scholarly journals Mushy-layer growth and convection, with application to sea ice

2019 ◽  
Vol 377 (2146) ◽  
pp. 20180165 ◽  
Author(s):  
Andrew J. Wells ◽  
Joseph R. Hitchen ◽  
James R. G. Parkinson
Keyword(s):  
Sea Ice ◽  
Layer Growth ◽  
Phase Behaviour ◽  
Salt Transport ◽  
Future Research ◽  
Mushy Layer ◽  
Convective Flows ◽  
Ice Growth ◽  
Mushy Layers ◽  
The Impact

Sea ice is a reactive porous medium of ice crystals and liquid brine, which is an example of a mushy layer. The phase behaviour of sea ice controls the evolving material properties and fluid transport through the porous ice, with consequences for ice growth, brine drainage from the ice to provide buoyancy fluxes for the polar oceans, and sea-ice biogeochemistry. We review work on the growth of mushy layers and convective flows driven by density gradients in the interstitial fluid. After introducing the fundamentals of mushy-layer theory, we discuss the effective thermal properties, including the impact of salt transport on mushy-layer growth. We present a simplified model for diffusively controlled growth of mushy layers with modest cooling versus the solutal freezing-point depression. For growth from a cold isothermal boundary, salt diffusion modifies mushy-layer growth by around 5–20% depending on the far-field temperature and salinity. We also review work on the onset, spatial localization and nonlinear development of convective flows in mushy layers, highlighting recent work on transient solidification and models of nonlinear convection with dissolved solid-free brine channels. Finally, future research opportunities are identified, motivated by geophysical observations of ice growth. This article is part of the theme issue ‘The physics and chemistry of ice: scaffolding across scales, from the viability of life to the formation of planets’.

scholarly journals New insight from CryoSat-2 sea ice thickness for sea ice modelling

2018 ◽  
Author(s):  
David Schröder ◽  
Danny L. Feltham ◽  
Michel Tsamados ◽  
Andy Ridout ◽  
Rachel Tilling
Keyword(s):  
Sea Ice ◽  
Thickness Distribution ◽  
Arctic Sea Ice ◽  
Ice Thickness ◽  
Atmospheric Conditions ◽  
Sea Ice Concentration ◽  
Sea Ice Thickness ◽  
Ice Growth ◽  
Melt Pond ◽  
The Impact

Abstract. Estimates of Arctic sea ice thickness are available from the CryoSat-2 (CS2) radar altimetry mission during ice growth seasons since 2010. We derive the sub-grid scale ice thickness distribution (ITD) with respect to 5 ice thickness categories used in a sea ice component (CICE) of climate simulations. This allows us to initialize the ITD in stand-alone simulations with CICE and to verify the simulated cycle of ice thickness. We find that a default CICE simulation strongly underestimates ice thickness, despite reproducing the inter-annual variability of summer sea ice extent. We can identify the underestimation of winter ice growth as being responsible and show that increasing the ice conductive flux for lower temperatures (bubbly brine scheme) and accounting for the loss of drifting snow results in the simulated sea ice growth being more realistic. Sensitivity studies provide insight into the impact of initial and atmospheric conditions and, thus, on the role of positive and negative feedback processes. During summer, atmospheric conditions are responsible for 50 % of September sea ice thickness variability through the positive sea ice and melt pond albedo feedback. However, atmospheric winter conditions have little impact on winter ice growth due to the dominating negative conductive feedback process: the thinner the ice and snow in autumn, the stronger the ice growth in winter. We conclude that the fate of Arctic summer sea ice is largely controlled by atmospheric conditions during the melting season rather than by winter temperature. Our optimal model configuration does not only improve the simulated sea ice thickness, but also summer sea ice concentration, melt pond fraction, and length of the melt season. It is the first time CS2 sea ice thickness data have been applied successfully to improve sea ice model physics.

The sensitivity of sea ice growth to the choice of ice shelf-ocean coupling algorithms.

