Sea Ice Deformation Research Articles

Thermodynamic sea ice growth in the central Weddell Sea, observed in upward‐looking sonar data

AbstractUpward‐looking sonar (ULS) data were used to analyze thermodynamic sea ice growth. The study was carried out for an ocean region in the central Weddell Sea, for which data of sea ice thickness variability and of the oceanic heat flux through the ice are rare. In the study area the contribution of sea ice deformation to vertical ice growth is relatively small in some years. This provides the opportunity to simulate thermodynamic sea ice growth considering the influence of a snow cover and of the oceanic heat flux. To this end, a modified version of Stefan's law was used. The resulting ice thickness variations were then compared with the ULS measurements. For the investigated cases, the best consistency between data and model results was obtained assuming a snow layer of less than 5 cm thickness and average oceanic heat fluxes between 6 and 14 W m−2. It is demonstrated that in conjunction with ice drift data and analytical models for thermal sea ice growth, ULS ice thickness measurements are useful for studying the seasonal cycle of growth and decay and for inferring the magnitude of the average oceanic heat flux under sea ice.

An assessment of the reliability of sea-ice motion and deformation retrieval using SAR images

AbstractThe local mass balance of sea ice is dependent on the advection of ice into and out of an area and on the deformation processes in that area. Sea-ice motion can be observed from space by synthetic aperture radar (SAR) and quantified by drift-detection algorithms. Due to the scarcity of field observations, it remains a challenging task to validate the resulting motion fields. We analyse the quality of sea-ice motion fields derived from SAR data, using an example dataset from the Weddell Sea region. We apply a quality indicator for sea-ice motion fields which is independent of field data and evaluate it with reference data obtained from visual analysis of the SAR images. Together with the motion field, sea-ice deformation can also be retrieved from SAR data. Similarly to ice motion, it is very difficult to obtain field data to evaluate the quality of the results. Based on a manually derived reference dataset, we introduce a method to validate the retrieved deformation rates. This procedure requires no additional field data. Our analysis shows that deformation rates derived from SAR data are consistent with results obtained from buoy analysis by previous studies.

Simulating transient ice-ocean Ekman transport in the Regional Arctic System Model and Community Earth System Model

AbstractThis work evaluates the fidelity of the polar marine Ekman layer in the Regional Arctic System Model (RASM) and Community Earth System Model (CESM) using sea-ice inertial oscillations as a proxy for ice-ocean Ekman transport. A case study is presented that demonstrates that RASM replicates inertial oscillations in close agreement with motion derived using the GPS. This result is obtained from a year-long case study pre-dating the recent decline in perennial Arctic sea ice, using RASM with sub-hourly coupling between the atmosphere, sea-ice and ocean components. To place this work in context, the RASM coupling method is applied to CESM, increasing the frequency of oceanic flux exchange from once per day in the standard CESM configuration, to every 30 min. For a single year simulation, this change causes a considerable increase in the median inertial ice speed across large areas of the Southern Ocean and parts of the Arctic sea-ice zone. The result suggests that processes associated with the passage of storms over sea ice (e.g. oceanic mixing, sea-ice deformation and surface energy exchange) are underestimated in Earth System Models that do not resolve inertial frequencies in their marine coupling cycle.

Sounds in the Ocean at 1–100 Hz

Very-low-frequency sounds between 1 and 100 Hz propagate large distances in the ocean sound channel. Weather conditions, earthquakes, marine mammals, and anthropogenic activities influence sound levels in this band. Weather-related sounds result from interactions between waves, bubbles entrained by breaking waves, and the deformation of sea ice. Earthquakes generate sound in geologically active regions, and earthquake T waves propagate throughout the oceans. Blue and fin whales generate long bouts of sounds near 20 Hz that can dominate regional ambient noise levels seasonally. Anthropogenic sound sources include ship propellers, energy extraction, and seismic air guns and have been growing steadily. The increasing availability of long-term records of ocean sound will provide new opportunities for a deeper understanding of natural and anthropogenic sound sources and potential interactions between them.

The elastic–viscous–plastic method revisited

In this paper, we show that one of the most widely used methods to solve the non-linear viscous–plastic (VP) sea ice rheology, the elastic–viscous–plastic (EVP) method, generates artificial linear bands of high deformation that may be confounded with real linear kinematic features observed in the Arctic ice pack. These numerical artefacts are easily filtered out by using a slightly different regularization of the internal stress. In addition, the EVP method is reinterpreted as an iterative solver and a clear distinction appears between the numerical and physical parameters. Two numerical parameters determine the stability and accuracy of the method and are adjusted to avoid the noisy ice deformation fields frequently observed with the EVP method in nearly rigid ice areas. This study also confirms the unsatisfactory numerical convergence of the EVP method and investigates the effects of the numerical parameters on sea ice deformation, internal stress and velocity fields obtained with unconverged solutions.

