In this study, the U-net with ResNet-34, i.e. a residual neural network with 34 layers, backbone semantic segmentation network is applied to C-band sea-ice SAR imagery over the Baltic Sea. Sentinel-1 Extra Wide Swath mode HH/HV-polarized SAR data acquired during the winter season 2018–2019, and corresponding segments derived from the daily Baltic Sea ice charts were used for training the segmentation algorithm. C-band SAR image mosaics of the winter season 2020–2021 were then used to evaluate the segmentation. The major objective was to study the suitability of semantic segmentation of SAR imagery for automated SAR segmentation and also to find a potential replacement for the outdated iterated conditional modes (ICM) algorithm currently in operational use. The results compared to the daily Baltic Sea ice charts and the operational ICM segmentation and visual interpretation were encouraging from the operational point of view. Open water areas were located very well and the oversegmentation produced by ICM was significantly reduced. The correspondence between the ice chart polygons and the segmentation results was also reasonably good. Based on the results, the studied method is a potential candidate to replace the operational ICM SAR segmentation used in the Copernicus Marine Service automated sea-ice products at Finnish Meteorological Institute.

A parameterization of the impact of internal waves on momentum transfer at the sea-ice–ocean interface based on previous work by McPhee has been implemented in a sea-ice model for the first time. The ice–ocean drag from internal waves is relevant for shallow mixed layer depth and the presence of a density jump at the pycnocline and is also a function of the strength of the stratification beneath the ocean mixed layer and geometry of the ice interface. We present results from a coupled sea-ice–ocean model where the parameterization of internal wave drag has been implemented. We conducted simulations spanning the years from 2000 to 2017. We find a deceleration of ice drift by 5–8% in both winter and summer, but with significant spatial and temporal variation reaching seasonal average values of ~10%. The spatial variation of ice transport leads to local impacts on deformed ice of magnitude ~0.05 m (2–5%), and reductions in ocean-to-ice heat fluxes of ~1 W m−2, and a decrease in bottom melt of ~0.02–0.04 cm d−1. There is an increase of up to 15% in thickness and ice concentration in the Canadian Arctic and a 10% overall impact on the total sea-ice volume.

We present a new model for understanding ice cliff dynamics within a debris-covered glacier ablation zone. This simple energy-balance model incorporates a moving frame of reference, made necessary by the melt of the surrounding debris-covered ice. In so doing, this also formalises how different types of field measurements can be utilised and compared. Our predictions include showing: ice cliffs can endogenously select their own slope angles; that there should be an indifference between illuminated north- and south-facing ice cliff slopes; that ice cliffs grow steeper with thicker debris layers; that ice cliffs cannot stably exist below a certain critical debris thickness and that some modelling of ice cliffs (when not incorporating the moving frame) may incorrectly estimate ice mass losses. All of our results are produced using parametrisations from Baltoro Glacier, Karakoram.

The increase in iceberg discharge into the polar oceans highlights the importance of understanding how quickly icebergs are deteriorating and where the resulting freshwater injection is occurring. Recent advances in quantifying iceberg deterioration through combinations of modeling, remote sensing and direct in situ measurements have successfully calculated overall ablation rates, and surface and sidewall ablation; however, in situ measurements of basal melt rates have been difficult to obtain. Radar has successfully measured iceberg thickness, but repeat measurements, which would capture a change in iceberg thickness with time, have not yet been collected. Here we test the applicability of using an on-iceberg autonomous phase-sensitive radar (ApRES) to quantify basal ablation rates of a large (~800 m long) non-tabular Arctic iceberg during an intensive 2019 summer field campaign in Sermilik Fjord, southeast Greenland. We find that ApRES can be used to measure basal ablation even over a short deployment period (10 d), and also provide a lower bound on sidewall melt. This study fills a critical gap in iceberg research and pushes the limits of field instrumentation.

The retrieval of sea ice thickness using L-band passive remote sensing requires robust models for emission from sea ice. In this work, measurements obtained from surface-based radiometers during the MOSAiC expedition are assessed with the Burke, Wilheit and SMRT radiative transfer models. These models encompass distinct methodologies: radiative transfer with/without wave coherence effects, and with/without scattering. Before running these emission models, the sea ice growth is simulated using the Cumulative Freezing Degree Days (CFDD) model to further compute the evolution of the ice structure during each period. Ice coring profiles done near the instruments are used to obtain the initial state of the computation, along with Digital Thermistor Chain (DTC) data to derive the sea ice temperature during the analyzed periods. The results suggest that the coherent approach used in the Wilheit model results in a better agreement with the horizontal polarization of the in situ measured brightness temperature. The Burke and SMRT incoherent models offer a more robust fit for the vertical component. These models are almost equivalent since the scattering considered in SMRT can be safely neglected at this low frequency, but the Burke model misses an important contribution from the snow layer above sea ice. The results also suggest that a more realistic permittivity falls between the spheres and random needles formulations, with potential for refinement, particularly for L-band applications, through future field measurements.

