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Over the past decade, Antarctic sea ice extent exhibited a sequence of record maxima, followed by a rapid decline in 2015/16, and record minima since. In this presentation, we show that this sudden and remarkable ice loss marks an abrupt transition from a high to a low ice state that cannot be explained by year-to-year variability. Instead, it is most likely associated with a longer term variability arising from ice–ocean feedbacks. The abrupt transition was preceded by a multi-decadal increase in persistence and variance of the sea ice anomalies, an increasing upper Southern Ocean density stratification, and an accumulation of heat at the subsurface; suggesting a decoupling of the surface from the subsurface ocean. During this period, the sea ice anomalies shifted from being structured predominantly regionally and seasonally to a largely circumpolar and interannual regime. In 2015/16, the upper ocean density stratification in the ice-covered region suddenly weakened, leading to a release of heat from the subsurface, contributing to the sea ice decline during winter. Our analysis suggests that the sudden sea ice loss in 2015/16, and the persisting low ice conditions since, arose from a systematic change in the physical state of the coupled circumpolar ice–ocean system. This change will have wide implications for global climate, ecosystems, and the Antarctic Ice Sheet.

Climate observations inform about the past and present state of the climate system. They underpin climate science, feed into policies for adaptation and mitigation, and increase awareness of the impacts of climate change. The Global Climate Observing System (GCOS), a body of the World Meteorological Organization (WMO), assesses the maturity of the required observing system and gives guidance for its development. The Essential Climate Variables (ECVs) are central to GCOS, and the global community must monitor them with the highest standards in the form of Climate Data Records (CDR). Today, a single ECV—the sea ice ECV—encapsulates all aspects of the sea ice environment. In the early 1990s it was a single variable (sea ice concentration) but is today an umbrella for four variables (adding thickness, edge/extent, and drift). In this contribution, we argue that GCOS should from now on consider a set of seven ECVs (sea ice concentration, thickness, snow depth, surface temperature, surface albedo, age, and drift). These seven ECVs are critical and cost effective to monitor with existing satellite Earth observation capability. We advise against placing these new variables under the umbrella of the single sea ice ECV. To start a set of distinct ECVs is indeed critical to avoid adding to the suboptimal situation we experience today and to reconcile the sea ice variables with the practice in other ECV domains.

Snow cover is a primary control on Antarctic sea ice mass balance as it controls basal ice growth and snow ice formation. It is also a primary control on the surface energy budget, partitioning of solar radiation, and sea ice biological communities. Finally, knowledge of its distribution is critical for accurate estimation of sea ice thickness from satellite altimeters. The floe-scale distribution of snow is highly variable, driven by wind redistribution over complex sea ice surface topography. Yet, our understanding of the seasonal evolution of snow depth distribution is poor and its representation in models is simple or non-existent.We present observations of the three-dimensional distribution of snow depth, ice thickness, and surface topography from a suite of cruises in the Weddell, Bellingshausen, Ross, and East Antarctic Seas that span the full growth season – from autumn, through winter, to late spring. The distribution of snow depth changes from a right-skewed distribution in autumn as snow initially accumulates around ridges to a gaussian by spring as snow deepens and ice surface topography roughens. While the distribution is spatially complex, the spectral distribution of snow features is similar across seasons. Using these data we construct a simple statistical model for the seasonal evolution of floe-scale snow depth distribution. We also compare our results to prior observations from drilling transects and larger-scale airborne observations from NASA’s Operation IceBridge. For the latter we use a convolutional neural network to demonstrate that the surface topography can be used as a reliable predictor of the snow depth distribution at regional scales.

This work presents the results of physical and biological investigations at 27 biogeochemical stations of early winter sea ice in the Ross Sea during the 2017 PIPERS cruise. Only two similar cruises occurred in the past, in 1995 and 1998. The year 2017 was a specific year, in that ice growth in the Central Ross Sea was considerably delayed, compared to previous years. These conditions resulted in lower ice thicknesses and Chl- a burdens, as compared to those observed during the previous cruises. It also resulted in a different structure of the sympagic algal community, unusually dominated by Phaeocystis rather than diatoms. Compared to autumn-winter sea ice in the Weddell Sea (AWECS cruise), the 2017 Ross Sea pack ice displayed similar thickness distribution, but much lower snow cover and therefore nearly no flooding conditions. It is shown that contrasted dynamics of autumnal-winter sea-ice growth between the Weddell Sea and the Ross Sea impacted the development of the sympagic community. Mean/median ice Chl- a concentrations were 3–5 times lower at PIPERS, and the community status there appeared to be more mature (decaying?), based on Phaeopigments/Chl- a ratios. These contrasts are discussed in the light of temporal and spatial differences between the two cruises., info:eu-repo/semantics/published

