Dinosaurs serve as excellent indicators in the study of the remarkable evolution of life. Their fossils are widely used for intercontinental stratigraphic correlation, providing crucial evidence for continental drift. In Antarctica, dinosaur fossils are mainly found in the continental sediments from the Beardmore Glacier area of the central Transantarctic Mountains and the marine sediments from James Ross Island in the Antarctic Peninsula. This paper presents a systematic summary of the species, distribution, and exposure of dinosaur fossils in Antarctica and examines the links between these dinosaurs and the evolution of Gondwana: (1) the dinosaurs found in the Beardmore Glacier area may have lived in the Early Jurassic under a seasonal dry climate in the river areas in the back-arc foreland basin; this corresponds to the initial break-up of Gondwanaland. (2) The dinosaurs found around James Ross Island lived in the Late Cretaceous under a warm and humid climate and were in a shallow-water delta in a backarc basin; this corresponds to the latter period of Gondwanaland during which the land masses separated completely.

To explore the cultivable microbial diversity in Antarctic offshore, this study employed traditional agar plate culture methods to isolate bacteria from marine sediment samples collected from 11 sites in the South Shetland Islands, the Cosmonaut Sea, and Prydz Bay during the 39th Chinese Antarctic Research Expeditions. A total of 882 bacterial strains were obtained. Through 16S rRNA gene sequencing and phylogenetic analysis, these strains were classified into 4 phyla, 5 classes, 54 genera, and 95 species, including 7 potential novel species. At five sites on the South Shetland Islands, a total of 39 genera were isolated, with Pseudoalteromonas being the dominant genus at station TY14 and Cellulophaga at station CJW01. The dominant genera of DA04A, DA03 and DA01 stations were all Sulfitobacter. At two sites in Prydz Bay (P1-06 and P1-12), 27 genera were isolated, with Croceibacter as the dominant genus. In the Cosmonaut Sea, 22 genera were isolated from four sites (CA1-10, C5-09, CD1-11, and CA1-09), all dominated by the genus Sulfitobacter. Additionally, 92 representative strains were selected for extracellular enzyme activity assays, including DNAase, amylase, lipase (Tween 20, 40, and 80), gelatinase, cellulase, fucoidanase, and caseinase. The results showed that 57.61% of the isolated strains exhibited activity in two or more kinds of enzymes, and most of the isolated strains had extracellular enzyme activities. These findings provide a reference for the utilization of Antarctic microbial resources and the development of cold-adapted enzymes.

Simultaneous nitrification and denitrification processes happened in marine sediments affect the nitrate (NO₃^–) cycling in the Ocean. Studies of nitrogen (N) transformation processes occurring in Bering Sea sediments are crucial for improving our understanding of the N cycling in polar and subpolar marine regions. In this study, we conducted preliminary analyses of nitrate and its stable nitrogen and oxygen isotopes (d¹⁵N-NO₃^–, d¹⁸O-NO₃^–) in the sediment pore water in Bering Sea sediments. Samples were extracted from sediment cores collected during the 5th Chinese Arctic Research Expedition from the Bering Sea Basin (BL-10) and the 7th Chinese Arctic Research Expedition from the Bering Sea shelf (B12). The results show that: (1) at BL-10 station, nitrate concentration in pore water was 0.61~22.52 μmol·L^–1, d¹⁵N-NO₃^– was 3.6‰~17.8‰, and d¹⁸O-NO₃^– was 10.5‰~20.9‰, suggesting coupling between nitrification-denitrification process. (2) At B12 station, the nitrate concentration in sediment pore water was 0.20~1.61 μmol·L^–1, in 0~2 cm d¹⁵N-NO₃^– was 10.3‰~16.4‰, d¹⁸O-NO₃^– was 13.2‰~19.7‰, which was significantly lower than that in bottom sea (18.60 μmol·L^–1). This indicates intense denitrification in the surface sediment pore water. (3) Denitrification appears to be more intense in shelf than in basin sediments because of the combined influence of water depth, primary productivity, and sediment organic carbon content.

