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To investigate patterns of horizontal atmospheric latent energy (LE) transport toward the Arctic, we applied the self-organizing maps (SOM) method to the daily vertically integrated horizontal LE flux from ERA5 in winter (January–March) during 1979–2021. A clear picture depicting the LE transport to the Arctic at a synoptic scale then emerged, with four primary transport pathways identified: the northern Europe, the Davis Strait, the Greenland Sea, and the Bering Strait pathways. The four primary pathways occurred at a comparable frequency, and noticeable interannual variability was observed in their time series of frequency during 1979–2021. Further analysis suggested that the northward LE transport through all these pathways is significantly modulated by cyclones, with the northern Europe and the Greenland Sea pathways being mostly affected. Generally, more frequent and stronger cyclones were observed near the entry regions of LE transport compared to other regions. Moreover, this study provides a comprehensive picture of how atmospheric LE transport is related to air temperature, moisture, surface heat flux, and sea ice anomalies over the Arctic Ocean in winter. Through a thermodynamic perspective, we argue that the deleterious impacts of poleward LE transport on Arctic sea ice are to a large extent attributable to the enhanced local atmosphere–ice interactions, which increase downward longwave radiation (DLR) plus turbulent fluxes, consequently warming the surface and promoting the loss of sea ice. According to the quantitative results, among the four primary pathways, LE transport through the Davis Strait and the Greenland Sea could cause the loss of Arctic sea ice most efficiently. [ABSTRACT FROM AUTHOR]

A distinguishing feature of Arctic sea ice is the rapid declining in the Pacific Arctic Sector (PAS) in recent years. The atmospheric variability during spring (March‐May) plays a critical role in determining the sea ice extent (SIE) during the following summer. The summertime (June‐August) SIE reduction in the eastern part of PAS, including the East Siberian Sea and the Laptev Sea, is strongly related to the first two leading atmospheric circulation modes in spring, the Arctic Oscillation and the Arctic Dipole, retrieved from empirical orthogonal function analysis. Here, we show that the third leading mode of atmospheric circulation in spring, namely the Barents‐Beaufort Oscillation (BBO), can also change the summer SIE, especially on the western regime of the PAS across the Beaufort and Chukchi Seas. We find that a positive phase of springtime BBO (i.e., BBO+), relative to the BBO−, acts to decrease sea ice thickness via advection and generate sea ice deformation through divergence and shear processes, thereby preconditioning for a rapid sea ice loss within the PAS in the following summer. Furthermore, the occurrence of BBO is state‐dependent and potentially modulated by the phase shift of the Atlantic Multidecadal Oscillation (AMO) and the Pacific Decadal Oscillation (PDO). Since the mid‐1990s, the AMO (PDO) index has changed from a dominant negative (positive) to a positive (negative) phase. These phase shifts in AMO and PDO would have contributed to the subsequently increased appearance of anomalous BBO+ after 2000 and enhanced the summertime sea ice loss in the western regions of the PAS in recent years. Plain Language Summary: Large‐scale atmospheric circulation plays a vital role in regulating the Arctic sea ice extent (SIE) changes in summer. Spring atmospheric circulation anomaly could precondition for a noticeable decline in SIE in the following summer. Arctic Oscillation and Arctic Dipole anomaly modes are well demonstrated in previous studies. In this study, we outline the effectiveness in leading to sea ice reduction by another important circulation pattern, namely the Barents‐Beaufort Oscillation (BBO). The spring BBO in its positive phase can change the summer SIE over the western Pacific‐Arctic sector, including Beaufort and Chukchi Seas. The two seas are the regions undergoing the rapidest shrinkage over the past decades. We also found that the decadal variability of BBO seems to be associated with the ocean activities at low latitudes. The frequent occurrence after 2000 is partly attributable to the phase shift by the Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation since mid‐1990s. Key Points: A special connection of summer Arctic sea ice extent shrinkage to spring Barents‐Beaufort Oscillation (BBO) is outlinedThe dynamic impacts on ice thickness decline through diverging and shearing processes linked to BBO are identified over the Pacific‐Arctic sectorThe effectiveness of BBO on Arctic sea ice changes depends on the states of Atlantic Multidecadal Oscillation and Pacific Decadal Oscillation [ABSTRACT FROM AUTHOR]

