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In order to improve the understanding of the dynamical deformation processes of sea ice in the seasonal ice zone (SIZ), measures to detect deformed ice were developed and validated using satellite L-band synthetic aperture radar (ScanSAR) images for the southern Sea of Okhotsk. To approach, sea ice was categorized into three ice types, typical of the sea ice in this region: nilas (thin level), pancake ice (thin rough), and deformed ice (thick rough), and then the measures to classify into these categories were developed using ALOS/Phased Array type L-band Synthetic Aperture Radar (PALSAR) as a function of backscatter coefficients at HH polarization ( $\sigma _{\text {HH}}^{0}$ ) and incidence angle ( $\theta _{i}$ ), based on the field observations. Comparative analysis confirmed that PALSAR can detect deformed ice more efficiently than RADARSAT-2 (C-band SAR). The temporal evolution of the area, judged as deformed ice from these measures, shows significant variability with both time and space, and deformed ice regions appear in relatively linear alignments with a width of a few tens of kilometers in the inner ice pack region, consistent with ice drift convergence. To confirm the results, PALSAR-2 images at HH and HV polarizations were examined as a function of $\theta _{i}$ , based on the four-year field observations in the same area. The results revealed that $\sigma _{\text {HH}}^{0}$ and $\sigma _{\text{HV}}^{0}$ are both subject to floe sizes as well as deformed ice, and $\sigma _{\text{HV}}^{0}$ is more sensitive. This indicates that care should be taken when applying these measures to the ice areas where significantly small floes are dominant like the marginal ice zone.

Poly- and perfluoroalkyl substances are synthetic chemicals that are widely present in the global environment including the Arctic. However, little is known about how these chemicals (particularly perfluoroalkyl acids, PFAA) enter the Arctic marine system and cycle between seawater and sea ice compartments. To evaluate this, we analyzed sea ice, snow, melt ponds, and near-surface seawater at two ice-covered stations located north of the Barents Sea (81 °N) with the aim of investigating PFAA dynamics in the late-season ice pack. Sea ice showed high concentrations of PFAA particularly at the surface with snow-ice (the uppermost sea ice layer strongly influenced by snow) comprising 26–62% of the total PFAA burden. Low salinities (, Sea ice accumulates perfluoroalkyl acids (PFAAs) from seawater and from atmospheric deposition in snow. Subsequent melting of surface ice layers through seasonal changes later results in high PFAA concentrations in the under-ice seawater.

The radiative transfer of shortwave solar radiation through the sea ice cover of the polar oceans is a crucial aspect of energy partitioning at the atmosphere–ice–ocean interface. A detailed understanding of how sunlight is reflected and transmitted by the sea ice cover is needed for an accurate representation of critical processes in climate and ecosystem models, such as the ice–albedo feedback. Due to the challenges associated with ice internal measurements, most information about radiative transfer in sea ice has been gained by optical measurements above and below the sea ice. To improve our understanding of radiative transfer processes within the ice itself, we developed a new kind of instrument equipped with a number of multispectral light sensors that can be frozen into the ice. A first prototype consisting of a 2.3 m long chain of 48 sideward planar irradiance sensors with a vertical spacing of 0.05 m was deployed at the geographic North Pole in late August 2018, providing autonomous, vertically resolved light measurements within the ice cover during the autumn season. Here we present the first results of this instrument, discuss the advantages and application of the prototype, and provide first new insights into the spatiotemporal aspect of radiative transfer within the sea ice itself. In particular, we investigate how measured attenuation coefficients relate to the optical properties of the ice pack and show that sideward planar irradiance measurements are equivalent to measurements of total scalar irradiance.

Airborne electromagnetic induction sensors have demonstrated their extensive capacities to measure sea-ice thickness distributions. However, biases can emerge when comparing these 1-D measurements to a broader 2-D regional scale due to the spatial anisotropy inherent to sea-ice cover. Automated processing of available sea-ice maps could significantly ease the decision on how to set up an optimised flight pattern, which would result in representative ice thickness numbers for the region. In this study, first we investigate the extent to which the sea-ice anisotropy can influence the representativeness of an airborne survey compared to the regional situation. Second, we propose a method to process sea-ice maps prior to flights to help preparing the most representative flight plan possible for the local area. The method is based on automated segmentation of radar satellite images and extensive simulation of flight transects over the image. The spatial analysis of these transects enables for the identification of the most representative survey trajectories for the area. The method was applied for seven different synthetic aperture radar satellite images over Arctic sea ice north of Svalbard. The results indicate that the proposed method improved the representativeness of the airborne survey by identifying the most suitable transect over the ice pack.

The role of synoptic-scale cyclones in the trends and variability of Arctic sea ice conditions has remained uncertain. In recognition, we conduct a systematic investigation of how sea-ice concentration (SIC) changes with cyclone passage, including all individual storms that pass over any part of the region's ice pack. For all seasons, especially summer and autumn, we find a pattern of higher ice concentration after a region is influenced by a cyclone compared to when it is not, primarily due to thermodynamic effects. During warm months, cyclones appear to slow the general day-to-day decline in concentration; in cold months, cyclones augment the day-to-day increase. These relationships are changing over time, with cyclone-associated concentration changes becoming less distinct from overall changes. Cyclone effects on ice divergence are spatially variable; computed fields are noisy. In summer, these dynamic effects of cyclone passage generally decrease SIC, but are outweighed by the thermodynamic effects (e.g., reductions in air temperature, shortwave radiation). In autumn, cyclone-associated concentration changes are not as easily explained by observed cyclone conditions. Key questions remain regarding the extent to which our findings are influenced by artifacts of surface melt and weather effects on the passive microwave retrievals.

Leads are a key feature of the Arctic ice pack during the winter owing to their substantial contribution to the surface energy balance. According to the present understanding, enhanced heat and moisture fluxes from high lead concentrations tend to produce more boundary layer clouds. However, described here in our composite analyses of diverse surface- and satellite-based observations, we find that abundant boundary layer clouds are associated with low lead flux periods, while fewer boundary layer clouds are observed for high lead flux periods. Motivated by these counterintuitive results, we conducted three-dimensional cloud-resolving simulations to investigate the underlying physics. We find that newly frozen leads with large sensible heat flux but low latent heat flux tend to dissipate low clouds. This finding indicates that the observed high lead fractions likely consist of mostly newly frozen leads that reduce any pre-existing low-level cloudiness, which in turn decreases downwelling infrared flux and accelerates the freezing of sea ice., Cracks in Arctic sea ice (leads) are becoming more prevalent and widespread, yet studies regarding their impacts on clouds are limited. Here, contrary to the present understanding, diverse observations and modelling simulations show that higher leads concentrations do not necessarily result in more low clouds.

