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# Seminars (SIPW01)

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Event When Speaker Title Presentation Material
SIPW01 11th September 2017
09:45 to 10:30
Donald K. Perovich Small to big, quick to slow: The many scales of sea ice properties and processes
Sea ice properties and processes exhibit tremendous variability over spatial scales from millimeters to megameters. Sea ice also evolves over temporal scales of hours to days to seasons to decades. To understand sea ice properties, it is critical to examine and connect the processes that occur on these different scales. For example, sea ice microstructure impacts the partitioning of sunlight. Melt ponds are governed by meter-scale topography and millimeter-scale brine channels. There are similarities in the size distributions of brine pockets, melt ponds, and floes; features that span spatial scales of several orders of magnitude. The timing of short term events, such as snowfall or lead openings, has a large impact on the seasonal evolution of the ice cover. Sea ice scale issues are also important when considering the interactions of the atmosphere-sea ice-ocean-biogeochemical system.
SIPW01 11th September 2017
11:00 to 11:45
Ken Golden Linking scales in the sea ice system
Sea ice exhibits complex structure ranging from the sub-millimeter scale brine inclusions to ice floes and coherent​ ​dynamics on the scale of hundreds of kilometers. I will give an overview of how we are using​ ​ theories of composite​ materials and statistical physics to link behavior on various scales in the sea ice system. In particular, we address key questions in sea ice homogenization, where information on smaller scales is incorporated into rigorous representations of effective large scale behavior. We also consider the inverse problem where small scale structure is inferred from larger scale effective properties.
SIPW01 11th September 2017
11:45 to 12:30
Agnieszka Herman Discrete-element models of sea ice dynamics and fracture
At geophysical scales, continuum models provide established and computationally efficient tools for simulating sea ice dynamics and thermodynamics. In recent years, rapidly increasing computational power and availability of high-resolution (esp. remote-sensing) data have contributed to a revival of discrete-element methods (DEM), enabling the analysis of sea ice at smaller spatial and temporal scales. Treating sea ice as a collection of individual, interacting floes, and thus recognizing it as an example of a granular material, opens a wide range of new tools and analysis possibilities for sea ice research. Bonded-particle DEM models enable to simulate brittle fragmentation of sea ice – a process that, in spite of substantial progress in recent years, still poses problems for continuum models. Moreover, there is growing evidence that the size distribution of sea ice floes has a substantial influence on a wide range of processes in the upper ocean, lower atmosphere and within sea ice itself, and it is in turn shaped by those processes. By directly taking into account fragmentation (i.e., floe formation) and dynamics of individual floes, DEMs provide tools to better understand complex interactions between sea ice, ocean and atmosphere acting at the floe-level.

In this talk, I will present and discuss selected examples of the application of DEM models to sea ice dynamics and fragmentation problems. The examples will include: wind- and current-induced drift of fragmented (granular’’) sea ice, and the influence of ice concentration and floe-size distribution on the sea ice response to forcing; jamming phase transition under compressive and shear strain, and force transmission in ice subject to different strain fields; sea ice breaking by waves analyzed with a coupled DEM–hydrodynamic model. Unsolved problems and challenges (both computational and theoretical) related to the application of DEMs to sea ice will be presented as well.

Most results presented in this talk were obtained with a Discrete-Element bonded-particle Sea Ice model DESIgn, implemented as a toolbox for the open-source numerical library LIGGGHTS (http://www.cfdem.com/). The code and documentation of DESIgn are freely available at http://herman.ocean.ug.edu.pl/LIGGGHTSseaice.html.

SIPW01 11th September 2017
14:00 to 14:30
Veronique Dansereau A new continuum rheological model for the deformation and drift of sea ice
Co-authors: Pierre Saramito (CNRS-LJK), Jérôme Weiss (CNRS-ISTerre), Philippe Lattes (Total S.A. E&P)

Axel Roy (1)
Véronique Dansereau (2)*
Jérôme Weiss (2)
Christian Haas (3)
Matthieu Chevalier (4)

1 École Nationale de la Météorologie, Météo France, Toulouse, France
2 Institut des Sciences de la Terre, CNRS UMR 5275, Université de Grenoble, Grenoble, France
3 Alfred Wegener Institute, Bremerhaven, Germany
4 CNRM/GMGEC/IOGA Météo France, Toulouse, France

Sea ice models are most often compared to each other and to observations in terms of the spatial distribution of the simulated ice thickness. An equally important, and perhaps more appropriate, metric to investigate the mechanical behaviour of the sea ice cover is the ice thickness distribution, i.e., the probability density function, of which some valuable information have been available for some time from drill-hole, upward looking submarine-mounted sonar (USL) and airborne electromagnetic (EM) sounding measurements.

An important issue naturally arises when comparing sea ice thickness distributions based on measurements made at the meter scale with that estimated from regional and global sea ice model simulations, with a typical resolution of a few kilometres; the issue of scale dependance. Using USL sea ice draft profiles and EM thickness measurements, we investigate the scaling properties of the sea ice thickness over the Arctic to address the following question: how does the sea ice thickness distribution evolve with the scale of observation?

