, version 1.3a – model description and implementation, Geosci. Model Dev., 9, 1219–1241, https://doi.org/10.5194/gmd-9-1219-2016, 2016. a
Hibler III, W. D. and Schulson, E. M.:
On modeling the anisotropic failure and flow of flawed sea ice,
J. Geophys. Res.-Oceans,
105, 17105–17120, https://doi.org/10.1029/2000JC900045, 2000. a
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, b
Hutter, N., Losch, M., and Menemenlis, D.:
Scaling Properties of Arctic Sea Ice Deformation in a High-Resolution Viscous-Plastic Sea Ice Model and in Satellite Observations,
J. Geophys. Res.-Oceans,
123, 672–687, https://doi.org/10.1002/2017JC013119, 2018. a
Hutter, N. C., Bouchat, A., Dupont, F., Dukhovskoy, D. S., Koldunov, N. V., Lee, Y. J., Lemieux, J.-F., Lique, C., Losch, M., Maslowski, W., Myers, P. G., Òlason, E. Ö., Rampal, P., Rasmussen, T. A. S., Talandier, C., Tremblay, B., and Wang, Q.:
Sea Ice Rheology Experiment (SIREx), Part II: Evaluating simulated linear kinematic features in high-resolution sea-ice simulations,
Earth and Space Science Open Archive,
p. 35, https://doi.org/10.1002/essoar.10507396.1, 2021. a, b, c, d
Itkin, P., Spreen, G., Hvidegaard, S. M., Skourup, H., Wilkinson, J., Gerland, S., and Granskog, M. A.:
Contribution of Deformation to Sea Ice Mass Balance: A Case Study From an N-ICE2015 Storm,
Geophys. Res. Lett.,
45, 789–796, https://doi.org/10.1002/2017GL076056, 2018. a
Karimi, K. and Barrat, J.-L.:
Correlation and shear bands in a plastically deformed granular medium,
Sci. Rep.,
8, 4021, https://doi.org/10.1038/s41598-018-22310-z, 2018. a
Kimmritz, M., Danilov, S., and Losch, M.:
The adaptive EVP method for solving the sea ice momentum equation,
Ocean Model.,
101, 59–67, https://doi.org/10.1016/j.ocemod.2016.03.004, 2016. a
Koldunov, N. V., Danilov, S., Sidorenko, D., Hutter, N., Losch, M., Goessling, H., Rakowsky, N., Scholz, P., Sein, D., Wang, Q., and Jung, T.:
Fast EVP Solutions in a High-Resolution Sea Ice Model,
J. Adv. Model. Earth Sy.,
11, 1269–1284, https://doi.org/10.1029/2018MS001485, 2019. a
Kozo, T. L.:
Initial model results for Arctic mixed layer circulation under a refreezing lead,
J. Geophys. Res.-Oceans,
88, 2926–2934, https://doi.org/10.1029/JC088iC05p02926, 1983. a
Ledley, T. S.:
A coupled energy balance climate-sea ice model: Impact of sea ice and leads on climate,
J. Geophys. Res.-Atmos.,
93, 15919–15932, https://doi.org/10.1029/JD093iD12p15919, 1988. a
Lemieux, J.-F., Tremblay, B., Thomas, S., Sedláček, J., and Mysak, L. A.:
Using the preconditioned Generalized Minimum RESidual (GMRES) method to solve the sea-ice momentum equation,
J. Geophys. Res.-Oceans,
113, C10004, https://doi.org/10.1029/2007JC004680, 2008. a, b, c
Lemieux, J.-F., Knoll, D. A., Losch, M., and Girard, C.:
A second-order accurate in time IMplicit–EXplicit (IMEX) integration scheme for sea ice dynamics,
J. Comput. Phys.,
263, 375–392, https://doi.org/10.1016/j.jcp.2014.01.010, 2014. a, b, c, d
Li, X., Krueger, S. K., Strong, C., Mace, G. G., and Benson, S.:
Midwinter Arctic leads form and dissipate low clouds,
Nat. Commun.,
11, 206, https://doi.org/10.1038/s41467-019-14074-5, 2020. a
Lüpkes, C., Vihma, T., Birnbaum, G., and Wacker, U.:
Influence of leads in sea ice on the temperature of the atmospheric boundary layer during polar night,
Geophys. Res. Lett.,
35, L03805, https://doi.org/10.1029/2007GL032461, 2008. a
Marko, J. R. and Thomson, R. E.:
Rectilinear leads and internal motions in the ice pack of the western Arctic Ocean,
J. Geophys. Res.,
82, 979–987, https://doi.org/10.1029/JC082i006p00979, 1977. a, b
Matsumura, Y. and Hasumi, H.:
Brine-Driven Eddies under Sea Ice Leads and Their Impact on the Arctic Ocean Mixed Layer,
J. Phys. Oceanogr.,
38, 146–163, https://doi.org/10.1175/2007JPO3620.1, 2008. a
Maykut, G. A.:
Large-scale heat exchange and ice production in the central Arctic,
J. Geophys. Res.-Oceans,
87, 7971–7984, https://doi.org/10.1029/JC087iC10p07971, 1982. a
Mohr, O.:
Welche Umstände bedingen die Elastizitätsgrenze und den Bruch eines Materials,
Z. Ver. Dtsch. Ing.,
46, 1572–1577, 1900. a
Murakami, S.:
Continuum damage mechanics: a continuum mechanics approach to the analysis of damage and fracture,
https://doi.org/10.1007/978-94-007-2666-6, 2012. a, b
