Arctic sea ice is becoming a more seasonal phenomenon as a direct result of global warming. Across the Arctic, the refreezing of the ocean surface each autumn now occurs a full month later than it did just 40 years ago. In the western Arctic (Canada Basin), the delay is related to an increase in the seasonal heat stored in surface waters; cooling to the freezing point requires more heat loss to the atmosphere in autumn. In the marginal ice zone, the cooling and freezing process is mediated by ocean mixing and by the presence of remnant sea ice, which may precondition the ocean surface for refreezing. The delay in refreezing has many impacts, including increased open ocean exposure to autumn storms, additional wave energy incident to Arctic coasts, shifts in animal migration patterns, and extension of the time window for transit by commercial ships along the Northern Sea Route. This article reviews the observed trends in the western Arctic and the processes responsible for these trends, and provides brief in situ observations from the Beaufort Sea that illustrate some of these processes.

The retreat of Arctic sea ice is enabling increased ocean wave activity at the sea ice edge, yet the interactions between surface waves and sea ice are not fully understood. Here, we examine in situ observations of wave spectra spanning 2012–2021 in the western Arctic marginal ice zone (MIZ). Swells exceeding 30 cm are rarely observed beyond 100 km inside the MIZ. However, local wind waves are observed in patches of open water amid partial ice cover during the summer. These local waves remain fetch-limited between ice floes with heights less than 1 m. To investigate these waves at climate scales, we conduct experiments varying wave attenuation and generation in ice with a global model including coupled interactions between waves and sea ice. A weak high-frequency attenuation rate is required to simulate the local waves in observations. The choices of attenuation scheme and wind input in ice have a remarkable impact on the extent of wave activity across ice-covered oceans, particularly in the Antarctic. As well as demonstrating the need for stronger constraints on wave attenuation, our results suggest that further attention should be directed towards locally generated wind waves and their role in sea ice evolution.

The magnitude, spectral composition, and variability of the Arctic sea ice surface albedo are key to understanding and numerically simulating Earth’s shortwave energy budget. Spectral and broadband albedos of Arctic sea ice were spatially and temporally sampled by on-ice observers along individual survey lines throughout the sunlit season (April–September, 2020) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The seasonal evolution of albedo for the MOSAiC year was constructed from spatially averaged broadband albedo values for each line. Specific locations were identified as representative of individual ice surface types, including accumulated dry snow, melting snow, bare and melting ice, melting and refreezing ponded ice, and sediment-laden ice. The area-averaged seasonal progression of total albedo recorded during MOSAiC showed remarkable similarity to that recorded 22 years prior on multiyear sea ice during the Surface Heat Budget of the Arctic Ocean (SHEBA) expedition. In accord with these and other previous field efforts, the spectral albedo of relatively thick, snow-free, melting sea ice shows invariance across location, decade, and ice type. In particular, the albedo of snow-free, melting seasonal ice was indistinguishable from that of snow-free, melting second-year ice, suggesting that the highly scattering surface layer that forms on sea ice during the summer is robust and stabilizing. In contrast, the albedo of ponded ice was observed to be highly variable at visible wavelengths. Notable temporal changes in albedo were documented during melt and freeze onset, formation and deepening of melt ponds, and during melt evolution of sediment-laden ice. While model simulations show considerable agreement with the observed seasonal albedo progression, disparities suggest the need to improve how the albedo of both ponded ice and thin, melting ice are simulated.