The autocorrelation calculations performed here allow extending previous analyses based on single USL transects (up to 50 km-long) and point to long-range correlations in the thickness of the sea ice cover reaching as far as a few hundreds of kilometres. Multi-fractal analyses are conducted to investigate the variability of the the ice thickness distribution with the spatial scale of observation up to these scales.
SIPW01 11th September 2017
14:30 to 15:00
Christopher Horvat Floe size and ice thickness distributions
SIPW01 11th September 2017
15:30 to 16:00
Courtenay Strong Filling the polar data gap with harmonic functions
Coauthors: Elena Cherkaev and Kenneth M. Golden

The “polar data gap” is a region around the North Pole where satellite orbits do not provide sufficient coverage for estimating sea ice concentrations. This gap is conventionally made circular and assumed to be ice-covered for the purpose of sea ice extent calculations, but recent conditions around the perimeter of the gap indicate that this assumption may already be invalid. We present partial differential equation-based models for estimating sea ice concentrations within the area of the data gap. In particular, the sea ice concentration field is assumed to satisfy Laplace’s equation with boundary conditions determined by observed sea ice concentrations on the perimeter of the gap region. This type of idealization in the concentration field has already proved to be quite useful in establishing an objective method for measuring the “width” of the marginal ice zone—a highly irregular, annular-shaped region of the ice pack that interacts with the ocean, and typically surrounds the inner core of most densely packed sea ice. Realistic spatial heterogeneity in the idealized concentration field is achieved by adding a spatially autocorrelated stochastic field with temporally varying standard deviation derived from the variability of observations around the gap. Testing in circular regions around the gap yields observation-model correlation exceeding 0.6 to 0.7, and sea ice concentration mean absolute deviations smaller than 0.01. This approach based on solving an elliptic partial differential equation with given boundary conditions has sufficient generality to also provide more sophisticated models which could be more accurate than the Laplace equation version, and such potential generalizations are explored.
SIPW01 11th September 2017
16:00 to 17:00
Elizabeth Hunke Rothschild Lecture: Large-scale sea ice modeling: societal needs and community development
The CICE sea ice model is used extensively by climate and Earth system research groups, and also by operational centers for applications such as numerical weather prediction and guidance for military operations.  While the research community is energetically improving the models, observationalists are busy taking measurements and operational experts are using all of it to produce predictive products via data assimilation.  In the past, the sea ice research and operational communities have been somewhat distinct with little cross-pollination.  Partly in response to this issue, the CICE Consortium has formed as a formal community effort to to provide a mechanism for accelerating further sea ice model development and its transfer into operational uses.  This colloquium will provide a broad overview of current CICE model capabilities and uses, highlight new analysis techniques for statistically assessing model skill against diverse observations, and discuss our community engagement effort, all toward addressing society's needs in the face of the Earth’s changing polar regions.

SIPW01 12th September 2017
09:00 to 09:45
Vernon Squire Marginal Ice Zone Evolution due to Wave-Induced Breaking
Co-authors: Vernon Squire (University of Otago, NZ), Fabien Montiel (University of Otago, NZ)

The influence of ice–albedo temperature feedback arising as a result of global climate change is believed to be enhanced by a contemporaneous intensification of wave climate in the polar seas. Waves break up the sea ice deeper into the ice-covered oceans, accelerating its melting and increasing the area of ice-free ocean, which in turn allows for more energetic waves and swells to develop. Although much attention has been given to the effect of a broken-up ice cover, e.g. the marginal ice zone, on the propagation of ocean waves, less is known about the impact of waves on the morphology of the sea ice. The latter is principally governed by the break-up of flexing sea-ice floes as a result of wave interactions. A sub-grid scale process-based model describing the two-way coupling between the ocean waves and sea ice systems will be discussed, with a particular focus on how to parametrize this coupling in ice/ocean models.
SIPW01 12th September 2017
09:45 to 10:30
Martin Vancoppenolle A compilation of research and thoughts on the future of sea ice models.
On the point of view of a model developer, it looks somehow desperating to see how little sensitive climate models seem to be to the representation of sea ice processes. By comparison, atmospheric and oceanic forcing, or mean climate state look much more influential. Is this a good reason to give up sea ice model development ? I will give a few elements of answer to explain why we should maintain our efforts, and illustrate how the European teams involved in NEMO will project themselves into the next generation of sea ice models.
SIPW01 12th September 2017
11:00 to 11:45
Daniel Feltham Sea ice model physics: in search of fidelity
SIPW01 12th September 2017
11:45 to 12:30
Wieslaw Maslowski Sensitivity of Arctic sea ice state to model parameter space, resolved processes and climate coupling
SIPW01 12th September 2017
14:00 to 14:30
Sukun Cheng A viscoelastic model for wave propagation in the marginal ice zone
Co-author: Hayley H. Shen (Clarkson Univerisity)

Regional wave forecasts for the Arctic rely on a good understanding of wave propagation through sea ice covers. Disagreements among the models and the lack of field validations cause uncertainty in wave forecasts. A recent viscoelastic ice model has been developed to simulate a wide range of ice covers. This model synthesized several previous models that considered ice covers as a continuum. In this model, a simple parameterization is used to include both energy storage and dissipation mechanisms. However, the model has two parameters, the equivalent elasticity and viscosity, which need to be determined. In this presentation, we will describe the basis of this model, and its calibration using data from a recent field campaign.
SIPW01 12th September 2017
14:30 to 15:00
Christian Samspon Effective Rheology and Wave Propagation in the Marginal Ice Zone
Co-authors: Ken Golden (University of Utah), Ben Murphy (University of Utah), Elena Cherkaev (University of Utah)

