Simulating and predicting Arctic sea ice accurately remains an academic focus due to the complex and unclear mechanisms of Arctic sea ice variability and model biases. Meanwhile, the relevant forecasting and monitoring authorities are searching for models to meet practical needs. Given the previous ideal performance of cGENIE model in other fields and notable features, we evaluated the model's skill in simulating Arctic sea ice using multiple methods and it demonstrates great potential and combined advantages. On this basis, we examined the direct drivers of sea-ice variability and predicted the future spatio-temporal changes of Arctic sea ice using the model under different Representative Concentration Pathways (RCP) scenarios. Further studies also found that Arctic sea ice concentration shows large regional differences under RCP 8.5, while the magnitude of the reduction in Arctic sea ice thickness is generally greater compared to concentration, showing a more uniform consistency of change.

The Atlantic Meridional Overturning Circulation (AMOC) is a crucial system influencing regional and even global climate changes, with the Subpolar North Atlantic (SPNA) being a key region affecting this system. In the context of global climate change, the impact and mechanisms of aerosols on the AMOC remain unclear. This study, based on state-of-the-art ensemble model simulations paired with latest observations, reveals that aerosols in the SPNA region significantly influence sea surface temperature anomalies by affecting cloud cover, which in turn affects ocean stratification, thus impacting the strength of the AMOC. Based on this, we present the trends and spatiotemporal characteristics of future AMOC under different forcings. Our research contributes to a deeper understanding and prediction of the AMOC.

The 44 years (1979–2022) of satellite-derived sea ice extent in the Arctic and Antarctic reveals the details and new trends in the process of polar sea ice coverage changes. The speed of Arctic sea ice extent reduction and the interannual difference significantly increased after 2004. Trend analysis suggests that the Arctic Ocean may experience an ice-free period around 2060. The maximum anomaly of Arctic sea ice extent has gradually transitioned from September to October, indicating a trend of prolonged melting period. The center of gravity of sea ice in the Arctic Ocean is biased towards the Pacific side, and the spatial distribution pattern of sea ice is greatly influenced by the Atlantic warm current. The dynamism of the sea ice extent on the Atlantic side is significantly greater than in other regions. Since 2014, the Antarctic sea ice extent has shifted from slow growth to a rapid decreasing trend; the sea ice extent reached a historical minimum in 2022, decreasing by 2.02 × 106 km2 compared to 2014. The Antarctic experiences seven months of ice growth each year and five months of ice melting period, the annual change patterns of sea ice extent in the Arctic and Antarctic are slightly different.

Occurrence of persistent organic pollutants (POPs) in the Polar Regions has received great concern in the past several decades due to their long-term adverse effect on biological health in such a fragile environment. However, there is still argument over their source and fate in these pristine areas. Here we attempted to use a novel approach (compound-specific isotope analysis of chlorine, CSIA-Cl) to identify the source of POPs in Antarctic air by comparison with the source area. The results showed that the relative isotope-ratio variation of Cl (δ37Cl′) values showed a large variation from − 137 to 9.04 ‰ in the gas-phase samples, and a significantly negative correlation (p < 0.01) was obtained against the logKoa values of PCBs. There were no significant correlations (p > 0.05) observed between the δ37Cl′ values and meteorological parameters except for PCB-28 which showed temperature dependence. By contrast, the δ37Cl′ values in the urban (Beijing) air ranged from − 12.8 to 2.03 ‰. The larger variation of δ37Cl′ in Antarctic air indicated evidently influence of long-range atmospheric transport (LRAT) on isotopologue fractionation of PCBs. This study may shed light on the application of CSIA-Cl for source identification of chlorinated POPs on a large scale.

Sea ice export through the Baffin Bay plays a vital role in modulating the sea ice cover variability in the Labrador Sea. In this study, satellite-derived sea ice products are used to obtain the sea ice area flux (SIAF) through the three passages in the Baffin Bay (referred to as A, B, and C for the north, middle, and south passages, respectively). The spatial variability of the monthly sea ice drift in the Baffin Bay is presented. The interannual variability and trends in SIAF via the three passages are outlined. The connection to several large-scale atmospheric circulation modes is assessed. Over the period of 1988–2015, the average annual (October to the following September) SIAF amounts to 555×103 km2, 642×103 km2, and 551×103 km2 through Passages A, B, and C, respectively. These quantities are less than that observed through the Fram Strait (FS, 707×103 km2) of the corresponding period. The positive trends in annual SIAF, on the order of 53.1×103 km2/(10 a) and 43.2×103 km2/(10 a) (significant at the 95% confidence level), are identified at Passages A and B, respectively. The trend of the south passage (C), however, is slightly negative (−13.3×103 km2/(10 a), not statistically significant). The positive trends in annual SIAF through the Passages A and B are primarily attributable to the significant increases after 2000. The connection between the Baffin Bay sea ice export and the North Atlantic Oscillation is not significant over the studied period. By contrast, the association with the cross-gate sea level pressure difference is robust in the Baffin Bay (R equals 0.69 to 0.71, depending on the passages considered), but relatively weaker than that over FS (R=0.74).