Recent reports on Arctic underice phytoplankton blooms have directed attention to primary production below the sea ice cover. Such underice blooms cannot be detected from space; thus, methods for autonomous underice measurements are critically needed to extend observations beyond ship-based surveys. One central aspect of the ecology of these blooms is whether they were advected from open-water areas or were able to develop below the ice cover under typically low light conditions. The photoacclimation state of the bloom can provide clues about the growth conditions and therefore its origin. Here we investigate the photoacclimation state of a Phaeocystis pouchetii-dominated underice bloom in the Arctic Ocean using ratios of photoprotective carotenoids (PPC) to photosynthetic carotenoids (PSC) and chlorophyll a. The pigment proxies indicate local growth under the ice pack. Furthermore, a method using in situ light absorption measurements to estimate the PPC:PSC ratio was in agreement with the pigment data. The slope of in situ phytoplankton absorption between 488 and 532nm, affected by both PPC and PSC, had a significant linear relationship to the PPC:PSC ratio, indicating that prediction of photoacclimation state can be obtained from absorption profiles. We also review, with regard to the pigment function, different ways of grouping pigments into PPC or PSC applied in previous studies. Although more validation data sets are needed to assess the impact of pigment packaging on the relationship between PPC:PSC and absorption measurement slopes, our study shows the potential for using in situ absorption measurements to collect information about phytoplankton physiology below sea ice. Plain Language Summary Phytoplankton blooms below sea ice cover, that is, underice blooms, can be advected by ocean currents below the ice pack from ice-free waters where they had sufficient light available for growth. They can also grow below the ice pack if sufficient light is transmitted through the ice, and they are able to adjust to the typically low light conditions. Algal pigments can indicate which of the two scenarios is more likely. Algal pigments capture sunlight for photosynthesis, but some of them are used to protect the algal cells from excess light. The ratio of photoprotective to photosynthetic pigments reveals the photoacclimation state ("short time adjustments") of the algae. In this study we investigate the photoacclimation state of an Arctic underice bloom based on pigment ratios, which indicate local growth below the ice pack. Furthermore, we validate a method to estimate the pigment ratios from light absorption measurements carried out with an instrument in the water column. Studies like these are important for developing methods to study remote areas. Ship-based surveys can only cover a restricted area, and satellite remote sensing does not provide biological information from ice-covered waters. Our study shows promising results for using water column instruments to study phytoplankton physiology.

Continuing losses of multi-year sea ice (MYI) across the Arctic are causing first-year sea ice (FYI) to dominate the Arctic ice pack. Melting FYI provides a strong seasonal pulse of dissolved organic matter (DOM) into surface waters; however, the biological impact of this DOM input is unknown. Here we show that DOM additions cause important and contrasting changes in under-ice bacterioplankton abundance, production and species composition. Utilization of DOM was influenced by molecular size, with 10–100 kDa and >100 kDa DOM fractions promoting rapid growth of particular taxa, while uptake of sulfur and nitrogen-rich low molecular weight organic compounds shifted bacterial community composition. These results demonstrate the ecological impacts of DOM released from melting FYI, with wide-ranging consequences for the cycling of organic matter across regions of the Arctic Ocean transitioning from multi-year to seasonal sea ice as the climate continues to warm. Arctic sea-ice melt causes a release of dissolved organic material (DOM) into the surface waters. The increased dominance of first-year ice and DOM release is impacting under-ice bacterial communities.

The diminishing Arctic sea ice pack has been widely studied, but previous research has mostly focused on time-mean changes in sea ice rather than on short-term variations that also have important physical and societal consequences. In this study we test the hypothesis that future interannual Arctic sea ice area variability will increase by utilizing 40 independent simulations from the Community Earth System Model's Large Ensemble (CESM-LE) for the 1920–2100 period and augment this with simulations from 12 models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Both CESM-LE and CMIP5 models project that ice area variability will indeed grow substantially but not monotonically in every month. There is also a strong seasonal dependence in the magnitude and timing of future variability increases that is robust among CESM ensemble members. The variability generally correlates with the average ice retreat rate, before there is an eventual disappearance in both terms as the ice pack becomes seasonal in summer and autumn by late century. The peak in variability correlates best with the total area of ice between 0.2 and 0.6 m monthly thickness, indicating that substantial future thinning of the ice pack is required before variability maximizes. Within this range, the most favorable thickness for high areal variability depends on the season, especially whether ice growth or ice retreat processes dominate. Our findings suggest that thermodynamic melting (top, bottom, lateral) and growth (frazil, congelation) processes are more important than dynamical mechanisms, namely ice export and ridging, in controlling ice area variability.

The ice arches that usually develop at the northern and southern ends of Nares Strait play an important role in modulating the export of Arctic Ocean multi-year sea ice. The Arctic Ocean is evolving towards an ice pack that is younger, thinner, and more mobile and the fate of its multi-year ice is becoming of increasing interest. Here, we use sea ice motion retrievals from Sentinel-1 imagery to report on the recent behavior of these ice arches and the associated ice fluxes. We show that the duration of arch formation has decreased over the past 20 years, while the ice area and volume fluxes along Nares Strait have both increased. These results suggest that a transition is underway towards a state where the formation of these arches will become atypical with a concomitant increase in the export of multi-year ice accelerating the transition towards a younger and thinner Arctic ice pack., Ice arches that form along Nares Strait, which separates Greenland and Ellesmere Island, act to reduce the export of thick multi-year ice out of the Arctic. Here, we show that there has been a recent trend towards shorter duration arch formation that has resulted in enhanced transport of ice along the strait.

The Earth’s climate is rapidly changing and some of the most drastic changes can be seen in the Arctic, where sea ice extent has diminished considerably in recent years. As the Arctic climate continues to change, gathering in situ sea ice measurements is increasingly important for understanding the complex evolution of the Arctic ice pack. To date, observations of ice stresses in the Arctic have been spatially and temporally sparse. We propose a measurement framework that would instrument existing sea ice buoys with strain gauges. This measurement framework uses a Bayesian inference approach to infer ice loads acting on the buoy from a set of strain gauge measurements. To test our framework, strain measurements were collected from an experiment where a buoy was frozen into ice that was subsequently compressed to simulate convergent sea ice conditions. A linear elastic finite element model was used to describe the response of the deformable buoy to mechanical loading, allowing us to link the observed strain on the buoy interior to the applied load on the buoy exterior. The approach presented in this paper presents an instrumentation framework that could use existing buoy platforms as in situ sensors of internal stresses in the ice pack.