Wave-ice interactions in the polar oceans comprise a complex but important set of processes influencing sea ice extent, ice pack albedo, and ice thickness. In both the Arctic and Antarctic, the ice floe size distribution in the Marginal Ice Zone (MIZ) plays a central role in the properties of wave propagation. Ocean waves break up and shape the ice floes which, in turn, attenuate various wave characteristics. Recently, continuum models have been developed which treat the MIZ as a two-component composite of ice and slushy water. The top layer has been taken to be purely elastic, purely viscous or viscoelastic. At the heart of these models are effective parameters, namely, the effective elasticity, viscosity, and complex viscoelasticity. In practice, these effective parameters, which depend on the composite geometry and the physical properties of the constituents, are quite difficult to determine. To help overcome this limitation, we employ the methods of homogenization theory, in a quasistatic, fixed frequency regime, to find a Stieltjes integral representation for the complex viscoelasticity.
This integral representation involves the spectral measure of a self adjoint operator and provides what we believe are the first rigorous bounds on the effective viscoelasticity of the sea ice pack. The bounds themselves depend on the moments of the measure which in turn depend on the geometry of the ice floe configurations. This work has the potential to provide simple parameterizations of wave properties which take into account floe concentration and geometry.
SIPW01 12th September 2017
15:30 to 16:00
Konrad Simon Flow-induced Coordinates for Transient Advection-Diffusion Equations with Multiple Scales
Co-author: Jörn Behrens (University of Hamburg, Germany)

Simulation over a long time scale in climate sciences as done, e.g., in paleo climate simulations require coarse grids due to computational constraints. Unresolved scales, however, significantly influence the coarse grid variables. Such processes include (slowly) moving land-sea interfaces or ice shields as well as flow over urbanic areas. Neglecting these scales amounts to unreliable simulation results. State-of-the-art dynamical cores represent the influence of subscale processes typically via subscale parametrizations and often employ heuristic coupling of scales.

Our aim is to improve the mathematical consistency of the upscaling process that transfers information from the subgrid to the coarse prognostic scale (and vice-versa). We investigate a new bottom-up techniques for advection dominated problems arising in climate simulations [Lauritzen et al. (2011)]. Our tools are based on ideas for multiscale finite element methods for elliptic problems that play a role in oil reservoir modeling and porous media in general [Efendiev and Hou (2009), Graham et al. (2012)]. Modifying these ideas is in necessary in order to account for the transient and advection dominated character which is typical for flows encountered in climate models.

We present a new Garlerkin based idea to account for the typical difficulties in climate simulations. Our modified ideas employ a change of coordinates based on a coarse grid characteristic transform induced by the advection term in order to account for appropriate subgrid boundary conditions for the multiscale basis functions which are essential for such approaches. We present results from sample runs for a simple advection-diffusion equation with rapidly varying coefficients on several scales.
SIPW01 12th September 2017
16:00 to 16:30
Noa Kraitzman Advection enhanced diffusion processes
We investigate thermal conduction in sea ice in the presence of fluid flow, as an important example of an advection diffusion process in the polar marine environment. Using new Stieltjes integral representations for the effective diffusivity in turbulent transport, we present a series of rigorous bounds on the effective diffusivity, obtained using Padé approximates in terms of the Péclet number.
We first analyze the effective thermal conductivity of sea ice in the presence of an averaged convective velocity field, neglecting the two phase microstructure of sea ice, and then present a homogenization analysis of the full two component system composed of brine and ice.
SIPW01 13th September 2017
09:00 to 09:45
Ian Eisenman Sea ice stability and rapid retreat
Changes in the Arctic sea ice cover involve an amplifying feedback associated with the surface albedo, which suggests the possibility of unstable climate states and bifurcations, or "tipping points". The first part of this talk will focus on the stability of the sea ice cover. Previous studies have identified sea ice bifurcations due to the ice-albedo feedback occurring in a range of idealized models but not in comprehensive global climate models (GCMs). We will propose a physical explanation for this discrepancy, drawing on a model that we developed to bridge the gap between low-order models and GCMs. The results support the finding from GCMs, suggesting that such bifurcations should not be expected in nature. Nonetheless, Arctic sea ice has been observed to retreat abruptly during recent decades. The second part of the talk will address how well the observed rate of Arctic sea ice retreat is simulated in the suite of current GCMs. Although the majority of these GCMs simulate less sea ice retreat than observed, a substantial minority of the simulations do capture the observed rate of retreat. Hence a number of recent studies have suggested that the GCMs and the observations are consistent. We will show that the observed rate of Arctic sea ice retreat actually occurs only in GCM simulations with substantially more global warming than observed. We will suggest an alternative metric for evaluating the GCMs that takes this factor into consideration. The results suggest that the GCMs may be getting the right Arctic sea ice trends for the wrong reasons.
SIPW01 13th September 2017
09:45 to 10:30
Andrew Roberts Modeling macro-porosity of ridged sea ice in basin-scale models
Co-authors: Elizabeth Hunke (Los Alamos National Laboratory), William Lipscomb (National Center for Atmospheric Research), Samy Kamal (Naval Postgraduate School), Wieslaw Maslowski (Naval Postgraduate School)

