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Microplastic (MP; plastic particles < 5 mm) pollution is pervasive in the marine environment, including remote polar environments. This study provides the first pan-Antarctic survey of MP pollution in Southern Ocean sea ice by analyzing sea ice cores from several diverse Antarctic regions. Abundance, chemical composition, and particle size data were obtained from 19 archived ice core samples. The cores were melted, filtered, and chemically analyzed using Fourier-transform infrared spectroscopy and 4,090 MP particles were identified. Nineteen polymer types were found across all samples, with an average concentration of 44.8 (± 50.9) particles·L-1. Abundance and composition varied with ice type and geographical location. Pack ice exhibited significantly higher particle concentrations than landfast ice, suggesting open ocean sources of pollution. Winter sea ice cores had significantly more MPs than spring and summer-drilled cores, suggesting ice formation processes play a role in particle incorporation. Smaller particles dominated across samples. Polyethylene (PE) and polypropylene (PP) were the most common polymers, mirroring those most identified across marine habitats. Higher average MP concentrations in developing sea ice during autumn and winter, contrasting lower levels observed in spring and summer, suggest turbulent conditions and faster growth rates are likely responsible for the increased incorporation of particles. Southern Ocean MP contamination likely stems from both local and distant sources. However, the circulation of deep waters and long-range transport likely contribute to the accumulation of MPs in regional gyres, coastlines, and their eventual incorporation into sea ice. Additionally, seasonal sea ice variations likely influence regional polymer compositions, reflecting the MP composition of the underlying waters.

Antarctic sea ice has exhibited significant variability over the satellite record, including a period of prolonged and gradual expansion, as well as a period of sudden decline. A number of mechanisms have been proposed to explain this variability, but how each mechanism manifests spatially and temporally remains poorly understood. Here, we use a statistical method called low-frequency component analysis to analyze the spatiotemporal structure of observed Antarctic sea ice concentration variability. The identified patterns reveal distinct modes of low-frequency sea ice variability. The leading mode, which accounts for the large-scale, gradual expansion of sea ice, is associated with the Interdecadal Pacific Oscillation and resembles the observed sea surface temperature trend pattern that climate models have trouble reproducing. The second mode is associated with the central Pacific El Niño–Southern Oscillation (ENSO) and the Southern Annular Mode and accounts for most of the sea ice variability in the Ross Sea. The third mode is associated with the eastern Pacific ENSO and Amundsen Sea Low and accounts for most of the pan-Antarctic sea ice variability and almost all of the sea ice variability in the Weddell Sea. The third mode is also related to periods of abrupt Antarctic sea ice decline that are associated with a weakening of the circumpolar westerlies, which favors surface warming through a shoaling of the ocean mixed layer and decreased northward Ekman heat transport. Broadly, these results suggest that climate model biases in long-term Antarctic sea ice and large-scale sea surface temperature trends are related to each other and that eastern Pacific ENSO variability is a key ingredient for abrupt Antarctic sea ice changes.

Maritime historical documentary sources of weather and state of sea surface including sea ice can aid in filling a known climate knowledge gap for the Southern Ocean and Antarctica for the first half of the 20th century. This study presents a data set of marine climate, sea ice and icebergs recovered from a collection of logbooks from mainly Norwegian whaling factory ships that operated in the Southern Ocean during 1929-1940. The data set comprises some 8000 weather and 4000 sea ice/open sea records from austral summers of the study period. This paper further discusses the structure and content of most common Norwegian maritime documentary sources of the period along with the practices of logging information relevant for the study, such as time keeping, positioning and making weather observations. An emphasis was made on recovery of notes on sea ice and icebergs and their interpretation in terms of WMO categories of sea ice concentration. Data, including ship-related metadata from all individual documents are homogenized and structured to a common machine-readable format that simplifies its ingestion into relevant climate data depositories.