Monthly measurements of ice shelf area and exploration of the spatiotemporal characteristics and factors influencing ice shelf extent improve our understanding of the mechanisms of ice shelf collapse. This study uses visual interpretation, coastline transition algorithms, and optical and synthetic aperture radar remote sensing images to extract data on ice shelf extent over the 284 months from January 2000 to August 2023. The periodic and seasonal characteristics of ice shelf area were examined. The influence of the Oceanic Niño index (ONI), the Southern Annular Mode (SAM), sea ice concentration (SIC), and sea surface temperature (SST) on ice shelf extent was analyzed. The results show that: (1) during the 24 years of the study period, the Dalk Ice Shelf experienced six “forward rapid retreat” cycles, each accompanied by strong El Niño or La Niña events. At the end of each cycle, the front edge of the ice shelf retreated to the area dominated by ice ridges with prominent topographical variations. (2) The retreat of the Dalk Ice Shelf exhibited clear seasonality. Retreat area was the largest in summer with maxima in March. In 2016, a strong El Niño year, the ice shelf experienced an abnormally rapid collapse event in winter. (3) Ice shelf area is significantly negatively correlated with SST (r=−0.35, p<0.01) and the magnitude of the correlation coefficient is modest. Ice shelf area is positively correlated with the SAM (r=0.26, p<0.01) with a small correlation coefficient. It is positively correlated with SIC (r=0.57, p<0.01) with a large coefficient. It is also positively correlated with the ONI (r=0.68, p<0.01).

Monitoring the spatial and temporal distribution of Arctic sea ice is important for improving our understanding of oceanic heat flux and sea-air mass exchange in the polar regions and for supporting the potential opening of Arctic shipping routes. Moderate resolution imaging spectroradiometer (MODIS) thermal infrared data, characterized by high spatial and temporal resolution and large coverage, are widely used to identify leads (ice-free waterways) in sea ice. However, there are significant discrepancies and uncertainties in the different products. This paper compares and evaluates the accuracy of three major thermal infrared lead products (the Willmes, Reiser, and Hoffman products, respectively) and analyzes lead extraction uncertainties and their sources. The results show that there are significant discrepancies between the daily lead areas in the three products, with the Willmes, Hoffman, and Reiser products extracting 53.1%, 106.0%, and 140.8% of the daily average lead area, respectively. There are three main sources of uncertainty in lead extraction: (1) narrow leads are inadequately extracted, resulting in misclassification rates exceeding 50% in all three products. (2) All three products are daily synthesis products that are based on the multiperiod thermal infrared data of a single day. Because of sea ice drift, the same lead is extracted repeatedly at different locations, resulting in overestimation of the width and area of rapidly drifting leads. (3) The Willmes and Reiser products are designed with a fuzzy cloud artifact filter (FCAF) to mitigate the effects of clouds and other high-temperature features on the extraction of ice-covered waterways. However, the different FCAF algorithms result in significant discrepancies in the extraction of the extent of ice-covered waterways. The results of this study can serve as a reference for the use of lead products in a variety of applications.

The Grove Mountains region in East Antarctica is one of the core areas for Chinese National Antarctic Research Expeditions. A high-precision Digital Elevation Model (DEM) for the region is important for supporting Antarctic expedition and glacier research. The ZY-3 satellite is a high-resolution optical stereo mapping satellite. Its images fully covers the core area of the Grove Mountains. This paper uses the triple linear-array stereo images to generate a high-resolution DEM for the Grove Mountains region (ZYDEM). Taking the elevation control points in the region as the reference, the elevation accuracy of ZYDEM is (−2.57± 8.15) m. Taking filtered ICESat-2 footprint data in the region as the reference, the elevation accuracy of ZYDEM is (0.47±2.03) m. The accuracy of ZYDEM is higher than that of common Antarctic DEMs, including BamberDEM, ICESatDEM, and TanDEM-XDEM, and is close to that of the Reference Elevation Model of Antarctica (REMA). The establishment and accuracy analysis of ZYDEM demonstrates the feasibility of using the ZY-3 satellite for the Antarctic region.