During the Arctic melt season, relatively fresh meltwater layers can accumulate under sea ice as a result of snow and ice melt, far from terrestrial freshwater inputs. Such under-ice meltwater layers, sometimes referred to as under-ice melt ponds, have been suggested to play a role in the summer sea ice mass balance both by isolating the sea ice from saltier water below, and by driving formation of 'false bottoms' below the sea ice. Such layers form at the interface of the fresher under-ice layer and the colder, saltier seawater below. During the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) expedition in the Central Arctic, we observed the presence of under-ice meltwater layers and false bottoms throughout July 2020 at primarily first-year ice locations. Here, we examine the distribution, prevalence, and drivers of under-ice ponds and the resulting false bottoms during this period. The average thickness of observed false bottoms and freshwater equivalent of under-ice meltwater layers was 0.08 m, with false bottom ice comprised of 74–87% FYI melt and 13–26% snow melt. Additionally, we explore these results using a 1D model to understand the role of dynamic influences on decoupling the ice from the seawater below. The model comparison suggests that the ice-ocean friction velocity was likely exceptionally low, with implications for air-ice-ocean momentum transfer. Overall, the prevalence of false bottoms was similar to or higher than noted during other observational campaigns, indicating that these features may in fact be common in the Arctic during the melt season. These results have implications for the broader ice-ocean system, as under-ice meltwater layers and false bottoms provide a source of ice growth during the melt season, potentially reduce fluxes between the ice and the ocean, isolate sea ice primary producers from pelagic nutrient sources, and may alter light transmission to the ocean below.

The ocean surface boundary layer is a gateway of energy transfer into the ocean. Wind-driven shear and meteorologically forced convection inject turbulent kinetic energy into the surface boundary layer, mixing the upper ocean and transforming its density structure. In the absence of direct observations or the capability to resolve sub-grid scale 3D turbulence in operational ocean models, the oceanography community relies on surface boundary layer similarity scalings (BLS) of shear and convective turbulence to represent this mixing. Despite their importance, near-surface mixing processes (and ubiquitous BLS representations of these processes) have been under-sampled in high energy forcing regimes such as the Southern Ocean. With the maturing of autonomous sampling platforms, there is now an opportunity to collect high-resolution spatial and temporal measurements in the full range of forcing conditions. Here, we characterize near-surface turbulence under strong wind forcing using the first long-duration glider microstructure survey of the Southern Ocean. We leverage these data to show that the measured turbulence is significantly higher than standard shear-convective BLS in the shallower parts of the surface boundary layer and lower than standard shear-convective BLS in the deeper parts of the surface boundary layer; the latter of which is not easily explained by present wave-effect literature. Consistent with the CBLAST (Coupled Boundary Layers and Air Sea Transfer) low winds experiment, this bias has the largest magnitude and spread in shallowest 10% of the actively mixing layer under low-wind and breaking wave conditions, when relatively low levels of turbulent kinetic energy (TKE) in surface regime are easily biased by wave events.

Accurate multidecadal radiative flux records are vital to understand Arctic amplification and constrain climate model uncertainties. Uncertainty in the NASA Clouds and the Earth's Radiant Energy System (CERES)-derived irradiances is larger over sea ice than any other surface type and comes from several sources. The year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic provides a rare opportunity to explore uncertainty in CERES-derived radiative fluxes. First, a systematic and statistically robust assessment of surface shortwave and longwave fluxes was conducted using in situ measurements from MOSAiC flux stations. The CERES Synoptic 1degree (SYN1deg) product overestimates the downwelling shortwave flux by +11.40 Wm^-2 and underestimates the upwelling shortwave flux by –15.70 Wm^-2 and downwelling longwave fluxes by –12.58 Wm^-2 at the surface during summer. In addition, large differences are found in the upwelling longwave flux when the surface approaches the melting point (approximately 0°C). The biases in downwelling shortwave and longwave fluxes suggest that the atmosphere represented in CERES is too optically thin. The large negative bias in upwelling shortwave flux can be attributed in large part to lower surface albedo (–0.15) in satellite footprint relative to surface sensors. Additionally, the results show that the spectral surface albedo used in SYN1deg overestimates albedo in visible and mid-infrared bands. A series of radiative transfer model perturbation experiments are performed to quantify the factors contributing to the differences. The CERES-MOSAiC broadband albedo differences (approximately 20 Wm^-2) explain a larger portion of the upwelling shortwave flux difference than the spectral albedo shape differences (approximately 3 Wm^-2). In addition, the differences between perturbation experiments using hourly and monthly MOSAiC surface albedo suggest that approximately 25% of the sea ice surface albedo variability is explained by factors not correlated with daily sea ice concentration variability. Biases in net shortwave and longwave flux can be reduced to less than half by adjusting both albedo and cloud inputs toward observed values. The results indicate that improvements in the surface albedo and cloud data would substantially reduce the uncertainty in the Arctic surface radiation budget derived from CERES data products.