One of the largest limitations of current-generation sea ice models is that they characterize sea ice morphology using a thickness distribution, g(h), over an area A(x). This inherently introduces a scale limitation to sea ice models, because g(h) only represents the relative quantity of ice of thickness, h, over a region, rather than describe how thickness is locally organized. Moreover, the approach assumes that sea ice deformed into rafts, folds, buckles, ridges and hummocks is equally as porous as undeformed ice, despite strong evidence to the contrary. This problem may be addressed by expanding the state space of the thickness distribution to become a multivariate distribution g(h,phi) where phi is the macro-porosity of sea ice rubble. Then, sea ice ridging may be described using a Euler-Lagrange equation for ridge cross-sections that mimic many of the characteristics of existing ridge-scale simulations. The approach requires careful consideration of non-conservative components of ridging, and, in the most basic approach, can use a Coulombic failure criteria applied vertically within ridges to predict their angle of repose, macro-porosity, extent and seperation in large scale models. This talk presents the theoretical basis for this new method of simulating sea ice thickness.
SIPW01 13th September 2017
11:00 to 11:45
Dirk Notz When is all the sea ice gone?
Co-author: Julienne Stroeve (University College London)

We examine the future evolution of Arctic sea ice, focusing in particular on the allowable carbon dioxide emissions that would prevent sea-ice loss in the various seasons. In this context, the relationship between model simulations and observations is crucial, and we will briefly discuss why it is so difficult to identify models that most reliably simulate the future of Arctic sea ice. Based on this discussion, we will then introduce an observation-based estimate of the future evolution of Arctic sea ice that considers our physical understanding of the main processes that cause the ongoing ice loss.
SIPW01 13th September 2017
11:45 to 12:30
Pat Langhorne Changes to sea ice thickness distribution due to Ice Shelf Water
Co-authors: Inga Smith, Greg Leonard, Andrew Pauling, Pat Wongpan, David Dempsey, Ken Hughes, Craig Purdie, Eamon Frazer (University of Otago), Mike Williams, Natalie Robinson, Craig Stevens (NIWA), Alena Malyarenko, Stefan Jendersie (NIWA & University of Otago), Wolfgang Rack, Gemma Brett, Dan Price (University of Canterbury), Christian Haas (Alfred Wegener Institute), Cecilia Bitz (University of Washington), Andy Mahoney (Geophysical Institute) and Tim Haskell (Callaghan Innovation Ltd)

Satellite observations show that the winter maximum sea ice extent around Antarctica has been increasing slowly over the past three decades, a behaviour superficially at odds with “global warming”.  One hypothesis is that an increase in freshwater input from the base of ice shelves has influenced sea ice extent. This process can drive seawater temperatures below the surface freezing point. Ice crystals then persist in the supercooled water and add to the mass of the coastal sea ice cover. The crystals may form a porous, friable layer, called the sub-ice platelet layer, which can be several metres thick beneath the two-metres of sea ice. Consequently platelet ice formation not only causes sea ice to be thicker, but it also alters the hydrostatic relationship between sea ice elevation and thickness, influencing satellite altimeter determination of sea ice thickness.

Here we describe ice shelf–sea ice interaction at a range of scales from parameterization in an Earth System Model, to the sub-metre detail of winter ice-ocean relationships. On a regional scale we have focused on a location affected by an ISW outflow at the surface. Regional ocean modeling and satellite altimeter observations provide context for airborne sea ice thickness surveys using electromagnetic (EM) induction sounding. These regional surveys have been supported over smaller geographic areas by detailed on-ice sea ice and snow thickness measurements, by on-ice EM induction transects of sea ice thickness, and by under-ice oceanographic observations that track the heat deficit and mixing in the upper ocean at selected sites.

SIPW01 14th September 2017
09:00 to 09:45
Andrew Wells Models of multi-scale and multi-phase sea ice thermodynamics
Sea ice is a multi-phase material, consisting of a mixture of solid ice crystals and liquid brine. The properties of this mixture vary significantly during initial ice growth, from the growth of suspensions of frazil ice crystals in supercooled leads and polynyas through to a reactive porous material during consolidated congelation growth. The resulting mixture is also inherently multi-scale, with the macroscopic scales of interest such as ice depth or mixed layer depth being many order of magnitude larger than the scale of an individual ice crystal. This talk will provide an introduction to key continuum models of the multi-phase and multi-scale thermodynamics of sea ice growth. I will introduce so-called "mushy layer theory" for characterising the evolution of reactive porous sea ice, and also review theories of crystal suspension dynamics derived from a master equation. Selected case studies will be used to illustrate the application of these theories to predict ice accumulation rates, structural properties of ice, and interaction with convective flow.
SIPW01 14th September 2017
09:45 to 10:30
Daniela Flocco Modeling Arctic melt ponds
SIPW01 14th September 2017
11:00 to 11:45
Robert Bridges Sea ice research - needs and gaps
SIPW01 14th September 2017
11:45 to 12:30
Erik Almkvist Different ice observation methods in marine operations
SIPW01 14th September 2017
14:00 to 14:30
Predrag Popovic Simple rules govern the patterns of Arctic sea ice melt ponds
Co-authors: BB Cael (MIT), Mary Silber (University of Chicago), Dorian Abbot (University of Chicago)