A number of feedbacks regulate the response of Arctic sea ice to local atmospheric warming. Using a realistic coupled ocean‐sea ice model and its adjoint, we isolate a mechanism by which significant ice growth at the end of the melt season may occur as a lagged response to Arctic atmospheric warming. A series of perturbation simulations informed by adjoint model‐derived sensitivity patterns reveal the enhanced ice growth to be accompanied by a reduction of snow thickness on the ice pack. Detailed analysis of ocean‐ice‐snow heat budgets confirms the essential role of the reduced snow thickness for persistence and delayed overshoot of ice growth. The underlying mechanism is a snow‐melt‐conductivity feedback, wherein atmosphere‐driven snow melt leads to a larger conductive ocean heat loss through the overlying ice layer. Our results highlight the need for accurate observations of snow thickness to constrain climate models and to initialize sea ice forecasts., Key Points Arctic sea ice sensitivity to atmospheric warming is computed using a numerical adjoint, revealing warming can lead to lagged sea ice growthSnow melt—in response to early warming—is the key preconditioner, enabling large conductive ocean heat loss to support lagged ice growth

A new enhanced resolution gridded passive microwave brightness temperature (TB) product is used to estimate sea ice concentration and motion. The effective resolution of the TBs is found to be roughly twice that of the standard 25 km resolution, though the gridded resolution of the distributed product is higher. Enhanced resolution sea ice concentrations from the Bootstrap algorithm show more detail in the sea ice, including relatively small open water regions within the ice pack. Sea ice motion estimates from the enhanced resolution TBs using a maximum cross-correlation method show a smoother motion circulation pattern, in comparison to buoys, RMS errors are 15&ndash, 20% lower than motion estimates from the standard resolution fields and the magnitude of the bias is smaller as well. The enhanced resolution product includes other potentially beneficial characteristics, including twice-daily grids based on local time of day and a complete timeseries of data from nearly all multi-channel passive microwave radiometers since 1978. These enhanced resolution TBs are potential new source for long-term records of sea ice concentration, motion, age, melt, as well as salinity and ocean-atmosphere fluxes.

The permeability of sea ice can strongly affect the dissipation of wave energy into the ice pack. Sea-ice permeability is known to be impacted by the brine volume fraction and the blockage of flow pathways by the freezing of infiltrating lower salinity water. Here we investigate another process impacting sea-ice permeability, namely, inelastic deformation. We report the results of a first-of-its-kind field-scale deformation experiment to investigate the impact of compressive loading on sea-ice permeability. We observed that deformation decreased permeability by four orders of magnitude or more in some locations, while elsewhere permeability was unaffected or possibly increased. We show that the observed changes in permeability are consistent with expected changes in stress state and, as a result, in the mechanisms of deformation.

We present a sensitivity analysis and discuss the probabilistic forecast capabilities of the novel sea ice model neXtSIM used in hindcast mode. The study pertains to the response of the model to the uncertainty on winds using probabilistic forecasts of ice trajectories. neXtSIM is a continuous Lagrangian numerical model that uses an elasto-brittle rheology to simulate the ice response to external forces. The sensitivity analysis is based on a Monte Carlo sampling of 12 members. The response of the model to the uncertainties is evaluated in terms of simulated ice drift distances from their initial positions, and from the mean position of the ensemble, over the mid-term forecast horizon of 10 days. The simulated ice drift is decomposed into advective and diffusive parts that are characterised separately both spatially and temporally and compared to what is obtained with a free-drift model, that is, when the ice rheology does not play any role in the modelled physics of the ice. The seasonal variability of the model sensitivity is presented and shows the role of the ice compactness and rheology in the ice drift response at both local and regional scales in the Arctic. Indeed, the ice drift simulated by neXtSIM in summer is close to the one obtained with the free-drift model, while the more compact and solid ice pack shows a significantly different mechanical and drift behaviour in winter. For the winter period analysed in this study, we also show that, in contrast to the free-drift model, neXtSIM reproduces the sea ice Lagrangian diffusion regimes as found from observed trajectories. The forecast capability of neXtSIM is also evaluated using a large set of real buoy's trajectories and compared to the capability of the free-drift model. We found that neXtSIM performs significantly better in simulating sea ice drift, both in terms of forecast error and as a tool to assist search and rescue operations, although the sources of uncertainties assumed for the present experiment are not sufficient for complete coverage of the observed IABP positions.

Heavy ice conditions along Canada's east coast during spring 2017 presented hazardous conditions for the maritime industry and required the Canadian Coast Guard to pull its research icebreaker, CCGS Amundsen, off its scientific cruise to provide ice escort services and conduct search and rescue operations along Newfoundland's northeast coast. Greater ice concentrations and a thicker ice pack than are typical of this area created the anomalous ice cover. Within this paper we present in situ observations of the ice cover, confirming that pieces of multiyear sea ice from the high Arctic were present within the ice cover, and subsequently examine the transport pathway that connects the export of thick multiyear sea ice from the Lincoln Sea and Canadian Arctic Archipelago to coastal communities in Newfoundland. We conclude with a discussion on how an increasingly mobile Arctic sea ice cover may increase these ice hazards in the south.

This study is on high-frequency temporal variability (HFV) and meso-scale spatial variability (MSV) of winter sea-ice drift in the Southern Ocean simulated with a global high-resolution (0.1°) sea ice-ocean model. Hourly model output is used to distinguish MSV characteristics via patterns of mean kinetic energy (MKE) and turbulent kinetic energy (TKE) of ice drift, surface currents, and wind stress, and HFV characteristics via time series of raw variables and correlations. We find that (1) along the ice edge, the MSV of ice drift coincides with that of surface currents, in particular such due to ocean eddies; (2) along the coast, the MKE of ice drift is substantially larger than its TKE and coincides with the MKE of wind stress; (3) in the interior of the ice pack, the TKE of ice drift is larger than its MKE, mostly following the TKE pattern of wind stress; (4) the HFV of ice drift is dominated by weather events, and, in the absence of tidal currents, locally and to a much smaller degree by inertial oscillations; (5) along the ice edge, the curl of the ice drift is highly correlated with that of surface currents, mostly reflecting the impact of ocean eddies. Where ocean eddies occur and the ice is relatively thin, ice velocity is characterized by enhanced relative vorticity, largely matching that of surface currents. Along the ice edge, ocean eddies produce distinct ice filaments, the realism of which is largely confirmed by high-resolution satellite passive-microwave data.

We studied small scale (50 m to 5 km) sea ice deformation from ship radar images recorded during the N-ICE2015 campaign. The campaign consisted of 4 consecutive drifting ice stations (Floes 1 to 4) north of Svalbard, with a total duration of nearly 5 months. Deformation was calculated using 5 different time intervals from 10 min to 24 h, and the deformation rate was found to depend strongly on the time scale. Floes 1 to 3 had a mean deformation rate within the range of 0.06 to 0.07 h– 1 with the interval of 10 min, and 0.03 to 0.04 h– 1 with the interval of 1 h. Floe 4 represented marginal ice zone (MIZ) with very high deformation rate, 0.14/0.08 h– 1 with the interval of 10 min/1 h. Deep in the ice pack, high deformation rates occurred only with high wind and drift speed, while in MIZ they were found also during calm conditions. The deformation rates were found to follow power law scaling with respect to length and time scale even on this small scales and in small domain (15 km × 15 km). The length scale dependence of deformation rate depends on the time scale: the power law scaling exponent β of the whole study period decreases from 0.82 to 0.52 with the time interval increasing from 10 min to 24 h. Ship radar images reveal the importance of the deformation history of the ice pack, since the deformation events were initialized along the lines of previous damages.