This study investigates the thermodynamical and dynamical influences of the intense cyclone in the Arctic Ocean in August 2012 on the synoptic‐scale sea ice evolution, using the Arctic Ice Ocean Prediction System (ArcIOPS). As it is hard to fully isolate sea ice loss owing to extreme cyclone from that owing to background atmospheric state in most previous studies on this topic, this study introduces a newly developed algorithm to remove the cyclone component in atmospheric forcing, and conducts sea ice and heat budget analyses in two simulations driven by atmospheric forcing with and without the cyclone. Strong impact of the intense cyclone on sea ice locates on the east side of the cyclone's path, that is, Pacific Arctic for this case. The cyclone affects sea ice in two ways. First, cyclone‐induced enhancement in ice‐ocean interaction leads to increased sea ice basal melt in the Pacific Arctic and part of the Atlantic Arctic, which induces strong sea ice area and volume loss when the cyclone's intensity peaks. Second, as the cyclone strengthens, the increases in air temperature, humidity and wind speed accelerate turbulent heat exchange at the air‐ocean and air‐ice interfaces, leading to enhanced local sea ice surface melt in the Chukchi Sea and northern Beaufort Sea. The cyclone‐induced strong winds stir sea ice leading to enhanced gradients in sea ice velocity field and thus increased sea ice deformation, which further induces strong sea ice area loss. This study also demonstrates a precise atmospheric forcing field is essential for sea ice modeling. Plain Language Summary: We use a numerical model to study the effects of a strong Arctic cyclone on sea ice. First, we use a newly developed "cyclone removal algorithm" to remove the cyclone from the atmospheric data that is used to force the model. We can then compare how the sea ice changes between the model runs with and without the cyclone. We find that the cyclone has a strong local impact on sea ice, and sea ice losses are different on the two sides of the cyclone's path. The cyclone results in warm, moist air and strong wind, which leads to strong sea ice surface melting. At the same time, the cyclone increases the transfer of heat from the ocean to the sea ice, causing strong sea ice bottom melting. The strong wind also leads to more sea ice ridging and a reduction in sea ice area. Our study indicates that the effects of cyclones on sea ice are complex and that atmospheric data must accurately represent cyclones if we want to correctly model changes in the Arctic sea ice. Key Points: Removing a cyclone from the atmospheric forcing in an Arctic model reveals its contributions to sea ice loss along its trajectoryOceanic and turbulent heat fluxes are the key factors driving enhanced ice basal and surface melt during an intense cyclone in the ArcticStrong sea ice loss locates on the east side of the trajectory of an intense cyclone [ABSTRACT FROM AUTHOR]

Arctic sea ice, especially the multiyear ice (MYI), is decreasing rapidly, partly due to melting triggered by global warming, in turn partly due to the possible acceleration of ice export from the Arctic Ocean to southern latitudes through identifiable gates. In this study, MYI and total sea ice areal flux through six Arctic gateways over the winters (October–April) of 2002–2021 were estimated using daily sea ice motion and MYI/total sea ice concentration data. Inconsistencies caused by different data sources were considered for the estimate of MYI flux. Results showed that, there is a slight declining trend in the Arctic MYI areal flux over the past two decades, which is attributable to the decrease in MYI concentration. Overall speaking, MYI flux through Fram Strait accounts for ~87% of the Arctic MYI outflow, with an average of ~325.92 × 103 km2 for the winters of 2002–2021. The monthly MYI areal flux through Fram Strait is characterized with a peak in March (~55.56 × 103 km2) and a trough in April (~40.97 × 103 km2), with a major contribution from MYI concentration. The connections between sea ice outflow and large-scale atmospheric circulations such as Arctic Oscillation (AO), North Atlantic Oscillation (NAO) and Dipole Anomaly (DA) were investigated. High correlation coefficients (CCs) were found in winter months such as January and February. While AO and NAO (especially NAO) exhibited generally weak correlations with the MYI/total sea ice flux, DA presented strong correlations with the areal flux, especially for MYI (CC up to 0.90 in January). However, the atmospheric circulation patterns are sometimes not fully characterized by the specific indices, which could have different effects on sea ice flux and its correlation with the atmospheric indices. [ABSTRACT FROM AUTHOR]