Climate change, amplified in the far north, has led to a rapid sea ice decline in recent years. Melt ponds that form on the surface of Arctic sea ice in the summer significantly lower the ice albedo, thereby accelerating ice melt. Pond geometry controls the details of this crucial feedback. However, a question of modeling pond geometry remains unresolved. Here we show that an extremely simple model of voids surrounding randomly sized and placed overlapping circles reproduces the essential features of pond patterns. The model has only two parameters, circle scale and the fraction of the surface covered by voids, which we choose by comparing the model to pond images. Using these parameters the void model robustly reproduces all of the examined pond features such as the ponds' area-perimeter relationship and the area-abundance relationship over nearly 7 orders of magnitude. By analyzing airborne photographs of sea ice, we also find that the pond width distribution is surpris ingly constant across different years, regions, and ice types. These results demonstrate that the geometric and abundance patterns of Arctic melt ponds can be simply described, and can guide future models of Arctic melt ponds to improve predictions of how sea ice will respond to Arctic warming.
SIPW01 14th September 2017
14:30 to 15:00
Yiping Ma Ising model for melt ponds on Arctic sea ice
Perhaps the most iconic feature of melting Arctic sea ice is the formation of distinctive, complex ponds on its surface during late spring. The evolution of melt ponds and their geometrical characteristics determines the albedo of sea ice, a key parameter in climate modeling. However, a theoretical understanding of this evolution, and predictions of geometrical features, have remained elusive. To address this fundamental problem in polar climate science, here we introduce a two dimensional random field Ising model for melt ponds. The ponds are identified as metastable states of the system, where the binary spin variable corresponds to the presence of melt water or ice on the sea ice surface. With only a minimal set of physical parameters, the model predictions agree very closely with observed power law scaling of the pond size distribution and critical length scale where melt ponds undergo a transition in fractal geometry.

This is joint work with
Ivan Sudakov, Courtenay Strong, and Kenneth M. Golden.
SIPW01 14th September 2017
15:30 to 16:00
Woosok Moon Nonlinear stochastic time series analysis for sea ice and climate
SIPW01 14th September 2017
16:00 to 17:00
Grae Worster Brine rejection from sea ice
Brine rejection from sea ice provides a significant contribution to the buoyancy flux that drives ocean circulations.  Indeed, it provides the dominant contribution in the case of polynyas but the situation with consolidated sea ice is more complex.  Although salt is rejected completely by the ice crystals that form when the ocean freezes, it can be retained as saturated brine within the interstices of sea ice.  Buoyancy-driven convection driven in the interior of sea ice can cause the dense brine to drain into the underlying ocean via brine channels that form by dissolution of the ice matrix.  These intricate interactions between fluid flow and phase change occur on the scale of millimetres to centimetres within sea ice but their consequences must be captured within the sea-ice components of climate models.  I will describe the fundamental physical processes that govern the occurrence and rates of brine rejection from sea ice, and show how the understanding gained from detailed mathematical models of local, three-dimensional processes can be incorporated into an appropriately parameterised one-dimensional model of convection in sea ice suitable for inclusion in climate models.
SIPW01 15th September 2017
08:55 to 09:00
Opening remarks, Danny Feltham
SIPW01 15th September 2017
09:00 to 09:40
Bruno Tremblay Using sea-ice deformation fields to constrain the mechanical strength parameters of geophysical sea ice
Co-author: Amelie Bouchat (McGill UniversityUsing sea-ice deformation fields to constrain the 2 mechanical strength parameters of geophysical sea ice)

We investigate the ability of viscous-plastic (VP) sea-ice models with an elliptical yield curve and normal flow rule to reproduce the shear and divergence distributions derived from the RADARSAT Geophysical Processor System (RGPS). In particular, we reformulate the VP elliptical rheology to allow independent changes in the ice compressive, shear and isotropic tensile strength parameters (P*, S*, T* respectively) in order to study the sensitivity of the deformation distributions to changes in the ice mechanical strength parameters. Our 10-km VP simulation with standard ice mechanical strength parameters P∗= 27.5 kNm−2 , S∗ = 6.9 kNm−2, and T∗ = 0 kNm−2 (ellipse aspect ratio of e = 2) does not reproduce the large shear and divergence deformations observed in the RGPS deformation fields, and specifically lacks well-defined, active linear kinematic features (LKFs). Probability density functions (PDFs) for the shear and divergence of are nonetheless not Gaussian. Simulations with a reduced compressive or increased shear strength are in good agreement with RGPS-derived shear and divergence PDFs, with relatively more large deformations compared to small deformations. The isotropic tensile strength of sea ice on the other hand does not significantly affect the shear and divergence distributions. When considering additional metrics such as the ice drift error, mean ice thickness fields, and spatial scaling of the deformations, our results suggest that reducing the ice compressive strength is a better solution than increasing the shear strength when performing Arctic-wide simulations of the sea-ice cover with the VP elliptical rheology.
SIPW01 15th September 2017
09:40 to 10:00
David Rees Jones Frazil-ice dynamics in mixed layers and sub-ice-shelf plumes
The growth of frazil ice is an important mode of ice formation in the cryosphere. We consider models of a population of ice crystals with different sizes to provide insight into the treatment of frazil ice in large-scale models. We apply our model to a simple mixed layer (such as at the surface of the ocean) and to a buoyant plume under a floating ice shelf. We provide numerical calculations and scaling arguments to predict the occurrence of frazil-ice explosions (periods of rapid ice growth). Faster crystal growth rate, higher secondary nucleation and slower gravitational removal make frazil-ice explosions more likely. We identify steady-state crystal size distributions, which are largely insensitive to crystal growth rate but are affected by the relative importance of secondary nucleation to gravitational removal. Finally, we show that the fate of plumes underneath ice shelves is dramatically affected by frazil-ice dynamics. Differences in the parameterization of crystal growth and nucleation give rise to radically different predictions of basal accretion and plume dynamics; and can even impact whether a plume reaches the end of the ice shelf or intrudes at depth.

