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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. Plain Language Summary: We observed in detail snow melt on two different tundra locations and one sea ice location in Arctic Alaska in the spring of 2019 and 2022. During the melt season, these landscapes go from reflecting over 80% of the sunlight to less than 20%, a transition that impacts the global climate. Our observations showed that while warming weather is what ultimately controls snowmelt, the re‐freezing and flow of meltwater within the snowpack, plays a crucial role in controlling local melt rates of individual snow patches. These water‐related melt mechanisms, together with wind‐driven laterally advected air and the reflective properties of the snow, largely control the date individual snow patches disappear, and therefore, when the most rapid changes in solar reflectivity will take place. Key Points: Water‐related processes in snow can promote or impede lateral advection of heat and mass, enhancing or inhibiting melt in the ArcticThe composition and topography of the substrate govern the nature of the water‐snow interactions and thereby influence meltout patternsThe most rapid and largest changes in surface albedo happen just prior to the snow‐free date when water‐snow melt mechanisms reach a peak [ABSTRACT FROM AUTHOR]

A precise knowledge of landfast sea-ice (fast-ice) thickness is relevant to many different disciplines. Sea Ice Monitoring Stations (SIMS) are used to measure time series of fast-ice thickness at a location. SIMS measure ice and ocean temperature via thermistor strings with many different methods for extracting sea-ice thickness from temperature existing. This study investigates: if thickness results from temperature recorded by SIMS of different designs, and analysed with different methods are comparable; which methods are recommended for their robustness, precision and accuracy and how they compare to independent thickness measurements; how otherwise unuseable data can be salvaged through specific SIMS designs. We present an analysis of fast-ice thickness calculated from SIMS deployed in McMurdo Sound, Antarctica and in the Chukchi Sea near Utqiaġvik, Alaska, over two decades. We find that median thicknesses derived by different methods agree within 1 ± 1.5 cm for McMurdo Sound and 2 ± 3 cm for Utqiaġvik. Thus, it is possible to confidently compare data collected from different stations and analysed with different methods. The vertical gradient of sea-ice temperature gives the best results for fast-ice thickness during the growth season and including standard resistors in a thermistor string can reduce potential data loss due to noise. [ABSTRACT FROM AUTHOR]

We investigate the application of ground-based radar interferometry for measuring flexural–gravity waves in sea ice. We deployed a GAMMA Portable Radar Interferometer (GPRI) on top of a grounded iceberg surrounded by landfast sea ice near Utqiaġvik, Alaska. The GPRI collected 238 acquisitions in stare mode during a period of moderate lateral ice motion during 23–24 April 2021. Individual 30 s interferograms exhibit ∼ 20–50 s periodic motion indicative of propagating infragravity waves with ∼ 1 mm amplitudes. Results include examples of onshore wave propagation at the speed predicted by the water depth and a possible edge wave along an ice discontinuity. Findings are supported through comparison with on-ice Ice Wave Rider (IWR) accelerometers and modeled wave propagation. These results suggest that the GPRI can be a valuable tool to track wave propagation through sea ice and possibly detect changes in such properties across variable ice conditions. [ABSTRACT FROM AUTHOR]

The inaugural data from the first systematic program of sea-ice observations in Kotzebue Sound, Alaska, in 2018 coincided with the first winter in living memory when the Sound was not choked with ice. The following winter of 2018–19 was even warmer and characterized by even less ice. Here we discuss the mass balance of landfast ice near Kotzebue (Qikiqtaġruk) during these two anomalously warm winters. We use in situ observations and a 1-D thermodynamic model to address three research questions developed in partnership with an Indigenous Advisory Council. In doing so, we improve our understanding of connections between landfast ice mass balance, marine mammals and subsistence hunting. Specifically, we show: (i) ice growth stopped unusually early due to strong vertical ocean heat flux, which also likely contributed to early start to bearded seal hunting; (ii) unusually thin ice contributed to widespread surface flooding. The associated snow ice formation partly offset the reduced ice growth, but the flooding likely had a negative impact on ringed seal habitat; (iii) sea ice near Kotzebue during the winters of 2017–18 and 2018–19 was likely the thinnest since at least 1945, driven by a combination of warm air temperatures and a persistent ocean heat flux. [ABSTRACT FROM AUTHOR]

The drift of sea ice is an important geophysical process with widespread implications for the ocean energy budget and ecosystems. Drifting sea ice can also threaten marine operations and present a hazard for ocean vessels and installations. Here, we evaluate single-pass along-track synthetic aperture radar (SAR) interferometry (S-ATI) as a tool to assess ice drift while discussing possible applications and inherent limitations. Initial validation shows that TanDEM-X phase-derived drift speed corresponds well with drift products from a ground-based radar at Utqiaġvik, Alaska. Joint analysis of TanDEM-X and Sentinel-1 data covering the Fram Strait demonstrates that S-ATI can help quantify the opening/closing rate of leads with possible applications for navigation. S-ATI enables an instantaneous assessment of ice drift and dynamic processes that are otherwise difficult to observe. For instance, by evaluating sea ice drift through the Vilkitsky Strait, Russia, we identified short-lived transient convergence patterns. We conclude that S-ATI enables the identification and analysis of potentially important dynamic processes (e.g., drift, rafting, and ridging). However, current limitations of S-ATI are significant (e.g., data availability and they presently only provide the cross-track vector component of the ice drift field) but may be significantly reduced with future SAR systems. [ABSTRACT FROM AUTHOR]