The surface flooding of Antarctic sea ice in summer covers 50% or more of the sea-ice area in the major summer ice packs, the western Weddell and the Bellingshausen-Amundsen Seas. Two CRREL ice mass-balance buoys were deployed on the Amundsen Sea pack in late December 2010 from the icebreaker Oden, bridging the summer period (January–February 2011). Temperature records from thermistors embedded vertically in the snow and ice showed progressive increases in the depth of the flooded layer (up to 0.3–0.35 m) on the ice cover during January and February. While the snow depth was relatively unchanged from accumulation (

Satellites have documented variability in sea ice areal extent for decades, but there are significant challenges in obtaining analogous measurements for sea ice thickness data in the Antarctic, primarily due to difficulties in estimating snow cover on sea ice. Sea ice thickness (SIT) can be estimated from snow freeboard measurements, such as those from airborne/satellite lidar, by assuming some snow depth distribution or empirically fitting with limited data from drilled transects from various field studies. Current estimates for large-scale Antarctic SIT have errors as high as ∼50 %, and simple statistical models of small-scale mean thickness have similarly high errors. Averaging measurements over hundreds of meters can improve the model fits to existing data, though these results do not necessarily generalize to other floes. At present, we do not have algorithms that accurately estimate SIT at high resolutions. We use a convolutional neural network with laser altimetry profiles of sea ice surfaces at 0.2 m resolution to show that it is possible to estimate SIT at 20 m resolution with better accuracy and generalization than current methods (mean relative errors ∼15 %). Moreover, the neural network does not require specification of snow depth or density, which increases its potential applications to other lidar datasets. The learned features appear to correspond to basic morphological features, and these features appear to be common to other floes with the same climatology. This suggests that there is a relationship between the surface morphology and the ice thickness. The model has a mean relative error of 20 % when applied to a new floe from the region and season. This method may be extended to lower-resolution, larger-footprint data such as such as Operation IceBridge, and it suggests a possible avenue to reduce errors in satellite estimates of Antarctic SIT from ICESat-2 over current methods, especially at smaller scales.

Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research-Oceans 123(12), (2018): 8887-8901, doi:10.1029/2018JC013797.

In cold polar waters, temperatures sometimes drop below the freezing point, a process referred to as supercooling. However, observational challenges in polar regions limit our understanding of the spatial and temporal extent of this phenomenon. We here provide observational evidence that supercooled waters are much more widespread in the seasonally ice-covered Southern Ocean than previously reported. In 5.8% of all analyzed hydrographic profiles south of 55° S, we find temperatures below the surface freezing point (‘potential’ supercooling), and half of these have temperatures below the local freezing point (‘in-situ’ supercooling). Their occurrence doubles when neglecting measurement uncertainties. We attribute deep coastal-ocean supercooling to melting of Antarctic ice shelves, and surface-induced supercooling in the seasonal sea-ice region to winter-time sea-ice formation. The latter supercooling type can extend down to the permanent pycnocline due to convective sinking plumes—an important mechanism for vertical tracer transport and water-mass structure in the polar ocean.

This paper reviews the scientific motivation and challenges, development, and use of underwater robotic vehicles designed for use in ice-covered waters, with special attention paid to the navigation systems employed for under-ice deployments. Scientific needs for routine access under fixed and moving ice by underwater robotic vehicles are reviewed in the contexts of geology and geophysics, biology, sea ice and climate, ice shelves, and seafloor mapping. The challenges of under-ice vehicle design and navigation are summarized. The paper reviews all known under-ice robotic vehicles and their associated navigation systems, categorizing them by vehicle type (tethered, untethered, hybrid, and glider) and by the type of ice they were designed for (fixed glacial or sea ice and moving sea ice). © 2020 by the authors.

Understanding the distribution of snow depth on Antarctic sea ice is critical to estimating the sea ice thickness distribution from laser altimetry data, such as from Operation IceBridge or ICESat-2. One major uncertainty in converting laser altimetry data to ice thickness is knowing the proportion of snow within the surface measurement. Snow redistributed by wind collects around areas of deformed ice, but it is not known how different surface morphologies affect this distribution. Here, we apply a textural segmentation algorithm to classify and group similar textures to infer the distribution of snow-ice ratios using snow surface freeboard measurements from Operation IceBridge (OIB) campaigns over the Weddell Sea. We find that texturally-similar regions have similar snow/ice ratios, but not similar snow depth measurements. This allows for the extrapolation of nadir-looking snow radar data using two-dimensional surface altimetry scans, providing a two-dimensional estimate of the snow depth. Using a convolutional neural network on an in-situ dataset, we find that local (~20 m) snow depth and sea ice thickness can be estimated with errors of < 20%, and that the learned convolutional filters imply that different surface morphologies have different proportions of snow/ice within the measured surface elevation. For the OIB data, we show that at slightly larger scales (~180 m), snow depths can be estimated using the snow surface texture, and that the learned filters are comparable to standard textural segmentation filters. We also examine the statistical variability in the distribution of snow/ice ratios across different years to determine if snow distribution patterns on sea ice exhibit universal behaviour, or have significant interannual variations. These results suggest that surface morphological information can improve remotely-sensed estimates of snow depth, and hence sea ice thickness, compared to current methods. Such methods may be useful for reducing errors in Antarctic sea ice thickness estimates from ICESat-2.