The "surface scattering layer" (SSL) is the highly-scattering, coarse-grained ice layer that forms on the surface of melting, drained sea ice during spring and summer. Ice of sufficient thickness with an SSL has an observed persistent broadband albedo of ~0.65, resulting in a strong influence on the regional solar partitioning. Experiments during the Multidisciplinary drifting Observatory for the Study of the Arctic Climate expedition showed that the SSL re-forms in approximately 1 day following manual removal. Coincident spectral albedo measurements provide insight into the SSL evolution, where albedo increased on sunny days with higher solar insolation. Comparison with experiments in radiative transfer and global climate models show that the sea ice albedo is greatly impacted by the SSL thickness. The presence of SSL is a significant component of the ice-albedo feedback, with an albedo impact of the same order as melt ponds. Changes in SSL and implications for Arctic sea ice within a warming climate are uncertain.

Melt ponds on sea ice play an important role in the Arctic climate system. Their presence alters the partitioning of solar radiation: decreasing reflection, increasing absorption and transmission to the ice and ocean, and enhancing melt. The spatiotemporal properties of melt ponds thus modify ice albedo feedbacks and the mass balance of Arctic sea ice. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition presented a valuable opportunity to investigate the seasonal evolution of melt ponds through a rich array of atmosphere-ice-ocean measurements across spatial and temporal scales. In this study, we characterize the seasonal behavior and variability in the snow, surface scattering layer, and melt ponds from spring melt to autumn freeze-up using in situ surveys and auxiliary observations. We compare the results to satellite retrievals and output from two models: the Community Earth System Model (CESM2) and the Marginal Ice Zone Modeling and Assimilation System (MIZMAS). During the melt season, the maximum pond coverage and depth were 21% and 22 ± 13 cm, respectively, with distribution and depth corresponding to surface roughness and ice thickness. Compared to observations, both models overestimate melt pond coverage in summer, with maximum values of approximately 41% (MIZMAS) and 51% (CESM2). This overestimation has important implications for accurately simulating albedo feedbacks. During the observed freeze-up, weather events, including rain on snow, caused high-frequency variability in snow depth, while pond coverage and depth remained relatively constant until continuous freezing ensued. Both models accurately simulate the abrupt cessation of melt ponds during freeze-up, but the dates of freeze-up differ. MIZMAS accurately simulates the observed date of freeze-up, while CESM2 simulates freeze-up one-to-two weeks earlier. This work demonstrates areas that warrant future observation-model synthesis for improving the representation of sea-ice processes and properties, which can aid accurate simulations of albedo feedbacks in a warming climate.

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice.