Analysis of sea ice motion and deformation using AMSR-E data from 2005 to 2007

Dynamics of Arctic sea ice, including motion and deformation, are studied utilizing data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (EOS) (AMSR-E) during 2005 and 2007. We first derive sea ice motion maps from the satellite data in a grid of 100 km × 100 km using a two-dimensional wavelet method. These sea ice motion results are compared with those derived from buoy data from the International Arctic Buoy Programme. Secondly, it is well known that sea ice deformation can be characterized by a strain-rate tensor calculated from the ice velocity field. Two components of the strain-rate tensor quantify the divergence and the shearing of the ice field, respectively. Daily maps for both sea ice motion and strain-rate tensor, as well as monthly averages and spatial sums, are computed and analysed. Comparison of the monthly ice motion maps for May 2005 and May 2007 indicates that the anti-cyclonic Beaufort Gyre and Transpolar Drift Stream in the western Arctic are relatively stronger during 2007 than 2005. Different patterns in the spring months' sea ice deformation rates as characterized by the absolute values of the strain-rate tensor are observed when we compare the data of 2007 with those of 2005 and 2006. The sea ice deformation activities in the spring of 2007 happen earlier and are relatively stronger than that of 2005 and 2006. These results might help to explain why the sea ice extent in the summer of 2007 is unprecedentedly low.

Analysis of interrelation between the scattering index of sea ice and its properties

Analyzed is the interrelation between the properties of the sea ice, its scattering index at the frequencies of 23 and 31 GHz, and the brightness temperature computed from the multispectral measurements with the AMSU radiometer. Within the frameworks of the simplified model representations, the quantitative estimates are obtained of the influence of the ice thickness, ice concentration, and presence of inhomogeneities in the emitting layer and snow cover on the ice surface on the ice scattering index values. It is demonstrated that the scattering on the dislocations formed near the surface of ice at its bend and compression can be the main reason for the rapid change in the scattering index of one-year and old ice observed in different seasons. The results of the analysis corroborated the validity of applying the scattering index for the revelation of the areas of deformation and hummocking of sea ice, as well as for the estimation of the age and thickness of thin and young ice.

Variability of sea ice deformation rates in the Arctic and their relationship with basin-scale wind forcing

Abstract. The temporal variability of the moments of probability distribution functions (pdfs) of total sea ice deformation rates in the Arctic is analyzed in the context of the basin-scale wind forcing acting on the ice. The pdfs are estimated for 594 satellite-derived sea ice deformation maps from 11 winter seasons between 1996/1997 and 2007/2008, provided by the RADARSAT Geophysical Processor System. The temporal scale analyzed equals 3 days. The moments of the pdfs, calculated for a range of spatial scales (12.5–900 km), have two dominating components of variability: a seasonal cycle, with deformation rates decreasing throughout winter towards a minimum in March; and a short-term, synoptic variability, strongly correlated with the area-averaged magnitude of the wind stress over the Arctic, estimated based on the NCEP-DOE Reanalysis-2 data (correlation coefficient of 0.71 for the mean deformation rate). Due to scaling properties of the moments, logarithms of higher moments are strongly correlated with the wind stress as well. Exceptions are observed only at small spatial scales, as a result of extreme deformation events, not directly associated with large-scale wind forcing. By repeating the analysis within regions of different sizes and locations, we show that the wind–ice deformation correlation is largest at the basin scale and decreases with decreasing size of the area of study. Finally, we suggest that a positive trend in seasonally averaged correlation between sea ice deformation rates and the wind forcing, present in the analyzed data, may be related to an observed decrease in the multi-year ice area in the Arctic, indicating possibly even stronger correlations in the future.

