The key regions for formation of the Antarctic Bottom Water occupied in the Indian sector of the Southern Ocean. The salinity change of the region has a profound influence on the global climate change. EN4 reanalysis-gridded data, measured seal data, WOD18 data combined with atmospheric reanalysis and sea ice concentration data were all used to explore the sea surface salinity changes in the Indian sector of the Southern Ocean and the response to large-scale circulation anomaly. The observation and reanalysis data both illustrated a significant positive surface salinity anomaly occurred in the Antarctic coast since 2008, especially in the Indian sector. The surface positive salinity anomaly was mainly centered in the Darnley Polynya and the north of Shackleton Ice Shelf. The high salinity shelf water expanded northward from the Antarctic coast and deepened. Meanwhile, the upwelling of Circumpolar Deep Water became increasingly distinct. Our study showed that this positive salinity anomaly was connected with the Antarctic Oscillation (AAO) and the Indian Ocean Dipole (IOD). During the positive AAO and IOD phases, the westerly wind enhanced significantly in the Indian sector and promoted the formation of sea ice, which increased surface salt flux. The significant negative wind curl and low pressure anomaly resulted in the upwelling of salty Circumpolar Deep Water and maintained the positive salinity anomaly. Additionally, increased locally zonal wind shear and enhanced evaporation were important factors as well.

Beaufort Gyre (BG) had presented the significant changes associated with the complicated interactions between the Arctic air-ice-ocean system. In this paper, the observed McLane Moored Profiler data combined with the oceanic and atmospheric reanalysis datasets are used to discuss the influence of atmospheric momentum input on the BG long term changes. The BG exhibited the three different stages from 1980 to 2018 (1980−1995, 1996−2007, 2008−2018). The BG kept a stable state during the recent period (2008−2018). Compared with the first period (1980−1995), the BG strength reached up to 4.39×10⁻⁷, and increased nearly twice during the recent period. Meanwhile, the upper ocean processes showed the measurable discrepancies, such as the BG area expanded, gyre moved northwestward, and upper baroclinicity enhanced. Accordingly, the leading upper circulation mode had undergone a significant shift during these two periods. During the recent period, that is the leading Pacific sector mode played the main role in the upper circulation, while the basin mode receded the domination. Since the air-ocean stress represents the atmospheric momentum input process, our study indicated the summer air-ocean stress (August−October) increased remarkably and was even equivalent to the contribution of sea ice. The increased atmospheric momentum input may benefit to the mean kinetic energy increasing, together with the Ekman pumping enhancing and cold halocline deepening. Thus, the mentioned processes resulted in the BG obvious enhancement during the recent period. The southern Canada basin was the key area for the atmospheric momentum input.

The GPS radiosonde data obtained during the 6th to 9th Chinese National Arctic Research Expedition was used to analyze the spatial and temporal variation characteristics of boundary layer temperature inversions over the seasonal ice zone in Arctic. The results show that: (1) There were strong interannual and spatial changes in the temperature inversions. There were more strong inversions over the pack ice zone at high latitude. And the thickness of inversions and the temperature change through the inversions had a significant logarithmic relationship. (2) The main factors controlling inversion properties were various in different years. The differences in sea ice cover leaded to different characteristics of inversions. Surface melt, radiative cooling, multi-layer cloud and warm-air advection provided different degrees of contribution to inversions in different years. (3) There were different reasons over the open water and sea ice zone. Both surface melt and warm-air advection played a very important role in the formation of inversions in sea ice zone. However, radiative cooling was one of the main factors in the generation of inversions over the open water.

The evolution of atmospheric factors and sea ice growth of the Arctic high latitude region process are analyzed based on the data observed by the drifting automatic weather station over the period from August 2018 to May 2019. The evolution shows two different phases according to the sea ice drifting trajectory. The sea ice mainly drifted to the southeast in the first phase and drifted to the northeast in the second phase. The averaged air temperature and averaged relative humidity are −6.6℃ and 93% for the first phase and those are −29.3℃ and 76% for the second phase. The averaged pressure is higher in the second than that in the first phase. The sea ice drifting trajectory are mainly affected by the Beaufort High. The sea ice velocity from automatic weather station derived and NSIDC (National Snow and Ice Data Center) are compared and the result show that the zonal velocity is unanimous. The sea ice is mainly melting in the first and sea ice thickness show decrease in the first phase. The sea ice growth rate is −0.11 cm/d in August. The sea ice growth mainly occurs in the second phase. The sea ice growth rate is larger than 0.9 cm/d from January to March 2019. The largest monthly averaged sea ice growth rate is in March with the value of 1.1 cm/d and the sea ice keep growth until the end of the observation period.

