Abstract. Accurate quantification of surface mass balance (SMB) in the Antarctic interior underpins ice sheet mass budget assessments and ice core interpretation. Stake measurements, however, systematically underestimate SMB because firn densification causes surface lowering unrelated to mass change. Here, we simulate firn compaction with a firn densification model and correct stake records from 2008-2024 at Dome Argus (Dome A), East Antarctica, thereby refining SMB estimates and their spatial variability. The mean annual corrected SMB is 24.14 kg m-2 yr-1, 8.8 % higher than the uncorrected value (22.19 kg m-2 yr-1). Over the stake array, the RACMO2.4p1 regional model yields lower and more spatially uniform SMB (17.50 kg m-2 yr-1). Using automatic weather station observations, we estimate annual sublimation of 2.34 mm w.e yr-1. and hoar deposition of 0.87 mm w.e. yr-1, indicating that the net vapor flux is equivalent to 5.7 % of the total mass input. This framework reduces densification induced bias in stake-derived SMB, provides an observational benchmark for evaluating regional climate models, and supports accurate dating of ice core climate records from Dome A.

The marginal ice zone (MIZ) is the region of sea ice that is strongly influenced by open-ocean processes, particularly ocean waves. The width of the Antarctic MIZ is often quantified by applying thresholds to satellite-derived maps of sea-ice concentration, although this definition lacks any connection to waves. Laser altimetry provides snapshots of wave penetration, but is restricted by cloud cover. To overcome these limitations, we refine radar altimetry techniques to estimate the Antarctic MIZ width from Ka-band radar altimeter data (2013-2024), producing a decade-long climatology of the wave-affected MIZ. Our analysis reveals the regionality and seasonality of the MIZ width, highlighting the under-appreciated dependence of wave penetration on ice-edge aspect (the alignment of the ice edge, relative to north). The wave-affected MIZ covers around 16% of the sea-ice zone. This technique offers a tool for measuring MIZ width and could be applied to earlier satellite datasets, enabling creation of a multi-decade climatology of this important zone and assessment of long-term changes in wave-ice interactions in the Southern Ocean.

Abstract Over the satellite period, Arctic and Antarctic sea ice extent seemed to follow opposite pathways. Arctic sea ice showed a strong and prolonged decrease until 2007 and then stalled in its rate of decline. Antarctic sea ice extent, on the other hand, displayed a small but significant increase until 2015. After 2015, Antarctic sea ice extent experienced a sharp decline, and has since been characterized by a lower mean state with enhanced variability, suggested as a new sea-ice regime. Arctic sea ice has continued transitioning towards a regime of substantially lower summertime coverage with reduced multiyear ice, increasingly resembling Antarctic sea ice in conditions and seasonality. We aim to provoke discussion by suggesting that the parallel changes in Arctic and Antarctic sea-ice behavior share a common mechanism: the breakdown of ocean stratification sustaining sea-ice decline, whilst episodic atmospheric forcing increasingly influences high-frequency sea-ice variability. In both the Antarctic and the Eurasian Basin of the Arctic, positive surface layer salinity anomalies have caused a weakening of the ocean halocline. The associated erosion of stratification makes sea ice more vulnerable to subsurface heat, and appears to underpin recent sea-ice loss and elevated variability. The convergence of the polar regions toward a seasonally dominated sea-ice regime leads us to call for continued and enhanced knowledge transfer and coordination between polar communities to accelerate understanding of recent sea-ice changes. A better understanding of the mechanisms driving changes in the coupled atmosphere–ocean–sea-ice system is needed to improve projections of future sea-ice loss and assess the cascading risks it poses to global climate and regional ecosystems.

Since 2015, Antarctic sea ice has entered a period of persistent record-low extent after decades of strong regional variability and large swings. The speed and persistence of this decline point to a system that may be changing state, with implications for the Southern Ocean, Antarctic ecosystems, and the global climate system. What is driving this shift remains insufficiently understood. Atmospheric variability plays a role, but ocean processes, including subsurface heat release and changes in stratification, are increasingly recognized as key pieces of the puzzle, alongside feedbacks involving snow, ice shelves, clouds, and freshwater input. This white paper focuses on four areas where progress is needed. First, improved understanding is needed of sea ice mass balance and dynamics: how sea ice grows, melts, moves, and deforms. Second, exchanges of heat, mass, and momentum between ocean, atmosphere, sea ice, and ice shelves need to be quantified across seasons and regions. Third, the consequences for ecosystems and biogeochemistry are likely substantial. Sea ice supports productive microbial communities and carbon and nutrient cycling, so its decline will affect polar food webs and Southern Ocean carbon storage. Finally, climate feedbacks, from albedo changes to cloud and ocean interactions, remain poorly constrained but could amplify ongoing change. A recurring limitation is the lack of coordinated, year-round observations across Antarctica. Existing data are sparse and uneven in space and time. Antarctica InSync is designed to address this by bringing together satellite observations, autonomous platforms, field campaigns, coastal observatories, harmonized data products, and modelling across pack ice, the marginal ice zone, landfast ice, and polynyas. The white paper recommends standardized observations of essential sea ice, snow, ocean, atmospheric, ecosystem, and biogeochemical variables, integrated into interoperable data products and models. Addressing these gaps is essential to improve predictability and anticipate future Antarctic sea ice change.