Remote sensing of sea ice: advances during the DAMOCLES project

Abstract. In the Arctic, global warming is particularly pronounced so that we need to monitor its development continuously. On the other hand, the vast and hostile conditions make in situ observation difficult, so that available satellite observations should be exploited in the best possible way to extract geophysical information. Here, we give a résumé of the sea ice remote sensing efforts of the European Union's (EU) project DAMOCLES (Developing Arctic Modeling and Observing Capabilities for Long-term Environmental Studies). In order to better understand the seasonal variation of the microwave emission of sea ice observed from space, the monthly variations of the microwave emissivity of first-year and multi-year sea ice have been derived for the frequencies of the microwave imagers like AMSR-E (Advanced Microwave Scanning Radiometer on EOS) and sounding frequencies of AMSU (Advanced Microwave Sounding Unit), and have been used to develop an optimal estimation method to retrieve sea ice and atmospheric parameters simultaneously. In addition, a sea ice microwave emissivity model has been used together with a thermodynamic model to establish relations between the emissivities from 6 GHz to 50 GHz. At the latter frequency, the emissivity is needed for assimilation into atmospheric circulation models, but is more difficult to observe directly. The size of the snow grains on top of the sea ice influences both its albedo and the microwave emission. A method to determine the effective size of the snow grains from observations in the visible range (MODIS) is developed and demonstrated in an application on the Ross ice shelf. The bidirectional reflectivity distribution function (BRDF) of snow, which is an essential input parameter to the retrieval, has been measured in situ on Svalbard during the DAMOCLES campaign, and a BRDF model assuming aspherical particles is developed. Sea ice drift and deformation is derived from satellite observations with the scatterometer ASCAT (62.5 km grid spacing), with visible AVHRR observations (20 km), with the synthetic aperture radar sensor ASAR (10 km), and a multi-sensor product (62.5 km) with improved angular resolution (Continuous Maximum Cross Correlation, CMCC method) is presented. CMCC is also used to derive the sea ice deformation, important for formation of sea ice leads (diverging deformation) and pressure ridges (converging). The indirect determination of sea ice thickness from altimeter freeboard data requires knowledge of the ice density and snow load on sea ice. The relation between freeboard and ice thickness is investigated based on the airborne Sever expeditions conducted between 1928 and 1993.

Rheology of Discrete Failure Regimes of Anisotropic Sea Ice

ABSTRACT A rheological model of sea ice is presented that incorporates the orientational distribution of ice thickness in leads embedded in isotropic floe ice. Sea ice internal stress is determined by coulombic, ridging and tensile failure at orientations where corresponding failure criteria are satisfied at minimum stresses. Because sea ice traction increases in thinner leads and cohesion is finite, such failure line angles are determined by the orientational distribution of sea ice thickness relative to the imposed stresses. In contrast to the isotropic case, sea ice thickness anisotropy results in these failure lines becoming dependent on the stress magnitude. Although generally a given failure criteria type can be satisfied at many directions, only two at most are considered. The strain rate is determined by shearing along slip lines accompanied by dilatancy and closing or opening across orientations affected by ridging or tensile failure. The rheology is illustrated by a yield curve determined by combining coulombic and ridging failure for the case of two pairs of isotropically formed leads of different thicknesses rotated with regard to each other, which models two events of coulombic failure followed by dilatancy and refreezing. The yield curve consists of linear segments describing coulombic and ridging yield as failure switches from one lead to another as the stress grows. Because sliding along slip lines is accompanied by dilatancy, at typical Arctic sea ice deformation rates a one-day-long deformation event produces enough open water that these freshly formed slip lines are preferential places of ridging failure.

Subsynoptic scale spatial variability of sea ice deformation in the western Weddell Sea during early summer

Ice Station Polarstern (ISPOL), deployed in the western Weddell Sea from November 2004 to January 2005, included a study of subsynoptic scale variability in sea ice velocity and deformation using an array of 24 buoys. Upon deployment, the ISPOL buoy array measured 70 km in both zonal and meridional extent and consisted of subarrays that resolved sea ice deformation on scales from 10 to 70 km. Across the ISPOL array, divergence varied and did not show a distinct coherent length scale. Spectral analysis of divergence and shear of subarrays revealed that deformation did not vary smoothly across the array. This indicates variability of internal ice stress on the scale of 10 km. Ice conditions within the ISPOL array encompassed two distinct regimes separated by shear along the continental shelf break. Differences in spectral power of the tidal and inertial bands across the two regions do not mirror expected differences due to spatial variability of tide‐induced deformation on the shelf break. Instead, they indicate that the pack ice's internal stress behaved anisotropically on the scale of the shear zone (across the buoy array, 70 km).

Toward a new elastic–decohesive model of Arctic sea ice

This paper argues for a new constitutive model, an elastic–decohesive model for sea ice. The model is motivated by examining satellite observations of the Arctic processed to show ice deformation in the form of divergence, shear and vorticity. The model is implemented numerically in the material-point method and used to predict motion and deformation of sea ice by simulating a region of the Beaufort Sea. The model is able to capture the qualitative and statistical behavior of localized deformation seen in the observations.