The melting of sea ice floes from the edges (lateral melting) results in open-water formation and subsequently increases absorption of solar shortwave energy. However, lateral melt plays a small role in the sea ice mass budget in both hemispheres in most climate models. This is likely influenced by the simple parameterization of lateral melting in sea ice models that are constrained by limited observations. Here we use a coupled climate model (CESM2.0) to assess the sensitivity of modeled sea ice state to the lateral melt parameterization in preindustrial and 2xCO₂ runs. The runs explore the implications of how lateral melting is parameterized and structural changes in how it is applied. The results show that sea ice is sensitive both to the parameters determining the effective lateral melt rate and the nuances in how lateral melting is applied to the ice pack. Increasing the lateral melt rate is largely compensated for by decreases in the basal melt rate but still results in a significant decrease in sea ice concentration and thickness, particularly in the marginal ice zone. Our analysis suggests that this is tied to the increased efficiency of lateral melting at forming open water during the summer melt season, which drives the majority of the ice-albedo feedback. The more seasonal Southern Hemisphere ice cover undergoes larger relative reductions in sea ice concentration and thickness for the same relative increase in lateral melt rate, likely due to the hemispheric differences in the role of the sea-ice-upper-ocean coupling. Additionally, increasing the lateral melt rate under a 2xCO₂ forcing, where sea ice is thinner, results in a smaller relative change in sea ice mean state but suggests that open-water-formation feedbacks are likely to steepen the decline to ice-free summer conditions. Overall, melt processes are more efficient at forming open water in thinner ice scenarios (as we are likely to see in the future), suggesting the importance of accurately representing thermodynamic evolution. Revisiting model parameterizations of lateral melting with observations will require finding new ways to represent salient physical processes.

We assess the influence of snow on sea ice in experiments using the Community Earth System Model version 2 for a preindustrial and a 2xCO2 climate state. In the preindustrial climate, we find that increasing simulated snow accumulation on sea ice results in thicker sea ice and a cooler climate in both hemispheres. The sea ice mass budget response differs fundamentally between the two hemispheres. In the Arctic, increasing snow results in a decrease in both congelation sea ice growth and surface sea ice melt due to the snow's impact on conductive heat transfer and albedo, respectively. These factors dominate in regions of perennial ice but have a smaller influence in seasonal ice areas. Overall, the mass budget changes lead to a reduced amplitude in the annual cycle of ice thickness. In the Antarctic, with increasing snow, ice growth increases due to snow–ice formation and is balanced by larger basal ice melt, which primarily occurs in regions of seasonal ice. In a warmer 2xCO2 climate, the Arctic sea ice sensitivity to snow depth is small and reduced relative to that of the preindustrial climate. In contrast, in the Antarctic, the sensitivity to snow on sea ice in the 2xCO2 climate is qualitatively similar to the sensitivity in the preindustrial climate. These results underscore the importance of accurately representing snow accumulation on sea ice in coupled Earth system models due to its impact on a number of competing processes and feedbacks that affect the melt and growth of sea ice.

Unprecedented quantities of heat are entering the Pacific sector of the Arctic Ocean through Bering Strait, particularly during summer months. Though some heat is lost to the atmosphere during autumn cooling, a significant fraction of the incoming warm, salty water subducts (dives beneath) below a cooler fresher layer of near-surface water, subsequently extending hundreds of kilometers into the Beaufort Gyre. Upward turbulent mixing of these sub-surface pockets of heat is likely accelerating sea ice melt in the region. This Pacific-origin water brings both heat and unique biogeochemical properties, contributing to a changing Arctic ecosystem. However, our ability to understand or forecast the role of this incoming water mass has been hampered by lack of understanding of the physical processes controlling subduction and evolution of this this warm water. Crucially, the processes seen here occur at small horizontal scales not resolved by regional forecast models or climate simulations; new parameterizations must be developed that accurately represent the physics. Here we present novel high resolution observations showing the detailed process of subduction and initial evolution of warm Pacific-origin water in the southern Beaufort Gyre.

Observations of surface waves and ice drift along a compact sea ice edge demonstrate the importance of waves in a marginal ice zone. An analytic model is presented for the along‐ice drift forced by the radiation stress gradient of oblique waves. A momentum balance using quadratic drag to oppose the wave forcing is sufficient to explain the observations. Lateral shear stresses in the ice are also evaluated, though this balance does not match the observations as well. Additional forcing by local winds is included and is small relative to the wave forcing. However, the wave forcing is isolated to a narrow region around 500‐m wide, whereas the wind forcing has effects on larger scales. The simplistic drag is assessed using observations of shear and turbulent dissipation rates. The results have implications for the shape and evolution of the ice edge, because the lateral shear may be a source of instabilities.