Further details can be found at www.the-cryosphere-discuss.net/tc-2017-155/ (Rees Jones, D. W. and Wells, A. J.).

SIPW01 15th September 2017
10:00 to 10:20
Harold Heorton Relationship between sea ice deformation and rheology
The drift and deformation of sea ice floating on the polar oceans is caused by the applied wind and ocean currents. The deformations of sea ice over ocean basin length scales have observable patterns. Cracks and leads can be observed in satellite images and within the velocity fields generated from floe tracking. In a climate sea ice model the deformation of sea ice over ocean basin length scales is modelled using a rheology that represents the relationship between stresses and deformation within the sea ice cover. Here we investigate the link between emergent deformation characteristics and the underlying internal sea ice stresses and force balance using the Los Alamos numerical sea ice climate model.

In order focus on the role of sea ice rheologies in producing deformation we have developed an idealised square domain that tests the model response at spatial resolutions of up to 500 m. We use the Elastic Anisotropic Plastic and Elastic Viscous Plastic rheologies, comparing their stability over varying resolutions and time scales. Sea ice within the domain is forced by idealised winds in order to compare the confinement of wind stresses and internal sea ice stresses. We document the characteristic deformation patterns of convergent, divergent and rotating stress states.
SIPW01 15th September 2017
10:20 to 10:40
Stefanie Rynders Impact of surface wave mixing on sea ice and mixed layer depth
Co-authors: Yevgeny Aksenov (National Oceanography Centre), Daniel Feltham (University of Reading), George Nurser (National Oceanography Centre), Gurvan Madec (L’OCEAN Sorbonne Universités)

Breaking waves cause mixing of the upper water column and present mixing schemes in ocean models take this into account through surface roughness. Sea surface roughness can be calculated from significant wave height, which is commonly parameterised from wind speed. We present results from simulations using modelled significant wave height instead, which accounts for the presence of sea ice and the effect of swell. The simulations use the NEMO ocean model coupled to the CICE sea ice model in a one degree configuration, with wave information from the ECWAM model of the European Centre for Medium-Range Weather Forecasts (ECMWF). It is found that in the simulations with modelled wave height mixing is reduced under the ice cover, since the parameterisation from wind speed overestimates wave height in the ice-covered regions. Decreased mixing decreases vertical heat fluxes to and from the sea ice, which in turn affects sea ice concentration and ice thickness. In the Arctic, ice thicknesses increase overall, with higher increases in the Western Arctic and decreases along the Siberian coast. In the Southern Ocean the meridional gradient in ice thickness and concentration is increased. The new mixing parameterisation improves sea ice volumes in the simulation, especially in the Southern Ocean, where the model has difficulty reproducing the winter sea ice volumes. The mixed layer depth under sea ice is also improved, without affecting mixed layer depth in ice-free regions. Wave and sea ice coupling will become more important in the future, when wave heights in a large part of the Arctic are expected to increase due to sea ice retreat and a larger wave fetch. Therefore, wave mixing constitutes a possible positive feedback mechanism for sea ice decline. The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 607476.
SIPW01 15th September 2017
11:10 to 11:30
Yevgeny Aksenov Waves, ice and ocean in the future projections of the Arctic and Southern oceans
Co-authors: Lucia Hosekova (University of Reading, UK), Stefanie Rynders (National Oceanography Centre, UK), Danny Feltham (University of Reading, UK), Gurvan Madec (Institut Pierre Simon Laplace (IPSL), France), George Nurser (National Oceanography Centre, UK), Tim Williams (Nansen Environmental and Remote Sensing Center (NERSC), Norway), Andrew Coward (National Oceanography Centre, UK)

