Wave–sea-ice interactions in a brittle rheological framework

Abstract. The decrease in Arctic sea ice extent is associated with an increase of the area where sea ice and open ocean interact, commonly referred to as the Marginal Ice Zone (MIZ). In this area, sea ice is particularly exposed to waves that can penetrate over tens to hundreds of kilometres into the ice cover. Waves are known to play a major role in the fragmentation of sea ice in the MIZ, and the interactions between wave-induced sea ice fragmentation and lateral melting have received particular attention in recent years. The impact of this fragmentation on sea ice dynamics, however, remains mostly unknown, although it is thought that fragmented sea ice experiences less resistance to deformation than pack ice. Here, we introduce a new coupled framework involving the spectral wave model WAVEWATCH III and the sea ice model neXtSIM, which includes a Maxwell-Elasto Brittle rheology. We use this coupled modelling system to investigate the potential impact of wave-induced sea ice fragmentation on sea ice dynamics. Focusing on the Barents Sea, we find that the decrease of the internal stress of sea ice resulting from its fragmentation by waves results in a more dynamical MIZ, in particular in areas where sea ice is compact. Sea ice drift is enhanced for both on-ice and off-ice wind conditions. Our results stress the importance of considering wave–sea-ice interactions for forecast applications. They also suggest that waves likely modulate the area of sea ice that is advected away from the pack by ocean (sub-)mesoscale eddies near the ice edge, potentially contributing to the observed past, current and future sea ice cover decline in the Arctic.

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Impact of wave-induced sea ice fragmentation on sea ice dynamics in the MIZ

10.5194/egusphere-egu2020-8657 ◽

2020 ◽

Author(s):

Guillaume Boutin ◽

Timothy Williams ◽

Pierre Rampal ◽

Einar Olason ◽

Camille Lique

Keyword(s):

Sea Ice ◽

Barents Sea ◽

Ice Cover ◽

Arctic Sea Ice ◽

The Arctic ◽

Sea Ice Extent ◽

Ice Dynamics ◽

Sea Ice Dynamics ◽

Wave Induced ◽

The Impact

<p>The decrease in Arctic sea ice extent is associated with an increase of the area where sea ice and open ocean interact, commonly referred to as the Marginal Ice Zone (MIZ). In this area, sea ice is particularly exposed to waves that can penetrate over tens to hundreds of kilometres into the ice cover. Waves are known to play a major role in the fragmentation of sea ice in the MIZ, and the interactions between wave-induced sea ice fragmentation and lateral melting have received particular attention in recent years. The impact of this fragmentation on sea ice dynamics, however, remains mostly unknown, although it is thought that fragmented sea ice experiences less resistance to deformation than pack ice. In this presentation, we will introduce a new coupled framework involving the spectral wave model WAVEWATCH III and the sea ice model neXtSIM, which includes a Maxwell-Elasto Brittle rheology. We use this coupled modelling system to investigate the potential impact of wave-induced sea ice fragmentation on sea ice dynamics. Focusing on the Barents Sea, we find that the decrease of the internal stress of sea ice resulting from its fragmentation by waves results in a more dynamical MIZ, in particular in areas where sea ice is compact. Sea ice drift is enhanced for both on-ice and off-ice wind conditions. Our results stress the importance of considering wave&#8211;sea-ice interactions for forecast applications. They also suggest that waves likely modulate the area of sea ice that is advected away from the pack by ocean (sub-)mesoscale eddies near the ice edge, potentially contributing to the observed past, current and future sea ice cover decline in the Arctic.&#160;</p>

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Wave–sea-ice interactions in a brittle rheological framework

The Cryosphere ◽

10.5194/tc-15-431-2021 ◽

2021 ◽

Vol 15 (1) ◽

pp. 431-457

Author(s):

Guillaume Boutin ◽

Timothy Williams ◽

Pierre Rampal ◽

Einar Olason ◽

Camille Lique

Keyword(s):