Spatial and temporal characterization of sea-ice deformation

AbstractIn late March 2007 an array of GPS ice drifters was deployed in the Beaufort Sea as part of the Sea Ice Experiment: Dynamic Nature of the Arctic (SEDNA). the drifters were deployed in an array designed to resolve four, nested spatial scales of sea-ice deformation, from 10 to 140 km, with the arrays maintaining appropriate shape for strain-rate calculation until mid-June. In this paper, we test whether sea-ice deformation displays fractal properties in the vicinity of SEDNA. We identify that deformation time series have different spectral properties depending on the spatial scale. At the scales around 100 km, deformation is a red-noise process, indicating the importance of the ice-pack surface forcing in determining the deformation rate of sea ice at this scale. At smaller scales, the deformation becomes an increasingly whiter process (it has pink noise properties), which suggests an increasing role of dissipative processes at smaller scales. At spatial scales of 10–100 km, and sub-daily scales, there is no deformation coherence across scales; coherence only becomes apparent at longer scales greater than 100 km. the lack of coherence at small scales aids in understanding previous observations where correlation between 10km regions adjacent to each other varied widely, with correlation coefficients between –0.3 and 1. This suggests it is not appropriate to think of sea ice as having a decorrelation length scale for deformation. We find that lead scale observations of deformation are required when estimating ice growth in leads and ridging time series. For the two SEDNA arrays, we find coherence between 140 and 20 km scale deformation up to periods of 16 days. This suggests sea-ice deformation displays coherent deformation between 100 km scale and the scale of the Beaufort Sea (of order 1000 km), over synoptic time periods (daily to weekly timescales). Organization of leads at synoptic and larger scales is an emergent feature of the deformation field that is caused by the smooth variation of surface forcing (wind) on the ice pack.

A new modeling framework for sea-ice mechanics based on elasto-brittle rheology

AbstractWe present a new modeling framework for sea-ice mechanics based on elasto-brittle (EB) behavior. the EB framework considers sea ice as a continuous elastic plate encountering progressive damage, simulating the opening of cracks and leads. As a result of long-range elastic interactions, the stress relaxation following a damage event can induce an avalanche of damage. Damage propagates in narrow linear features, resulting in a very heterogeneous strain field. Idealized simulations of the Arctic sea-ice cover are analyzed in terms of ice strain rates and contrasted to observations and simulations performed with the classical viscous–plastic (VP) rheology. the statistical and scaling properties of ice strain rates are used as the evaluation metric. We show that EB simulations give a good representation of the shear faulting mechanism that accommodates most sea-ice deformation. the distributions of strain rates and the scaling laws of ice deformation are well captured by the EB framework, which is not the case for VP simulations. These results suggest that the properties of ice deformation emerge from elasto-brittle ice-mechanical behavior and motivate the implementation of the EB framework in a global sea-ice model.

Analysis of measurement data on carbon dioxide concentration in the near-ice surface atmosphere at North Pole-35 drifting ice station (2007–2008)

Significant CO2 concentration disturbances with an amplitude of 150 ppm are observed in October–November in the region of North Pole-35 drifting ice station over the continental slope of the Arctic Ocean. A local maximum of the CO2 concentration disturbances is observed in April; it is connected with a change in the regime of the sea ice deformation at that time of the year in the western Arctic basin. Changes in the CO2 concentration have oscillations at the frequency of oceanic tides. Several episodes of the initial phase of CO2 release into the near-ice surface atmosphere in October 2007 are recorded. The CO2 amount released into the atmosphere as a result of ice formation in the Arctic Ocean is a significant quantity in the total balance of the CO2 release on the global scale and accounts for approximately 30% of the anthropogenic release of CO2 per year.

Spatial scaling of Arctic sea ice deformation

Arctic sea ice deformation arises from spatial gradients in the ice velocity field. This deformation occurs across a wide range of spatial scales, from meters to thousands of kilometers. We analyze 7 years of sea ice deformation data from the RADARSAT Geophysical Processor System (RGPS) covering the western Arctic Ocean. We find that the mean deformation rate is related to the spatial scale over which it is measured according to a power law with exponent ∼−0.2, over a scale range from 10 to 1000 km (e.g., deformation rate doubles for a 30‐fold reduction in scale). Both the exponent and the deformation rate have distinct annual cycles. The exponent becomes more negative in summer as the ice pack weakens and internal stresses are not as readily transmitted over long distances. The deformation rate reaches a minimum in late winter when the ice pack is strongest. The deformation also exhibits considerable localization, in which the largest deformation rates are confined to smaller and smaller areas as the scale of measurement decreases. This supports a model for sea ice based on granular or fracture mechanics. The scaling exponent in the power law relationship tends to be larger in magnitude where the concentration of multiyear ice is low, consistent with a thinner and weaker ice pack. With decreasing multiyear ice in the Arctic and a thinning ice pack, an increase in the deformation rate has already been documented (from buoy data). However, the net effect of several deformation/thickness feedbacks is still uncertain.