Abstract In this study, the subseasonal Antarctic sea ice edge prediction skill of the Copernicus Climate Change Service (C3S) and Subseasonal to Seasonal (S2S) projects was evaluated by a probabilistic metric, the spatial probability score (SPS). Both projects provide subseasonal to seasonal scale forecasts of multiple coupled dynamical systems. We found that predictions by individual dynamical systems remain skillful for up to 38 days (i.e., the ECMWF system). Regionally, dynamical systems are better at predicting the sea ice edge in the West Antarctic than in the East Antarctic. However, the seasonal variations of the prediction skill are partly system-dependent as some systems have a freezing-season bias, some had a melting-season bias, and some had a season-independent bias. Further analysis reveals that the model initialization is the crucial prerequisite for skillful subseasonal sea ice prediction. For those systems with the most realistic initialization, the model physics dictates the propagation of initialization errors and, consequently, the temporal length of predictive skill. Additionally, we found that the SPS-characterized prediction skill could be improved by increasing the ensemble size to gain a more realistic ensemble spread. Based on the C3S systems, we constructed a multi-model forecast from the above principles. This forecast consistently demonstrated a superior prediction skill compared to individual dynamical systems or statistical observation-based benchmarks. In summary, our results elucidate the most important factors (i.e., the model initialization and the model physics) affecting the currently available subseasonal Antarctic sea ice prediction systems and highlighting the opportunities to improve them significantly.

Accurate satellite measurements of the thickness of Antarctic sea ice are urgently needed but pose a particular challenge. The Antarctic data presented here were produced using a method to derive the sea ice thickness from 1.4 GHz brightness temperatures previously developed for the Arctic, with only modified auxiliary data. The ability to observe the thickness of thin sea ice using this method is limited to cold conditions, meaning it is only reasonable during the freezing period, typically March to October. The Soil Moisture and Ocean Salinity (SMOS) level-3 sea ice thickness product contains estimates of the sea ice thickness and its uncertainty up to a thickness of about 1 m. The sea ice thickness is provided as a daily average on a polar stereographic projection grid with a sample resolution of 12.5 km, while the SMOS brightness temperature data used have a footprint size of about 35–40 km in diameter. Data from SMOS have been available since 2010, and the mission's operation has been extended to continue until at least the end of 2025. Here we compare two versions of the SMOS Antarctic sea ice thickness product which are based on different level-1 input data (v3.2 based on SMOS L1C v620 and v3.3 based on SMOS L1C 724). A validation is performed to generate a first baseline reference for future improvements of the retrieval algorithm and synergies with other sensors. Sea ice thickness measurements to validate the SMOS product are particularly rare in Antarctica, especially during the winter season and for the valid range of thicknesses. From the available validation measurements, we selected datasets from the Weddell Sea that have varying degrees of representativeness: Helicopter-based EM Bird (HEM), Surface and Under-Ice Trawl (SUIT), and stationary Upward-Looking Sonars (ULS). While the helicopter can measure hundreds of kilometres, SUIT's use is limited to distances of a few kilometres and thus only captures a small fraction of an SMOS footprint. Compared to SMOS, the ULS are point measurements and multi-year time series are necessary to enable a statistically representative comparison. Only four of the ULS moorings have a temporal overlap with SMOS in the year 2010. Based on selected averaged HEM flights and monthly ULS climatologies, we find a small mean difference (bias) of less than 10 cm and a root mean square deviation of about 20 cm with a correlation coefficient R > 0.9 for the valid sea ice thickness range between 0 and about 1 m. The SMOS sea ice thickness showed an underestimate of about 40 cm with respect to the less representative SUIT validation data in the marginal ice zone. Compared with sea ice thickness outside the valid range, we find that SMOS strongly underestimates the real values, which underlines the need for combination with other sensors such as altimeters. In summary, the overall validity of the SMOS sea ice thickness for thin sea ice up to a thickness of about 1 m has been demonstrated through validation with multiple datasets. To ensure the quality of the SMOS product, an independent regional sea ice extent index was used for control. We found that the new version, v3.3, is slightly improved in terms of completeness, indicating fewer missing data. However, it is worth noting that the general characteristics of both datasets are very similar, also with the same limitations.