2020 ◽  
Author(s):  
Stefan Jendersie ◽  
Alena Malyarenko
Keyword(s):  
Sea Ice ◽  
Ocean Model ◽  
Data Sets ◽  
Ice Shelf ◽  
Ice Shelves ◽  
Ice Growth ◽  
Continental Scale ◽  
Complex Models ◽  
Coupling Algorithms ◽  
The Impact

<p>To quantify Antarctic ice mass loss and the subsequent sea level rise the geophysical modelling community is pushing towards frameworks that fully couple increasingly complex models of atmosphere, ocean, sea ice and ice sheets & shelves.  One particular hurdle remains the accurate representation of the vertical ocean-ice interaction at the base of ice shelves.  Parameterizations that are tuned to particular data sets naturally perform best in comparable ice shelf cavity environments. This poses the challenge in continental scale ocean-ice shelf models to chose one melt parameterizaton that performs sufficiently well in diverse cavity environment.  Thus adding uncertainty in ice shelf induced ocean freshening crucially affects modelled sea ice growth.  The impact magnitude of ice shelf supplied melt water on growth rates, thickness and extent of sea ice in the open ocean is currently debated in the literature.  <br>We reviewed and compared 16 commonly utilized melting/freezing parameterizations in coupled ocean-ice shelf models.  Melt rates differ hugely, in identical idealized conditions between 0.1m/yr to 3m/yr.  In this talk we present results of a realistic circum-Antarctic ice shelf and sea ice coupled ocean model (CICE, ROMS), where we look at the effects of the chosen ice shelf melt parameterization on modeled sea surface conditions and sea ice growth, regionally and circum Antarctic.</p>

scholarly journals Interannual variability in Transpolar Drift ice thickness and potential impact of Atlantification

2020 ◽  
Author(s):  
H. Jakob Belter ◽  
Thomas Krumpen ◽  
Luisa von Albedyll ◽  
Tatiana A. Alekseeva ◽  
Sergei V. Frolov ◽  
...  
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Thickness ◽  
Fram Strait ◽  
Ice Growth ◽  
Arctic Sea ◽  
Transpolar Drift ◽  
The Impact

Abstract. Changes in Arctic sea ice thickness are the result of complex interactions of the dynamic and variable ice cover with atmosphere and ocean. Most of the sea ice exits the Arctic Ocean through Fram Strait, which is why long-term measurements of ice thickness at the end of the Transpolar Drift provide insight into the integrated signals of thermodynamic and dynamic influences along the pathways of Arctic sea ice. We present an updated time series of extensive ice thickness surveys carried out at the end of the Transpolar Drift between 2001 and 2020. Overall, we see a more than 20 % thinning of modal ice thickness since 2001. A comparison with first preliminary results from the international Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) shows that the modal summer thickness of the MOSAiC floe and its wider vicinity are consistent with measurements from previous years. By combining this unique time series with the Lagrangian sea ice tracking tool, ICETrack, and a simple thermodynamic sea ice growth model, we link the observed interannual ice thickness variability north of Fram Strait to increased drift speeds along the Transpolar Drift and the consequential variations in sea ice age and number of freezing degree days. We also show that the increased influence of upward-directed ocean heat flux in the eastern marginal ice zones, termed Atlantification, is not only responsible for sea ice thinning in and around the Laptev Sea, but also that the induced thickness anomalies persist beyond the Russian shelves and are potentially still measurable at the end of the Transpolar Drift after more than a year. With a tendency towards an even faster Transpolar Drift, winter sea ice growth will have less time to compensate the impact of Atlantification on sea ice growth in the eastern marginal ice zone, which will increasingly be felt in other parts of the sea ice covered Arctic.

scholarly journals Evidence for an increasing role of ocean heat in Arctic winter sea ice growth

2021 ◽  
pp. 1-42
Author(s):  
Robert Ricker ◽  
Frank Kauker ◽  
Axel Schweiger ◽  
Stefan Hendricks ◽  
Jinlun Zhang ◽  
...  
Keyword(s):  
Sea Ice ◽  
Reanalysis Data ◽  
Arctic Sea Ice ◽  
Satellite Observations ◽  
The Arctic ◽  
Ice Growth ◽  
Marginal Seas ◽  
Air Temperatures ◽  
Barents And Kara Seas ◽  
The Impact

AbstractWe investigate how sea ice decline in summer and warmer ocean and surface temperatures in winter affect sea ice growth in the Arctic. Sea ice volume changes are estimated from satellite observations during winter from 2002 to 2019 and partitioned into thermodynamic growth and dynamic volume change. Both components are compared to validated sea ice-ocean models forced by reanalysis data to extend observations back to 1980 and to understand the mechanisms that cause the observed trends and variability. We find that a negative feedback driven by the increasing sea ice retreat in summer yields increasing thermodynamic ice growth during winter in the Arctic marginal seas eastward from the Laptev Sea to the Beaufort Sea. However, in the Barents and Kara Seas, this feedback seems to be overpowered by the impact of increasing oceanic heat flux and air temperatures, resulting in negative trends in thermodynamic ice growth of -2 km3month-1yr-1 on average over 2002-2019 derived from satellite observations.