Sea Ice ◽

Barents Sea ◽

Ocean Waves ◽

Ice Cover ◽

The Arctic ◽

Sea Ice Extent ◽

Ice Dynamics ◽

Coupled Modelling ◽

Wave Induced ◽

The Impact

Abstract. As sea ice extent decreases in the Arctic, surface ocean waves have more time and space to develop and grow, exposing the marginal ice zone (MIZ) to more frequent and more energetic wave events. Waves can fragment the ice cover over tens of kilometres, and the prospect of increasing wave activity has sparked recent interest in the interactions between wave-induced sea ice fragmentation and lateral melting. The impact of this fragmentation on sea ice dynamics, however, remains mostly unknown, although it is thought that fragmented sea ice experiences less resistance to deformation than pack ice. Here, we introduce a new coupled framework involving the spectral wave model WAVEWATCH III and the sea ice model neXtSIM, which includes a Maxwell elasto-brittle rheology. This rheological framework enables the model to efficiently track and keep a “memory” of the level of sea ice damage. We propose that the level of sea ice damage increases when wave-induced fragmentation occurs. We used this coupled modelling system to investigate the potential impact of such a local mechanism on sea ice kinematics. Focusing on the Barents Sea, we found that the internal stress decrease of sea ice resulting from its fragmentation by waves resulted in a more dynamical MIZ, particularly in areas where sea ice is compact. Sea ice drift is enhanced for both on-ice and off-ice wind conditions. Our results stress the importance of considering wave–sea-ice interactions for forecast applications. They also suggest that waves likely modulate the area of sea ice that is advected away from the pack by the ocean, potentially contributing to the observed past, current and future sea ice cover decline in the Arctic.

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The Impact of Stratospheric Circulation Extremes on Minimum Arctic Sea Ice Extent

Journal of Climate ◽

10.1175/jcli-d-17-0495.1 ◽

2018 ◽

Vol 31 (18) ◽

pp. 7169-7183 ◽

Cited By ~ 10

Author(s):

Karen L. Smith ◽

Lorenzo M. Polvani ◽

L. Bruno Tremblay

Keyword(s):

Sea Ice ◽

Barents Sea ◽

Arctic Sea Ice ◽

The Arctic ◽

Sea Ice Extent ◽

The Barents Sea ◽

Arctic Sea ◽

Stratospheric Circulation ◽

The Impact ◽

Arctic Sea Ice Extent

Given the rapidly changing Arctic climate, there is an urgent need for improved seasonal predictions of Arctic sea ice. Yet, Arctic sea ice prediction is inherently complex. Among other factors, wintertime atmospheric circulation has been shown to be predictive of summertime Arctic sea ice extent. Specifically, many studies have shown that the interannual variability of summertime Arctic sea ice extent (SIE) is anticorrelated with the leading mode of extratropical atmospheric variability, the Arctic Oscillation (AO), in the preceding winter. Given this relationship, the potential predictive role of stratospheric circulation extremes and stratosphere–troposphere coupling in linking the AO and Arctic SIE variability is examined. It is shown that extremes in the stratospheric circulation during the winter season, namely, stratospheric sudden warming (SSW) and strong polar vortex (SPV) events, are associated with significant anomalies in sea ice concentration in the Barents Sea in spring and along the Eurasian coastline in summer in both observations and a fully coupled, stratosphere-resolving general circulation model. Consistent with previous work on the AO, it is shown that SSWs, which are followed by the negative phase of the AO at the surface, result in sea ice growth, whereas SPVs, which are followed by the positive phase of the AO at the surface, result in sea ice loss, although the mechanisms in the Barents Sea and along the Eurasian coastline are different. The analysis suggests that the presence or absence of stratospheric circulation extremes in winter may play a nontrivial role in determining total September Arctic SIE when combined with other factors.

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Polar cod in jeopardy under the retreating Arctic sea ice

Communications Biology ◽

10.1038/s42003-019-0649-2 ◽

2019 ◽

Vol 2 (1) ◽

Cited By ~ 6

Author(s):

Mats Brockstedt Olsen Huserbråten ◽

Elena Eriksen ◽

Harald Gjøsæter ◽

Frode Vikebø

Keyword(s):