Antarctic sea ice and its snow cover play a pivotal role in regulating the global climate system through feedback on both the atmospheric and the oceanic circulations. Understanding the intricate interplay between atmospheric dynamics, mixed-layer properties, and sea ice is essential for accurate future climate change estimates. This study investigates the mechanisms behind the observed sea-ice and snow characteristics at a coastal site in East Antarctica using in situ measurements in winter-spring 2022. The observed sea-ice thickness peaks at 1.16 m in mid-late October and drops to 0.06 m at the end of November, following the seasonal solar cycle. On the other hand, the snow thickness variability is impacted by atmospheric forcing, with significant contributions from precipitation, Foehn effects, blowing snow, and episodic warm and moist air intrusions, which can lead to changes of up to 0.08 m within a day for a field that is in the range of 0.02-0.18 m during July-November 2022. A high-resolution simulation with the Polar Weather Research and Forecasting model for the 14 July atmospheric river (AR), the only AR that occurred during the study period, reveals the presence of AR rapids and highlights the effects of katabatic winds from the Antarctic Plateau in slowing down the low-latitude air masses as they approach the Antarctic coastline. The resulting convergence of the two airflows, with meridional wind speeds in excess of 45 m s-1, leads to precipitation rates above 3 mm h-1 around coastal Antarctica. The unsteady wind field in response to the passage of a deep low-pressure system with a central pressure that dropped to 931 hPa triggers satellite-derived pack ice drift speeds in excess of 60 km d-1 and promotes the opening up of a polynya in the Southern Ocean around 64 degrees S, 45 degrees E from 14 to 22 July. Our findings contribute to a better understanding of the complex interactions within the Antarctic climate system, providing valuable insights for climate modeling and future projections.

Abstract Snow on Antarctic sea ice modulates albedo, thermodynamic growth, and snow–ice formation, yet remains a leading uncertainty in altimetry‐derived sea‐ice thickness. Here we use the post‐2022 CRYO2ICE configuration to derive along‐track winter snow thickness from ICESat‐2 laser and CryoSat‐2 Ku‐band radar freeboards over the Weddell and Ross sectors. We analyze 82,341 winter matchups (August 2022–September 2025) using a 5 km, 4 hr collocation criterion and propagate freeboard and snow‐density uncertainties. Retrieved snow thickness is consistently larger in the Weddell Sea (mean 0.255 m, median 0.188 m) than the Ross Sea (0.217 m, 0.156 m), consistent with the older, thicker western Weddell ice. The contrast persists across sampled months and years and under common snow‐density and penetration‐factor assumptions. Formal per‐matchup precision (0.039–0.040 m) is dominated by CryoSat‐2 radar‐freeboard uncertainty, whereas the absolute magnitude is set by the unresolved Ku‐band scattering horizon. Comparison with AMSR2 passive‐microwave snow depth shows weak point‐to‐point agreement (r2=0.062 and <0.001 in the Weddell and Ross sectors), reflecting differing measurement physics and spatial support. Nevertheless, both independently reproduce thicker Weddell than Ross snow. Under a common penetration factor, absolute sector‐mean snow thickness varies by approximately a factor of two across the tested range, whereas the sector ordering is preserved under any uniform choice of penetration factor. CRYO2ICE therefore resolves a repeatable regional freeboard‐difference signal, but conversion of that signal to absolute snow thickness remains conditional on the poorly constrained, ice‐regime‐dependent Ku‐band scattering horizon.