Accurate measurements of sea ice thickness are critical to better understand climate change, to provide situational awareness in ice-covered waters, and to reduce risks for communities that rely on sea ice. Nonetheless, remotely measuring the thickness of sea ice is difficult. The only regularly employed technique that accurately measures the full ice thickness involves drilling a hole through the ice. Other presently used methods are either embedded in or through the ice (e.g., ice mass balance buoys) or calculate thickness from indirect measurements (e.g., ice freeboard from altimetry; ice draft using sonars; total snow and ice thickness using electromagnetic techniques). Acoustic techniques, however, may provide an alternative approach to measure the total ice thickness. Here laboratory-grown sea ice thicknesses, estimated by inverting the time delay between echoes from the water-ice and ice-air interfaces, are compared to those measured using ice cores. A time-domain model capturing the dominant scattering mechanisms is developed to explore the viability of broadband acoustic techniques for measuring sea ice thickness, to compare with experimental measurements, and to investigate optimal frequencies for in situ applications. This approach decouples ice thickness estimates from water column properties and does not preclude ice draft measurements using the same data.

Observations of waves, winds, turbulence, and the geometry and circulation of windrows were made in a shallow bay in the winter of 2018 outside of Rimouski, Québec. Water velocities measured from a forward-looking pulse-coherent ADCP mounted on a small zodiac show spanwise (cross-windrow) convergence, streamwise (downwind) velocity enhancement, and downwelling in the windrows, consistent with the view that windrows are the result of counterrotating pairs of wind-aligned vortices. The spacing of windrows, measured with acoustic backscatter and with surface imagery, was measured to be approximately twice the water depth, which suggests an aspect ratio of 1. The magnitude and vertical distribution of turbulence measured from the ADCP are consistent with a previous scaling and observations of near-surface turbulence under breaking waves, with dissipation rates larger and decaying faster vertically than what is expected from a shear-driven boundary layer. Measurements of dissipation rate are partitioned to within, and outside of the windrow convergence zones, and measurements inside the convergence zones are found to be nearly an order of magnitude larger than those outside with similar vertical structure. A ratio of time scales suggests that turbulence likely dissipates before it can be advected horizontally into convergences, but the advection of wave energy into convergences may elevate the surface flux of TKE and could explain the elevated turbulence in the windrows. These results add to a limited number of conflicting observations of turbulence variability due to windrows, which may modify gas flux, and heat and momentum transport in the surface boundary layer.

The Ross Sea is known for showing the greatest sea-ice increase, as observed globally, particularly from 1979 to 2015. However, corresponding changes in sea-ice thickness and production in the Ross Sea are not known, nor how these changes have impacted water masses, carbon fluxes, biogeochemical processes and availability of micronutrients. The PIPERS project sought to address these questions during an autumn ship campaign in 2017 and two spring airborne campaigns in 2016 and 2017. PIPERS used a multidisciplinary approach of manned and autonomous platforms to study the coupled air/ice/ocean/biogeochemical interactions during autumn and related those to spring conditions. Unexpectedly, the Ross Sea experienced record low sea ice in spring 2016 and autumn 2017. The delayed ice advance in 2017 contributed to (1) increased ice production and export in coastal polynyas, (2) thinner snow and ice cover in the central pack, (3) lower sea-ice Chl-a burdens and differences in sympagic communities, (4) sustained ocean heat flux delaying ice thickening and (5) a melting, anomalously southward ice edge persisting into winter. Despite these impacts, airborne observations in spring 2017 suggest that winter ice production over the continental shelf was likely not anomalous., SCOPUS: ar.j, info:eu-repo/semantics/published