Revealing the changes in the Fram Strait (FS) multiyear ice (MYI) export is crucial due to their climate relevance in the context of the loss rate of MYI being faster than that of the total ice in the Arctic. Here, we estimated winter (October–April) MYI area export through the FS over the last 2 decades by using updated MYI concentration data retrieved from active and passive microwave satellite observations. We divided the period into two regimes relative to the ice index: D1 (2002/03–2010/11) and D2 (2012/13–2019/20). The observed variations of winter MYI exports D2 were compared with those of the previous decade D1. The results show that the MYI area exports display strong interannual variability. A significant decrease in MYI export for the periods between D1 and D2 is noted. On average, the wintertime MYI area exports declined sharply by 22% from 3.82 × 105 km2 in D1 to 3.00 × 105 km2 in D2. In addition, the percentage of MYI in the total sea ice outflow through the FS (PCM) also decreased distinctly from 72% in D1 to 59% in D2. Statistics show that weekly sea ice drift across the strait can explain 76% of the MYI area export variability. Furthermore, the dominant atmospheric drivers contributing to the decline in MYI area export during D2 were examined. In the last decade (D2), the strengthened low pressure in the North Atlantic sector, combined with an eastward shift in the axis of dipole anomaly (DA), resulted in reduced MYI advection from the Beaufort Sea and Siberian Coast toward the FS. Moreover, weakened cyclonic activity south of the FS also contributed to the reduction in MYI export during D2. [ABSTRACT FROM AUTHOR]

• Energetic sea ice drift occurs under negative phase of Arctic Oscillation with positive phase of Arctic Dipole. • Wind-ice stress dominates ice floes away from islands and continents. • Balance exists between internal ice stress and sea surface height gradient in thick multiyear ice zone. By analyzing an Arctic ice-ocean coupled simulation, we study the linkage between wintertime sea ice drift and atmospheric circulation, and interpret the driving force terms in the sea ice dynamic equation. Sea ice drift anomaly is featured by an anticyclonic (cyclonic) gyre when regulated by negative (positive) phase of Arctic Oscillation with positive (negative) phase of Arctic Dipole, and a quasi-meridional stream from Chukchi-Beaufort (Barents-Kara) Seas to Barents-Kara (Chukchi-Beaufort) Seas when regulated by positive (negative) phase of Arctic Oscillation with positive (negative) phase of Arctic Dipole. Sea ice drift anomaly, when regulated by the mode alone, resembles spatial pattern of leading atmospheric mode. Decomposing sea ice dynamical equation shows that wind-ice stress dominates sea ice drift in areas away from islands and continental coastlines, ocean-ice stress acts as a resistant power to partly cancel the wind-ice stress in these areas, while in the coastal areas such as the thick multiyear ice zone north of the Canadian Arctic Archipelago, the wind-ice and ocean-ice stresses are small, the balance exists between sea surface height potential gradient and internal ice stress divergence. Developing more sophisticated internal ice stress expression in ice model is of great important to correctly project future sea ice change for the ice modeling community. [ABSTRACT FROM AUTHOR]

The satellite observations unveiled that the July sea ice extent of the Arctic shrank to the lowest value, since 1979, in 2020 with a major ice retreat in the Eurasian shelf seas including Kara, Laptev, and East Siberian seas. Based on the ERA-5 reanalysis products, we explored the impacts of warm and moist air-mass transport on this extreme event. The results revealed that anomalously high energy and moisture converged into these regions in the spring months (April to June) of 2020, leading to a burst of high moisture content and warming within the atmospheric column. The convergence is accompanied by local enhanced downward longwave surface radiation and turbulent fluxes, which is favorable for initiating an early melt onset in the region with severe ice loss. Once the melt begins, solar radiation plays a decisive role in leading to further sea ice depletion due to ice–albedo positive feedback. The typical trajectories of the synoptic cyclones that occurred on the Eurasian side in spring 2020 agree well with the path of atmospheric flow. Assessments suggest that variations in characteristics of the spring cyclones are conducive to the severe melt of sea ice. We argue that large-scale atmospheric circulation and synoptic cyclones acted in concert to trigger the exceptional poleward transport of total energy and moisture from April to June to cause this record minimum of sea ice extent in the following July. [ABSTRACT FROM AUTHOR]