Katabatic winds in coastal polynyas expose the ocean to extreme heat loss, causing intense sea ice production and dense water formation around Antarctica throughout autumn and winter. The advancing sea ice pack, combined with high winds and low temperatures, has limited surface ocean observations of polynyas in winter, thereby impeding new insights into the evolution of these ice factories through the dark austral months. Here, we describe oceanic observations during multiple katabatic wind events during May 2017 in the Terra Nova Bay and Ross Sea polynyas. Wind speeds regularly exceeded 20 m s^-1, air temperatures were below –25°C, and the oceanic mixed layer extended to 600 m. During these events, conductivity–temperature–depth (CTD) profiles revealed bulges of warm, salty water directly beneath the ocean surface and extending downwards tens of meters. These profiles reflect latent heat and salt release during unconsolidated frazil ice production, driven by atmospheric heat loss, a process that has rarely if ever been observed outside the laboratory. A simple salt budget suggests these anomalies reflect in situ frazil ice concentration that ranges from 13 to 266x10^-3 kg m^-3. Contemporaneous estimates of vertical mixing reveal rapid convection in these unstable density profiles and mixing lifetimes from 7 to 12 min. The individual estimates of ice production from the salt budget reveal the intensity of short-term ice production, up to 110 cm d^-1 during the windiest events, and a seasonal average of 29 cm d^-1. We further found that frazil ice production rates covary with wind speed and with location along the upstream–downstream length of the polynya. These measurements reveal that it is possible to indirectly observe and estimate the process of unconsolidated ice production in polynyas by measuring upper-ocean water column profiles. These vigorous ice production rates suggest frazil ice may be an important component in total polynya ice production.

Quantifying the rate of wave attenuation in sea ice is key to understanding trends in the Antarctic marginal ice zone extent. However, a paucity of observations of waves in sea ice limits progress on this front. We deployed 14 waves-in-ice observation systems (WIIOS) on Antarctic sea ice during the Polynyas, Ice Production, and seasonal Evolution in the Ross Sea expedition (PIPERS) in 2017. The WIIOS provide in situ measurement of surface wave characteristics. Two experiments were conducted, one while the ship was inbound and one outbound. The sea ice throughout the experiments generally consisted of pancake and young ice < 0.5 m thick. The WIIOS survived a minimum of 4 d and a maximum of 6 weeks. Several large-wave events were captured, with the largest recorded significant wave height over 9 m. We find that the total wave energy measured by the WIIOS generally decays exponentially in the ice and the rate of decay depends on ice concentration.

In the marginal ice zone, surface waves drive motion of sea ice floes. The motion of floes relative to each other can cause periodic collisions, and drives the formation of pancake sea ice. Additionally, the motion of floes relative to the water results in turbulence generation at the interface between the ice and ocean below. These are important processes for the formation and growth of pancakes, and likely contribute to wave energy loss. Models and laboratory studies have been used to describe these motions, but there have been no in situ observations of relative ice velocities in a natural wave field. Here, we use shipboard stereo video to measure wave motion and relative motion of pancake floes simultaneously. The relative velocities of pancake floes are typically small compared to wave orbital motion (i.e. floes mostly follow the wave orbits). We find that relative velocities are well-captured by existing phase-resolved models, and are only somewhat over-estimated by using bulk wave parameters. Under the conditions observed, estimates of wave energy loss from ice–ocean turbulence are much larger than from pancake collisions. Increased relative pancake floe velocities in steeper wave fields may then result in more wave attenuation by increasing ice–ocean shear.

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.