Scenario–neutral methods are commonly used to rapidly compare system responses to changes in climate. Using glacier mass balance as a system response, we present a bottom-up, scenario–neutral method as an effective tool for preliminary and overview studies on glacier sensitivity and a complementary approach to traditional top–down methods. The method's main characteristic is its visual result: two–dimensional response surfaces depicting glacier mass balance. Their axes represent perturbations in temperature and precipitation relative to a baseline. The simplicity of our approach makes it applicable to all global glaciers. As a proof–of–concept, the Open Global Glacier Model (OGGM) is used to perform a scenario–neutral glacier sensitivity analysis for four glaciers. In addition, the integration with a top–down approach is demonstrated by overlaying temperature and precipitation from four Coupled Model Intercomparison Project Phase 6 (CMIP6) models, under four Shared Socioeconomic Pathways (SSP). Finally, the benefits of the method are discussed for decision–making and science communication. Assessing results shows that overall, this scenario–neutral method can provide useful information for the research of climate change impact on glacier mass, from aiding study design to science communication.

In this study an operational sea ice thickness (SIT) estimation algorithm, based on HH-polarized X-band synthetic aperture radar (SAR) data, background information from the most recent, typically from the previous day, available daily Baltic Sea ice chart and the operational Finnish Meteorological Institute (FMI) thermodynamic ice model, was developed and evaluated. The algorithm was designed to complement the C-band SAR SIT algorithm developed earlier at FMI and applied daily as part of the operational Copernicus Marine Service (CMS). The X-band SIT algorithm was developed by utilizing the sea ice thickness measurements made onboard the Finnish and Swedish ice breakers during two winters seasons: 2021–2022 and 2022–2023. The former season measurements were used for defining the algorithm parameters and the later season for evaluation of the algorithm performance. According to the evaluation metrics the X-band algorithm performance is slightly better than that of the operational CMS C-band SAR SIT algorithm, indicating its suitability for operational use in CMS.

The changing conditions in which sea ice forms and exists are likely to affect the properties of sea ice itself, and potential climate feedbacks need to be identified and understood to improve future projections. Here we perform a set of idealised laboratory experiments that model sea-ice growth under a range of freezing conditions. The results confirm existing theories; sea-ice growth rate is largest for cooler freezing temperatures, fresher ambient salinities and cases with bottom cooling. Our primary metric of interest is the brine fraction (the volume ratio of brine inclusions to the total sea ice), which we quantify and determine its sensitivity with respect to the ambient salinity, freezing temperature and, for the first time, the freezing direction. We find that the brine fraction of our model sea ice is most sensitive to freezing temperature, and increases 2.5% per 1$^\circ$C increase of freezing temperature.

A surge of Mittie Glacier, a 50 km-long tidewater outlet glacier of Manson Icefield, occurred between approximately 1992 and 2007. Velocities increased slowly at first, but then increased rapidly to reach a peak of 4800 m a−1 in early 1996, the highest ever reported for a glacier in the Canadian Arctic. The surge initiated at the terminus and propagated up-glacier, with a maximum terminus advance of 7.3 km between 1994 and 1999. The surge was almost entirely restricted to the lower ~30 km of the glacier, in a region which radio-echo sounding shows to be grounded below sea level. A 3 km-wide crevasse with a 150 m opening occurred at the separation between faster moving ice downstream and slower moving ice upstream. Surge initiation appears to have been triggered by flotation of the lower terminus, caused by long-term thinning of this region during quiescence.

Evaluating CMIP6 model performance helps to improve the prediction of future changes in Arctic sea ice. We analyze the seasonal cycles, distribution, and evolution of sea ice in different regions from 1979 to 2014. We compare the output from selected CMIP6 models with reference data for sea ice motion. We also discuss the correlations between sea ice motion(SIM) and sea ice thickness (SIT) in reference data, and how CMIP6 models explain them. We select EC-Earth3, ACCESS-CM2, BCC-CSM2-MR, MPI-ESM1-2-HR, and NorESM2-LM for CMIP6 study. We compare outputs with reference data: Sea ice extent (SIE) from NSIDC; SIT from PIOMAS; and SIM from the IABP buoy data. Analytical techniques include Theil-Sen and Ordinary least squares (OLS) regression. Most selected CMIP6 models have seasonal cycles of SIM lagging behind IABP observations by 1-2 month and overestimate central Arctic SIM magnitude, with MPI-ESM1-2-HR having the highest discrepancy and NorESM2-LM lowest. The models show better simulation of SIM in the ice melting season than in the growing season. Models perform worse at capturing regional differences in SIM evolution and are overly conservative when simulating the increasing trend in ice motion, especially in coastal Arctic seas during summer. There is significant negative correlation between SIT and SIM in October.

