Iceberg-induced snowdrift formation on Antarctic landfast sea ice: effects of wind and iceberg size

The state of research on snow mass balance over sea ice has advanced in recent years, with significant progress in understanding the complex snow-ice interactions. However, challenges remain in accurately assessing the snow depth variability over sea ice in both space and time, particularly when considering the effect of snow transport by wind. In Antarctica, the calving of ice shelves generates icebergs that get trapped in landfast sea ice and act as obstacles to drifting snow. By accumulating snow around them, icebergs may influence the dynamics of land-fast ice in coastal areas but their precise impact on the mass balance and spatial distribution of snow remains uncertain. Drifting snow models are valuable for isolating the geometric properties of obstacles and independently examining their impact on snowdrifts. In our study, we investigate the effect of iceberg geometry on snowdrift quantities by combining aerial laser scanner observations and numerical Euler-Lagrange simulations. Properties such as iceberg size, roundness and elongation were evaluated and the model outcome was compared to the observations. Results show that the size of icebergs governs the snowdrift quantities, while other shape characteristics mostly affect the snow distribution across the iceberg sides. A new scaling law has been discovered, revealing a clear power-law relationship between the size of snowdrifts and icebergs. Our work improves the understanding of drifting snow processes over Antarctic land-fast ice, particularly the impact of large-scale features on the snow distribution. It can offer deeper insights into the comparison of regions with small and large icebergs, along with their associated land-fast ice characteristics and help to quantitatively predict sea ice dynamics.

In 2016, Antarctic sea ice experienced a regime shift when a persisting decreasing trend emerged from a relatively stable annual cycle. Drivers of the sea ice regime shift and future projections of Southern Ocean sea ice remain unresolved. One possible contributing phenomena are atmospheric rivers (ARs), which are long, narrow, and transient features responsible for the majority of global poleward water vapor transport. Though infrequent over Antarctica, ARs wield a substantial influence on the Antarctic ice mass balance. Previous studies highlight their significance, attributing 35% of the interannual precipitation variability over the Antarctic Ice Sheet (AIS) to ARs. The interaction between ARs and Antarctic sea ice has not been as clearly defined. Our ongoing work uses ERA5 reanalysis data, results from an AR tracking algorithm, and passive microwave sea ice concentration data from 1980 to 2023 to examine the relationship between ARs and Antarctic sea ice, especially in the context of the changing sea ice state. In this study, we explore the relationship between AR activity and sea ice area at a region and seasonal scale, then analyse the contribution of ARs to precipitation over sea ice and how that contribution has changed through the 40-year study period. On average, ARs can be attributed with 11% of total precipitation, 11% of snowfall, and 13% of rain over Antarctic sea ice. While the AR contribution to sea ice snowfall is fairly consistent through the year, the predominant AR contribution to rain rotates around the Southern Ocean sequentially by season. The strongest signal of AR precipitation over sea ice is in the Weddell Sea winter, when ARs constitute 25% of winter rain. The trends of these contributions vary by season and by region. For example, while AR precipitation on sea ice has an increasing trend across all types of precipitation in each season in the Weddell Sea, the opposite is true for the Ross Sea. These findings underscore the importance of the AR interaction with Antarctic sea ice, particularly in the context of seasonal and regional variability and change. This work will improve our understanding of the spatiotemporal variability and trends of ARs as precipitation mechanisms, which is vital for understanding and predicting sea ice mass balance in a changing climate.

Simulating the mass balance and salinity of Arctic and Antarctic sea ice. 2. Importance of sea ice salinity variations

Historical sea ice core chlorophyll‐a (Chla) data are used to describe the seasonal, regional, and vertical distribution of ice algal biomass in Antarctic landfast sea ice. The analyses are based on the Antarctic Fast Ice Algae Chlorophyll‐a data set, a compilation of currently available sea ice Chla data from landfast sea ice cores collected at circum‐Antarctic nearshore locations between 1970 and 2015. Ice cores were typically sampled from thermodynamically grown first‐year ice and have thin snow depths (mean = 0.052 ± 0.097 m). The data set comprises 888 ice cores, including 404 full vertical profile cores. Integrated ice algal Chla biomass (range: <0.1–219.9 mg/m2, median = 4.4 mg/m2, interquartile range = 9.9 mg/m2) peaks in late spring and shows elevated levels in autumn. The seasonal Chla development is consistent with the current understanding of physical drivers of ice algal biomass, including the seasonal cycle of irradiance and surface temperatures driving landfast sea ice growth and melt. Landfast ice regions with reported platelet ice formation show maximum ice algal biomass. Ice algal communities in the lowermost third of the ice cores dominate integrated Chla concentrations during most of the year, but internal and surface communities are important, particularly in winter. Through comparison of biomass estimates based on different sea ice sampling strategies, that is, analysis of full cores versus bottom‐ice section sampling, we identify biases in common sampling approaches and provide recommendations for future survey programs: for example, the need to sample fast ice over its entire thickness and to measure auxiliary physicochemical parameters.