Totten Glacier is in the region that has undergone the most dramatic thinning in the East Antarctic ice sheet in recent years. The mass balance of this region may be affected by the hydrological activity of Totten₂—an active subglacial lake in the upstream catchment of the glacier—over a time scale of several decades. This study applied the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) to 57 Sentinel-1 radar images from April 2022 to March 2024 to monitor changes in the ice surface elevation of Totten₂ at a high spatiotemporal resolution. Results were compared with ICESat-2 ATL11 data. Over the study period, ice sheet elevation decreased continuously, indicating continuous draining of the lake. Close agreement between Sentinel-1 and ICESat-2 data demonstrates that SBAS-InSAR is an effective tool for monitoring subglacial lake activity at small spatiotemporal scales and for studying the hydrological activity of Antarctic subglacial lakes.

Using the data collected by the automatic weather stations along coastal East Antarctica in 2023, this study compares the performance of DHC2 (domestic) and HMP155A (imported) temperature and humidity sensors, as well as that of ZQZ-TSF (domestic) and Young 05106 (imported) wind sensors. The results show that: (1) the observations from both types of temperature and humidity sensors are highly approximate. The systematic deviation between the sensors is –0.15 ℃ and the major of the gross errors occurs in the range of –25 to –10 ℃. Systematic deviation for relative humidity (RH) is 0.45%, it decreases with the increase of RH at RH <80%, and increases with RH at RH >80%. (2) The observations from both types of wind sensors are essentially consistent.Systematic deviation for wind speed is as low as 0.02 m·s^–1, the major of the most gross errors occurs at wind speeds of 6~7 levels. As wind speed increases, measurements from the different sensors tend to converge and the number of gross errors reduces significantly. For wind direction, the systematic deviation is approximately –3.05°, consistency between the different sensors is high along the primary (east–southeast) and secondary (southeast) wind direction. At low wind speeds, the number of gross errors in wind direction increases, the number of gross errors in air temperature and RH also increase because of insufficient air mixing.

As the climate warms in the Arctic region, the sea ice extent (SIE) in the Arctic Ocean is rapidly decreasing and retreating northward, making Arctic sea ice forecasting increasingly important for scientific expeditions and commercial navigability assessments. This study utilizes hindcast data from the First Institute of Oceanography-Climate Prediction System (FIO-CPS) v1.0. After applying bias correction to the Arctic sea ice predictions, the system’s predictive capability for summer (June–September) Arctic sea ice extent and sea ice concentration (SIC) was evaluated. The evaluation results indicate that: (1) There is a systematic bias in the FIO-CPS v1.0 predictions of summer Arctic SIE. After bias correction, the prediction performance improves significantly, with the most notable improvement observed in July; (2) Following bias correction, FIO-CPS v1.0 demonstrates good performance in predicting Arctic SIE, with root mean square errors for both monthly and daily predictions below 0.5×10⁶ km², and anomaly correlation coefficients exceeding 0.7; (3) The prediction skill of FIO-CPS v1.0 is significantly higher than that of linear trend climatology predictions and, to some extent, superior to damped anomaly persistence predictions. However, this advantage gradually diminishes as the lead time increases; (4) During years with extremely low Arctic SIE, the prediction performance of FIO-CPS v1.0 is relatively weaker, but it still holds a significant advantage over linear trend climatology predictions; (5) After bias correction, FIO-CPS v1.0 also exhibits high predictive capability for SIC, with the root mean square error of predicted sea ice concentration generally below 30%.