In light of the recent increase in polar shipping and potential future increase with continued climate change reliable routing in ice-covered waters becomes increasingly important for environmental, economic and safety concerns. Dependable route suggestions have the potential to reduce travel times through polar waters significantly. We apply the Anytime Repairing A* pathfinding algorithm to classified Copernicus Sentinel 1 radar images to estimate how much travel times can be reduced. For multiple example scenarios, it is quantified how much the travel time is reduced if a ship follows these suggestions compared to navigating without any ice information available exterior to the visual range (VR). It was found that having ice information available is most beneficial in complex ice situations, where it can reduce travel time by up to 34% for a VR of 2 km.

This paper presents geomorphological and historical records of the surge-type behaviour of Hansbreen, one of the most studied tidewater glaciers in Svalbard. The surge-type behaviour of the glacier has not been considered before due to the lack of evidence of this phenomenon. We integrate geomorphological mapping of the terrestrial and submarine forefields with historical data from the 19th and 20th centuries to reconstruct the glacier dynamics and identify the possible timing of surging. Landform assemblages are representative of the surging glacier landsystem, including crevasse-squeeze ridges (CSRs) and submarine streamlined glacial lineations. Abundant CSRs in the outer part of the terrestrial forefield were also documented in the 1980s, but most have been obliterated since then. We suggest the identified surge landsystem was produced during a surge of Hansbreen detected from photographs taken during the Austro-Hungarian expedition in 1872. Historical photogrammetric photos from the Norwegian expedition in 1918 revealed surge-diagnostic features in the glacier surface, including a folded medial moraine and a dense, complex network of crevasses. A potential next surge remains questionable in the following decades due to the low-lying accumulation area of the main stream hindering the mass build-up, but potential surges of the tributary glaciers should not be excluded.

Understanding sea-ice dynamics at the floe scale is crucial to comprehend polar climate systems. While continuum models are commonly used to simulate large-scale sea-ice dynamics, they have limitations in accurately representing sea-ice behaviour at small scales. DEMs, on the other hand, are well-suited for modelling the behaviour of individual ice floes but face limitations due to computational constraints. To address the limitations of both approaches while combining their strengths, we explored the feasibility of using a DEM within a continuum model, where the latter provides boundary conditions for a rectangular high-resolution DEM domain. This paper presents a feasibility study where a discrete model of a 100 × 100 km2 icefield was created using high-resolution optical satellite imagery. Sea-ice dynamics were simulated in the DEM considering environmental forces and integrating large-scale ice-drift velocities as boundary conditions. Model predictions were compared with satellite observations for ice drift and deformation parameters. This numerical approach showed potential for offering accurate, high-resolution predictions of sea ice, particularly in coastal areas and near islands, and may find applications in ice navigation and climate studies. However, further development of the DEM, along with upgrades to the coupled ocean models providing data for the ice component, may be necessary. Additionally, challenges remain to develop a two-way coupling between the DEM and a continuum model, which may be needed to improve the accuracy of large-scale simulations.

We estimate sea-ice type specific incidence angle (IA) dependencies for dual polarized (HH/HV) L and C-band synthetic aperture radar (SAR) for the winter, melt onset and advanced melt seasons for level and deformed ice, using time-series of Advanced Land Observing Satellite-2 (ALOS-2) and Sentinel-1 imagery off the north-east coast of Greenland. The IA dependencies are used to radiometrically correct the L and C-band backscatter time-series, which enables analysis of their seasonal evolution. From this, we observe that the L-band backscatter intensity increases for both ice types at the transition from winter to melt onset. We use these results to estimate ice type separability and to train an IA aware Bayesian classifier at both frequencies. These results show that while both frequencies are capable of distinguishing level and deformed ice during the winter, only L-band SAR can reliably make this separation during the melt onset season. During the advanced melt season, the overall classification accuracies are similarly low for L and C-band. This study demonstrates the potential of L-band SAR for sea-ice mapping, which is highly relevant in the light of several upcoming L-band SAR missions.

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.