Radiometers operating at L-band (1.4 GHz) are used to retrieve sea surface salinity over ice-free oceans and have been used recently to study the cryosphere. One hindrance of their use in the high latitudes is the preponderance of mixed scenes, where seawater and sea ice are both present in the sensor's field of view (FOV). Accurately characterizing the scene is crucial for oceanographic and cryospheric applications. To that end, a sea ice fraction model, composed of passive microwave sea ice concentration retrievals and an instrument simulator that integrates radiative power coming from all around the antenna, is used. We investigate the model currently used operationally to derive the ice fraction affecting the Aquarius observations and show that it can be significantly improved. On the one hand, the current model tends to overestimate sea ice fraction in the marginal ice zone where observations are used for salinity retrievals. On the other hand, the current model underestimates ice fraction within the ice pack where observations are used to derive sea ice properties. For the northern hemisphere, we also find evidence of the sea ice type impact on L-band radiometric observations. We present a model to derive sea ice fractions that are in better agreement with Aquarius radiometric observations using the Advanced Microwave Scanning Radiometer 2 Bootstrap algorithm for sea ice concentration and using high-resolution integration over the sensor's FOV.

A promising means for increasing skill of seasonal predictions of Arctic sea ice is improving sea ice thickness (SIT) initial conditions; however, sparse SIT observations limit this potential. Using the Canadian Climate Model, version 3 (CanCM3), three statistical models designed to estimate SIT fields for initialization in a real-time forecasting system are applied to initialize sea ice hindcasts over 1981–2012. Hindcast skill is assessed relative to two benchmark SIT initialization methods (SIT-IMs): a climatological initialization currently used operationally and SIT values from the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS). Based on several measures of skill, sea ice predictions are generally improved relative to a climatological initialization. The accuracy with which the initialization fields represent both the thinning of the ice pack over time and interannual variability impacts predictive skill for pan-Arctic sea ice area (SIA) and regional sea ice concentration (SIC), with the most robust improvements obtained with SIT-IMs that best represent both processes. Similar skill to that achieved by initializing with PIOMAS, including skillful predictions of detrended September SIA from May, is obtained by initializing with two of the statistical models. Regional skill for September SIC is also enhanced using improved SIT-IMs, with an increase in the spatial coverage of statistically significant skill from 10% to 60%–70% of the appreciably varying ice pack. Reduced skill is seen, however, in the Nordic seas using the improved SIT-IMs, resulting from an inherent cold sea surface temperature bias in CanCM3 that is amplified by a thicker initial ice cover.

Four years of data on for new (nitrate), regenerated (ammonium), and primary (carbon) productivity (2007 through 2010) confirm the elevated productivity associated with the marginal ice zone (MIZ) of the eastern Bering Sea (EBS) in spring. The greatest levels of productivity were associated with ice-melt regions along the western edge of the ice pack. Population seeding and the shallowing of the mixed-layer depth near the ice edge were less important in the development of elevated MIZ productivity than was the amount of ice melt entering surface water, suggesting that ice contributed substances stimulating phytoplankton growth. Based on ice melt as an index of bloom development, primary productivity continued to increase after new productivity peaked. At the MIZ environments with optimal growth conditions, new productivity averaged 18.6 mmol N m−2 d−1, with a ƒ-ratio of 0.61 and primary productivity averaged 492 mmol C m−2 d−1. Although these features were consistently recorded in late April/early May, they varied with the dynamics of ice cover, whose retreat was later in 2008 relative to 2007 and 2009. The intense but localized MIZ blooms appear to be under-sampled in ocean-color imagery. Under ice productivity was generally low (ave. ρNO3=0.45 mmol N m−2 d−1; ave. primary prod.=4.16 mmol C m−2 d−1), although larger values were measured under the western edge of the ice pack and in the St. Lawrence polynya region. The advection of ice and water may contribute to the large values under the western ice edge and the highly transparent new ice may play a role in the polynya. New and primary productivity rates of under-ice samples were significantly inhibited when exposed to ice-free irradiance levels. In situ productivity could be estimated to ±35% from rates measured on-deck by adjusting for the impact of ice on submarine light. The carbon to nitrate uptake ratio was closely related to specific carbon production in the in situ incubations.

Atmospheric data from the Atmospheric Infrared Sounder (AIRS) were used to study an extreme warm and humid air mass transported over the Barents–Kara Seas region by an Arctic cyclone at the end of December 2015. Temperature and humidity in the region was ~10°C (>3σ above the 2003–14 mean) warmer and ~1.4 g kg−1 (>4σ above the 2003–14 mean) wetter than normal during the peak of this event. This anomalous air mass resulted in a large and positive flux of energy into the surface via the residual of the surface energy balance (SEB), compared to the weakly negative SEB from the surface to the atmosphere expected for that time of year. The magnitude of the downwelling longwave radiation during the event was unprecedented compared to all other events detected by AIRS in December/January since 2003. An approximate budget scaling suggests that this anomalous SEB could have resulted in up to 10 cm of ice melt. Thinning of the ice pack in the region was supported by remotely sensed and modeled estimates of ice thickness change. Understanding the impact of this anomalous air mass on a thinner, weakened sea ice state is imperative for understanding future sea ice–atmosphere interactions in a warming Arctic.

Recent observations in the Atlantic sector of the Arctic reveal a sea-ice scape that functions quite differently than earlier assumed. It is also in a state where it responds more quickly to external forcing. Significant thinning of sea ice in this region has resulted in emergence of new features of the ice pack, that in many instances resemble the seasonal ice pack in the Southern Ocean. Thus in some sense an “antarctification” of the sea ice in the Arctic has occurred. This is a consequence of a thinner sea ice cover and a heavy enough snow load that now results in features, such as flooding- the phenomenon not thought to widely occur in the Arctic before. In addition to this, the thinner ice pack is more dynamic resulting in more deformation of the ice pack. These emerging physical properties of the new icescape also impact the functioning of the ice-associated ecosystem.

The behaviour of sea ice on geophysical length scales is considered. Hence, the motion and deformation of a large ice pack consisting of a multitude of interacting ice floes and driven by wind drag and ocean current stresses is investigated. The behaviour of the pack is analysed by treating the ice cover as a two-dimensional continuum of horizontal dimensions of the order of tens to hundreds kilometres, with local properties defined by the ice thickness and the ice area concentration. The equations governing the macroscopic behaviour of the ice pack are solved in the material coordinates by applying two discrete methods: a finite-element method and a smoothed particle hydrodynamics method. The results of numerical simulations, carried out for several constitutive models describing the large-scale rheology of sea ice, are presented to illustrate the evolution of the pack under the action of wind, including variation in the ice thickness and ice concentration.

The vertical diffuse attenuation coefficient for downward plane irradiance ( K d ) is an apparent optical property commonly used in primary production models to propagate incident solar radiation in the water column. In open water, estimating K d is relatively straightforward when a vertical profile of measurements of downward irradiance, E d , is available. In the Arctic, the ice pack is characterized by a complex mosaic composed of sea ice with snow, ridges, melt ponds, and leads. Due to the resulting spatially heterogeneous light field in the top meters of the water column, it is difficult to measure at single-point locations meaningful K d values that allow predicting average irradiance at any depth. The main objective of this work is to propose a new method to estimate average irradiance over large spatially heterogeneous area as it would be seen by drifting phytoplankton. Using both in situ data and 3D Monte Carlo numerical simulations of radiative transfer, we show that (1) the large-area average vertical profile of downward irradiance, E d &macr, ( z ) , under heterogeneous sea ice cover can be represented by a single-term exponential function and (2) the vertical attenuation coefficient for upward radiance ( K L u ), which is up to two times less influenced by a heterogeneous incident light field than K d in the vicinity of a melt pond, can be used as a proxy to estimate E d &macr, ( z ) in the water column.