We present a new development to couple a Sea Ice-Ocean General Circulation Model (OGCM) with ocean waves and analyse the impact of the waves on sea ice and upper ocean. The motivation for the study stems from the recent changes in the Arctic sea ice: not only sea ice extent has been significantly lower in the recent decade than the climatology in summer and winter, but also it is much more broken and mobile, allowing the ocean surface waves propagate in the central Arctic. This mobile sea ice moderates momentum transfer from the atmosphere to the ocean and affects the heat storage in the mixed layer and halocline. We present the simulations with the newly implemented sea ice rheology, combined with floe size distribution analysis and discuss the implications of the observed wave increase and sea ice fragmentation for the present and future of the Polar Oceans. The study was a part of the EU FP7 Project ‘Ships and waves reaching Polar Regions (SWARP)’ and is linked to several ongoing UK national research initiatives.
SIPW01 15th September 2017
11:30 to 11:50
Phil Hwang Winter-to-summer transition of Arctic sea ice breakup and floe size distribution in the Beaufort Sea
Breakup of the near-continuous winter sea ice into discrete summer ice floes is an important transition that dictates the evolution and fate of the marginal ice zone (MIZ) of the Arctic Ocean.  During the spring of 2014, more than 50 autonomous drifting buoys were deployed in four separate clusters on the sea ice in the Beaufort Sea, as part of the Office of Naval Research MIZ program. These systems measured the ocean-ice-atmosphere properties at their location whilst the sea ice parameters in the surrounding area of these buoy clusters were continuously monitored by satellite TerraSAR-X Synthetic Aperture Radar. This approach provided a unique Lagrangian view of the winter-to-summer transition of sea ice breakup and floe size distribution at each cluster between March and August. The results show the critical timings of a) temporary breakup of winter sea ice coinciding with strong wind events and b) spring breakup (during surface melt, melt ponding and drainage) leading to distinctive summer ice floes. Importantly our results suggest that summer sea ice floe distribution is potentially affected by the state of winter sea ice, including the composition and fracturing (caused by deformation events) of winter sea ice, and that substantial mid-summer breakup of sea ice floes is likely linked to the timing of thermodynamic melt of sea ice in the area. As the rate of deformation and thermodynamic melt of sea ice has been increasing in the MIZ in the Beaufort Sea, our results suggest that these elevated factors would promote faster and more enhanced breakup of sea ice, leading to a higher melt rate of sea ice and thus a more rapid advance of the summer MIZ.
SIPW01 15th September 2017
11:50 to 12:10
Ann Keen Investigating future changes in the volume budget of the Arctic sea ice in a coupled climate model
Arctic September sea ice cover has declined at a rate of 13% per decade since satellite observations began, and there is much interest in how this decline will continue in the future, both in terms of the predictability of ice cover in a given year, and in terms of the manner and timing of the transition to a seasonally ice-free Arctic. Global coupled models are arguably the best tool we have for making future projections of the Arctic sea ice, but generate a wide spread of projections of future ice decline. There are many factors potentially contributing to this spread, and it is becoming increasingly clear that as well as investigating ‘integrated’ quantities like ice cover and volume directly, it is also necessary to consider, compare and evaluate the underlying processes, and how they change.

Here we consider the volume budget of the sea ice in the Arctic Basin in the HadGEM2-ES global coupled model (which was the UK/Met Office contribution to CMIP5), and how the budget components evolve during the 21st century under a range of different forcing scenarios. In terms of what happens per unit surface area of the ice, the processes that change most as the climate warms are summer melting at the top surface of the ice, and basal melting due to extra heat from the warming ocean. However, due to the declining ice cover these are not the budget components that contribute most to reductions in the ice volume, and the largest budget change is a reduction in the total amount of basal ice formation during the autumn and early winter.