Sea Ice ◽

Barents Sea ◽

Keystone Species ◽

Ice Cover ◽

Arctic Sea Ice ◽

Biophysical Model ◽

The Arctic ◽

Polar Cod ◽

Arctic Sea ◽

Shelf Sea

Abstract The Arctic amplification of global warming is causing the Arctic-Atlantic ice edge to retreat at unprecedented rates. Here we show how variability and change in sea ice cover in the Barents Sea, the largest shelf sea of the Arctic, affect the population dynamics of a keystone species of the ice-associated food web, the polar cod (Boreogadus saida). The data-driven biophysical model of polar cod early life stages assembled here predicts a strong mechanistic link between survival and variation in ice cover and temperature, suggesting imminent recruitment collapse should the observed ice-reduction and heating continue. Backtracking of drifting eggs and larvae from observations also demonstrates a northward retreat of one of two clearly defined spawning assemblages, possibly in response to warming. With annual to decadal ice-predictions under development the mechanistic physical-biological links presented here represent a powerful tool for making long-term predictions for the propagation of polar cod stocks.

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Late-Twentieth-Century Simulation of Arctic Sea Ice and Ocean Properties in the CCSM4

Journal of Climate ◽

10.1175/jcli-d-11-00201.1 ◽

2012 ◽

Vol 25 (5) ◽

pp. 1431-1452 ◽

Cited By ~ 82

Author(s):

Alexandra Jahn ◽

Kara Sterling ◽

Marika M. Holland ◽

Jennifer E. Kay ◽

James A. Maslanik ◽

...

Keyword(s):

Twentieth Century ◽

Sea Ice ◽

Internal Variability ◽

Ice Cover ◽

Arctic Sea Ice ◽

The Arctic ◽

Motion Field ◽

Sea Ice Extent ◽

Arctic Sea ◽

Ensemble Mean

To establish how well the new Community Climate System Model, version 4 (CCSM4) simulates the properties of the Arctic sea ice and ocean, results from six CCSM4 twentieth-century ensemble simulations are compared here with the available data. It is found that the CCSM4 simulations capture most of the important climatological features of the Arctic sea ice and ocean state well, among them the sea ice thickness distribution, fraction of multiyear sea ice, and sea ice edge. The strongest bias exists in the simulated spring-to-fall sea ice motion field, the location of the Beaufort Gyre, and the temperature of the deep Arctic Ocean (below 250 m), which are caused by deficiencies in the simulation of the Arctic sea level pressure field and the lack of deep-water formation on the Arctic shelves. The observed decrease in the sea ice extent and the multiyear ice cover is well captured by the CCSM4. It is important to note, however, that the temporal evolution of the simulated Arctic sea ice cover over the satellite era is strongly influenced by internal variability. For example, while one ensemble member shows an even larger decrease in the sea ice extent over 1981–2005 than that observed, two ensemble members show no statistically significant trend over the same period. It is therefore important to compare the observed sea ice extent trend not just with the ensemble mean or a multimodel ensemble mean, but also with individual ensemble members, because of the strong imprint of internal variability on these relatively short trends.

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The impact of sea-ice dynamics on the Arctic climate system

Climate Dynamics ◽

10.1007/s00382-003-0309-5 ◽

2003 ◽

Vol 20 (7-8) ◽

pp. 741-757 ◽

Cited By ~ 38

Author(s):

S. Vavrus ◽

S. P. Harrison

Keyword(s):

Sea Ice ◽

Climate System ◽

Arctic Climate ◽

The Arctic ◽

Ice Dynamics ◽

Sea Ice Dynamics ◽

The Impact

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The Impact of Regional Arctic Sea Ice Loss on Atmospheric Circulation and the NAO

Journal of Climate ◽

10.1175/jcli-d-15-0315.1 ◽

2016 ◽

Vol 29 (2) ◽

pp. 889-902 ◽

Cited By ~ 51

Author(s):

Rasmus A. Pedersen ◽

Ivana Cvijanovic ◽

Peter L. Langen ◽

Bo M. Vinther

Keyword(s):