Melt pond fraction (MPF) on sea ice is an important factor for ice-albedo feedback throughout the Arctic Ocean. We propose an algorithm to estimate MPF using satellite passive microwave data in this study. The brightness temperature (TB) data obtained from the Advanced Microwave Scanning Radiometer-Earth observing system (AMSR-E) were compared to the ship-based MPF in the Beaufort Sea and Canadian Arctic Archipelago. The difference between the TB at horizontal and vertical polarizations of 6.9 and 89.0 GHz (MP06H–89V), respectively, depends on the MPF. The correlation between MP06H–89V and ship-based MPF was higher than that between ship-based MPF and two individual channels (6.9 and 89.0 GHz of horizontal and vertical polarizations, respectively). The MPF determined with the highest resolution channel, 89.0 GHz (5 km × 5 km), provides spatial information with more detail than the 6.9 GHz channel. The algorithm estimates the relative fraction of ice covered by water (1) over areas where sea ice concentration is higher than 95%, (2) during late summer, and (3) in areas with low atmospheric humidity. The MPF estimated from AMSR-E data (AMSR-E MPF) in early summer was underestimated at lower latitudes and overestimated at higher latitudes, compared to the MPF obtained from the Moderate Resolution Image Spectrometer (MODIS MPF). The differences between AMSR-E MPF and MODIS MPF were less than 5% in most the regions and the periods. Our results suggest that the proposal algorithm serves as a basis for building time series of MPF in regions of consolidated ice pack.

The recent precipitous losses of summer Arctic sea ice have outpaced the projections of most climate models. A number of efforts to improve these models have focused in part on a more accurate accounting of sea ice albedo or reflectance. In late spring and summer, the albedo of the ice pack is determined primarily by melt ponds that form on the sea ice surface. The transition of pond configurations from isolated structures to interconnected networks is critical in allowing the lateral flow of melt water toward drainage features such as large brine channels, fractures, and seal holes, which can alter the albedo by removing the melt water. Moreover, highly connected ponds can influence the formation of fractures and leads during ice break-up. Here we develop algorithmic techniques for mapping photographic images of melt ponds onto discrete conductance networks which represent the geometry and connectedness of pond configurations. The effective conductivity of the networks is computed to approximate the ease of lateral flow. We implement an image processing algorithm with mathematical morphology operations to produce a conductance matrix representation of the melt ponds. Basic clustering and edge elimination, using undirected graphs, are then used to map the melt pond connections and reduce the conductance matrix to include only direct connections. The results for images taken during different times of the year are visually inspected and the number of mislabels is used to evaluate performance.

An ice watch, encompassing visual observation of sea ice conducted from the ship's bridge, is typically performed on sea-ice oriented research cruises. Ice watch data collected during a decade, 2006–2015, of annual cruises to the Beaufort Sea and Canadian Basin characterizes sea-ice morphology during mid to late summer. Observations not otherwise available on extensive regional scales with remote sensing are highlighted, including stage of melt, floe size, and surface topography in summer. The summer ice pack in the Canada Basin is found to be of smaller floe size than found in 1973–1975. A disintegrating ice pack of mainly small floe size covered much on the Canada Basin in 2006–2009 and 2011–2012. Since 2007 the ice in the Canada Basin has experienced more extensive melt, and more advanced stages of melt than in 1973–1975, during the Arctic Ice Dynamics Joint Experiment (AIDJEX), and early 1990s. Since 2007, Summer ridge sail heights are lower and ridges less extensive compared to the AIDJEX period.

The diminishing Arctic sea ice pack has been widely studied, but mostly focused on time-mean changes in sea ice rather than on short-term variations that also have important physical and societal consequences. In this study we test the hypothesis that future interannual Arctic sea ice area variability will increase by utilizing a set of 40 independent simulations from the Community Earth System Model's Large Ensemble (CESM-LE) for the 1920–2100 period, and augment this with simulations from 12 models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Both CESM-LE and CMIP5 models project that ice area variability will indeed grow substantially, but not monotonically, in all months, and with a strong seasonal dependence in magnitude and timing that is robust among CESM ensemble members. The variability in every month is inversely correlated with the average ice retreat rate before there is an eventual disappearance in both terms as the ice pack becomes seasonal in summer and autumn by late century. The peak in variability correlates best with the total area of ice between 0.2 m and 0.6 m monthly thickness, indicating that substantial future thinning of the ice pack is required before variability maximizes. Within this range, the most favorable thickness for high areal variability depends on the season, primarily due to whether ice growth or ice retreat processes dominate. Thermodynamic processes are found to be more important than dynamical mechanisms, namely ice export and ridging, in controlling ice area variability.

This paper describes the methods used to operate the underwater robotic vehicle Nereid Under Ice (NUI) beneath the Arctic ice pack during expeditions in 2014 and 2016 and discusses to what extent those methods might be transferable to future robotic missions to our Solar System's ocean worlds. NUI is capable of operating both autonomously and, with the addition of a hair-thin unarmormed fiber optic tether, as a remotely operated vehicle. We operated NUI in both modes during the expeditions. Overlying ice makes operating robotic vehicles on the sea floor challenging because sea ice moves and ice breakers typically cannot hold station with equipment over the side. Operators on board the ship and the vehicle will drift apart during a mission, often by kilometers. This complicates navigation, communication and recovery. NUI's unique tether enables standoff distances of several kilometers while under direct human control. Autonomous operation and recovery operations in case of tether loss rely on a combination of onboard autonomy and acoustic communication. We report the design and operation of NUI's unarmored microtether, the hybrid control methodology that enables operating the vehicle directly or semi-autonomously and handles forced transitions between modes in case of tether loss, and the use of acoustics for communication and navigation. We conclude by discussing what aspects of the technology already developed for under-ice robotic exploration of deep ocean environments and presented here, would be most readily transferable to future NASA missions.