Organophosphate esters (OPEs) were comprehensively investigated in the air samples collected using high-volume samplers near the Chinese Great Wall Station in the Western Antarctic Peninsula over the period of 2014-2018. The concentrations of Sigma 8OPEs (gaseous thorn particle phases) ranged from 33.9 to 404 pg/m(3) with a geometric mean of 119 +/- 12.0 pg/m(3). Tris [(2R)-1-chloro-2-propyl] phosphate (TCIPP) and tris(2-chloroethyl) phosphate (TCEP) dominated in the gaseous phase, while tris-n-butyl phosphate (TnBP) was the most abundant OPEs in the particle phase, followed by TCIPP and TCEP. An apparently temporal trend was observed for atmospheric Sigma 8OPEs over the five years, with a doubling time of about 3.8 years, which indicated continuous inputs of OPEs into the sampling area. The particle-bound Sigma 8OPEs accounted for 45% of the total, generally lower than that reported in the Arctic. Gas-particle partitioning modeling suggested that the partitioning of OPEs with higher logK(OA) values approached the steady state in the Antarctic air. The back-trajectory modeling showed that high levels of OPEs were usually associated with air inputs from the northwest of the peninsula. This suggested that long-range transport from South America, which was confirmed by the no temperature dependencies of OPEs concentrations (excluding TnBP). Nevertheless, a steady high level of particle-bound TnBP implied local sources in the Western Antarctic Peninsula, which required further investigation in future works. (C) 2020 Elsevier Ltd. All rights reserved.

Novel brominated flame retardants (NBFRs) were comprehensively investigated in both gaseous and particle phase samples collected using a high-volume active air sampler (HV-AAS) at the Chinese Great Wall Station in King George Island, West Antarctica from 2011 to 2018. The concentrations of Sigma(12)NBFRs ranged from 0.27 to 3.0 pg m(-3), with a mean value of 1.1 +/- 0.50 pg m(-3) and the levels showed a slightly increasing trend over the eight years. Decabromodiphenyl ethane (DBDPE) was the predominant NBFR with a relative contribution of 50% on average. Most of the studied NBFRs tended to distribute in gaseous phase with an average ratio of 72 +/- 16% while NBFRs with higher log K-OA values had higher proportions in particle phase. The gas/particle partitioning models were employed to evaluate the environmental behavior of NBFRs. Compared to the equilibrium-state-based model, the steady-state-based model performed much better to predict the gas/particle partitioning of NBFRs in the West Antarctic atmosphere. Additionally, no temperature dependence was found for NBFRs except rac-(1R,2R,5R,6R)-1,2,5,6-tetrabromocyclooctane (beta-TBCO). The annual mean concentrations of Sigma(12)NBFRs showed a significantly negative correlation with the frequency of east-southeast (ESE, 112.5 degrees) wind and calm wind (similar to 0 m s(-1)) (p < 0.05), and a significantly positive correlation with the frequency of wind from northwest interval (west to north-northwest, 270 degrees to 337.5 degrees) (p < 0.05), suggesting a significant effect of air mass from the ocean area. Furthermore, the chiral signature of NBFRs showed commonly non-racemic residue in the atmosphere. The enantiomer fractions (EF) of rac-(1R,2R)-1,2-dibromo-(4S)-4-((1R)-1,2-dibromoethly) cyclohexane (alpha-TBECH) and beta-TBCO were 0.115-0.962 and 0.281-0.795, revealing secondary sources of NBFRs, e.g., seawater-air exchange and/or non-racemic residue in the source regions. As far as we know, this is one of very few studies on NBFRs in the Antarctic atmosphere. (C) 2020 Elsevier B.V. All rights reserved.