Role of off‐shelf to on‐shelf transitions for East Antarctic sea ice dynamics during spring 2003

During austral spring 2003, mesoscale sea ice drift and deformation off East Antarctica were investigated using in situ data from a nine‐buoy array. Upon deployment, the array comprised an area of about 4000 km2 with a mean ice concentration of 96%. Half‐hourly sea ice velocities were coherent across all buoys at zonal (meridional) separations of less than 160 km (70 km). Regional cross‐spectral correlation was high at synoptic scales and also at semidiurnal periods off the continental shelf. Atmospheric synoptic‐scale forcing explained in excess of 85% of the ice drift variability. This is significantly more than found in the Weddell Sea, where significant ice drift variability is derived from oceanic forcing. Peak frequencies of semidiurnal contributions covaried with latitude and are largely associated with the inertial response. Over the continental shelf, coincident diurnal and semidiurnal variances in ice motion arose from tidal forcing. Net divergence over 37 days resulted in an expansion to 270% of the initial area, although regional ice concentration reduced only slightly. High‐frequency processes, namely inertial response and to a lesser degree tidal forcing, dominated the variability of all deformation parameters. In contrast to ice motion, low‐frequency processes played a secondary role in sea ice deformation. This high‐frequency dominance is similar to what has been found in the Weddell Sea, although many observations there were limited to the continental shelf, where tidal processes dominate. Sea ice motion and deformation were not affected by a seasonal transition, nor did the regional ice characteristics show any signal of seasonal change. Instead, local ice dynamics were strongly influenced by bathymetrically dependent processes.

Analysis of sea ice motion and deformation in the marginal ice zone of the Bering Sea using SAR data

This paper presents a study of sea ice motion and deformation in the marginal ice zone (MIZ) of the Bering Sea in the winter season. Segmentation techniques and statistical methods are applied to high‐resolution synthetic aperture radar (SAR) images to derive ice motion and deformation maps. These techniques involve dynamic local thresholding (DLT), which allows separation of sea ice into different classes of thickness and type. Two ice motion characteristics are observed, one consisting of a translation and a rotation at a scale larger than about 10 km day−1 and the other consisting of field deformations at a spatial scale of less than about 5 km over a 3‐day period. Sea ice deformation rates are calculated, and the divergence and shear feature of the sea ice in different regions identified. Possible causes, associated with wind, wave, current and internal ice forces, for the sea ice motion and deformation are discussed.

Positive trend in the mean speed and deformation rate of Arctic sea ice, 1979–2007

Using buoy data from the International Arctic Buoy Program, we found that the sea ice mean speed has substantially increased over the last 29 years (+17% per decade for winter and +8.5% for summer). A strong seasonal dependence of the mean speed is also revealed, with a maximum in October and a minimum in April. The sea ice mean strain rate also increased significantly over the period (+51% per decade for winter and +52% for summer). We check that these increases in both sea ice mean speed and deformation rate are unlikely to be consequences of a stronger atmospheric forcing. Instead, they suggest that sea ice kinematics play a fundamental role in the albedo feedback loop and sea ice decline: increasing deformation means stronger fracturing, hence more lead opening, and therefore a decreasing albedo. This accelerates sea ice thinning in summer and delays refreezing in early winter, therefore decreasing the mechanical strength of the cover and allowing even more fracturing, larger drifting speed and deformation, and possibly a faster export of sea ice through the Fram Strait. The September minimum sea ice extent of 2007 might be a good illustration of this interplay between sea ice deformation and sea ice shrinking, as we found that for both winter 2007 and summer 2007 exceptionally large deformation rates affected the Arctic sea ice cover.

Modeling viscoplastic behavior and heterogeneous intracrystalline deformation of columnar ice polycrystals

A full-field formulation based on fast Fourier transforms (FFT) has been adapted and used to predict the micromechanical fields that develop in two-dimensional columnar Ih ice polycrystals deforming in compression by dislocation creep. The predicted intragranular mechanical fields are in qualitative good agreement with experimental observations, in particular those involving the formation of shear and kink bands. These localized bands are associated with the large internal stresses that develop during creep in such anisotropic material, and their location, intensity, morphology and extension are found to depend strongly on the crystallographic orientation of the grains and on their interaction with neighboring crystals. The predictions of the model are also discussed in relation to the deformation of columnar sea and lake ice, as well as with the mechanical behavior of granular ice of glaciers and polar ice sheets.