The dissipation of wave energy in the marginal ice zone is often attributed to wave scattering and the dissipative mechanisms associated with the ice layer. In this study we present observations indicating that turbulence generated by the differential velocity between the sea ice cover and the orbital wave motion may be an important dissipative mechanism of wave energy. Through field measurements of under‐ice turbulence dissipation rates in pancake and frazil ice, it is shown that turbulence‐induced wave attenuation coefficients are in agreement with observed wave attenuation in the marginal ice zone. The results suggest that the turbulence‐induced attenuation rates can be parameterized by the characteristic wave properties and a coefficient. The coefficient is determined by the ice layer properties.

Near‐surface turbulent kinetic energy dissipation rates are altered by the presence of sea ice in the marginal ice zone, with significant implications for exchanges at the air‐ice‐ocean interface. Observations spanning a range of conditions are used to parameterize dissipation rates in marginal ice zones with relatively thin, newly formed ice, and two regimes are identified. In both regimes, the turbulent dissipation rates are matched to the turbulent input rate, which is formulated as the surface stress acting on roughness elements moving at an effective transfer velocity. In marginal ice zones with waves, the short waves are the roughness elements, and the phase speed of these waves is the effective transfer velocity. The wave amplitudes are attenuated by the ice, and thus, the size of the roughness elements is reduced; this is parameterized as a reduction in the effective transfer velocity. When waves are sufficiently small, the ice floes are the roughness elements, and the relative velocity between the sea ice and the ocean is the effective transfer velocity. A scaling is introduced to determine the appropriate transfer velocity in a marginal ice zone based on wave height, ice thickness and concentration, and ice‐ocean shear. The results suggest that turbulence underneath new sea ice is mostly related to the wind forcing and that marginal ice zones generally have less turbulence than the open ocean under similar wind forcing.

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.

High‐resolution measurements of the air‐ice‐ocean system during an October 2015 event in the Beaufort Sea demonstrate how stored ocean heat can be released to temporarily reverse seasonal ice advance. Strong on‐ice winds over a vast fetch caused mixing and release of heat from the upper ocean. This heat was sufficient to melt large areas of thin, newly formed pancake ice; an average of 10 MJ/m² was lost from the upper ocean in the study area, resulting in ~3–5 cm pancake sea ice melt. Heat and salt budgets create a consistent picture of the evolving air‐ice‐ocean system during this event, in both a fixed and ice‐following (Lagrangian) reference frame. The heat lost from the upper ocean is large compared with prior observations of ocean heat flux under thick, multi‐year Arctic sea ice. In contrast to prior studies, where almost all heat lost goes into ice melt, a significant portion of the ocean heat released in this event goes directly to the atmosphere, while the remainder (~30–40%) goes into melting sea ice. The magnitude of ocean mixing during this event may have been enhanced by large surface waves, reaching nearly 5 m at the peak, which are becoming increasingly common in the autumn Arctic Ocean. The wave effects are explored by comparing the air‐ice‐ocean evolution observed at short and long fetches, and a common scaling for Langmuir turbulence. After the event, the ocean mixed layer was deeper and cooler, and autumn ice formation resumed.

This study presents the most comprehensive set of in situ and remote sensing measurements of wave number, and hence the dispersion relation, in ice to date. A number of surface‐following buoys were deployed in sea ice from the R/V Sikuliaq, which also hosted an X‐band marine radar, during the ONR Arctic Sea State field experiment. The heave‐slope‐correlation method was used to estimate the root‐mean‐square wave number from the buoys. The method was highly sensitive to noise, and extensive quality control measures were developed to isolate real signals in the estimated wave number. The buoy measurements were complemented by shipboard marine X‐band radar dispersion measurements, which are limited to lower frequencies (<0.32 Hz). Overall, deviation from the linear open water dispersion relation was not significant, and matched the open water relation nearly exactly for the range 0.10–0.30 Hz. Isolating a subset of data during the strongest wave event showed evidence of increased wave numbers at frequencies greater than 0.30 Hz. The ice conditions and deviation from linear open water dispersion were qualitatively consistent with predictions from the mass loading model. However, the dispersion curves did not exactly follow the contours of the mass loading model, suggesting either measurement error or other processes at play.