Baffin Bay serves as a huge reservoir of sea ice which would provide the solid freshwater sources to the seas downstream. By employing satellite-derived sea ice motion and concentration fields, we obtain a nearly 40-year-long record (1978–1979 to 2016–2017) of the sea ice area flux through key fluxgates of Baffin Bay. Based on the estimates, the Baffin Bay sea ice area budget in terms of inflow and outflow are quantified and possible causes for its interannual variations and trends are analyzed. On average, the annual (September–August) inflows through the northern gate and Lancaster Sound are on the order of 205.8(±74.7)×103 km2 and 55.2(±17.8)×103 km2. In particular, a comparison with published results seems to suggest that about 75 %–85 % of the inflow through the northern gates is newly formed ice produced in the recurring North Water Polynya (NOW), in addition to the inflow via Nares Strait and Jones Sound. Meanwhile, the mean outflow via the southern gate approaches 394.3(±110.2)×103 km2. The distinct interannual variability for ice area flux through the northern gate and southern gate is partly explained by wind forcing associated with cross-gate sea level pressure difference, with correlations of 0.62 and 0.68, respectively. Also, significant increasing trends are found for the annual sea ice area flux through the three gates, amounting to 38.9×103, 82.2×103, and 7.5×103 km2 decade−1 for the northern gate, southern gate, and Lancaster Sound. These trends are chiefly related to the increasing ice motion, which is associated with thinner ice owing to the warmer climate (i.e., higher surface air temperature and shortened freezing period) and increased air and water drag coefficients over the past decades.

Arctic sea ice cover has decreased dramatically over the last three decades. This study quantifies the sea ice concentration (SIC) trends in the Arctic Ocean over the period of 1979–2016 and analyzes their spatial and temporal variations. During each month the SIC trends are negative over the Arctic Ocean, wherein the largest (smallest) rate of decline found in September (March) is -0.48%/a (-0.10%/a). The summer (-0.42%/a) and autumn (-0.31%/a) seasons show faster decrease rates than those of winter (-0.12%/a) and spring (-0.20%/a) seasons. Regional variability is large in the annual SIC trend. The largest SIC trends are observed for the Kara (-0.60%/a) and Barents Seas (-0.54%/a), followed by the Chukchi Sea (-0.48%/a), East Siberian Sea (-0.43%/a), Laptev Sea (-0.38%/a), and Beaufort Sea (-0.36%/a). The annual SIC trend for the whole Arctic Ocean is -0.26%/a over the same period. Furthermore, the infl uences and feedbacks between the SIC and three climate indexes and three climatic parameters, including the Arctic Oscillation (AO), North Atlantic Oscillation (NAO), Dipole anomaly (DA), sea surface temperature (SST), surface air temperature (SAT), and surface wind (SW), are investigated. Statistically, sea ice provides memory for the Arctic climate system so that changes in SIC driven by the climate indices (AO, NAO and DA) can be felt during the ensuing seasons. Positive SST trends can cause greater SIC reductions, which is observed in the Greenland and Barents Seas during the autumn and winter. In contrast, the removal of sea ice (i.e., loss of the insulating layer) likely contributes to a colder sea surface (i.e., decreased SST), as is observed in northern Barents Sea. Decreasing SIC trends can lead to an in-phase enhancement of SAT, while SAT variations seem to have a lagged infl uence on SIC trends. SW plays an important role in the modulating SIC trends in two ways: by transporting moist and warm air that melts sea ice in peripheral seas (typically evident inthe Barents Sea) and by exporting sea ice out of the Arctic Ocean via passages into the Greenland and Barents Seas, including the Fram Strait, the passage between Svalbard and Franz Josef Land (S-FJL), and the passage between Franz Josef Land and Severnaya Zemlya (FJL-SZ).

北极海冰正处于快速减退时期,北极海冰体积变化是全球气候变化的重要指示因子.本文利用两种卫星高度计数据(ICESat和CryoSat-2)反演得到的海冰厚度数据,结合星载辐射计提取的海冰密集度数据以及海冰年龄数据,估算了近期的北极海冰体积以及一年冰和多年冰体积变化.CryoSat-2观测时段(2011-2013年)与ICESat观测时段(2003-2008年)相比,北极海冰体积在秋季(10-11月)和冬季(2-3月)分别减少了1426 km3和412 km3.其中,秋季和冬季的一年冰的体积增加了702 km3和2975 km3.相反,多年冰分别减少了2108 km3和3206 km3.多年冰的大量流失是造成北极海冰净储量下降的主要原因.