scholarly journals Suppression of Arctic sea ice growth by winter clouds and snowfall

2021 ◽  
Author(s):  
Won-il Lim ◽  
Hyo-Seok Park ◽  
Andrew Stewart ◽  
Kyong-Hwan Seo
Keyword(s):  
Sea Ice ◽  
Longwave Radiation ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Ice Growth ◽  
Downward Longwave Radiation ◽  
Arctic Sea ◽  
The Impact

Abstract The ongoing Arctic warming has been pronounced in winter and has been associated with an increase in downward longwave radiation. While previous studies have demonstrated that poleward moisture flux into the Arctic strengthens downward longwave radiation, less attention has been given to the impact of the accompanying increase in snowfall. Here, utilizing state-of-the art sea ice models, we show that typical winter snowfall anomalies of 1.0 cm, accompanied by positive downward longwave radiation anomalies of ~5 W m-2 can decrease sea ice thickness by around 5 cm in the following spring over the Eurasian Seas. This basin-wide ice thinning is followed by a shrinking of summer ice extent in extreme cases. In the winter of 2016–17, anomalously strong warm/moist air transport combined with ~2.5 cm increase in snowfall decreased spring ice thickness by ~10 cm and decreased the following summer sea ice extent by 5–30%. Projected future reductions in the thickness of Arctic sea ice and snow will amplify the impact of anomalous winter snowfall events on winter sea ice growth and seasonal sea ice thickness.

Evaluation of a multilayer snow scheme in NEMO-LIM3

2020 ◽  
Author(s):  
Gaëlle Gilson ◽  
Thierry Fichefet ◽  
Olivier Lecomte ◽  
Pierre-Yves Barriat ◽  
Jean Sterlin ◽  
...  
Keyword(s):  
Sea Ice ◽  
Ocean Circulation ◽  
Climate Models ◽  
Thickness Distribution ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Optimum Number ◽  
Ice Growth ◽  
Arctic Sea ◽  
The Impact

<p>Arctic sea ice is a major component of the Earth’s climate system and has been experiencing a drastic decline over the past decades, with important consequences regionally and globally. With the sustained warming of the Arctic, sea ice loss is expected to continue in the future. However, the estimation of its magnitude is model-dependent. As a result, the representation of sea ice in climate models requires further consideration. A major issue relates to the long-standing misrepresentation of snow properties on sea ice. However, the presence of snow strongly impacts sea ice growth and surface energy balance. Through its high albedo, snow reflects more solar radiation than bare sea ice does. When a snow cover is present, sea ice growth is reduced because snow is an effective insulator, with a thermal conductivity an order of magnitude lower than that of sea ice. Ocean circulation models usually use multiple layers to resolve sea ice thermodynamics but only one single layer for snow. Lecomte et al. (2013) developed a multilayer snow scheme for ocean circulation models and improved the snow depth distribution by considering the macroscopic effects of wind packing and redeposition. Since then, this snow scheme has been revisited and implemented in a more recent and much more robust NEMO-LIM version, using a simpler technical approach. In addition, new instrumental observations of snow thickness, distribution and density are available since these exploratory works. They are used in the current study to: 1) evaluate the performance of the multilayer snow scheme for sea ice in the NEMO-LIM3 model, and 2) investigate the climatic importance of this snow scheme. Here, we present results of simulations with a varying number of snow layers. By comparing these to the latest observational datasets, we recommend an optimum number of snow  layers to be used in ocean circulation models in both hemispheres. Finally, we explore the impact of a few specific parameterizations of snow thermophysical properties on the representation of sea ice in climate models.</p>

scholarly journals New insight from CryoSat-2 sea ice thickness for sea ice modelling

2019 ◽  
Vol 13 (1) ◽  
pp. 125-139 ◽  
Author(s):  
David Schröder ◽  
Danny L. Feltham ◽  
Michel Tsamados ◽  
Andy Ridout ◽  
Rachel Tilling
Keyword(s):  
Sea Ice ◽  
Thickness Distribution ◽  
Arctic Sea Ice ◽  
Ice Thickness ◽  
Atmospheric Conditions ◽  
Component Community ◽  
Sea Ice Thickness ◽  
Ice Growth ◽  
Melt Pond ◽  
The Impact

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

scholarly journals Solidification of binary aqueous solutions under periodic cooling. Part 2. Distribution of solid fraction