Global marine ecosystem models (MEMs) are increasingly being used for assessingclimate impacts at various spatial scales (global, regional, countries, etc.), but theiroutputs are influenced by uncertainties linked to the ocean models used as forcings.We run simulations following Track A of the Fisheries and Marine Ecosystem ModelIntercomparison Project 2.0 using the Dynamic Benthic Pelagic Model (DBPM). Wethen evaluated the impact of three sources of uncertainty influencing the accuracy ofsimulated fishing catches in the Southern Ocean (1961–2010): (1) coarseninghorizontal resolution of environmental forcings (from 0.25° to 1°), (2) restricting spatialdistribution of fishing effort using a sea ice mask, and (3) using regional versus globalfishing effort forcing data. Our results indicate that DBPM captured observed spatialcatch distributions, with minimal differences between forcings resolutions. DBPMoverestimated observed fishing catches to a similar degree in both horizontalresolutions. Temporal trends aligned more closely with observations prior to the 1990s,but catch overestimation grew larger thereafter. Overestimation appears to be linked toan unrealistic spatial distribution of effort by DBPM, which was improved by theinclusion of a sea ice mask, and to errors and biases in the underlying fishing effortforcing data, which continues to represent a major hurdle for model skill improvement.Our findings suggest that coarsening inputs from an eddy-permitting ocean model maybe an effective approach to improve MEM performance without increasingcomputational costs.

Abstract. Antarctic sea ice has experienced an unprecedented decline in the past decade (2016–2025). Changes in sea ice concentration (SIC) and derived sea ice extent have been monitored using microwave radiometers since the late 1970s, providing information about the polar response to global climate change, hence making SIC an invaluable variable for numerical models. However, in the highly dynamic Marginal Ice Zone (MIZ), the region in between the pack ice and the open ocean, physical properties undergo intense variability, which may impact the accuracy of the SIC products retrieved from brightness temperature measurements. For the purpose of this study the MIZ is defined as the area with SIC between 15 % and 80 %. We simulate the variations of brightness temperature due to changes in the physical parameters describing the sea ice, the snow and the ocean with the Snow Microwave Radiative Transfer Model (SMRT) and the Passive and Active Reference Microwave to Infrared Ocean model (PARMIO) for a range of prescribed SIC. We then apply the core of the Bootstrap SIC algorithm on the simulated brightness temperatures and compare the retrieved and prescribed SIC, yielding the SIC error. This allows us to assess the impact of changes on the SIC retrieval by means of numerical radiative transfer simulations. Our work identifies the key parameters leading to high uncertainty in the retrieval: in the snowpack, the liquid water content and snow grain size cause SIC uncertainties of 5–10 % in the summer MIZ. In the cold season, the most influential factor is the presence of thin ice, inducing errors up to 30 %. Ocean roughness caused by the high-wind conditions affects both warm and cold seasons and gives rise to biases up to 15 % on the lower SIC MIZ boundary. However, other snowpack parameters that were expected to modify the SIC results, such as the salinity or temperature, showed a negligible impact in the tested range. We found that the core of the Bootstrap algorithm is largely robust to the variations in the snowpack, with no parameter introducing errors greater than 10 % across the MIZ SIC range. In contrast, ocean surface roughness due to wind speed and the presence of thin ice in the pixel are the variables leading to the greatest uncertainties, suggesting they are the primary targets to achieve more accurate SIC retrievals.

Human-caused climate change worsens with every increment of additional warming, although some impacts can develop abruptly. The potential for abrupt changes is far less understood in the Antarctic compared with the Arctic, but evidence is emerging for rapid, interacting and sometimes self-perpetuating changes in the Antarctic environment. A regime shift has reduced Antarctic sea-ice extent far below its natural variability of past centuries, and in some respects is more abrupt, non-linear and potentially irreversible than Arctic sea-ice loss. A marked slowdown in Antarctic Overturning Circulation is expected to intensify this century and may be faster than the anticipated Atlantic Meridional Overturning Circulation slowdown. The tipping point for unstoppable ice loss from the West Antarctic Ice Sheet could be exceeded even under best-case CO2 emission reduction pathways, potentially initiating global tipping cascades. Regime shifts are occurring in Antarctic and Southern Ocean biological systems through habitat transformation or exceedance of physiological thresholds, and compounding breeding failures are increasing extinction risk. Amplifying feedbacks are common between these abrupt changes in the Antarctic environment, and stabilizing Earth's climate with minimal overshoot of 1.5 °C will be imperative alongside global adaptation measures to minimise and prepare for the far-reaching impacts of Antarctic and Southern Ocean abrupt changes.