The choice of forcing scenario affects the rate of ice decline and the timing of change in the volume budget components, but for this model and for the range of scenarios considered for CMIP5, the mean changes in the volume budget depend on the evolving ice area, and are independent of the speed at which the ice cover declines.
SIPW01 15th September 2017
12:10 to 12:30
Jamie Rae How much should we believe correlations between Arctic cyclones and sea ice extent?
I will present an analysis of Arctic summer cyclones in a climate model and in a reanalysis dataset, including results from a cyclone identification and tracking algorithm, and correlations between characteristics of the cyclones and September Arctic sea ice extent.  Results will be presented for output from model simulations at two resolutions, and for the reanalysis, using two different tracking variables (mean sea-level pressure and 850 hPa vorticity) for identification of the cyclones.  I will explore the influence of the tracking variable, the spatial resolution of the model, and spatial and temporal sampling, on the correlations.  I will conclude that the correlations obtained depend on all of these factors, and that care should be taken when interpreting the results of such analyses, especially when the focus is on one reanalysis, or output from one model, analysed with a single tracking variable for a short time period.
SIPW01 15th September 2017
13:30 to 14:10
Julienne Stroeve Integrating Observations and Models to Better Understand a Changing Arctic Sea Ice Cover
SIPW01 15th September 2017
14:10 to 14:30
Ian Renfrew Atmospheric response to marginal-ice-zone drag parameterisation
A physically-based parameterization of atmospheric surface drag over the marginal-ice-zone has recently been validated and tuned based on a large set of observations of surface stress from the ACCACIA project (Elvidge et al. 2016, Atmos. Chem. and Physics). This parameterization has now been implemented in the Met Office Unified Model (MetUM) and is available for both weather and climate applications. Here we present test results for a case study of a cold-air outbreak over and downstream of the MIZ, and for a collection of cases from the ACCACIA field campaign. Our focus is on the response of the atmosphere to the changes in surface drag. Preliminary results show that the new parameterization has a significant impact on simulated boundary layer conditions. For example, boundary layer temperatures over the MIZ during cold air outbreaks are generally reduced by 2-3 K in the model, in response to markedly reduced surface heat fluxes. Comparisons with aircraft observations reveal the changes to generally be beneficial. The implications of these changes for the climate system will be discussed.
SIPW01 15th September 2017
14:30 to 14:50
Michel Tsamados Challenges in estimating ocean surface stresses in sea ice covered Arctic and Antarctic regions
SIPW01 15th September 2017
14:50 to 15:30
Peter Wadhams Statistics of the sea ice thickness distribution
Measurements of the shape of the sea ice underside by submarine and other methods have enabled us to determine the statistical distributions which described under-ice morphology. Two of the most interesting findings are that (a) the probability density function of deep ice draft
and of the drafts of individual pressure ridges both obey a negative exponential distribution, and (b) the distribution of the spacings between successive pressure ridge keels obey a log-normal distribution. Agreement with the equations is very close. Other parameters of the ice underside, including fractal properties, are much more variable, as are characteristics such as the slop angles of pressure ridges. We examine to what extent the topography of the upper ice surface (freeboard instead of draft; sails instead of keels) obeys the same relationships, and speculate on the physical reasons for these distributions.
SIPW01 15th September 2017
16:00 to 16:20
Christian Haas Arctic Sea Ice Thickness Change
SIPW01 15th September 2017
16:20 to 16:40
Alex West Using Arctic ice mass balance buoys for model evaluation
Since 1993 the Arctic Ocean has seen the deployment of over 100 ice mass balance buoys (IMBs), devices which measure elevation of the sea ice surface and base, as well as internal ice temperatures at a vertical resolution of 10cm.  Here the thermodynamic data provided by the IMBs is used to evaluate the sea ice simulation of the CMIP5 model HadGEM2-ES, which simulates anomalously high summer melting and winter freezing in the recent historical period.  Monthly mean fluxes of topmelt, snowfall, conduction, basal growth and ocean-to-ice heat are calculated for the entire IMB network, giving a distribution of around 500 data points for each variable. Model evaluation is concentrated in two regions of the Arctic that are particularly densely sampled by the IMBs, the North Pole and the Beaufort Sea. Distributions of modelled and observed fluxes in these regions are compared, and severe biases in June top melting fluxes and winter conductive fluxes are identified which are too large to be attributed to sampling biases in the IMBs.  Consistent with previously identified biases in the Arctic climate simulation of HadGEM2-ES, the results allow detailed attribution of the sea ice simulation biases to particular drivers in the atmosphere and sea ice.
SIPW01 15th September 2017
16:40 to 17:00
Ed Blockley Impact of initialising sea ice forecasts using CryoSat-2 thickness observations for seasonal sea ice prediction with the Met Office GloSea system
Met Office seasonal predictions are made with the GloSea coupled forecasting system. The (NEMO) ocean and (CICE) sea ice components of GloSea are initialised using analysis fields from the FOAM ocean-sea ice analysis and forecast system. FOAM assimilates satellite and in-situ observations of temperature, salinity, sea level anomaly and sea ice concentration each day using the NEMOVAR 3D-Var scheme. Sea ice thickness is not yet assimilated by FOAM but the Met Office are currently developing capability to assimilate sea ice freeboard and thickness observations from CryoSat-2 and SMOS sensors within the NEMOVAR 3D-Var framework.

Here we present the findings of a recent study undertaken to assess the impact on the evolution of sea ice seasonal forecasts of initialising with CryoSat2-derived thickness observations. We will show that the initialisation of thickness leads to improved skill for seasonal predictions of Arctic summer sea ice extent and ice-edge location whilst highlighting persistent biases in the modelled thickness distribution.
SIPW01 15th September 2017
17:00 to 17:20
David Schroeder New insight from CryoSat-2 sea ice thickness for sea ice modelling
Estimates of Arctic sea ice thickness are available from the CryoSat-2 radar altimetry mission during the ice growth seasons since 2010. We derive the sub-grid scale ice thickness distribution (ITD) with respect to 5 ice thickness categories used e.g. in the sea ice component CICE of HadGEM3 climate simulations: (1) ice thickness h 3.6 m. This allows us both to verify the simulated cycle of ice thickness and to initialize the ITD in stand-alone simulations with the sea ice model CICE. We find that a default CICE simulation strongly underestimates the ice thickness, in spite of doing a reasonable job regarding the inter-annual variability of summer sea ice extent. We can identity the underestimation of winter ice growth being responsible and show that using ice and snow conductivity values on the upper end of the observed range (2.63 and 0.5 W/m/K) makes sea ice growth more realistic and generally improves the model simulation. Sensitivity studies provide insight on the role of ice strength, momentum and heat turbulent fluxes on the annual cycle of sea ice thickness. We show that the width of ITD plays an important role for the summer lead fraction and basal ice melt. Furthermore, a major discrepancy is revealed regarding the annual cycle of sub-grid scale thick sea ice (category 5). According to Cryosat-2 there is a strong formation of thick ice during winter, but hardly any thick ice survives the summer. CICE simulations only show a weak seasonal cycle, indicating that both the formation and the melting of thick is underestimated. Coupled simulations with the ocean – sea ice model NEMO-CICE confirm our results highlighting that sea ice physics and parameters are responsible for differences with Cryosat estimates and improvements are required.