During the N-ICE2015 drift expedition north-west of Svalbard, we observed the establishment and development of algal communities in first-year ice (FYI) ridges and at the snow-ice interface. Despite some indications of being hot spots for biological activity, ridges are under-studied largely because they are complex structures that are difficult to sample. Snow infiltration communities can grow at the snow-ice interface when flooded. They have been commonly observed in the Antarctic, but rarely in the Arctic, where flooding is less common mainly due to a lower snow-to-ice thickness ratio. Combining biomass measurements and algal community analysis with under-ice irradiance and current measurements as well as light modeling, we comprehensively describe these two algal habitats in an Arctic pack ice environment. High biomass accumulation in ridges was facilitated by complex surfaces for algal deposition and attachment, increased light availability, and protection against strong under-ice currents. Notably, specific locations within the ridges were found to host distinct ice algal communities. The pennate diatoms Nitzschia frigida and Navicula species dominated the underside and inclined walls of submerged ice blocks, while the centric diatom Shionodiscus bioculatus dominated the top surfaces of the submerged ice blocks. Higher light levels than those in and below the sea ice, low mesozooplankton grazing, and physical concentration likely contributed to the high algal biomass at the snow-ice interface. These snow infiltration communities were dominated by Phaeocystis pouchetii and chain-forming pelagic diatoms (Fragilariopsis oceanica and Chaetoceros gelidus). Ridges are likely to form more frequently in a thinner and more dynamic ice pack, while the predicted increase in Arctic precipitation in some regions in combination with the thinning Arctic icescape might lead to larger areas of sea ice with negative freeboard and subsequent flooding during the melt season. Therefore, these two habitats are likely to become increasingly important in the new Arctic with implications for carbon export and transfer in the ice-associated ecosystem. Copyright © 2018 Fernández-Méndez, Olsen, Kauko, Meyer, Rösel, Merkouriadi, Mundy, Ehn, Johansson, Wagner, Ervik, Sorrell, Duarte, Wold, Hop and Assmy. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY)

A study of the sea-ice dynamics in the periods of time prior to and during the cycles of basin-wide fragmentation of the ice cover in the Arctic Ocean is presented. The fractal geometry of the ice-sheets limited by leads and ridges was assessed using the satellite images, while the data on the correlated sea-ice motion were obtained in the research stations "North Pole 32" and "North Pole 33" established on the ice pack. The revealed decrease of the fractal dimension as a result of large-scale fragmentation is consistent with the localization of the fracture process (leads propagation). At the same time, the scaling properties of the distribution of amplitudes of ice-fields accelerations were insensitive to the event of sea-ice fragmentation. The temporal distribution of the accelerations was scale-invariant during "quiet" periods of sea-ice drift but disordered in the period of mechanical perturbation. The period of decorrelated (in time) ice-field motion during the important fracture event was interpreted as an inter-level transition in the hierarchic dynamical system. The mechanism of the long-range correlations in the sea-ice cover, including the fracture process, is suggested to be in relation with the self-organized oscillation dynamics inherent in the ice pack.

We present a study of the development of a thermo-erosional notch at the waterline and its influence on calving of Hansbreen, a medium-sized grounded tidewater glacier in southern Svalbard. The study is based on the results of undercut notch melt modelling, based on measurements of sea-water properties, repeated terrestrial laser scans and analysis of time-lapse camera images. There is a strong correlation between observed calving activity and modelled melt rate of the undercut notch. Measured depths of the undercut reach 4 m and vary greatly over time. The calving activity of Hansbreen was significantly lower in 2011 than in 2012, due to the persistent presence of the ice pack in Hornsund fjord, which cooled the sea surface and suppressed the wave action. Calving on Hansbreen is controlled by a local imbalance of forces at the front, due to thermo-erosional undercutting at the sea waterline. Calving activity is therefore sensitive to changes in sea-water temperature and wave height. It may be expected that calving rates will rise with increased advection of warm oceanic water to the Arctic.

Satellite microwave radiometers are widely used to estimate sea ice cover properties (concentration, extent, and area) through the use of sea ice concentration (IC) algorithms. Rare are the algorithms providing associated IC uncertainty estimates. Algorithm uncertainty estimates are needed to assess accurately global and regional trends in IC (and thus extent and area), and to improve sea ice predictions on seasonal to interannual timescales using data assimilation approaches. This paper presents a method to provide relative IC uncertainty estimates using the enhanced NASA Team (NT2) IC algorithm. The proposed approach takes advantage of the NT2 calculations and solely relies on the brightness temperatures (TBs) used as input. NT2 IC and its associated relative uncertainty are obtained for both the Northern and Southern Hemispheres using the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) TB. NT2 IC relative uncertainties estimated on a footprint-by-footprint swath-by-swath basis were averaged daily over each 12.5-km grid cell of the polar stereographic grid. For both hemispheres and throughout the year, the NT2 relative uncertainty is $ 5%. In the Southern Hemisphere, it is low in the interior ice pack, and it increases in the marginal ice zone up to 5%. In the Northern Hemisphere, areas with high uncertainties are also found in the high IC area of the Central Arctic. Retrieval uncertainties are greater in areas corresponding to NT2 ice types associated with deep snow and new ice. Seasonal variations in uncertainty show larger values in summer as a result of melt conditions and greater atmospheric contributions. Our analysis also includes an evaluation of the NT2 algorithm sensitivity to AMSR-E sensor noise. There is a 60% probability that the IC does not change (to within the computed retrieval precision of 1%) due to sensor noise, and the cumulated probability shows that there is a 90% chance that the IC varies by less than $\pm$ 3%. We also examined the daily IC variability, which is dominated by sea ice drift and ice formation/melt. Daily IC variability is the highest, year round, in the MIZ (often up to 20%, locally 30%). The temporal and spatial distributions of the retrieval uncertainties and the daily IC variability is expected to be useful for algorithm intercomparisons, climate trend assessments, and possibly IC assimilation in models.

We present a sensitivity analysis, and discuss the probabilistic forecast capabilities, of the novel sea ice model neXtSIM. The study pertains to the response of the model to the uncertainty on winds using probabilistic forecasts of ice trajectories. neXtSIM is a continuous Lagrangian numerical model, and uses an elasto-brittle rheology to simulate the ice response to external forces. The sensitivity analysis is based on a Monte Carlo sampling of 12 members. The response of the model to the uncertainties is evaluated in terms of simulated ice drift distances from their initial positions, and from the mean position of the ensemble, over the mid-term forecast horizon of 10-days. The simulated ice drift is decomposed into advective and diffusive parts that are characterised separately both spatially and temporally and compared to what is obtained with a free-drift model, that is, when the ice rheology does not play any role on the modelled physics of the ice. The seasonal variability of the model sensitivity is presented, and shows the role of the ice compactness and rheology in the ice drift response at both local and regional scales in Arctic. Indeed, the ice drift simulated by neXtSIM in summer is close to the one obtained with the free-drift model, while the more compact and solid ice pack shows a significantly different mechanical and drift behaviour in winter. For the winter period analysed in this study, we also show that, in contrast to of free-drift model, neXtSIM reproduces the sea ice Lagrangian diffusion regimes as found from observed trajectories. The forecast capability of neXtSIM is also evaluated using a large set of real buoys' trajectories, and compared to the capability of the free-drift model. We found that neXtSIM performs significantly better in simulating sea ice drift, both in terms of forecast error and as a tool to assist search-and-rescue operations, although the sources of uncertainties assumed for the present experiment are not sufficient for a complete coverage of the observed IABP positions.

It is often remarked that Arctic coastal communities are on the frontlines of the impacts related to the rapidly diminishing ice pack. These impacts can have direct effects on communities, such as reduced access to subsistence hunting species, or increased wave height and coastal erosion. There are also indirect effects driven by external socioeconomic systems, such as increased maritime activity, which may provide local economic benefits while increasing potential for disruption to subsistence activities. Here, we use the Historical Sea Ice Atlas (HSIA) dataset to assess the potential direct and indirect impacts from sea ice change for selected Alaska communities. The HSIA provides sea ice concentration for the Bering, Chukchi and Beaufort Seas on a 0.25-degree grid for the period 1953–2013. We estimate the timing of freeze-up and break-up, which is reported by local residents to be of critical importance for subsistence hunting activities and food security. We calculate the open water season length and extend the existing timeseries of the Barnett Severity Index (BSI), which assesses the impact of ice conditions on maritime traffic destined for the Beaufort Sea. We find consistent trends toward later freeze-up and earlier break-up, leading to a lengthened open water period. In Utqiavik (formerly Barrow), there is evidence of a navigational regime change in the 1990s when the pack ice edge started to routinely retreat beyond this most northern community.