Salt is often present in the snow overlying seasonal sea ice, and has profound thermodynamic and electromagnetic effects. However, its provenance and behaviour within the snow remain uncertain. We describe two investigations tracing upward brine movement in snow: one conducted in the laboratory and one in the field. The laboratory experiments involved the addition of dyed brine to the base of terrestrial snow samples, with subsequent wicking being measured. Our field experiment involved dye being added directly (without brine) to bare sea-ice and lake ice surfaces, with snow then accumulating on top over several days. On the sea ice, the dye migrated upwards into the snow by up to 5 cm as the snow's basal layer became more salty, whereas no migration occurred in our control experiment over non-saline lake ice. This occurred in relatively dry snowpacks where brine took up $< 6\%$ of the snow's calculated pore volume, suggesting pore saturation is not required for upward salt transport. Our results highlight the potential role of microstructural parameters beyond those currently retrievable with penetrometry, and the potential value of longitudinal, process-based field studies of young snowpacks.

We present a fully-automated workflow to map sea ice types from Sentinel-1 data and transfer the results in near real-time to the research vessel Kronprins Haakon (KPH) in order to support tactical navigation and decision-making during a research cruise conducted towards Belgica Bank in April and May 2022. We used overlapping SAR and optical imagery to train a pixel-wise classifier for the required season and region, and implemented a processing chain with the Norwegian Ice Service at MET Norway that automatically classifies all Sentinel-1 images covering the area of interest. During the cruise, classification results were available on KPH within hours after image acquisition, which is significantly faster than manually produced ice charts. We evaluate the results both quantitatively, based on manually selected validation regions, and qualitatively in comparison to in-situ observations and photographs. Our findings show that open water, level ice, and deformed ice are classified with high accuracy, while young ice remains challenging due to its variable small-scale surface roughness. This work presents one of the first attempts to transfer automated ice type classification results into the field in near real-time and contributes to bridging the gap between research and operations in automated sea ice mapping.

Cryoconite holes are structures characteristic of the glacierised ablation areas, formed from dark sediment deposition which melt the glacier ice leading to their cylindrical structure formation. The present study focuses on an unstudied blue ice area of East Antarctica over the Hells Gate Ice Shelf in Northern Victoria Land. Taking advantage of neural network methodology applied on drone acquisitions, an automatic detection of cryoconite holes was carried out (88% of accuracy), mapping ~3500 m2 (0.4% fractional cover) of cryoconite holes over an area of 900 000 m2. The surveyed area showed heterogeneity in cryoconite hole distribution, with some regions showing an area fraction of holes (regions exhibiting frozen ponds and ice bands) as high as 8%. Thanks to this detection, the spatially integrated radiative forcing of cryoconite holes over blue ice surface was estimated to be almost 1 Wm−2. This estimation was based on the measured albedo difference between the two surfaces, which averages 0.31. However, the radiative forcing is strongly increased if calculated at a single cryoconite hole scale, showing an average of ~200 Wm−2. In conclusion, the present research represents a first attempt of analysing cryoconite holes as factors impacting the blue ice in Northern Victoria Land, deepening our understanding of their glaciological role at the margins of the East Antarctic Ice Sheet.

Knowledge of how glaciations formed landscapes is particularly important as receding glaciers currently uncover subglacial landscapes that are prone to a series of natural hazards, but that also bring opportunities for hydropower or water resources. We present high-resolution (1 × 1 m) swath bathymetric data of a proglacial lake in front of the Rhonegletscher (Swiss Alps) that started to form in the early 2000s allowing a look into a freshly uncovered glacier bed and its characterized morphology in an overdeepened setting. The comparison of two surveys from 2015 and 2021 allows an unprecedented quantification of the accumulation and erosion processes in the central lake basin. This highly dynamic environment is characterized by iceberg calving, fluctuating outflow conduits, rapid sedimentation due to particle-laden meltwaters and dumped glacial debris. Assuming constant sediment yield, the Rhone Lake would persist for ~300 years. However, as intense glacier retreat continues in the coming decades, a chain of overdeepened lakes will be revealed that will act as long persisting sediment traps.

This study investigates the impacts of the timing of an extreme cyclone that occurred in August 2012 on the sea-ice volume evolution based on the Arctic Ice Ocean Prediction System (ArcIOPS). By applying a novel cyclone removal algorithm to the atmospheric forcing during 4–12 August 2012, we superimpose the derived cyclone component onto the atmospheric forcing one month later or earlier. This study finds that although the extreme cyclone leads to strong sea-ice volume loss in all runs, large divergence occurs in sea-ice melting mechanism in response to various timing of the cyclone. The extreme cyclone occurred in August, when enhanced ice volume loss is attributed to ice bottom melt primarily and ice surface melt secondarily. If the cyclone occurs one month earlier, ice surface melt dominates ice volume loss, and earlier appearance of open water within the ice zone initiates positive ice-albedo feedback, leading to a long lasting of the cyclone-induced impacts for approximately one month, and eventually a lower September ice volume. In contrast, if the cyclone occurs one month later, ice bottom melt entirely dominates ice volume loss, and the air-open water heat flux in the ice zone tends to offset ice volume loss.