(2017-147) In 2014, researchers from ten organizations came to the U.S. Army Corps of Engineers, Cold Regions Research and Engineering Laboratory (CRREL) in New Hampshire to conduct a first of its kind large-scale experiment aimed at determining current sensor capabilities for detecting oil in and under sea ice. This project was the second phase of the Oil Spill Detection in Low Visibility and Ice research project of the International Association of Oil and Gas Producers (IOGP), Arctic Oil Spill Response Technology - Joint Industry Programme. The objectives of the project were to:Acquire acoustic, thermal, optical and radar signatures of oil on, within, and underneath a level sheet of laboratory sea ice.Determine the capabilities of various sensors to detect oil in specific ice environments created in a test tank, including freeze-up, growth and melt.Model the potential performance of the sensors under realistic field conditions using the test data for validation.Recommend the most effective sensor suite of existing sensors for detecting oil in the ice environment. The sensor testing spanned a two-month ice growth phase and a one-month decay/melt period. The growth phase produced an 80 centimeter thick level sheet of salt water ice representative of natural sea ice grown under quiescent conditions. Above-ice sensors included frequency modulated continuous wave radar, ground penetrating radar, laser fluorescence polarization sensor, spectral radiometer, visible and infrared cameras. Below-ice sensors included acoustics (broadband, narrowband, and multibeam sonars), spectral radiometers, cameras, and fluorescence polarization. Measurements of physical and electrical properties of the ice and oil within the ice were provided to optical, acoustic, and radar modelers as inputs into their models. The models were then used to extrapolate the sensors’ laboratory performance to potential performance over a range of field conditions. All selected sensors detected oil under some conditions. The radar systems were the only above-ice sensors capable of detecting oil below or trapped within the ice. Cameras below the ice detected oil at all stages of ice growth, and the acoustic and fluorescence systems detected encapsulated oil through limited amounts of new ice growth beneath the oil. No single sensor detected oil in and below ice under all conditions tested. However, we used the test results to identify suites of sensors that could be deployed today both above and below the ice to detect and map an oil spill within ice covered waters.

Snow distribution over sea ice is an important control on sea ice physical and biological processes. We combine measurements of the atmospheric boundary layer and blowing snow on an Antarctic sea ice floe with terrestrial laser scanning to characterize a typical storm and its influence on the spatial patterns of snow distribution at resolutions of 1-10 cm over an area of 100 m x 100 m. The pre-storm surface exhibits multi-directional elongated snow dunes formed behind aerodynamic obstacles. Newly deposited dunes are elongated parallel to the predominant wind direction during the storm. Snow erosion and deposition occur over 62% and 38% of the area, respectively. Snow deposition volume is more than twice that of erosion (351 m3 vs. 158 m3), resulting in a modest increase of 2 +/- 1 cm in mean snow depth, indicating a small net mass gain despite large mass relocation. Despite significant local snow depth changes due to deposition and erosion, the statistical distributions of elevation and the two-dimensional correlation functions remain similar to those of the pre-storm surface. Pre- and post-storm surfaces also exhibit spectral power-law relationships with little change in spectral exponents. These observations suggest that for sea ice floes with mature snow cover features under conditions similar to those observed in this study, spatial statistics and scaling properties of snow surface morphology may be relatively invariant. Such an observation, if confirmed for other ice types and conditions, may be a useful tool for model parameterizations of the sub-grid variability of sea ice surfaces.

Satellites have documented variability in sea ice areal extent for decades, but there are significant challenges in obtaining analogous measurements for sea ice thickness data in the Antarctic, primarily due to difficulties in estimating snow cover on sea ice. Sea ice thickness can be estimated from surface elevation measurements, such as those from airborne/satellite LiDAR, by assuming some snow depth distribution or empirically fitting with limited data from drilled transects from various field studies. Current estimates for large-scale Antarctic sea ice thickness have errors as high as ~ 50 %, and simple statistical models of small-scale mean thickness have similarly high errors. Averaging measurements over hundreds of meters can improve the model fits to existing data, though these results do not necessarily generalize to other floes. At present, we do not have algorithms that accurately estimate sea ice thickness at high resolutions. We use a convolutional neural network with laser altimetry profiles of sea ice surfaces at 0.2 m resolution to show that it is possible to estimate sea ice thickness at 20 m resolution with better accuracy and generalization than current methods (mean relative errors ~ 15 %). Moreover, the neural network does not require specifying snow depth/density, which increases its potential applications to other LiDAR datasets. The learned features appear to correspond to basic morphological features, and these features appear to be common to other floes with the same climatology. This suggests that there is a relationship between the surface morphology and the ice thickness. The model has a mean relative error of 20 % when applied to a new floe from the region and season, which is much lower than the mean relative error for a linear fit (errors up to 47 %). This method may be extended to lower-resolution, larger-footprint data such as such as IceBridge, and suggests a possible avenue to reduce errors in satellite estimates of Antarctic sea ice thickness from ICESat-2 over current methods, especially at smaller scale.