On the basis of the refractive index gradient method, the Arctic planetary boundary layer height (PBLH) from 2007 to 2019 was estimated using radio occultation data from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellite and was verified using Integrated Global Radiosonde Archive radiosonde observations. The spatiotemporal variation of the PBLH was analyzed, focusing on the potential relationship between PBLH, temperature inversion characteristics, and low cloud fraction (Low CF). The results are as follows: (1) PBLH over land and ocean was the highest in summer, second highest in autumn, third highest in spring, and the lowest in winter. (2) The intensity and frequency of Surface-based inversion (SBI) are higher in winter and autumn than in spring and summer, whereas the intensity of elevated inversion (EI) is higher in winter and summer than in spring and autumn. The frequency of EI is higher in summer and autumn than in winter and spring. (3) The monthly mean variations of PBLH and those of SBI and EI intensities over land and ocean exhibit opposite trends. The monthly variations of PBLH and Low CF cover over land are the highest in summer and the lowest in winter, but there is no obvious relationship between PBLH and Low CF over ocean. (4) Between the anomalies in Low CF amount over land and PBLH anomalies, there is a significant negative correlation in spring and a positive correlation in autumn. For each season over land, the anomalies of Low CF amount are negatively correlated with the anomalies of SBI intensity, but are only positively correlated with the anomalies of EI intensity in summer. However, over the ocean, anomalies of Low CF amount are only significantly negatively correlated with SBI intensity anomalies in autumn.

The E-Layer Dominated Ionosphere (ELDI) is characterized by high electron density in the E-layer and occurs primarily in the polar regions. This paper used data from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellite to analyze the ionospheric electron density in the Antarctic region during winter for 2007—2010. Functional principal component analysis was used to identify the two principal components of ELDI events. k-means clustering was carried out to categorize the events. The results show that categories differ in terms of electron density profiles: some are bimodal while others are unimodal. Categories also differ significantly in terms of the geomagnetic latitude and time of dominant events. The distributions of the characteristic ionospheric parameters of different types of ELDI events were compared and analyzed and clear differences were found (p<0.05).

The convection of the Earth’s ionospheric plasma maps the large-scale convective circulation of the magnetosphere and the convective electric field in the polar ionosphere that is driven by the interaction between the solar wind and the Earth’s magnetic field; it is closely related to the coupling system between the interplanetary magnetic field and Earth’s magnetic field. SuperDARN is a radar network for the study of space weather phenomena in the Earth’s magnetosphere. It is an important source of polar ionospheric convection velocity data and is useful for studying ionospheric convection at mid- to high-latitudes. This paper employed the two-dimensional, fitted ionospheric convective velocity data obtained from 20 high-frequency coherent scattering radars in the SuperDARN network in the northern hemisphere in 2015 and 2016. Using the BP-Adaboost model, the FC-GRU model, and the ED-ConvLSTM spatiotemporal sequence model, a two-dimensional global prediction model of ionospheric convection velocity for 2 minutes was developed. Model input includes the three components of the interplanetary magnetic field, the six near-Earth space parameters of solar wind speed, solar wind density, and geomagnetic index, as well as the longitude and latitude corresponding to the echo point. Two-dimensional convection velocity is the model output. Independent datasets were used to evaluate the performance of the BP-Adaboost, FC-GRU, and ED-ConvLSTM spatiotemporal sequence models on the basis of the Root Mean Square Error (E_RMSE) and Mean Absolute Error (E_MAE) between predicted and measured values. The coefficient of determination R² was introduced to compare the performance of the three models. The results show that BP-Adaboost, the neural network model based on ensemble learning, has the smallest prediction error: (1) the E_RMSE for predictions of the magnitude and direction of convection velocity are 119.62 m·s^–1 and 62.23°, respectively; (2) the E_MAE for predictions of the magnitude and direction of convection velocity are 75.70 m·s^–1 and 41.80°, respectively; (3) the R² for predictions of magnitude and direction are 0.70 and 0.59, respectively. Relative to the FC-GRU and ED-ConvLSTM models, the performance of the BP-Adaboost model in predicting ionospheric convection velocity is superior in terms of E_RMSE, E_MAE, and R² values for both convection velocity magnitude and direction.

