Andrew Richard Mahoney

We present a new 27‐year record of landfast sea ice extent in northern Alaska and adjacent waters, which uses ice chart data to extend a previous analysis based on synthetic aperture radar (SAR) imagery. This new climatology provides updated information on the decline of landfast ice in a region of the Arctic that has seen extensive losses of sea ice in recent summers. By comparing our results with early satellite data analysis from the 1970s, we find that trends in the timing of landfast ice have been ongoing for at least 50 years. Over the period 1996–2023, the landfast season shortened by 19 days/decade in the Chukchi Sea and 13 days/decade in the Beaufort Sea, primarily due to later formation of landfast ice. Also, the time between onset of freezing air temperatures and landfast ice formation is increasing, which is consistent with a coastal ocean that takes longer to freeze. While it was previously reported that the typical annual maximum width of landfast ice in the Chukchi Sea declined by 13 km between periods 1970–1976 and 1996–2008, we find this retreat has slowed with a decline of 3.3 km over the course of our data set as few areas of extensive landfast remain to be lost. Conversely, landfast sea ice extent in the Beaufort Sea had previously been found to have remained constant since the 1970s, but we find an average reduction of 2.5 km. We attribute this emergent phenomenon to a reduction in the number grounded ridges forming offshore.

We present a new 27-year record of landfast sea ice extent in northern Alaska and adjacent waters, which uses ice chart data to extend a previous analysis based on synthetic aperture radar (SAR) imagery. This new climatology provides updated information on the decline of landfast ice in a region of the Arctic that has seen extensive losses of sea ice in recent summers. By comparing our results with early satellite data analysis from the 1970s, we find that trends in the timing of landfast ice have been ongoing for at least 50 years. Over the period 1996-2023, the landfast season shortened by 19 days/decade in the Chukchi Sea and 13 days/decade in the Beaufort Sea, primarily due to later formation of landfast ice. Also, the time between onset of freezing air temperatures and landfast ice formation is increasing, which is consistent with a coastal ocean that takes longer to freeze. While it was previously reported that the typical annual maximum width of landfast ice in the Chukchi Sea declined by 13 km between periods 1970-76 and 1996-2008, we find this retreat has slowed with a decline of 3.3 km over the course of our dataset as few areas of extensive landfast remain to be lost. Conversely, landfast sea ice extent in the Beaufort Sea had previously been found to have remained constant since the 1970s, but we find an average reduction of 2.5 km. We attribute this emergent phenomenon to a reduction in the number grounded ridges forming offshore.

Assessing the trafficability of Arctic sea ice is vital for Arctic communities, researchers, and operational users who depend on over-ice mobility. While synthetic aperture radar (SAR)-based methods have shown promise for evaluating sea ice roughness, they are limited in resolving surface conditions influenced by snow. In this study, we explore the potential of high-resolution optical satellite imagery for characterizing sea ice surface roughness and estimating trafficability through texture analysis. Using the Grey-Level Co-occurrence Matrix (GLCM) method, we calculate texture measures (contrast, homogeneity, and energy) from optical imagery over landfast sea ice near Utqiaġvik, Alaska. Parameter sensitivity tests across multiple window sizes, orientations, and displacements inform optimal settings for extracting meaningful spatial texture metrics. The texture measures are compared against snowmachine travel speed data collected during field surveys near Utqiaġvik, Alaska. Our results show that GLCM-derived contrast metrics strongly correlate with observed travel speeds. Based on these correlations, we generate speed maps and apply an optimal pathfinding algorithm to identify efficient travel corridors across the ice. This remote sensing–driven approach enables fast, scalable assessments of sea ice trafficability that incorporate snow-related surface complexity. By linking texture measures from high-resolution optical satellite imagery to in situ travel velocity data, we demonstrate a transferable methodology for sea ice condition assessment at spatial scales relevant to both local and regional applications. This framework supports community travel planning and remote logistics and is increasingly valuable with the growing availability of high-resolution, high-temporal-frequency optical imagery across polar environments.

Stress–strain relationships are fundamental to understanding deformation mechanics in any material. In sea ice, stress–strain relationships are typically observed by measuring the strain resulting from known stress in samples wholly or partially isolated from the surrounding ice. Such observations show sea ice behaves elastically at short timescales, and the effective parameters describing this elastic behavior vary with temperature, salinity, and strain rate. However, these experiments often employ larger strain rates than are typical for intact, in situ ice, are labor intensive, and are typically limited to meter scale. Here we utilize a novel synthesis of existing observation techniques to quantify the effective elastic modulus and Poisson's ratio of a km‐scale area of heterogeneous, drifting sea ice surrounding the Sea Ice Dynamics Experiment (SIDEx) drifting ice camp in the Beaufort Sea. In‐ice point measurements of two‐dimensional horizontal stress from an array of 31 vibrating wire stress gauges (VWSG), distributed over a ∼1.5 km radius area, allow us to observe natural forcing conditions. A ground‐based interferometric radar provides contemporaneous one‐dimensional surface strain measurements collocated with stress within 22.5 m resolution cells. We find an effective elastic modulus of 2.4 0.6 GPa and effective Poisson's ratio of 0.5 0.2 describe the heterogeneous, mixed multi‐ and first‐year ice within the area of the VWSG array. These values are broadly consistent with prior laboratory and field experiments while offering a novel point of reference for real‐world sea ice deformation behavior under natural conditions.