2019 ◽  
Vol 870 ◽  
pp. 147-174 ◽  
Author(s):  
Guang-Yu Ding ◽  
Andrew J. Wells ◽  
Jin-Qiang Zhong
Keyword(s):  
Solid Fraction ◽  
Phase Behaviour ◽  
Mushy Layer ◽  
Late Time ◽  
Basal Region ◽  
Solute Content ◽  
Bottom Boundary ◽  
Initial Concentration ◽  
Time Dynamics ◽  
Mushy Layers

We report an experimental study of the distributions of temperature and solid fraction of growing $\text{NH}_{4}\text{Cl}$–$\text{H}_{2}\text{O}$ mushy layers that are subjected to periodical cooling from below, focusing on late-time dynamics where the mushy layer oscillates about an approximate steady state. Temporal evolution of the local temperature $T(z,t)$ at various heights in the mush demonstrates that the temperature oscillations of the bottom cooling boundary propagate through the mushy layer with phase delays and substantial decay in the amplitude. As the initial concentration $C_{0}$ increases, we show that the decay rate of the thermal oscillation with height also decreases, and the propagation speed of the oscillation phase increases. We interpret this as a result of the solid fraction increasing with $C_{0}$, which enhances the thermal conductivity but reduces the specific heat of the mushy layer. We present a new methodology to determine the distribution of solid fraction $\unicode[STIX]{x1D719}(z)$ in mushy layers for various $C_{0}$, using only measurements of the temperature $T(z,t)$. The method is based on the phase behaviour during thermal modulation, and opens up a new approach for inferring mushy-layer properties in geophysical and engineering settings, where direct measurements are challenging. In our experiments, profiles of the solid fraction $\unicode[STIX]{x1D719}(z)$ exhibit a cliff–ramp–cliff structure with large vertical gradients of $\unicode[STIX]{x1D719}$ near the mush–liquid interface and also near the bottom boundary, but much more gradual variation in the interior of the mushy layer. Such a profile structure is more pronounced for higher initial concentration $C_{0}$. For very low concentration, the solid fraction appears to be linearly dependent on the height within the mush. The volume-average of the solid fraction, and the local fluctuations in $\unicode[STIX]{x1D719}(z)$ both increase as $C_{0}$ increases. We suggest that the fast increase of $\unicode[STIX]{x1D719}(z)$ near the bottom boundary is possibly due to diffusive transport of solute away from the bottom boundary and the depletion of solute content near the basal region.

Three-dimensional convection, phase change, and solute transport in mushy sea ice

2020 ◽  
Author(s):  
Andrew Wells ◽  
James Parkinson ◽  
Dan Martin ◽  
Richard Katz
Keyword(s):  
Sea Ice ◽  
Adaptive Mesh Refinement ◽  
Three Dimensional ◽  
Winter Season ◽  
Adaptive Mesh ◽  
Mushy Layer ◽  
Ice Growth ◽  
Buoyancy Forcing ◽  
Wide Range ◽  
Brine Rejection

<p>Sea ice is a porous mushy layer composed of ice crystals and interstitial brine. The dense brine tends to sink through the ice, driving convection. Downwelling at the edge of convective cells leads to dissolution of the ice matrix and the development of narrow, entirely liquid brine channels. The channels provide an efficient pathway for drainage of the cold, saline brine into the underlying ocean. This brine rejection provides an important buoyancy forcing for the polar oceans, and causes variation of the internal structure and properties of sea ice on seasonal and shorter timescales. This process is inherently multiscale, with simulations requiring resolution from O(mm) brine-channel scales to O(m) mushy-layer dynamic scales.</p><p> </p><p>We present new, fully 3-dimensional numerical simulations of ice formation and convective brine rejection that model flow through a reactive porous ice matrix with evolving porosity. To accurately resolve the wide range of dynamical scales, our simulations exploit Adaptive Mesh Refinement using the Chombo framework. This allows us to integrate over several months of ice growth, providing insights into mushy-layer dynamics throughout the winter season. The convective desalination of sea ice promotes increased internal solidification, and we find that convective brine drainage is restricted to a narrow porous layer at the ice-ocean interface. This layer evolves as the ice grows thicker over time. Away from this interface, stagnant sea ice consists of a network of previously active brine channels that retain higher solute concentrations than the surrounding ice. We investigate the response of ice growth and brine drainage to varying atmospheric cooling conditions, and consider the potential implications for ice-ocean brine fluxes, nutrient transport, and sea ice ecology.</p><p><br><br></p>

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