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

Snow depth and sea ice thickness were observed applying an ice mass balance buoy (IMB) in the drifting ice station
\nTara during the International Polar Year in 2007. Detailed in situ observations on meteorological variables and surface fluxes were
\ntaken during May to August. For this study, the operational analyses and short-term forecasts from two numerical weather
\nprediction (NWP) models (ECMWF and HIRLAM) were extracted for the Tara drift trajectory. We compared the IMB,
\nmeteorological and surface flux observations against the NWP products, also applying a one-dimensional thermodynamic sea ice
\nmodel (HIGHTSI) to calculate the snow and ice mass balance and its sensitivity to atmospheric forcing. The modelled snow depth
\ntime series, controlled by NWP-based precipitation, was in line with the observed one. HIGHTSI reproduced well the snowmelt
\nonset, the progress of the melt, and the first date of snow-free conditions. HIGHTSI performed well also in the late August freezing
\nseason. Challenges remain to model the “false bottom” observed during the melting season. The evolution of the vertical
\ntemperature profiles in snow and ice was better simulated when the model was forced by in situ observations instead of NWP
\nresults. During the melting period, the nonlinear ice temperature profile was successfully modelled with both forcing options.
\nDuring spring and the melting season, total sea ice mass balance was most sensitive to uncertainties in NWP results for the
\ndownward longwave radiation, followed by the downward shortwave radiation, air temperature, and wind speed.

Comparison of Arctic and Antarctic sea ice spatial–temporal changes during 1979–2018

Although snow plays an important role in the energy and mass balance of sea ice, it is little studied in the Southern Ocean. We present a Lagrangian model of snow on sea ice, CASSIS, that simulates the daily creation and drift of floes. Drifting floes accumulate snow from the atmosphere and the Antarctic ice sheet, and lose snow to the ocean and snow‐ice formation. The depth of snow on Southern Ocean sea ice increases in all sectors between autumn and spring 1981–2021, reaching 40 cm in much of the Weddell Sea, coastal Amundsen Sea and south east Indian Ocean. The root mean square difference between seasonally‐averaged model and ship‐based snow depths is 13.1 cm, and between modeled and airborne snow depths from Operation IceBridge is 13.5 cm. Our model offers an alternative long‐term snow depth record to that from passive microwave (PM) radiometry, which does not capture the seasonal growth of the snow cover. We find that although the average circumpolar snow layer thickness has increased by 16 mm between 1981 and 2021 ( P = 0.004), there has been a decrease of 13 mm in the Southern Pacific Ocean ( P = 0.133, but significant in spring and autumn), driven by a reduction of summer sea ice extent in this region. Our model paves the way for improved satellite‐based estimates of Antarctic sea ice thickness.

Calcium carbonate precipitation in sea ice is thought to potentially drive significant CO2 uptake by the ocean. However, little is known about the quantitative spatial and temporal distribution of CaCO3 within sea ice, although it is hypothesized that high quantities of dissolved organic matter and/or phosphate (common in sea ice) may inhibit its formation. In this quantitative study of hydrous calcium carbonate as ikaite, sea ice cores and brine samples were collected from pack and land fast sea ice between September and December 2007 during two expeditions, one in the East Antarctic sector and the other off Terre Adélie. Samples were analysed for CaCO3, salinity, dissolved organic carbon/nitrogen, inorganic phosphate, and total alkalinity. No relationship between these parameters and CaCO3 precipitation was evident. Ikaite was found mostly in the uppermost layers of sea ice with maximum concentrations of up to 126 mg ikaite per litre melted sea ice being measured, although both the temporal and horizontal spatial distributions of ikaite were highly heterogeneous. The precipitate was also found in the snow on top of the sea ice at some of the sampling locations.