The existence of ice-edge phytoplankton blooms in the Southern Ocean is well described, yet direct observations of the mechanisms of phytoplankton bloom development following seasonal sea-ice melt remain scarce. This study constrains such responses using biological and biogeochemical datasets collected along a coastal-to-offshore transect that bisects the receding sea-ice zone in the Kong Håkon VII Hav (off the coast of Dronning Maud Land). We documented that the biogeochemical growing conditions for phytoplankton vary on a latitudinal gradient of sea-ice concentration, where increased sea-ice melting creates optimal conditions for growth with increased light availability and potentially increased iron supply. The zones of the study area with the least ice cover were associated with diatom dominance, the greatest chlorophyll a concentrations, net community production, and dissolved inorganic carbon drawdown, as well as lower sea surface fugacity of CO2. Together, these associations imply higher potential for an oceanic CO2 sink due, at least in part, to more advanced bloom phase and/or larger bloom magnitude stemming from a relatively longer period of light exposure, as compared to the more ice-covered zones in the study area. From stable oxygen isotope fractions, sea-ice meltwater fractions were highest in the open ocean zone and meteoric meltwater fractions were highest in the coastal and polynya zones, suggesting that potential iron sources may also change on a latitudinal gradient across the study area. Variable phytoplankton community compositions were related to changing sea-ice concentrations, with a typical species succession from sympagic flagellate species (Pyramimonas sp. and Phaeocystis antarctica) to pelagic diatoms (e.g., Dactyliosolen tenuijunctus) observed across the study area. These results fill a spatiotemporal gap in the Southern Ocean, as sea-ice melting plays a larger role in governing phytoplankton bloom dynamics in the future Southern Ocean due to changing sea-ice conditions caused by anthropogenic global warming.

Model projections suggest that the continental shelf in the southern Weddell Sea may experience a shift from today's near-freezing temperature to a much warmer state, where warm water floods the shelf and basal melt rates beneath the Filchner Ronne Ice Shelf increase dramatically. Today, the Filchner Trough serves as a conduit for the southward flow of Warm Deep Water (WDW) during summer and, thus, requires continuous monitoring of its hydrographic conditions. An extensive network of moorings was installed at key sites along the inflow pathway from 2017 to 2021, to expand on existing mooring records starting in 2014. The moorings complemented with under-ice profiling floats reveal two inflow pathways, where WDW enters along the eastern flank of the Filchner Trough as well as through a smaller trough east of there. Within the observed period, 2017 and 2018 feature anomalously warm inflows. The inflow is regulated by the heaving of isopycnals over the continental slope, and the southward propagation toward Filchner Ice Shelf is two times faster during these warm years. Furthermore, the warm years coincide with low summer sea ice concentration, which enhances surface stratification through increased freshwater input and modifies sea ice-ocean stresses that both act to lift the warm water layer and increase the temperatures on the continental shelf. Finally, the recent record low sea ice conditions around the Antarctic emphasize the importance of our findings and raise concerns regarding a potentially increasing presence of WDW on the southern Weddell Sea shelf.

Did you know that ecosystems support the wellbeing of humans by simply existing? An ecosystem describes the living things in an area, their interactions, and their environment. The ways that ecosystems benefit the wellbeing of humans are called ecosystem services. There are several types of ecosystem services: supporting (they support animals and their homes), provisioning (they provide food and other materials), cultural (they support our hobbies and cultural activities, such as tourism and arts), or regulating (they regulate our climate, for example by taking up carbon dioxide). Understanding the importance of an ecosystem through its ecosystem services helps guide decisions regarding the environment, such as how much fishing or ship traffic should be allowed in an area, or if an area or species should be protected. In this article, we describe the specific ecosystem services of the sea ice and Southern Ocean around Antarctica.

Much of the Antarctic coast is covered by seasonal landfast sea ice (fast ice), which serves as an important habitat for ice algae. Fast-ice algae provide a key early season food source for pelagic and benthic food webs, and contribute to biogeochemical cycling in Antarctic coastal ecosystems. Summertime fast ice is undergoing a decline, leading to more seasonal fast ice with unknown impacts on interconnected Earth system processes. Our understanding of the spatiotemporal variability of Antarctic fast ice, and its impact on polar ecosystems is currently limited. Evaluating the overall productivity of fast-ice algae has historically been hampered by limitations in observations and models. By linking new fast-ice extent maps with a one-dimensional sea-ice biogeochemical model, we provide the first estimate of the spatio-seasonal variability of Antarctic fast-ice algal gross primary production (GPP) and its annual primary production on a circum-Antarctic scale. Experiments conducted for the 2005?2006 season provide a mean fast ice-algal production estimate of 2.8 Tg C/y. This estimate represents about 12% of overall Southern Ocean sea-ice algae production (estimated in a previous study), with the mean fast-ice algal production per area being 3.3 times higher than that of pack ice. Our Antarctic fast-ice GPP estimates are probably underestimated in the Ross Sea and Weddell Sea sectors because the sub-ice platelet layer habitats and their high biomass are not considered.