Since 2010 the SeaBED-class Autonomous Underwater Vehicles (AUVs) have advanced the 3D mapping of sea ice draft in both polar regions, revealing a new richness of thickness and morphology data previously hidden from traditional observation methods. The limiting factor for the complete 3D characterisation of sea ice has been the reduced area of surface measurements from TLS (100 x 100m) relative to the AUV survey (500 x 500m). Accordingly, we developed a low-cost fixed wing Unmanned Aerial System (UAS) to conduct photogrammetric surveys for Digital Elevation Model construction of the sea ice surface at the same time as the AUV missions were completed below. Here we detail this UAS system and discuss how this methodology can be improved and potentially evolve to medium-range (10 km) 'Beyond Visual Line of Sight' transect-based missions with the next generation of longer range AUVs.

A comprehensive set of autonomous, ice-ocean measurements were collected across the Canada Basin to study the summer evolution of the ice-ocean boundary layer (IOBL) and ocean mixed layer (OML). Evaluation of local heat and freshwater balances and associated turbulent forcing reveals that melt ponds (MPs) strongly influence the summer IOBL-OML evolution. Areal expansion of MPs in mid-June start the upper ocean evolution resulting in significant increases to ocean absorbed radiative flux (19 W m−2 in this study). Buoyancy provided by MP drainage shoals and freshens the IOBL resulting in a 39 MJ m−2 increase in heat storage in just 19 days (52% of the summer total). Following MP drainage, a near-surface fresh layer deepens through shear-forced mixing to form the summer mixed layer (sML). In late summer, basal melt increases due to stronger turbulent mixing in the thin sML and the expansion of open water areas due in part to wind-forced divergence of the sea ice. Thermal heterogeneities in the marginal ice zone (MIZ) upper ocean led to large ocean-to-ice heat fluxes (100–200 W m−2) and enhanced basal ice melt (3–6 cm d−1), well away from the ice edge. Calculation of the upper ocean heat budget shows that local radiative heat input accounted for at least 89% of the observed latent heat losses and heat storage (partitioned 0.77/0.23). These results suggest that the extensive area of deteriorating sea ice observed away from the ice edge during the 2014 season, termed the “thermodynamically forced MIZ,” was driven primarily by local shortwave radiative forcing.

Arctic sea ice has declined precipitously in both extent and thickness over the past four decades; by contrast, Antarctic sea ice has shown little overall change, but this masks large regional variability. Climate models have not captured these changes. But these differences do not represent a paradox. The processes governing, and impacts of, natural variability and human-induced changes differ markedly at the poles largely because of the ways in which differences in geography control the properties of and interactions among the atmosphere, ice, and ocean. The impact of natural variability on the ice cover is large at both poles, so modeled ice trends are not entirely inconsistent with contributions from both natural variability and anthropogenic forcing. Despite this concurrence, the coupling of natural climate variability, climate feedbacks, and sea ice is not well understood, and significant biases remain in model representations of the ice cover and the processes that drive it.

Remote sensing of Antarctic sea ice is required to characterize properties of the vast sea ice cover to understand its long-term increase in contrast to the decrease of Arctic sea ice. For this objective, the OIB/TanDEM-X Coordinated Science Campaign (OTASC) was successfully conducted in 2017 to obtain contemporaneous and collocated remote sensing data from NASA's Operation IceBridge (OIB) and the German Aerospace Center (DLR) TanDEM-X Synthetic Aperture Radar (SAR) system at X band together with Sentinel-1 and RADARSAT-2 SARs at C band in conjunction with WorldView satellite spectral sensors, surface measurements, and field observations. The Weddell Sea and the Ross Sea were two primary regions while SAR data were also collected over six other regions in the Southern Ocean. Satellite SAR data included both polarimetric and interferometric capabilities to infer snow and sea ice information in three dimensions (3D), while OIB/P-3 aircraft data include snow radar together with altimeter data for snow and sea ice observations in 3D over the Weddell Sea. Across the Ross Sea, IcePOD and AntNZ/York-University flights were carried out together with satellite SAR data acquisitions.