Sea ice is a fundamental, highly variable element of the polar environments. Its variability deeply affects, not only the local climate- and ecosystem but also the global Earth system. Until recently Arctic sea ice experienced a general retreat as expected under global warming whilst Antarctic sea ice extent increased up to 2014. However, Antarctic sea-ice extent at maximum annual cover shifted from a record high (2014) to a record minimum extent (2023), begging to explore the relationship between sea ice and ocean/atmospheric forcing. In this work, we pinpoint some extreme atmospheric events, specifically, atmospheric rivers (ARs) to analyse their influence on sea ice and snow properties. ARs can have a direct impact on the nature of oceanic surface gravity waves. Increasing wind speed causes an increase in wave height and energy, leading to greater repercussions on snow and sea ice. The sea ice area most affected by this forcing is the one that separates the pack ice from the open oceans, known as the marginal ice zone (MIZ). Our analysis aims to understand wave-sea ice interaction and its effect on accelerating snow melt or changing sea ice morphology. To accomplish this we focus on the influence of wave overwash on sea ice surfaces during the spring season in the Weddell Sea. The MIZ is identified by posing the limits of sea ice concentration (SIC) ranging from 15% to 80%. ARs events are identified using ERA5 reanalysis data, estimating their integrated water vapour transport (IWV) and vertically integrated vapour transport (vIVT) values, which are considered extreme if they exceed 95% of historical norms for the same location and time of year over a time interval that spreads from 1980 to 2022. Data obtained from AMSRE, AMSR2 & SMOS passive microwave sensors are used to generate time series and local maps of brightness temperature. These microwave signatures serve in the analysis of the possible spatial and temporal correlation between ARs events and sea ice and snow characteristics. Initial findings suggest that ARs and their subsequent gravity waves may significantly affect the wetting of sea ice and of the snow on it leading to increased melting of the MIZ. This study will improve the methods to inform models used to forecast the impact that extreme atmospheric events can have on sea ice and snow, offering new directions to investigate the coupled ocean-sea ice-atmosphere system in a changing climate.

Landfast ice plays a significant role in climate and ecosystems in Antarctic coastal regions. From October to December 2022, we investigated the physical properties of snow and sea ice on Antarctic landfast ice in McMurdo Sound, following the protocols from the MSOAiC expedition. Our measurements confirmed some findings from MOSAiC (e.g. the potential mass transfer from the sea ice surface to snow , the high spatial variability of snow depth}, and the discrepancy between meteorological snowfall and snow accumulation), but we also had observations that were contrasting our MOSAiC data, for example: 1) presence of salt up to 15 cm of snow height (as opposed to MOSAiC's 5 cm for a relatively similar total snow height), 2) the lack of the surface scattering layer on melting sea ice, which caused significantly lower albedos of bare sea ice (0.45, as opposed to MOSAiC's 0.65), 3) average densities of non-melting snow of 450 kg/m3 (as opposed to MOSAIC'S 350 kg/m3 ). Here, we will discuss the microCT measurements from our samples and relate them to the macroscale obervations of parameters like snow density, snow height, snow surface roughness, salinity or stable water isotopes. The main focus in this study in on the prevalance of a prominent depth hoar layer at the snow-ice interface, which we to be caused by the mass transfer between snow and ice because of the large vertical temperature gradients. This is also visible by the microscale roughness of the interface. Additionally, we will discuss the microstructure of the extremely dense wind slab that dominates most of the snow profile and the implications of these findings for modelling and remote sensing of snow on sea ice.

Species distribution models (SDMs) quantify the relationship between species presence and environmental factors. They are often used to guide conservation management plans, but limited availability of environmental and biological data in undersampled regions, such as the Southern Ocean, represent an important challenge preventing us from accurately estimating species distributions. We used a weighted ensemble of 4 SDMs to predict crabeater seal Lobodon carcinophagus distribution in East Antarctica. We combined georeferenced occurrence records from multiple open-source databases to fit an SDM ensemble. Environmental data from satellites and a high-resolution sea ice-ocean model were used to fit SDMs. Outputs were compared to evaluate if predicted crabeater seal distributions were similar. Sea-ice-related variables and the distribution of Antarctic krill, the main prey of crabeater seals, were identified as key drivers of crabeater seal distribution. The inclusion of prey in our SDMs improved their performance, highlighting the importance of predator-prey relationships. We emphasise the importance of including a comprehensive suite of ecologically relevant environmental predictors in SDMs, as a reduced set may not capture key drivers of distribution. We reiterate that prior to estimating habitat distribution for any species, an evaluation of the ability of an ocean model to realistically reproduce observed past environmental conditions within the area of interest is necessary. These steps add rigour to SDM development and build confidence when using high-resolution coupled ocean models to predict the fate of top-level predators and inevitably the ecosystem as a whole.