The Fram Strait（FS） is the primary region of sea ice export from the Arctic Ocean and thus plays an important role in regulating the amount of sea ice and fresh water entering the North Atlantic seas. A 5 a（2011–2015） sea ice thickness record retrieved from Cryo Sat-2 observations is used to derive a sea ice volume flux via the FS. Over this period, a mean winter accumulative volume flux（WAVF） based on sea ice drift data derived from passivemicrowave measurements, which are provided by the National Snow and Ice Data Center（NSIDC） and the Institut Francais de Recherche pour d’Exploitation de la Mer（IFREMER）, amounts to 1 029 km~3（NSIDC） and1 463 km~3（IFREMER）, respectively. For this period, a mean monthly volume flux（area flux） difference between the estimates derived from the NSIDC and IFREMER drift data is –62 km~3 per month（–18×10~6 km~2 per month）.Analysis reveals that this negative bias is mainly attributable to faster IFREMER drift speeds in comparison with slower NSIDC drift data. NSIDC-based sea ice volume flux estimates are compared with the results from the University of Bremen（UB）, and the two products agree relatively well with a mean monthly bias of（5.7±45.9） km~3 per month for the period from January 2011 to August 2013. IFREMER-based volume flux is also in good agreement with previous results of the 1990 s. Compared with P1（1990/1991–1993/1994） and P2（2003/2004–2007/2008）, the WAVF estimates indicate a decline of more than 600 km~3 in P3（2011/2012–2014/2015）. Over the three periods, the variability and the decline in the sea ice volume flux are mainly attributable to sea ice motion changes, and second to sea ice thickness changes, and the least to sea ice concentration variations.

北极海冰对全球气候变化起重要的指示作用.除了海水冻结和融化过程以外,通过弗拉姆海峡(Fram Strait)的海冰输出也是影响北极海冰质量变化的重要动力机制.观测数据中的多源卫星遥感数据(尤其是辐射计观测数据)在获取大尺度连续观测方面具有独特的优势,在研究北极海冰输出面积通量变化方面有着广泛应用.本文总结了北极弗拉姆海峡、其他通道(S-FJL、FJL-SZ、加拿大群岛、Nares海峡通道)海冰输出面积或体积通量,着重介绍了弗拉姆海峡不同年龄海冰输出情况,并总结和分析了影响北极海冰输运的大尺度大气活动模态.最后,本文阐明北极海冰输出方面现有研究的不足之处以及未来的突破方向.

Abstract. Sea ice export through Baffin Bay plays a vital role in modulating the meridional overturning process in the downstream Labrador Sea. In this study, satellite-derived sea ice products are explored to obtain the sea ice flux (SIF) through three passages (referred to as A, B, and C for the north, middle, and south passages, respectively) of Baffin Bay. Over the period 1988–2015, the average annual (October–September) sea ice area export is 555 × 103 km2, 642 × 103 km2, and 551 × 103 km2 through passages A, B, and C, respectively. These amounts are less than that observed through the Fram Strait (FS, 707 × 103 km2). Clear increasing trends in annual sea ice export on the order of 53.1 × 103 km2/de and 43.2 × 103 km2/de are identified at passages A and B, respectively. The trend at the south passage (C), however, is slightly negative (−13.3 × 103 km2/de). The positive trends in annual SIF at A and B are primarily attributable to the increase during winter months, which is triggered by the accelerated sea ice motion (SIM) and partly compensated by the reduced sea ice concentration (SIC). During the summer months, the sea ice export through each Baffin Bay passage usually presents a negative trend, primarily because of the decline in SIM and it is further enhanced by a dramatic decrease in SIC. A significant positive trend in the net SIF (i.e. net ice inflow) is found for between the passages A (or B) and C at 54.5 (or 64.2) × 103 km2/de. Therefore, Baffin Bay may have presented a greater convergence of ice. Overall, the connection between Baffin Bay sea ice export and the North Atlantic Oscillation (NAO) is tenuous, although the correlation is sensitive to variations in the selected time period. In contrast, the association with the cross-gate sea level pressure difference (SLPD) is robust in Baffin Bay (R = 0.69–0.71 depending on the passages), but relatively weaker compared with that in the FS (R = 0.74). Baffin Bay is bounded by Baffin Island to the west and Greenland to the east, thus, sea ice drift is not converted to the free state observed in the FS.