A storm with significant wave heights exceeding 4 m occurred in the Beaufort Sea on 11–13 October 2015. The waves and ice were captured on 12 October by the Synthetic Aperture Radar (SAR) on board Sentinel‐1A, with Interferometric Wide swath images covering 400 x 1,100 km at 10 m resolution. This data set allows the estimation of wave spectra across the marginal ice zone (MIZ) every 5 km, over 400 km of sea ice. Since ice attenuates waves with wavelengths shorter than 50 m in a few kilometers, the longer waves are clearly imaged by SAR in sea ice. Obtaining wave spectra from the image requires a careful estimation of the blurring effect produced by unresolved wavelengths in the azimuthal direction. Using in situ wave buoy measurements as reference, we establish that this azimuth cutoff can be estimated in mixed ocean‐ice conditions. Wave spectra could not be estimated where ice features such as leads contribute to a large fraction of the radar backscatter variance. The resulting wave height map exhibits a steep decay in the first 100 km of ice, with a transition into a weaker decay further away. This unique wave decay pattern transitions where large‐scale ice features such as leads become visible. As in situ ice information is limited, it is not known whether the decay is caused by a difference in ice properties or a wave dissipation mechanism. The implications of the observed wave patterns are discussed in the context of other observations.

New sea ice in the polar regions often begins as small pancake floes in autumn and winter that grow laterally and weld together into larger floes. However, conditions in polar oceans during freeze‐up are harsh, rendering in‐situ observations of small‐scale sea ice growth processes difficult and infrequent. Here, we apply image processing techniques to images obtained by drifting wave buoys (SWIFTs) deployed in the autumn Arctic Ocean to quantify these processes in situ for the first time. Small pancake ice floes were observed to form and grow gradually in freezing, low‐wave conditions. We find that pancake floe diameters are limited by the wave field, such that floe diameter is proportional to wavelength and amplitude over time. Floe welding correlates well with sea ice concentration, and the observations can be used to estimate a key model parameter for floe size evolution. There is some agreement between observed lateral growth rates and those predicted using a theoretical model based on heat flux balance, but the model lateral growth rates are too conservative in these conditions. These results will be used to inform description of lateral floe growth and floe welding in new models that evolve sea ice floe size distribution.

This paper presents a wave-in-ice model calibration study. Data used were collected in the thin ice of the advancing autumn marginal ice zone of the western Arctic Ocean in 2015, where pancake ice was found to be prevalent. Multiple buoys were deployed in seven wave experiments; data from four of these experiments are used in the present study. Wave attenuation coefficients are calculated utilizing wave energy decay between two buoys measuring simultaneously within the ice covered region. Wavenumbers are measured in one of these experiments. Forcing parameters are obtained from simultaneous in-situ and remote sensing observations, as well as forecast/hindcast models. Cases from three wave experiments are used to calibrate a viscoelastic model for wave attenuation/dispersion in ice cover. The calibration is done by minimizing the difference between modeled and measured complex wavenumber, using a multi-objective genetic algorithm. The calibrated results are validated using two methods. One is to directly apply the calibrated viscoelastic parameters to one of the wave experiments not used in the calibration and then compare the attenuation from the model with measured data. The other is to use the calibrated viscoelastic model in WAVEWATCH III over the entire western Beaufort Sea and then compare the wave spectra at two remote sites not used in the calibration. Both validations show reasonable agreement between the model and the measured data. The completed viscoelastic model is believed to be applicable to the fall marginal ice zone dominated by pancake ice.

Highlights

• An algorithm is proposed to obtain orbital velocity maps from SAR images over sea ice.
• The algorithm is validated in terms of ocean wave spectra using in situ measurements.
• Wave height retrieval works best in the absence of unresolved short waves.