International audience; Polar areas show fast changes linked to global warming. The reduction of the ice pack and the melting of the ice sheet modify the conditions of living of marine fauna. We propose the simultaneous monitoring of the ice and benthic fauna using passive acoustics. Thanks to a compact sensor array of 4 hydrophones (2m*2m*2m), we detected, localized and mapped in three dimensions ({azimuth, elevation} or {x, y, z}) the biophonic and geophonic contributions made up of short and wideband pulses. Tridimensional maps of benthic biophony and ice geophony of Antarctic and Arctic 7 days-long recording sessions (2015, 2016) are built and analyzed over a surface of the order of 1 km2. Benthic invertebrates emit high energetic pulses with peak frequencies ranging from 2 to 55 kHz, most of them below 15 kHz. Geophony is structured into two parts. The ice sheet, located several kilometers or tens of kilometers away, creates a stable spatial distribution of low energetic pulses (representing the majority of pulses in the soundscape) modulated by the temporal variability. The movements of isolated icebergs or pack ice produce localized acoustic events identifiable by the high sound levels and the stable peak frequencies of the emitted pulses.

Seven ice mass balance instruments deployed near 83°N on different first-year and second-year ice floes, representing variable snow and ice conditions, documented the evolution of snow and ice conditions in the Arctic Ocean north of Svalbard in January–March 2015. Frequent profiles of temperature and thermal diffusivity proxy were recorded to distinguish changes in snow depth and ice thickness with 2 cm vertical resolution. Four instruments documented flooding and snow-ice formation. Flooding was clearly detectable in the simultaneous changes in thermal diffusivity proxy, increased temperature, and heat propagation through the underlying ice. Slush then progressively transformed into snow-ice. Flooding resulted from two different processes: (i) after storm-induced breakup of snow-loaded floes and (ii) after loss of buoyancy due to basal ice melt. In the case of breakup, when the ice was cold and not permeable, rapid flooding, probably due to lateral intrusion of seawater, led to slush and snow-ice layers at the ocean freezing temperature (−1.88°C). After the storm, the instruments documented basal sea-ice melt over warm Atlantic waters and ocean-to-ice heat flux peaked at up to 400 W m−2. The warm ice was then permeable and flooding was more gradual probably involving vertical intrusion of brines and led to colder slush and snow-ice (−3°C). The N-ICE2015 campaign provided the first documentation of significant flooding and snow-ice formation in the Arctic ice pack as the slush partially refroze. Snow-ice formation may become a more frequently observed process in a thinner ice Arctic.

In this paper we examine the potential of multi-polarization SAR systems to detect and discriminate oil pollution from uncontaminated recently formed thin sea ice in the Arctic Ocean, where both oil and thin sea ice have similar low backscatter returns on SAR imagery. In this study, we present a theoretical model of the relative permittivity of oil-in-sea-ice mixtures and apply it to determine the effect of dielectric properties on the co-polarized backscatter ratio for sea ice, ocean, and oil. To support the theoretical discussion, we investigate available multi-polarization and multi-frequency SAR measurements. We compare SAR data collected over oil spills in seawater in the Gulf of Mexico and the North Sea with available similar data covering sea ice in the Arctic region. The results suggest that multi-polarization SAR systems will be useful to detect Arctic oil spills should a spill occur in new and young sea ice conditions, particularly in the marginal ice zones adjacent to the main polar ice pack.

The sea-ice cover around Antarctica has experienced a slight expansion in area over the past decades1, 2. This small overall increase is the sum of much larger opposing trends in different sectors that have been proposed to result from changes in atmospheric temperature or wind stress3, 4, 5, precipitation6, 7, ocean temperature8, and atmosphere or ocean feedbacks9, 10. However, climate models have failed to reproduce the overall increase in sea ice11. Here we present a data set of satellite-tracked sea-ice motion for the period of 1992–2010 that reveals large and statistically significant trends in Antarctic ice drift, which, in most sectors, can be linked to local winds. We quantify dynamic and thermodynamic processes in the internal ice pack and show that wind-driven changes in ice advection are the dominant driver of ice-concentration trends around much of West Antarctica, whereas wind-driven thermodynamic changes dominate elsewhere. The ice-drift trends also imply large changes in the surface stress that drives the Antarctic ocean gyres, and in the fluxes of heat and salt responsible for the production of Antarctic bottom and intermediate waters.

The “polar data gap” is a region around the North Pole where satellite orbit inclination and instrument swath for SMMR and SSM/I-SSMIS satellites preclude retrieval of sea ice concentrations. Data providers make the irregularly shaped data gap round by centering a circular “pole hole mask” over the North Pole. The area within the pole hole mask has conventionally been assumed to be ice-covered for the purpose of sea ice extent calculations, but recent conditions around the perimeter of the mask indicate that this assumption may already be invalid. Here we propose an objective, partial differential equation based model for estimating sea ice concentrations within the area of the pole hole mask. 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 mask. To test the model, we examined composite annual cycles of observation-model agreement for three circular regions adjacent to the pole hole mask. The composite annual cycle of observation-model correlation ranged from approximately 0.6 to 0.7, and sea ice concentration mean absolute deviations were of order 10 − 2 or smaller. The model thus provides a computationally simple approach to solving the increasingly important problem of how to fill the polar data gap. Moreover, 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 potentially be more accurate than the Laplace equation version. Such generalizations and potential validation opportunities are discussed.

Variation of ice/ocean drag (momentum exchange) is an important yet often overlooked aspect of pack ice modeling. It is commonly parameterized as proportional to the square of the velocity difference between the ice and the undisturbed ocean, often with a constant angle offset to account for rotational effects in the ice–ocean boundary layer. This approach is critiqued in light of extensive observations that have revealed the underlying turbulence scales governing momentum exchange within the IOBL. Fluid dynamical similarity implied by these scales provides a framework for addressing several factors that affect the drag relationship, including variation in ice roughness, relative drift speed, buoyancy flux at the ice/ocean interface, and stratification in the upper ocean. These are examined and discussed in light of recent changes in the Arctic ice pack. The drag law is formulated in terms of dimensionless surface velocity, which in its simplest form is called Rossby similarity, and accounts explicitly for variation in undersurface hydraulic roughness, z 0 . A generalization that includes interfacial buoyancy flux is also described and illustrated, and the impact of near surface ocean stratification is discussed. Estimates of z 0 based on underice measurements vary widely; by a combination of observations and simple IOBL modeling, an attempt is made to reduce these to a manageable set associated with distinct ice types.