We conduct observations of sea ice thermal strain using a laser theodolite in situ (0.3–1 km distances) and InSAR remote sensing (1–22 km). We capture the thermal strain relationship of sea ice at geophysical scales never before measured. Net strain was, unexpectedly, observable only in cooling First Year Ice below −11°C and found to be dependent on cumulative, as opposed to net, temperature decrease. Prior work, at smaller scales, shows other behaviors. Analysis in the context of prior work and theory indicates multiple processes driving sea ice thermal strain. Strain is a combination of (a) solid ice matrix expansion/contraction, (b) expansion/contraction due to brine inclusion phase changes, (c) apparent mass exchange of brine from non‐enclaved inclusions, (d) apparent internal void formation, and (e) internal stress state. We hypothesize that differential thermal strain in First Year and Multi‐Year Ice contributes to changing ice strength and deformation rates observed in the Arctic.

Observing continuous strain in sea ice at geophysical scales of tens of meters to kilometers requires displacement measurements made with millimeter-scale precision. Satellite-based interferometric synthetic aperture radar (InSAR) provides such precise measurements of relative surface displacement over broad spatial areas at regular intervals and, unlike point displacement measurements, it allows confident delineation of continuously deforming regions. However, InSAR only captures the 1-D component of surface displacement parallel to a radar's lines-of-sight. Additional analysis is required to translate between these 1-D observations and the horizontal or vertical displacements they arose from. Previous studies utilize an iterative inverse model to constrain estimates of horizontal surface displacement from InSAR. Here we build upon that work outlining a new analytical inverse modeling method for quantifying displacement and strain over continuous regions of sea ice and provide comparison between model results and independent displacement observations. We demonstrate the inverse method over both landfast and drifting ice along the Alaskan coastline. These intercomparisons highlight environments in which displacements inverted from interferograms may be used as an independent estimator of surface strain, as well as the potential for the outlined inverse methods to be used in conjunction with other observing methods.

From April through June in 2019 and 2022, we monitored snow melt at three sites near Utqiaġvik, Alaska. Along 200‐m lines we measured snow depth, density, stratigraphy, snow‐covered area, and spectral albedo. Site 1 (ARM) was sloped tundra drained by water tracks. Site 2 (BEO) was flat polygonal tundra. Site 3 (ICE) was on undeformed landfast sea ice. All three sites were within a 6 km radius. Despite similar pre‐melt snow distributions and weather, the melt progression differed markedly between sites. In 2019, by mid‐melt, there was 40% less snow‐covered area at ARM versus ICE, and 34% less snow‐covered area at ARM versus BEO. The 2022 melt started 2 weeks later than in 2019 and was rapid, so smaller differences in snow‐covered areas developed. In both years meltout dates varied by up to 25 days between sites, and more than 20 days within sites, with melt rates at locations only meters apart differing by up to a factor of seven. This melt diachroneity led to highly heterogeneous meltout patterns at all three sites. Our measurements and observations indicate that, in addition to reductions in snow reflective properties and wind‐driven heat advection, the fate of meltwater plays a key role in producing melt diachroneity. We identify seven snow‐water mechanisms that can enhance or inhibit melt rates, all largely controlled by the local topography and the nature of the substrate. These mechanisms are important because the most rapid changes in albedo coincide with the peak of water‐snow melt interactions.

Antarctic landfast sea ice (fast ice) is stationary sea ice that is attached to the coast, grounded icebergs, ice shelves, or other protrusions on the continental shelf. Fast ice forms in narrow (generally up to 200 km wide) bands, and ranges in thickness from centimeters to tens of meters. In most regions, it forms in autumn, persists through the winter and melts in spring/summer, but can remain throughout the summer in particular locations, becoming multi‐year ice. Despite its relatively limited extent (comprising between about 4% and 13% of overall sea ice), its presence, variability and seasonality are drivers of a wide range of physical, biological and biogeochemical processes, with both local and far‐ranging ramifications for the Earth system. Antarctic fast ice has, until quite recently, been overlooked in studies, likely due to insufficient knowledge of its distribution, leading to its reputation as a “missing piece of the Antarctic puzzle.” This review presents a synthesis of current knowledge of the physical, biogeochemical and biological aspects of fast ice, based on the sub‐domains of: fast ice growth, properties and seasonality; remote‐sensing and distribution; interactions with the atmosphere and the ocean; biogeochemical interactions; its role in primary production; and fast ice as a habitat for grazers. Finally, we consider the potential state of Antarctic fast ice at the end of the 21st Century, underpinned by Coupled Model Intercomparison Project model projections. This review also gives recommendations for targeted future work to increase our understanding of this critically‐important element of the global cryosphere.

In polar regions, sea ice is a crucial mediator of the interaction between earth’s atmosphere and oceans. Its formation and breakup is intimately connected with local weather patterns and larger-scale climatic processes. During the spring melt and breakup period, snow-covered ice transitions to open water in a matter of weeks. This has a profound impact on the use of sea ice in coastal Arctic regions by Indigenous People, where activities such as hunting and fishing are central to community livelihood. In order to investigate the physical phenomena at the heart of this process, a set of targeted, intensive observations were made over Spring sea ice melt and breakup in Kotzebue Sound, Alaska. This program is part of the Ikaaġvik Sikukun project, a collaborative effort in which an Indigenous Elder advisory council from Kotzebue and scientists participated in co-production of hypotheses and observational research, including a stronger understanding of the physical properties of sea ice during spring melt. Data were collected using high-endurance, fixed-wing uncrewed aerial vehicles (UAVs) containing custom-built scientific payloads. Here we present the results of these measurements. Repeated flights over the measurement period captured the early stages of the transition from a white, snow-covered state to a broken up, bare/blue-green state. We found that the reflectivity of a surface type depends on the size and shape of the features which constitute it. Specifically, large bare blue-green ice features were found to be least reflective, while large snowy/white ice features were found to be most reflective.