Sea Ice ◽

Atmospheric Circulation ◽

General Circulation ◽

Ice Cover ◽

Arctic Sea Ice ◽

The Arctic ◽

Near Surface ◽

Arctic Sea ◽

The Impact ◽

Sea Ice Reduction

Abstract Reduction of the Arctic sea ice cover can affect the atmospheric circulation and thus impact the climate beyond the Arctic. The atmospheric response may, however, vary with the geographical location of sea ice loss. The atmospheric sensitivity to the location of sea ice loss is studied using a general circulation model in a configuration that allows combination of a prescribed sea ice cover and an active mixed layer ocean. This hybrid setup makes it possible to simulate the isolated impact of sea ice loss and provides a more complete response compared to experiments with fixed sea surface temperatures. Three investigated sea ice scenarios with ice loss in different regions all exhibit substantial near-surface warming, which peaks over the area of ice loss. The maximum warming is found during winter, delayed compared to the maximum sea ice reduction. The wintertime response of the midlatitude atmospheric circulation shows a nonuniform sensitivity to the location of sea ice reduction. While all three scenarios exhibit decreased zonal winds related to high-latitude geopotential height increases, the magnitudes and locations of the anomalies vary between the simulations. Investigation of the North Atlantic Oscillation reveals a high sensitivity to the location of the ice loss. The northern center of action exhibits clear shifts in response to the different sea ice reductions. Sea ice loss in the Atlantic and Pacific sectors of the Arctic cause westward and eastward shifts, respectively.

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An enhancement to sea ice motion and age products

10.5194/tc-2019-40 ◽

2019 ◽

Cited By ~ 5

Author(s):

Mark A. Tschudi ◽

Walter N. Meier ◽

J. Scott Stewart

Keyword(s):

Sea Ice ◽

Ice Cover ◽

The Arctic ◽

Significant Shift ◽

High Concentration ◽

Sea Ice Extent ◽

Previous Version ◽

Arctic Ice ◽

The Impact ◽

Snow And Ice

Abstract. A new version of the sea ice motion and age products distributed at the National Snow and Ice Data Center's NASA Snow and Ice Distributed Active Archive Center has been developed. The new version, 4.0, includes several significant upgrades in processing, corrects known issues with the previous version, and updates the time series through 2018, with regular updates planned for the future. Here, we provide a history of the product development, discuss the improvements to the algorithms that create these products, and compare the Version 4 products to the previous version. While Version 4 algorithm changes were significant, the impact on the products is relatively minor, particularly for more recent years. Trends in motion and age are not substantially different between the versions. Changes in sea ice motion and age derived from the product 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 first-year ice, which is more susceptible to summer melt. We also observe an increase in the speed of the ice in recent years, which is anticipated with the annual decrease in sea ice extent.

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Seasonal Forecasts of the Pan-Arctic Sea Ice Extent Using a GCM-Based Seasonal Prediction System

Journal of Climate ◽

10.1175/jcli-d-12-00612.1 ◽

2013 ◽

Vol 26 (16) ◽

pp. 6092-6104 ◽

Cited By ~ 73

Author(s):

Matthieu Chevallier ◽

David Salas y Mélia ◽

Aurore Voldoire ◽

Michel Déqué ◽

Gilles Garric

Keyword(s):

Sea Ice ◽

General Circulation ◽

Global Climate Model ◽

Circulation Model ◽

Ice Cover ◽

Arctic Sea Ice ◽

The Arctic ◽

Seasonal Forecasts ◽

Sea Ice Extent ◽

Arctic Sea

Abstract An ocean–sea ice model reconstruction spanning the period 1990–2009 is used to initialize ensemble seasonal forecasts with the Centre National de Recherches Météorologiques Coupled Global Climate Model version 5.1 (CNRM-CM5.1) coupled atmosphere–ocean general circulation model. The aim of this study is to assess the skill of fully initialized September and March pan-Arctic sea ice forecasts in terms of climatology and interannual anomalies. The predictions are initialized using “full field initialization” of each component of the system. In spite of a drift due to radiative biases in the coupled model during the melt season, the full initialization of the sea ice cover on 1 May leads to skillful forecasts of the September sea ice extent (SIE) anomalies. The skill of the prediction is also significantly high when considering anomalies of the SIE relative to the long-term linear trend. It confirms that the anomaly of spring sea ice cover in itself plays a role in preconditioning a September SIE anomaly. The skill of predictions for March SIE initialized on 1 November is also encouraging, and it can be partly attributed to persistent features of the fall sea ice cover. The present study gives insight into the current ability of state-of-the-art coupled climate systems to perform operational seasonal forecasts of the Arctic sea ice cover up to 5 months in advance.

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