Sea ice is a quite sensitive indicator in response to regional and global climate changes. Based on monthly mean Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) sea ice thickness fields, we computed the conductive heat flux (CHF) in the Arctic Ocean in the four winter months (November–February) for a long period of 36 years (1979–2014). The calculated results for each month manifest the increasing extension of the domain with high CHF values since 1979 till 2014. In 2014, regions of roughly 90% of the central Arctic Ocean have been dominated by the CHF values larger than 18 W m −2 (November–December) and 12 W m −2 (January–February), especially significant in the shelf seas around the Arctic Ocean. Moreover, the population distribution frequency (PDF) patterns of the CHF with time show gradually peak shifting toward increased CHF values. The spatiotemporal patterns in terms of the trends in sea ice thickness and other three geophysical parameters, surface air temperature (SAT), sea ice thickness (SIT), and CHF, are well coupled. This suggests that the thinner sea ice cover preconditions for the more oceanic heat loss into atmosphere (as suggested by increased CHF values), which probably contributes to warmer atmosphere which in turn in the long run will cause thinner ice cover. This represents a positive feedback mechanism of which the overall effects would amplify the Arctic climate changes.

In this study, changes in Arctic sea ice thickness for each ice age category were examined based on satellite observations and modelled results. Interannual changes obtained from Ice, Cloud, and Land Elevation Satellite（ICESat）-based results show a thickness reduction over perennial sea ice（ice that survives at least one melt season with an age of no less than 2 year） up to approximately 0.5–1.0 m and 0.6–0.8 m（depending on ice age） during the investigated winter and autumn ICESat periods, respectively. Pan-Arctic Ice Ocean Modeling and Assimilation System（PIOMAS）-based results provide a view of a continued thickness reduction over the past four decades. Compared to 1980 s, there is a clear thickness drop of roughly 0.50 m in 2010 s for perennial ice. This overall decrease in sea ice thickness can be in part attributed to the amplified warming climate in north latitudes. Besides, we figure out that strongly anomalous southerly summer surface winds may play an important role in prompting the thickness decline in perennial ice zone through transporting heat deposited in open water（primarily via albedo feedback） in Eurasian sector deep into a broader sea ice regime in central Arctic Ocean. This heat source is responsible for enhanced ice bottom melting, leading to further reduction in ice thickness.

Satellite remote sensing provides new insight into the large-scale changes within the Arctic sea ice cover. In this study, satellite-derived sea ice parameters (thickness and age) were explored to investigate age-dependent Arctic sea ice volume changes. Between 2003-2008 (ICESat) and 2011-2015 (CyroSat-2), Arctic Ocean sea ice experienced a net depletion of roughly 4.68 x 10(3) km(3) during autumn (October-November) and about 87% (or 4.11 x 10(3) km(3)) is caused by the removal in multiyear ice (two years and older). In spring (February-March), the net ice depletion amounts to 1.46 x 10(3) km(3), with the multiyear ice loss of 3.74 x 10(3) km(3) and seasonal ice increment of 2.24 x 10(3) km(3). Among multiyear ice loss, about 74% (autumn) and 93% (spring) of the loss were attributable to the depletion of the oldest ice type (5 years and older). Analyses also affirm that the marvelous volume loss of multiyear ice during cold months (October-May) in 2006/2007 and 2011/2012, along with the low replenishment of perennial ice as noted in the following autumns in 2007 and 2012, plays a major role in leading to a younger Arctic sea ice cover. Consequently, these processes together favors for the overall substantial volume loss observed in the Arctic sea ice cover.

Sea-ice outflow from the Laptev Sea is of considerable importance in maintaining the Arctic Ocean sea-ice budget. In this study, a method exclusively using multiple satellite observations is used to calculate sea-ice volume flux across the eastern boundary (EB) and northern boundary (NB) of the Laptev Sea during the October–November and February–March or March–April periods (corresponding to the ICESat autumn and winter campaigns) between 2003 and 2008. Seasonally, the mean total ice volume flux (i.e., NB+EB) over the investigated autumn period (1.96 km3/day) is less than that over the winter period (2.57 km3/day). On the other hand, the large standard deviations of the total volume flux, 3.45 and 0.91 km3/day for the autumn and winter campaigns, indicate significant interannual fluctuations in the calculated quantities. A statistically significant (P>0.99) positive correlation, R=0.88 (or 0.81), is obtained between volume flux across the EB (or NB) and mean ice-drift speed over the boundary for the considered 11 ICESat campaigns. In addition, statistics show that a large fraction of the variability in volume flux across the NB over the 11 investigated campaigns, roughly 40%, is likely explained by ice thickness variability. On average, flux through the Laptev Sea amounts to approximately one-third of that across Fram Strait during the autumn and winter campaigns. These large contributions of sea ice from the Laptev Sea demonstrate its importance as an ice source, affecting the entire sea-ice mass balance in the Arctic Ocean.