Using RADASAT-2 sea ice SAR images, by the way of Prewitt, Sobel and Canny edge detection operators to calculate the sea ice perimeter in the image, and consider the influence of different image resolutions and different edge detection operators on the calculation results respectively. Combined with the ice lateral melting rate parameterization scheme, the sensitivity experiment of the lateral melting of sea ice to temperature was carried out, and the effect of image reconstruction resolution on the simulation results of sea ice lateral melting was analyzed. The results show that the best edge detection operator corresponding to different degrees of sea ice breakage in the image is different, and the best resolution is also different. Under the condition of only lateral melting, the melting area of sea ice increases exponentially with increasing temperature. The simulation trends of the three operators are basically the same. The Prewitt operator has the best simulation effect, and the corresponding optimal reconstruction resolution is 30 m×30 m, 65 m×65 m and 155 m×155 m.

The Nares Strait, located between Ellesmere Island, Canada and Greenland, is one of the important channels for the export of Arctic sea ice. The surface fresh water brought by the melting of these sea ice has a vital impact on the formation of deep water in the Baffin Bay and the Labrador Sea. However, due to its relatively narrow structure, there is no detailed study on the sea ice motion in this area. In this study, the daily Sentinel-1 images were used to extract the information of sea ice motion in the northern region of Nares Strait from September 2016 to August 2017, to show the motion process of ice floes in the strait, and to analyze the characteristics and influencing factors of ice floe motion combined with wind speed, current speed and other data. The results show that wind and current jointly dominate the motion of sea ice, with the correlation coefficients are 0.767 and 0.709, respectively. The multiple linear regression model established by wind speed, current speed and sea ice concentration with ice speed also has the complex determination coefficient reaching 0.727. Further analysis shows that both wind and sea current have relatively less influence on sea ice speed when their speed is relatively stable. The results of this study on the influence of wind and ocean currents on the process of sea ice motion can provide references for the study of ocean-atmospheric dynamics models.

Along with the global warming, the sea ice in the Arctic decreased rapidly, however the sea ice in the Antarctic has experienced a weak expansion. While many researchers are studying the mechanisms for this paradox in the Antarctic, the sea ice extent (SIE) began a rapid decline in 2016 and reached a record low in austral spring 2016. A rapid decrease of SIE anomaly occurred in December, with a 20.5% (2.13$ \times $10⁶ km²) reduction compared with the long-term (1981−2010) mean (10.41$ \times $10⁶ km²). It attracted a lot of attentions and scientists have investigated the causes of its occurrence from various aspects, such as the atmosphere circulations, the thermal state of the ocean, the polynya and so on. Their main results are summarized in this review. On the atmospheric aspect, the general circulation signals include a zonal height anomalies chain with wave number three during September and October, a Southern Annular Mode anomaly during November and December, and intensified cyclonic activity. The atmospheric zonal wave number three is modulated by the sea surface temperature anomalies in the tropical Pacific and Indian Ocean, and the Southern Annular Mode anomaly is mainly a result of downward weakening stratospheric polar vortex. On the ocean aspect, the upper ocean temperature is warmer than normal, and there is a large polynya in the Weddell Sea, which has the greatest area in the period of 1976−2016. However, it is difficult to identify the relative contributions of the external forcings of the climate system, the internal variability of the climate system, or their collaborative roles. We hope the summary can be useful to improve the understanding of the changes of Antarctic sea ice and its origins.