Snow cover on Antarctic sea ice is highly heterogeneous, yet climate models have historically simplified it to a uniform layer in winter and bare ice in summer, introducing uncertainty in simulated surface energy fluxes. Here, using shipborne, high-resolution, close-range imagery of the sea ice surface, visual observations, and concurrent atmospheric data from five expeditions across the Antarctic marginal ice zone (2019-2024), we show that fine-scale (sub-grid) snow cover heterogeneity persists across all seasons, is largely independent of ice concentration, and is governed by ice morphology and regional accumulation history. When the heterogeneity is incorporated into flux calculations, it introduces systematic biases in surface energy fluxes relative to uniform-surface assumptions. These findings, based on observations from two Southern Ocean sectors, suggest that the inclusion of sub-grid snow distribution should be considered for simulating Antarctic sea ice evolution and its broader polar climate feedback.

Antarctic ice-free coastal environments, like the Vestfold Hills (East Antarctica), are shaped by a complex interplay of physical processes. This study synthesizes new data and existing research from the Vestfold Hills across marine, terrestrial and cryosphere science, meteorology, geomorphology, coastal oceanography and hydrology to explore interconnected processes ranging from icescape morphology and sediment transport to ocean-floor scouring and ocean-atmosphere interactions. Coastal landforms and habitats result from the interaction of marine dynamics with the aeolian and fluvial transport of glacially derived sediments and geomorphic features. Rocky shorelines dominate the region, and extensive fjords are prominent coastal features, whereas intertidal sediments and beaches are scarce. The marine environment is characterized by slow currents, low-energy waves, annually variable land-fast ice, irregular sedimentation rates and a geomorphologically complex shoreline. Aeolian and fluvial sediment deposition into coastal waters and onto sea ice can significantly impact local ecological and physical processes. Human activity further modifies these dynamics. Ice-free coastal areas such as the Vestfold Hills are predicted to experience substantial environmental shifts due to climate change. Wind speeds, temperature and precipitation are increasing in the Vestfold Hills. Retreating grounded ice sheets are likely to expand this coastal area and increase meltwater and sediment inputs into nearshore marine systems. Concurrently, changes in sea-ice extent, thickness and/or duration may profoundly alter the structure and function of this coastal environment.

Abstract The Coupled Model Inter‐comparison Project Phase 6 (CMIP6) multi‐models predict future warming over Antarctica under five different scenarios, but their uncertainties remain high and have not been well constrained. Here we find that the projected Antarctic warming robustly correlates with simulated averaged temperature trends during 1958–2012 across the CMIP6 multi‐models under each scenario, which is thereby used to refine future air temperature projections using observation‐based temperature reconstruction. The median of future warming projections under the five scenarios reduces by 24%, 19%, 18%, 21%, and 21%, respectively. The constrained uncertainty ranges are narrowed down, with the likely range by the end of the century relative to 1850–1900 baseline declining from 4.2°C–6.8°C to 3.2°C–6.1°C under the highest emission scenario. The application of ERA5 for the same constraint shows an increase in future warming and constrained uncertainty ranges. This suggests a key role of observational data set uncertainties in the performance of emergent constraints.

Over the last decade, the Southern Ocean has experienced episodes of severe sea ice area decline. Abrupt events of sea ice loss are challenging to predict, in part due to incomplete understanding of processes occurring at the scale of individual ice floes. Here, we use high-resolution altimetry (ICESat-2) to quantify the seasonal life cycle of floes in the perennial sea ice pack of the Weddell Sea. The evolution of the floe chord distribution (FCD) shows an increase in the proportion of smaller floes between November and February, which coincides with the asymmetric melt–freeze cycle of the pack. The freeboard ice thickness distribution (fITD) suggests mirrored seasonality between the western and southern sections of the Weddell Sea ice cover, with an increasing proportion of thicker floes between October and March in the south and the opposite in the west. Throughout the seasonal cycle, there is a positive correlation between the mean chord length of floes and their average freeboard thickness. Composited floe profiles reveal that smaller floes are more vertically round than larger floes and that the mean roundness of floes increases during the melt season. These results show that regional differences in ice concentration and type at larger scales occur in conjunction with different behaviors at the small scale. We therefore suggest that floe-derived metrics obtained from altimetry could provide useful diagnostics for floe-aware models and improve our understanding of sea ice processes across scales.