The article of record as published may be found at https://doi.org/10.1002/2018JC013766 A large collaborative program has studied the coupled air‐ice‐ocean‐wave processes occurring in the Arctic during the autumn ice advance. The program included a field campaign in the western Arctic during the autumn of 2015, with in situ data collection and both aerial and satellite remote sensing. Many of the analyses have focused on using and improving forecast models. Summarizing and synthesizing the results from a series of separate papers, the overall view is of an Arctic shifting to a more seasonal system. The dramatic increase in open water extent and duration in the autumn means that large surface waves and significant surface heat fluxes are now common. When refreezing finally does occur, it is a highly variable process in space and time. Wind and wave events drive episodic advances and retreats of the ice edge, with associated variations in sea ice formation types (e.g., pancakes, nilas). This variability becomes imprinted on the winter ice cover, which in turn affects the melt season the following year. This program was supported by the Office of Naval Research, Code 32, under Program Managers Scott Harper and Martin Jeffries. The crew of R/V Sikuliaq provide outstanding support in collecting the field data, and the US National Ice Center, German Aerospace Center (DLR), and European Space Agency facilitated the remote sensing collections and daily analysis products. RADARSAT‐2 Data and Products are from MacDonald, Dettwiler, and Associates Ltd., courtesy of the U.S. National Ice Center. Data, supporting information, and a cruise report can be found at http://www.apl.uw.edu/arcticseastate

Traditional measures for detecting oil spills in the open-ocean are both difficult to apply and less effective in ice-covered seas. In view of the increasing levels of commercial activity in the Arctic, there is a growing gap between the potential need to respond to an oil spill in Arctic ice-covered waters and the capability to do so. In particular, there is no robust operational capability to remotely locate oil spilt under or encapsulated within sea ice. To date, most research approaches the problem from on or above the sea ice, and thus they suffer from the need to ‘see’ through the ice and overlying snow. Here we present results from a large-scale tank experiment which demonstrate the detection of oil beneath sea ice, and the quantification of the oil layer thickness is achievable through the combined use of an upward-looking camera and sonar deployed in the water column below a covering of sea ice. This approach using acoustic and visible measurements from below is simple and effective, and potentially transformative with respect to the operational response to oil spills in the Arctic marine environment. These results open up a new direction of research into oil detection in ice-covered seas, as well as describing a new and important role for underwater vehicles as platforms for oil-detecting sensors under Arctic sea ice.

Satellites have documented trends in Antarctic sea-ice extent and its variability for decades, but estimating sea-ice thickness in the Antarctic from remote sensing data remains challenging. In situ observations needed for validation of remote sensing data and sea-ice models are limited; most have been restricted to a few point measurements on selected ice floes, or to visual shipboard estimates. Here we present three-dimensional (3D) floe-scale maps of sea-ice draft for ten floes, compiled from two springtime expeditions by an autonomous underwater vehicle to the near-coastal regions of the Weddell, Bellingshausen, and Wilkes Land sectors of Antarctica. Mean drafts range from 1.4 to 5.5 m, with maxima up to 16 m. We also find that, on average, 76% of the ice volume is deformed ice. Our surveys indicate that the floes are much thicker and more deformed than reported by most drilling and ship-based measurements of Antarctic sea ice. We suggest that thick ice in the near-coastal and interior pack may be under-represented in existing in situ assessments of Antarctic sea ice and hence, on average, Antarctic sea ice may be thicker than previously thought.

The article of record as published may be found at http://dx.doi.org/10.1525/elementa.241/ The interplay between sea ice concentration, sea ice roughness, ocean stratification, and momentum transfer to the ice and ocean is subject to seasonal and decadal variations that are crucial to understanding the present and future air-ice-ocean system in the Arctic. In this study, continuous observations in the Canada Basin from March through December 2014 were used to investigate spatial differences and temporal changes in under-ice roughness and momentum transfer as the ice cover evolved seasonally. Observations of wind, ice, and ocean properties from four clusters of drifting instrument systems were complemented by direct drill-hole measurements and instrumented overhead flights by NASA operation IceBridge in March, as well as satellite remote sensing imagery about the instrument clusters. Spatially, directly estimated ice-ocean drag coefficients varied by a factor of three with rougher ice associated with smaller multi-year ice floe sizes embedded within the first-year-ice/multi-year-ice conglomerate. Temporal differences in the ice-ocean drag coefficient of 20�30% were observed prior to the mixed layer shoaling in summer and were associated with ice concentrations falling below 100%. The ice-ocean drag coefficient parameterization was found to be invalid in September with low ice concentrations and small ice floe sizes. Maximum momentum transfer to the ice occurred for moderate ice concentrations, and transfer to the ocean for the lowest ice concentrations and shallowest stratification. Wind work and ocean work on the ice were the dominant terms in the kinetic energy budget of the ice throughout the melt season, consistent with free drift conditions. Overall, ice topography, ice concentration, and the shallow summer mixed layer all influenced mixed layer currents and the transfer of momentum within the air-ice-ocean system. The observed changes in momentum transfer show that care must be taken to determine appropriate parameterizations of momentum transfer, and imply that the future Arctic system could become increasingly seasonal. Office of Naval Research The deployment of the ITP-Vs and the subsequent analysis effort was supported by the Office of Naval Research under grants N00014-12-10140 and N00014-12-10799.