The fracture-induced oscillations in sea ice were detected by seismographs and seismic tiltmeters established on the Arctic ice pack. Field observations were supplemented with a laboratory experiment. The energy distributions in elastic waves generated during: (i) large-scale ice pack fragmentation over area of about 105 km2, (ii) local crack propagation in ice floe, and (iii) laboratory ice crashing were constructed and analyzed using principles of the Tsallis statistics. The energy release regimes at different stages of fracturing were characterized by the parameter of nonextensivity q. In terms of the non-extensive statistical mechanics, q > 1 evidences the correlated (non-extensive) dynamics of the process in nonequilibrium system, q = 1 responds to the additivity of events occurring in equilibrium system, and q < 1 takes place when the energy release is additive and limited by an upper cut-off. All these scenarios were revealed in fracture processes occurring at three hierarchic levels. The variation of the q-value demonstrates high thermodynamic changeability of the fracture process driven by irregular external source. The role of energy conservation in fracturing sea ice is discussed in connection with the observed reversible transitions between extensive and non-extensive modes of fracture.

The ice floe speed variations were monitored at the research camp North Pole 35 established on the Arctic ice pack in 2008. A three-month time series of measured speed values was used for determining changes in the kinetic energy of the drifting ice floe. The constructed energy distributions were analyzed by methods of nonextensive statistical mechanics based on the Tsallis statistics for open nonequilibrium systems, such as tectonic formations and drifting sea ice. The nonextensivity means the nonadditivity of externally induced energy changes in multicomponent systems due to dynamic interrelation of components having no structural links. The Tsallis formalism gives one an opportunity to assess the correlation between ice floe motions through a specific parameter, the so-called parameter of nonextensivity. This formalistic assessment of the actual state of drifting pack allows one to forecast some important trends in sea ice behavior, because the level of correlated dynamics determines conditions for extended mechanical perturbations in ice pack. In this work, we revealed temporal fluctuations of the parameter of nonextensivity and observed its maximum value before a large-scale sea ice fragmentation (faulting) of consolidated sea ice. The correlation was not detected in fragmented sea ice where long-range interactions are weakened.

In 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 discrete-element model of sea ice is used to study how a 90˚ change in wind direction alters the pattern of faults generated through mechanical failure of the ice. the sea-ice domain is 400 km in size and consists of polygonal floes obtained through a Voronoi tessellation. Initially the floes are frozen together through viscous–elastic joints that can break under sufficient compressive, tensile and shear deformation. A constant wind-stress gradient is applied until the initially frozen ice pack is broken into roughly diamond-shaped aggregates, with crack angles determined by wing-crack formation. Then partial refreezing of the cracks delineating the aggregates is modelled through reduction of their length by a particular fraction, the ice pack deformation is neglected and the wind stress is rotated by 90˚. New cracks form, delineating aggregates with a different orientation. Our results show the new crack orientation depends on the refrozen fraction of the initial faults: as this fraction increases, the new cracks gradually rotate to the new wind direction, reaching 90˚ for fully refrozen faults. Such reorientation is determined by a competition between new cracks forming at a preferential angle determined by the wing-crack theory and at old cracks oriented at a less favourable angle but having higher stresses due to shorter contacts across the joints.

Newly obtained data on the critical dynamics of the drifting/fracturing sea ice in the Arctic Ocean were analyzed and compared with published data on the dynamic processes in the Earth’s crust. Substantial similarities were found in the scaling behavior of both geophysical systems; the most important of them is the b -value space/time variability including a pre-failure drop of this parameter. The b -value pattern of the ensemble of drifting ice floes is an analogue of the b -value distribution over areas and depths in tectonic structures. A common feature of the pre-failure state in the cryosphere and in the Earth’s crust is the increased degree of the energy conservation that manifests itself both in the sea ice consolidation prior to basin-wide ice pack fragmentations, and in involving harder geological formations in the fracture process before earthquakes, respectively. From the viewpoint of the conservative SOC concept, this relation between the system’s conservativity and the occurrence of large-scale fracture events means that the expected scale level of failure is determined by the system’s closeness to “true” SOC behavior.

The motion of an individual ice floe in the Arctic Ocean was monitored at the Russian research station North Pole 35 established on the ice pack in 2008. The ice floe speed (V) was found to be correlated with wind speed (v) in main features, such as the positions of maxima and minima of V and v. However, the fine structure of the V-variation cannot be explained by the wind forcing alone. There were periods of time when the floe drift was affected by the interactions of ice floes between each other or by the periodical forcing due to either the Coriolis inertia effect or the tidal activity. These data were compared with the "waiting times" statistics that are the distributions of time intervals between subsequent, sufficiently strong changes in the kinetic energy of drifting ice floe. These distributions were measured in several time windows differing in the average wind speed and wind direction, and/or in the mechanical state of the ice pack. The distribution functions N (t>τ), where N is the number of successive events of energy change separated by the time interval t that exceeds τ, constructed in different time windows demonstrate fractal or a multifractal nature of the time series during motion in the consolidated ice pack but were truly random when the ice floe drifted in the highly fragmented sea ice. The latter result shows the existence of a relationship between the long-range mechanical interactions in the pack and long-term memory (time scaling behaviour) of the sea-ice motion.

New technological developments in animal-borne satellite-tracking devices in combi- nation with increased access to satellite-based environmental data are creating new possibilities for studying movement patterns and habitat selection by animals in remote, logistically challenging environments. In the present study, we report the first year-round data on movement patterns of wal- ruses in the High Arctic, including at-sea positions. Using first-passage times (FPT) to study habitat use and quantifying habitat selection using mixed-effects Cox proportional hazards models, we dis- pelled the conventional perception that seasonal movement patterns of Atlantic walruses are simply a result of them following the retraction and expansion of annually formed sea ice. Walruses in this study (n = 17 males) actively moved into areas of high ice concentration (>90%) during winter; travelling far into the ice pack, as far as 600 km from ice-free water. Additionally, high inter-annual, seasonal site fidelity was documented. Seasonal differences in habitat use patterns were also observed. In summer, when walruses feed intensively, FPTs were affected by water depth and distance to the coast (R 2 = 0.571), but these variables had no effect on walrus habitat use in winter. Sea ice concentration was the most important environmental condition during the winter season (R 2 = 0.162), though there are clearly other factors influencing where individuals occur in winter that are currently unaccounted for in these analyses. The male walruses in this study did not do much benthic diving during winter, suggesting that they did not feed often during the time that they are known to breed. Instead, they remained in areas with high ice coverage, far from their coastal summering areas, spending much of their time hauled out or in surface waters.

Marine ice melting topic is a repetitive phenomenon in alarmist speeches on climate change. The present positive evolution of air temperatures has in all probability many impacts on the environment and more or less directly on societies. Face to the temperature elevation, the ice pack is undergone to an important temporal variability of ice growth and melting. Human populations can be exposed to meteorological and ice hazards engendering a societal risk. The purpose of this paper is to better understand how ICT get integrated into the risk question through the example of the Bay of Bothnia in the northern extremity of the Baltic Sea. The study deals with the way that Finnish society, advanced in the ICT field, faces to new technology use in risk prevention and accident management on sea ice.