The polar icebreaker R/V Xuelong is an important platform for China’s polar scientific expeditions as well as China’s ability to deliver its projects in the polar regions. To facilitate scientific operations, the hull of R/V Xuelong is often oriented to create an area of open water—free of floes from the surrounding broken ice field—on one side of the ship. Currently, R/V Xuelong’s resistance to lateral pressure is often assessed on the basis of the experience of the ship operator without relevant theoretical or quantitative support. Against this backdrop, the present study uses the nonsmooth discrete element approach and develops an efficient numerical model based on the theory of rigid body dynamics and mixed compensation problems to simulate interactions between the ship and broken sea ice fields as well as the corresponding resistance to ice. Ice accumulation along the side of R/V Xuelong and corresponding increases in lateral pressure under different conditions were investigated. The simulation results indicate that: (1) the scale of ice accumulation and pressure along the hull is positively correlated with the sea ice friction coefficient, ice concentration, and relative ice speed; (2) ice resistance increased from 948.5 to 6102.3 kN as relative velocity was adjusted from 0.05, 0.2, 0.5 m·s⁻¹ to 0.15, 0.4, 1.5 m·s⁻¹. Ice resistance is the most strongly impacted by relative ice velocity; it is less impacted by ice concentration and the least impacted by the ice friction coefficient. This study provides a theoretical basis for evaluating and predicting R/V Xuelong’s resistance to lateral pressure during on-site operations in the polar regions, as well as offering technical support for the selection of operation sites and for ensuring the safety of operations.

The icing of equipment and pipelines on ships affects the structural strength, stability, and power systems of the vessels when navigating in the polar regions. Anti-icing technology based on electric heating is effective for addressing the icing of equipment and facilities on the upper decks. This study analyzes the relationship between the coating layer and the convective heat transfer coefficient of the round pipe and the thermal balance performance of the electric trace heating handrail pipe. The research findings indicate that: (1) the temperature increase of the surface of a coated pipe is higher than that in an uncoated pipe and heat stored in the wall is also higher. The coating layer can increase the thermal resistance for heat radiation from the pipe and reduce the convective heat transfer coefficient of the round pipe. (2) Within the environmental range of –40 to –10 ℃, the difference in surface temperature rise of handrail pipes is not significant. At the same temperature, when the wind speed increases from 5 m·s^–1 to 7 m·s^–1, the magnitude of its surface temperature rise decreases by approximately 24%. Additionally, the surface temperature rise of coated handrail pipes is generally about 30% higher than that of uncoated round pipes. (3) The coating layer has a certain insulation effect; it changes the convective heat transfer coefficient of the pipe surface. Under similar environmental conditions, the surface temperature of the coated handrail is 1~2 ℃ higher than that of the an uncoated, thereby improving the anti-icing effect.

With the intensified development of oil and gas resources and increasing oil transportation activities in the polar regions, the risk of oil spill accidents from ships has also increased. However, oil containment booms often fail in sea ice areas. To ensure navigation safety in sea ice areas and protect the fragile polar environment, this paper reports results of numerical experiments of oil containment by booms in ice-covered waters using the volume of fluid (VOF) and the Realizable k-ε turbulence model. Using different oil spill scenarios, the influence of factors such as boom depth, layout, water flow rate, and oil viscosity on containment was analyzed. The results show that: (1) with the increase of boom depth, the effective area of oil containment increases. The success rate of containment increases linearly with h. The time to entrainment failure increases and containment is more effective. (2) As the relative distance between the boom and the ice cover increases, the effect of the boundary layer on the fluid decreases. Oil droplets form. The success rate of containment increases linearly with D. The time to entrainment failure also increases, augmenting containment effectiveness. (3) As the water flow velocity increases, fluid kinetic energy also increases. The success rate of containment decreases linearly with u. The time to entrainment failure decreases and containment becomes less effective. (4) As the viscosity of the oil increases, the success rate of oil containment initially increases and then decreases. These results contribute to improving our understanding of oil containment by booms in the vicinity of sea ice, thereby providing information to support emergency responders in making decisions when addressing oil spill accidents in ice-covered waters.