An array of novel directional wavebuoys was designed and deployed into the Beaufort Sea ice cover in March 2014, as part of the Office of Naval Research Marginal Ice Zone experiment. The buoys were designed to drift with the ice throughout the year and monitor the expected breakup and retreat of the ice cover, forced by waves travelling into the ice from open water. Buoys were deployed from fast-and-light air-supported ice camps, based out of Sachs Harbour on Canada’s Banks Island, and drifted westwards with the sea ice over the course of spring, summer and autumn, as the ice melted, broke up and finally re-froze. The buoys transmitted heave, roll and pitch timeseries at 1 Hz sample frequency over the course of up to eight months, surviving both convergent ice dynamics and significant waves-in-ice events. Twelve of the 19 buoys survived until their batteries were finally exhausted during freeze-up in late October/November. Ice impact was found to have contaminated a significant proportion of the Kalman-filter-derived heave records, and these bad records were removed with reference to raw x/y/z accelerations. The quality of magnetometer-derived buoy headings at the very high magnetic field inclinations close to the magnetic pole was found to be generally acceptable, except in the case of four buoys which had probably suffered rough handling during transport to the ice. In general, these new buoys performed as expected, though vigilance as to the veracity of the output is required.

Autonomous underwater vehicles (AUVs) are rapidly becoming the platform of choice for mapping the underside of sea ice, as well as for geological and biological oceanographic measurements in the Arctic and Antarctic.

We examine the snow radar data from the Weddell and Bellingshausen Seas acquired by eight IceBridge (OIB) flightlines in October of 2010 and 2011. In snow depth retrieval, the sidelobes from the stronger scattering snow-ice (s-i) interfaces could be misidentified as returns from the weaker air-snow (a-s) interfaces. In this paper, we first introduce a retrieval procedure that accounts for the structure of the radar system impulse response followed by a survey of the snow depths in the Weddell and Bellingshausen Seas. Limitations and potential biases in our approach are discussed. Differences between snow depth estimates from a repeat survey of one Weddell Sea track separated by 12 days, without accounting for variability due to ice motion, is −0.7 ± 13.6 cm. Average snow depth is thicker in coastal northwestern Weddell and thins toward Cape Norvegia, a decrease of >30 cm. In the Bellingshausen, the thickest snow is found nearshore in both Octobers and is thickest next to the Abbot Ice Shelf. Snow depth is linearly related to freeboard when freeboards are low but diverge as the freeboard increases especially in the thicker/rougher ice of the western Weddell. We find correlations of 0.71–0.84 between snow depth and surface roughness suggesting preferential accumulation over deformed ice. Retrievals also seem to be related to radar backscatter through surface roughness. Snow depths reported here, generally higher than those from in situ records, suggest dissimilarities in sample populations. Implications of these differences on Antarctic sea ice thickness are discussed.

In ice-covered seas, traditional air-side oil spill detection methods face practical challenges. Conversely, under-ice remote sensing techniques are increasingly viable due to improving operational capabilities of autonomous and remotely operated vehicles. To investigate the potential for under-ice detection of oil spills using active acoustics, laboratory measurements of high-frequency, broadband backscatter (75–590 kHz) from crude oil layers (0.7–8.1 cm) under and encapsulated within sea ice were performed at normal and 20° incidence angles. Discrete interfaces (water-oil, oil-ice, and ice-oil) are identifiable in observations following oil injections under the ice and during the subsequent encapsulation. A one-dimensional model for the total normal incidence backscatter from oil under ice, constrained by oil sound speed measurements from −10 °C to 20 °C and improved environmental measurements compared to previous studies, agrees well with pre-encapsulation observations. At 20° incidence angles echoes from the ice and oil under ice are more complex and spatially variable than normal incidence observations, most likely due to interface roughness and volume inhomogeneities. Encapsulated oil layers are only detected at normal incidence. The results suggest that high-frequency, broadband backscatter techniques may allow under-ice remote sensing for the detection and quantification of oil spills.