Overland, J. E., McNutt, S. L., Salo, S., Groves, J., and Li, S.:
Arctic sea ice as a granular plastic,
J. Geophys. Res.-Oceans,
103, 21845–21867, https://doi.org/10.1029/98JC01263, 1998. 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, c
Rampal, P., Dansereau, V., Olason, E., Bouillon, S., Williams, T., Korosov, A., and Samaké, A.: On the multi-fractal scaling properties of sea ice deformation, The Cryosphere, 13, 2457–2474, https://doi.org/10.5194/tc-13-2457-2019, 2019. a, b
Rice, J. R.:
Solid Mechanics,
Harvard University, Cambridge, MA, 2010. a
Ringeisen, D., Tremblay, L. B., and Losch, M.: Non-normal flow rules affect fracture angles in sea ice viscous–plastic rheologies, The Cryosphere, 15, 2873–2888, https://doi.org/10.5194/tc-15-2873-2021, 2021. a, b
Roscoe, K. H.:
The Influence of Strains in Soil Mechanics,
Géotechnique,
20, 129–170, https://doi.org/10.1680/geot.1970.20.2.129, 1970. a
Schulson, E. M.:
Compressive shear faults within arctic sea ice: Fracture on scales large and small,
J. Geophys. Res.-Oceans,
109, C07016, https://doi.org/10.1029/2003JC002108, 2004. a, b, c
Sodhi, D. S.: Ice arching and the drift of pack ice through restricted channels, Crrel report 77-18, Cold Regions Research And Engineering Laboratory, Hanover, New Hampshire, 1977. a
Stern, H. L., Rothrock, D. A., and Kwok, R.:
Open water production in Arctic sea ice: Satellite measurements and model parameterizations,
J. Geophys. Res.-Oceans,
100, 20601–20612, https://doi.org/10.1029/95JC02306, 1995. a
Sulsky, D. and Peterson, K.:
Toward a new elastic–decohesive model of Arctic sea ice,
Physica D, special Issue: Fluid Dynamics: From Theory to Experiment,
240, 1674–1683, https://doi.org/10.1016/j.physd.2011.07.005, 2011. a, b, c
Tabata, T.:
A Measurement of Visco-Elastic Constants of Sea Ice,
Journal of the Oceanographical Society of Japan,
11, 185–189, 1955. a
Timco, G. and Weeks, W.:
A review of the engineering properties of sea ice,
Cold Reg. Sci. Technol.,
60, 107–129, https://doi.org/10.1016/j.coldregions.2009.10.003, 2010. a
Tremblay, L.-B. and Hakakian, M.:
Estimating the Sea Ice Compressive Strength from Satellite-Derived Sea Ice Drift and NCEP Reanalysis Data,
J. Phys. Oceanogr.,
36, 2165–2172, https://doi.org/10.1175/JPO2954.1, 2006. a
Tuhkuri, J. and Lensu, M.:
Laboratory tests on ridging and rafting of ice sheets,
J. Geophys. Res.-Oceans,
107, 8-1–8-14, https://doi.org/10.1029/2001JC000848, 2002. a, b
Turnbull, I. D., Torbati, R. Z., and Taylor, R. S.:
Relative influences of the metocean forcings on the drifting ice pack and estimation of internal ice stress gradients in the Labrador Sea,
J. Geophys. Res.-Oceans,
122, 5970–5997, https://doi.org/10.1002/2017JC012805, 2017.
a
Vardoulakis, I.:
Shear band inclination and shear modulus of sand in biaxial tests,
Int. J. Numer. Anal. Met.,
4, 103–119, https://doi.org/10.1002/nag.1610040202, 1980. a
Wachter, L., Renshaw, C., and Schulson, E.:
Transition in brittle failure mode in ice under low confinement,
Acta Mater.,
57, 345–355, https://doi.org/10.1016/j.actamat.2008.09.021, 2009. a
Wang, K.:
Observing the yield curve of compacted pack ice,
J. Geophys. Res.-Oceans,
112, C05015, https://doi.org/10.1029/2006JC003610, 2007. a
Wilchinsky, A. V. and Feltham, D. L.:
A continuum anisotropic model of sea-ice dynamics,
P. Roy. Soc. Lond. A Math.,
460, 2105–2140, https://doi.org/10.1098/rspa.2004.1282, 2004. a, b
Wilchinsky, A. V., Heorton, H. D. B. S., Feltham, D. L., and Holland, P. R.:
Study of the Impact of Ice Formation in Leads upon the Sea Ice Pack Mass Balance Using a New Frazil and Grease Ice Parameterization,
J. Phys. Oceanogr.,
45, 2025–2047, https://doi.org/10.1175/JPO-D-14-0184.1, 2015. a
Short summary
We propose a generalized form for the damage parameterization such that super-critical stresses can return to the yield with different final sub-critical stress states. In uniaxial compression simulations, the generalization improves the orientation of sea ice fractures and reduces the growth of numerical errors. Shear and convergence deformations however remain predominant along the fractures, contrary to observations, and this calls for modification of the post-fracture viscosity formulation.
We propose a generalized form for the damage parameterization such that super-critical stresses...