Snow plays an important role in the Arctic climate system, modulating heat transfer in terrestrial and marine environments and controlling feedbacks. Changes in snow depth over Arctic sea ice, particularly in spring, have a strong impact on the surface energy budget, influencing ocean heat loss, ice growth and surface ponding. Snow conditions are sensitive to the phase (solid or liquid) of deposited precipitation. However, variability and potential trends of rain-on-snow events over Arctic sea ice and their role in sea-ice losses are poorly understood. Time series of surface observations at Utqiaġvik, Alaska, reveal rapid reduction in snow depth linked to late-spring rain-on-snow events. Liquid precipitation is key in preconditioning and triggering snow ablation through reduction in surface albedo as well as latent heat release determined by rainfall amount, supported by field observations beginning in 2000 and model results. Rainfall was found to accelerate warming and ripening of the snowpack, with even small amounts (such as 0.3 mm recorded on 24 May 2017) triggering the transition from the warming phase into the ripening phase. Subsequently, direct heat input drives snowmelt, with water content of the snowpack increasing until meltwater output occurs, with an associated rapid decrease in snow depth. Rainfall during the ripening phase can further raise water content in the snow layer, prompting onset of the meltwater output phase in the snowpack. First spring rainfall in Utqiaġvik has been observed to shift to earlier dates since the 1970s, in particular after the mid-1990s. Early melt season rainfall and its fraction of total annual precipitation also exhibit an increasing trend. These changes of precipitation over sea ice may have profound impacts on ice melt through feedbacks involving earlier onset of surface melt. [ABSTRACT FROM AUTHOR]

Using thresholds of physical climate variables developed from community observations, together with two large-scale datasets, we have produced local indices directly relevant to the impacts of a reduced sea ice cover on Alaska coastal communities. The indices include the number of "false freeze-ups" defined by transient exceedances of ice concentration prior to a corresponding exceedance that persists, "false break-ups", timing of freeze-up and break-up, length of the open water duration, number of days when the winds preclude hunting via boat (wind speed threshold exceedances), the number of wind events conducive to geomorphological work or damage to infrastructure from ocean waves, and the number of these wind events with onand along-shore components promoting water setup along the coastline. We demonstrate how community observations can inform use of large-scale datasets to derive these locally relevant indices. The two primary large-scale datasets are the Historical Sea Ice Atlas for Alaska and the atmospheric output from a regional climate model used to downscale the ERA-Interim atmospheric reanalysis. We illustrate the variability and trends of these indices by application to the rural Alaska communities of Kotzebue, Shishmaref, and Utqiaġgvik (previously Barrow), although the same procedure and metrics can be applied to other coastal communities. Over the 1979-2014 time period, there has been a marked increase in the number of combined false freeze-ups and false break-ups as well as the number of days too windy for hunting via boat for all three communities, especially Utqiaġvik. At Utqiaġvik, there has been an approximate tripling of the number of wind events conducive to coastline erosion from 1979 to 2014. We have also found a delay in freeze-up and earlier break-up, leading to a lengthened open water period for all of the communities examined. [ABSTRACT FROM AUTHOR]

In this work, we evaluate landfast sea ice dynamics using ground-based radar interferometry. During two field campaigns in Utqiaġvik, Alaska, we collected three ∼24-h series of measurements on 16 May 2012 and 21–23 April 2021 using the Gamma portable radar interferometer (GPRI). These data enable examination of progressive strain of landfast ice on the sub-cm scale. The results indicate near spatially uniform divergence strains exceeding 10−6 in response to an increase in offshore winds from 0 to 7 m s−1. Exceptions to uniform divergence are grounded ridges with either negligible or reduced motion. We also track uniform vertical shifts in response to cm-scale sea level change correlated with NOAA model tidal predictions. We evaluate and take steps to remove contributions from moisture variability, thereby reducing potential errors from atmospheric effects to less than 5 mm. The results suggest that the GPRI can be a valuable tool for monitoring ice-covered coastal zones. The system has possible applications for monitoring tides and ocean surges and tracking small-scale deformation of otherwise stationary ice that can lead to fracture and destabilization. • We resolve wind-induced ice strain over kilometers with cm-scale accuracy. • We track vertical displacement of sea ice in microtidal environment. • We obtain minute-scale temporal resolution and sub-meter range resolution. • Allows accurate location and timing of episodic events e.g., cracks and detachments. • Atmospheric effects can be mitigated by removing phase change from static targets. [ABSTRACT FROM AUTHOR]

Landfast ice along the Arctic coasts plays an important role in supporting ecosystem services, local communities and offshore activities by industry. Seasonal predictions of landfast ice conditions are generally lacking in current seasonal forecasting products but are needed especially for planning of on-ice activities such as the construction of ice roads. This study focuses on the planned offshore development of Liberty Island where there is a need to generate seasonal forecasts for the construction of ice roads in Foggy Island Bay along the Beaufort Sea coast in northern Alaska. Due to the lack of prior in-situ observations of ice thickness in the region, a combination of newly obtained field measurements, remote sensing data analysis and modeling were employed to produce prototype seasonal forecasts of ice thickness in the landfast ice around Liberty Island. Seasonal forecasts initialized in September and March were built using Climate Forecast System seasonal forecast model data coupled with a single column ice model to forecast ice thickness that capture the start and end of the operational season, respectively. The results showed that the model forecasts had modest skill in capturing the timing of key ice thickness thresholds needed to support vehicle traffic during the start of the season in November–December but very limited skill with end of season and ice breakup forecasts. Much of the forecast skill was improved through bias correction but such improvement was hampered by the lack of long-term observational data in the region. Integration of the observational data and modeling is necessary to begin development of seasonal forecasts in this data sparse region. • Seasonal sea ice thickness forecasts developed for Foggy Island Bay, Alaska. • Forecasts needed to support ice road operations for Liberty Island development. • Required integration of field observations, forecast model data, and an ice model. • Forecast skill was improved through bias correction. [ABSTRACT FROM AUTHOR]