Intercomparisons of Antarctic sea ice types from visual ship, RADARSAT-1 SAR, Envisat ASAR, QuikSCAT, and AMSR-E satellite observations in the Bellingshausen Sea

<h3><span>Snow cover is a primary control on Antarctic sea ice mass balance as it controls basal ice growth and snow ice formation. It is also a primary control on the surface energy budget, partitioning of solar radiation, and sea ice biological communities. Finally, knowledge of its distribution is critical for accurate estimation of sea ice thickness from satellite altimeters. The floe-scale distribution of snow is highly variable, driven by wind redistribution over complex sea ice surface topography. Yet, our understanding of the seasonal evolution of snow depth distribution is poor and its representation in models is simple or non-existent.</span></h3><h3><span>We present observations of the three-dimensional distribution of snow depth, ice thickness, and surface topography from a suite of cruises in the Weddell, Bellingshausen, Ross, and East Antarctic Seas that span the full growth season – from autumn, through winter, to late spring. The distribution of snow depth changes from a right-skewed distribution in autumn as snow initially accumulates around ridges to a gaussian by spring as snow deepens and ice surface topography roughens. While the distribution is spatially complex, the spectral distribution of snow features is similar across seasons. Using these data we construct a simple statistical model for the seasonal evolution of floe-scale snow depth distribution. We also compare our results to prior observations from drilling transects and larger-scale airborne observations from NASA’s Operation IceBridge. For the latter we use a convolutional neural network to demonstrate that the surface topography can be used as a reliable predictor of the snow depth distribution at regional scales.</span></h3>

Synoptic mode of Antarctic summer sea ice superimposed on interannual and decadal variability

Changes in the Antarctic ice sheet play a critical role in the Southern Ocean and global climates. Although many studies have pointed out that enhanced ocean heat delivery onto the Antarctic continental shelf regions can cause significant changes in Antarctic ice-shelf basal melting, the associated physical mechanisms require further research. Here, we perform numerical experiments using an ocean–sea ice model with an ice-shelf component to simulate future projections in Antarctic ice-shelf basal melting in a warming climate, focusing on the driving mechanism and the physical linkages with the seasonal Antarctic sea ice fields and coastal water masses. The model projects a distinct superlinear response of ice-shelf basal melting to future atmospheric warming, demonstrating that future projections of the Antarctic and Southern Ocean climate bifurcate with the level of global warming. Detailed examinations of sea ice and water masses show that in an extreme warming scenario, a combination of enhanced intrusions of warm deep water and warm summertime surface water can cause the nonlinear response of Antarctic ice-shelf basal melting. A large reduction in Antarctic coastal sea ice and the associated ocean freshening by decreasing coastal sea ice production in winter provide favorable conditions for summertime warm surface water formation and warm deep water intrusions onto some continental shelves. The model results demonstrate that disappearing summertime sea ice along the Antarctic coastal margins in a warming climate heralds the nonlinear increase in Antarctic ice-shelf basal melting, presumably contributing to the negative mass balance of the Antarctic ice sheet and the sea level rise.

The changes invoked in the Southern Ocean physics are dynamically linked to Southern Hemisphere westerlies, ocean currents, and Antarctic sea ice distribution. Therefore, it is necessary to understand the response of the Southern Ocean dynamics to the Antarctic sea ice distribution on a basin scale. This modeling study employs a fully coupled Earth system model to investigate the effect of Antarctic Sea ice distribution on the Southern Ocean Overturning circulation during the past twenty thousand years before the present. The simulation shows that the Southern Ocean surface buoyancy flux influences the Southern Ocean overturning circulation. The results indicate that the formation and melting of Antarctic sea ice feedback affect the coverage of surface buoyancy flux over the Southern Ocean. The simulated sea ice boundary (ocean surface area covered with more than a 5% sea ice fraction) almost demarcates the boundary between the upper and lower meridional overturning cells in the Southern Ocean. The Antarctic quasi-permanent sea ice boundary (ocean surface area covered with more than eighty percent sea ice fraction) overlaps with the transition of surface buoyancy flux from positive (surface buoyancy gain) to negative (surface buoyancy loss). Moreover, similar to the Antarctic sea ice coverage, the negative surface buoyancy flux zone has displaced polewards for the past twenty thousand years except for about 14.1 thousand years. Our study highlights that the melting and formation of Antarctic sea ice modulates the Southern Ocean surface buoyancy flux, which affects the Southern Ocean Overturning circulation.

Dimethylsulphide and dimethylsulphoniopropionate in Antarctic sea ice and their release during sea ice melting