Snow depth and sea ice thickness in the Polar Regions are significant indicators of climate change and have been measured over several decades by ice-tethered buoys. However, sea ice temperature profiles measured by ice-tethered buoys are rarely used to infer snow depth and sea ice thickness owing to the lack of automatic discrimination algorithms, restricting the use of the data for sea ice thermodynamics studies. In this study, snow depth and sea ice thickness were retrieved through the measurements of sea ice temperature profiles using discrimination algorithms of the change point and the maximum likelihood detection methods. The data measured by 50 ice-tethered buoys were used to evaluate the accuracy of the results determined by the algorithm. Influences on the seasonal sea ice thermodynamic state, vertical interval of temperature sensors on the buoys, and initial ice thickness on the estimation errors were also evaluated. The performance of the discrimination algorithm for the data from the Arctic and Antarctic regions was also compared. There were no identifiable differences between the estimation errors from the Arctic and Antarctica. Increases in both the interval of the temperature sensors and the initial ice thickness enlarged the error for the estimation of ice thickness. A procedure developed in this study strengthens the potential application of measurements from the ice-tethered buoys only with the measurements of the vertical temperature profile of the layer of snow-covered ice, but not the measurements of ice basal and surface positions using acoustic sounding.

China has built four stations in Antarctica so far, and Zhongshan Station is the largest station among them. Continuous power supply for manned stations mainly relies on fuel. With the gradual increase in energy demand at the station and cost of fuel traffic from China to Zhongshan station in Antarctica, reducing fuel consumption and increasing green energy utilization are urgent problems. This research considers a standalone renewable energy system. The polar environments and renewable energy distribution of area of Zhongshan station are analyzed. The physical model, operation principle, and mathematical modeling of the proposed power system were designed. Low-temperature performance and state of charge (SOC) estimation method of the lead–acid battery were comprehensively tested and evaluated. A temperature control strategy was adopted to prevent the battery from low-temperature loss of the battery capacity. Energy management strategy of the power system was proposed by designing maximum power point tracking (MPPT) control strategies for wind turbine and PV array. The whole power system is broadly composed of a power generator (wind turbine and PV array), an uploading circuit, a three-phase rectifier bridge, an interleaved Buck circuit, a DC/DC conversion circuit, a switch circuit, a power supply circuit, an amplifier, a driver circuit, a voltage and current monitoring, a load, battery units and a control system. A case study in Antarctica was applied and can examine the technical feasibility of the proposed system. The results of the case study reveal that the scheme of standalone renewable energy system can satisfy the power demands of Zhongshan Station in normal operation.

Temperature profiles of sea ice have been recorded more than a few decades. However, few high-precision temperature sensors can complete the observation of temperature profile of sea ice, especially in extreme environments. At present, the most widely used sea ice observation instruments can reach an accuracy of sea ice temperature measurement of 0.1 °C. In this study, a multilayer sea ice temperature sensor is developed with temperature measurement accuracy from −0.0047 °C to 0.0059 °C. The sensor system composition, structure of the thermistor string, and work mode are analyzed. The performance of the sensor system is evaluated from −50 °C to 30 °C. The temperature dependence of the constant current source, the amplification circuit, and the analog-to-digital converter (ADC) circuit are comprehensive tested and quantified. A temperature correction algorithm is designed to correct any deviation in the sensor system. A sea-ice thickness discrimination algorithm is proposed in charge of determining the thickness of sea ice automatically. The sensor system was field tested in Wuliangsuhai, Yellow River on 31 January 2018 and the second reservoir of Fen River, Yellow River on 30 January 2018. The integral practicality of this sensor system is identified and examined. The multilayer sea ice temperature sensor will provide good temperature results of sea ice and maintain stable performance in the low ambient temperature.

Continuous power supply for unmanned and automatic observation systems without suitable energy-storage capabilities in the polar regions is an urgent problem and challenge. However, few power-supply systems can stably operate over the long term in extreme environments, despite excellent performance under normal environments. In this study, a standalone hybrid wind–solar system is proposed, based on operation analysis of the observing system in the Arctic Ocean, the polar environments, and renewable-energy distribution in the polar regions. Energy-storage technology suitable for cold regions is introduced to support the standalone hybrid wind–solar system. Mathematical models of the power system at low temperature are also proposed. The low-temperature performance and characteristics of lead–acid battery are comprehensively elucidated, and a dedicated charging strategy is developed. A hybrid wind–solar charging circuit is developed using a solar charging circuit, a wind turbine charging circuit, a driver circuit, a detection circuit, an analog-to-digital converter (ADC) circuit, and an auxiliary circuit. The low temperature stability of charging circuit is test from −50 °C to 30 °C. Temperature correction algorithm is designed to improve the efficiency of the power supply system. The power generation energy of the power system was simulated based on the monthly average renewable energy data of Zhongshan Station. A case study was applied to examine the technical feasibility of the power system in Antarctica. The five-month application results indicate that the power system based on renewable energy can maintain stable performance and provide sufficient power for the observing system in low ambient temperatures. Therefore, this power system is an ideal solution to achieve an environmentally friendly and reliable energy supply in the polar regions.

Ice density is an important physical parameter affecting the mechanical properties of ice. Due to bad field environments, the traditional density measurement method cannot achieve continuous monitoring of ice density. Therefore, the authors of this paper propose a new idea: to use the acoustic characteristics of ice to obtain ice density. The acoustic and physical properties of artificially frozen ice samples, with salinity values in the range of 0~8.5‰, were tested using a nonlinear high-energy ultrasonic testing system to explore the relationships among ice density, sound velocity, temperature, and salinity when the temperatures of the ice samples rose from −30 °C to −5 °C. The test results show that the freshwater ice density decreases from 915.5 kg/m³ to 911.9 kg/m³ when the ice temperature rises from −30 °C to −5 °C. The density of saltwater ice varies from 899.8 kg/m³ to 912.9 kg/m³. When the salinity remains the same, the density of an ice sample decreases with an increase in temperature and increases with an increase in sound velocity. When the ice temperature remains the same, the density of saltwater ice increases with an increase in salinity and decreases with an increase in sound velocity. Based on the test results, a prediction model of ice density with respect to sound velocity, temperature, and salinity is established. The root mean square error between the predicted values of the model and the measured values is 0.337 kg/m³, indicating that the prediction accuracy is high.