The article of record as published may be found at http://dx.doi.org/10.1016/j.ocemod.2016.02.009 The sea state of the Beaufort and Chukchi seas is controlled by the wind forcing and the amount of ice-free water available to generate surface waves. Clear trends in the annual duration of the open water season and in the extent of the seasonal sea ice minimum suggest that the sea state should be increasing independent of changes in the wind forcing. Wave model hindcasts from four selected years spanning recent conditions are consistent with this expectation. In particular, larger waves are more common in years with less summer sea ice and/or a longer open water season, and peak wave periods are generally longer. The increase in wave energy may affect both the coastal zones and the remaining summer ice pack, as well as delay the autumn ice-edge advance. However, trends in the amount of wave energy impinging on the ice-edge are inconclusive, and the associated processes, especially in the autumn period of new ice formation, have yet to be well-described by in situ observations. There is an implicit trend and evidence for increasing wave energy along the coast of northern Alaska, and this coastal signal is corroborated by satellite altimeter estimates of wave energy.

As climate change reshapes the Earth's polar regions, scientists turn to drone-mounted cameras to measure sea ice. One expedition found out that flying drones near Antarctica isn't easy.

Over 1979–2007 near-surface air temperatures on the maritime western side of the Antarctic Peninsula have increased throughout the year, with the greatest monthly temperature rise of 1.7 °C dec−1 occurring in July as recorded at Faraday/Vernadsky (F/V) station (65.4°S, 64.4°W). The warming trend in this month has been the result of a loss of very cold days at the station with the average number of days with mean temperature below − 15 °C decreasing from 7 during 1979–1988 to 0.6 over 1998–2007. There is a high anti-correlation between temperatures at F/V and the extent of sea ice in July just to the west of the station. Passive microwave satellite imagery reveals that monthly ice concentrations here have decreased by up to 25% since the late 1970s creating a polynya-like feature along the west coast of the peninsula. Sea ice extent over the southern Bellingshausen Sea has decreased markedly during the late summer and early autumn so that there has been a lengthening of the ice-free season. Yet faster ice advance in June as a result of changes in the meridional component of the wind means that the overall ice extent in the Bellingshausen Sea in July (offshore of the F/V region) has not changed significantly. Years of extensive sea ice can occur as frequently now as in the earlier part of the record, but a combination of the changing nature of the ice advance and subtle shifts in the wind direction have led to the more frequent occurrence of the ice-free area to the west of F/V in recent years. There are also indications of pre-conditioning of the ice/ocean system to the west of F/V well before winter that is associated with the presence or absence of the ice anomaly that is observed in July.

The 2007 International Polar Year (IPY) in the Antarctic was distinguished by strong regional and seasonal ice-atmosphere-ocean anomalies associated with an overall weakening of the prevailing westerly circulation. Here we assess the ice-atmosphere-ocean conditions leading up to and during two IPY field campaigns that took place in early spring (September-October): the U.S.-led Sea Ice Mass Balance Antarctica (SIMBA, 68-72°S, 90-95°W) and the Australian-led Sea Ice Physics and Ecosystems eXperiment (SIPEX, 63-67°S, 115-130°E). Our regional analysis is presented within the context of circumpolar and inter-annual variability relevant to other IPY Antarctic studies. Using satellite-derived and numerically analyzed surface and atmospheric variables, we examine relationships between (i) winds and sea-ice concentration and drift, (ii) sea-surface temperature and ice-edge anomalies, and (iii) precipitation and snow accumulation. Though Antarctic-averaged sea-ice extent in September 2007 was the second highest observed for 1979-2007, the SIMBA and SIPEX studies sampled the two regions showing the largest negative sea-ice anomalies in the Southern Ocean. Maps of sea-surface temperature (SST) and sea-ice concentration (SIC) anomalies revealed distinct regional patterns, showing warm SST/low SIC in the greater SIMBA (including all of the Bellingshausen and Amundsen seas) and western SIPEX regions, versus cool SST/high SIC in the Weddell, Ross and eastern SIPEX regions. In the SIMBA and western SIPEX regions, warm northerly winds in May (overlying the warm SSTs) brought anomalously high precipitation to those regions, but due to the regional delays in sea-ice advance (by up to 2 months), most fell on open ocean, which in turn contributed to negative and near-zero September snow depth anomalies in those two regions, respectively. During autumn (March to May), warm SSTs offshore of those regions extended from mid-to-high latitudes, resulting from meridional advection of heat associated with a wave-3 atmospheric circulation pattern. In the SIMBA and SIPEX regions, the late sea-ice advance followed unusually long ice-free summer periods, which suggests that solar ocean warming was relatively high in those regions. The warm ocean conditions may help to explain why the ice edge remained well south of its mean position despite instances during winter of cold southerly winds and northward sea-ice drift. Finally, with respect to the 1978-2008 record, year 2007 was a continuation of decreasing sea ice in the SIMBA region (e.g., decreased annual sea-ice extent and ice season duration), whereas in the SIPEX region, year 2007 was a negative departure from an otherwise slightly positive trend in annual sea-ice extent and ice season duration. © 2010 Elsevier Ltd.