Based on one-dimensional sea ice column model Icepack, albedo and depth of melt pond were simulated. Atmospheric forcing data were collected from ICE06, a long-term ice station established during the Sixth Chinese National Arctic Research Expedition in 2014 in which the radiation and meteorological parameters of three melt ponds were continuously observed. In this paper, observed melt pond depth and thickness of sea ice under ponds were used as initial conditions. Furthermore, the calculation of sea ice freeboard in the melt pond scheme of level ice was improved by considering the effect of melt pond fraction. Consequently, by improving the formula of the maximum depth of melt pond above sea ice, simulation of melt pond albedo as well as other related parameters were successfully realized. Additionally, the inconsistency between the proportion coefficient of the incident solar radiation component and the weight coefficient of the corresponding albedo component was modified. The average errors between the simulated and observed albedo of the three ponds in the standard experiments were 0.01, 0.05 and 0.13, respectively. The sensitivity experiment results for the incident radiation proportion suggested that when the proportion of visible radiation increased by 8%, the simulation results of the melt pond albedo increased by 6%−8%. Results of the melt pond refreezing experiments suggested that when the thickness of lid ice is less than 0.02 m, the increase of simulated ice albedo is less than 0.006, resulting in a decrease of surface energy budget by about 1.1 W/m². It is pointed out that providing an accurate proportion of incident radiation is necessary to improve the simulation of Arctic sea ice albedo. Furthermore, there are still some physical processes which need to be improved in Icepack/CICE model such as melt pond surface refreezing schemes, surface heat budget calculation, surface snow blowing effect and so on.

The PHC, ECCO2, SODA, GECCO3 and CMIP6 data were used to analyze the horizontal distribution characteristics, seasonal variation and long-term trend of the Arctic Ocean heat content, and analyze the simulation ability of the CMIP6 models in this paper. The results show that the heat content of the Arctic Ocean shows obvious seasonal change, with the lowest in April and the highest in September. Under historical circumstances (1850−2014), compared with the observation and reanalysis data, the heat content of the upper 500 m of the CMIP6 models ensemble average (MME) is warmer in the Greenland Sea, colder in the Norwegian sea, Barents Sea and Eurasian Basin, while the whole water column heat content of MME is warmer in almost all regions of the Arctic Ocean, with the largest deviation in the Greenland Sea. CMIP6 models have a large deviation in the simulation of Arctic Ocean temperature profile, and the average temperature of MME is higher than the observation and reanalysis data at the depth of more than 1 000 m. In the future case (2015−2100), the simulation of ocean heat content of MME shows obvious Arctic Ocean warming, but most of the Chinese models show no obvious warming situation. BCC-CSM2-MR and BCC-ESM1 are poor in simulating the annual mean heat content of the Arctic Ocean, CIESM is poor in simulating the seasonal and interdecadal variations of ocean heat content, while FIO-ESM-2-0 is good in simulating the annual heat content of the upper 500 m, the seasonal and interdecadal variations of heat content of the Arctic Ocean.

Based on the CryoSat-2 L1B data for April 2017−2019, this study compares and analyzes the multi temporal and spatial scale differences of UCL13, DTU10, DTU13, DTU15 and DTU18 mean sea surface height (MSS) models and the Arctic sea ice freeboard retrieval. The differences of various mean sea surface height models and the sea ice freeboard retrieval are compared with UCL13. The experimental results show that the average absolute deviation range between different MSS models is 0.19−0.26 m as well as the standard deviation range is 0.55−0.57 m, among which the difference between DTU18 and UCL13 is the smallest. The mean absolute deviation range of sea ice freeboard retrieved by the other four MSS models is 0.50−0.79 cm with the standard deviation range is 1.17−1.74 cm. Compared to airborne Operation IceBridge (OIB) data, the correlation coefficients of sea ice freeboard retrieved by the five MSS models range from 0.70 to 0.71 with the root mean square error range is 7.7−7.8 cm. Therefore, the biases between various MSS models have little influence on sea ice freeboard retrievals in the entire Arctic region, since biases impact both the lead and ice floe height measurements in the same way, and thus cancel out. However, in the areas with sparse leads, such as the northern Canadian Islands and the Laptev Sea, the sea ice freeboard retrieved by different MSS models varies greatly.