This paper proposes an independent microgrid optimization configuration model comprising surplus solar hydrogen production and solar hydrogen storage in devices such as batteries and supercapacitors for Zhongshan Station. The special environment of Antarctica and the influence of low temperature on the power generation units are taken into consideration. The model has the following characteristics: (1) the system structure of the entire microgrid is analyzed and each device is simulated taking into consideration the real-time effects of the low temperature environment on the output of fans and solar panels, the capacity of batteries, the capacity of supercapacitors, and the power load. (2) The improved gray wolf algorithm was adopted to optimize the configuration of the microgrid for the polar environment. Constraints included the operating conditions of each equipment, the annual wind and light abandonment rate, and load loss rate. Continuous and reliable operation of the system and minimum annual average cost were the primary and secondary goals, respectively. (3) The proposed method was verified with a numerical experiment. Experimental results show that the proposed algorithm can be used to design a microgrid with a wide range and superior convergence and accuracy. The results of this study can serve as a reference for future developments.

The environmental conditions in the Arctic are complex and harsh, and iceberg drift poses a potential threat to the safety of long-term operation point facilities in the Arctic. This study evaluates the iceberg collision risk of Arctic long-term operation point facilities during stationary operations and proposes a Dynamic Bayesian Network (DBN)-based iceberg drift path prediction method. The method combines the iceberg drift equilibrium equation with the momentum conservation method to construct a network structure and realize the dynamic probabilistic prediction of the iceberg drift path. Through real-time environmental data updating, the model outputs the distance of the iceberg relative to the Arctic long-term operation point facilities, providing a quantitative basis for collision risk assessment. The risk scenario analysis based on the prediction results quantifies the collision risk at each time point using the utility function, which is of guiding significance for improving the risk assessment and safety protection capability of Arctic long-term operation point facilities.

To assess the implications of  the Arctic Northeast Passage (NEP) opening on China’s foreign trade pattern, this paper used the general equilibrium method and combined the shipping cost model with the Global Trade Analysis Project (GTAP) model, based on the scenarios about the different length of the navigation period of the NEP. Based on existing research, analysis of trade flow and trade structure, as well as dynamic prediction, are added in this paper. The research on the trade impact of the NEP is no longer limited to estimating the trade volume and static prediction. The results show that: (1) China’s foreign trade will benefit from the use of the NEP. In the short, medium, and long term, China’s export volume will increase by an average of 17.49%, 32.84%, and 40.58%. (2) There is a spatial differentiation in the impact of the NEP on the trade between China and different trading partners. For instance, the trade links between China and Russia, Northwestern Europe, and Central and Eastern Europe will be further strengthened. Without considering preferential trading arrangements between China and other trading partners, the scale of China’s exports to East Asia, Southeast Asia, North America, and other countries (regions) in the world may decrease to varying degrees. (3) The use of the NEP has an impact on China’s trade commodity structure, and there is sectoral heterogeneity. For example, in the short term, the export growth of each sector is between 0.40% and 7.23%, and the import growth is between 0.90% and 8.77%. (4) When the HFO ban pushes up the fuel price for the NEP shipping, the trade impact of the NEP will be weakened; when geopolitical conflicts lead to a general increase in the fuel price, the trade impact of the NEP will be strengthened significantly.

Owing to global climate change and Arctic amplification, Arctic sea ice is melting rapidly, significantly increasing the likelihood of routine commercial shipping along the Arctic shipping routes. The adoption of the Arctic routes has led to a substantial increase in trade potential between China and countries along the Northeast Passage. This study is based on the International Standard Industrial Classification (ISIC Rev4). It focuses on primary industries and 17 manufacturing sectors and calculates the value-added trade between China and the countries along the Arctic route using the method developed by Wang, Wei, and Zhu (WWZ). Additionally, it employs the intra-industry trade index and the modified revealed comparative advantage index (NRCA) to analyze the industrial complementarity between China and these countries. The results of the study show that: (1) China maintains a trade surplus with countries along the Arctic route in primary industries and the 17 manufacturing sectors. Relative to traditional measures of trade, trade in value added reveals a smaller trade surplus for China. (2) There is significant industrial complementarity between China and the countries along the Arctic route. In terms of labor-intensive industries, China demonstrates a clear competitive advantage in textile and garment manufacturing. In terms of technology-intensive industries, China holds a stronger competitive edge in the fields of computer, electronic, and optical equipment, whereas countries such as Denmark and Belgium have a more pronounced competitive advantage in the pharmaceutical manufacturing sector.