In this study, a regional linear Markov model is developed to assess seasonal sea ice predictability in the Pacific-Arctic sector. Unlike an earlier pan-Arctic Markov model that was developed with one set of variables for all seasons, the regional model consists of four seasonal modules with different sets of predictor variables, accommodating seasonally varying driving processes. A series of sensitivity tests are performed to evaluate the predictive skill in cross-validated experiments and to determine the best model configuration for each season. The prediction skill, as measured by the sea ice concentration (SIC) anomaly correlation coefficient (ACC) between predictions and observations, increased by 32 % in the Bering Sea and 18 % in the Sea of Okhotsk relative to the pan-Arctic model. The regional Markov model's skill is also superior to the skill of an anomaly persistence forecast. SIC trends significantly contribute to the model skill. However, the model retains skill for detrended sea ice extent predictions for up to 7-month lead times in the Bering Sea and the Sea of Okhotsk. We find that subsurface ocean heat content (OHC) provides a crucial source of prediction skill in all seasons, especially in the cold season, and adding sea ice thickness (SIT) to the regional Markov model has a substantial contribution to the prediction skill in the warm season but a negative contribution in the cold season. The regional model can also capture the seasonal reemergence of predictability, which is missing in the pan-Arctic model. [ABSTRACT FROM AUTHOR]

The extreme Arctic sea ice minima in the twenty-first century have been attributed to multiple factors, such as anomalous atmospheric circulation, excess solar radiation absorbed by open ocean, and thinning sea ice in a warming world. Most likely it is the combination of these factors that drives the extreme sea ice minima, but how the factors rank in setting the conditions for these events has not been quantified. To address this question, the sea ice budget of an Arctic regional sea ice–ocean model forced by atmospheric reanalysis data is analyzed to assess the development of the observed sea ice minima. Results show that the ice area difference in the years 2012, 2019, and 2007 is driven to over 60% by the difference in summertime sea ice area loss due to air–ocean heat flux over open water. Other contributions are small. For the years 2012 and 2020 the situation is different and more complex. The air–ice heat flux causes more sea ice area loss in summer 2020 than in 2012 due to warmer air temperatures, but this difference in sea ice area loss is compensated by reduced advective sea ice loss out of the Arctic Ocean mainly caused by the relaxation of the Arctic dipole. The difference in open water area in early August leads to different air–ocean heat fluxes, which distinguishes the sea ice minima in 2012 and 2020. Further, sensitivity experiments indicate that both the atmospheric circulation associated with the Arctic dipole and extreme storms are essential conditions for a new low record of sea ice extent. [ABSTRACT FROM AUTHOR]

Atmospheric circulation associated with the Arctic dipole (AD) pattern plays a crucial role in modulating the variations of summertime sea ice concentration (SIC) within the Pacific Arctic sector (PAS). Based on reanalysis data and satellite observations, we found that the impacts of atmospheric circulation associated with a positive AD (AD+) on SIC change over different regions of the PAS [including the East Siberian Sea (ESS), Beaufort and Chukchi Seas (BCS), and Canadian Arctic Archipelago (CAA)] are dependent on the phase shifts of Pacific decadal oscillation (PDO). Satellite observations reveal that SIC anomalies, influenced by AD+ during PDO− relative to that during PDO+, varies significantly in summer by 4.9%, −7.3%, and −6.4% over ESS, BCS, and CAA, respectively. Overall, the atmospheric anomalies over CAA and BCS in terms of specific humidity, air temperature, and thereby downward longwave radiation (DLR), are enhanced (weakened) in the atmospheric conditions associated with AD+ during PDO− (PDO+). In these two regions, the larger (smaller) increases in specific humidity and air temperature, associated with AD+ during PDO− (PDO+), are connected to the increased (decreased) poleward moisture flux, strengthened (weakened) convergence of moisture and heat flux, and in part to adiabatic heating. As a consequence, the DLR and surface net energy flux anomalies over the two regions are reinforced in the atmospheric scenarios associated with AD+ during PDO− compared with that during PDO+. Therefore, smaller SIC anomalies are identified over CAA and BCS in the cases related to AD+ during PDO− than during PDO+. Essentially, the changes of the DLR anomaly in CAA and BCS are in alignment with geopotential height anomalies, which are modulated by the anticyclonic circulation pattern in association with AD+ during varying PDO phases. In contrast, the SIC changes over ESS is primarily attributed to the variations in mechanical wind forcing and sea surface temperature (SST) anomalies. The cloud fraction anomalies associated with AD+ during different PDO phases are found not to be a significant contributor to the variations of sea ice anomaly in the studied regions. Given the oscillatory nature of PDO, we speculate that the recent shift to the PDO+ phase may temporarily slow the observed significant decline trend of the summertime SIC within PAS of the Arctic. [ABSTRACT FROM AUTHOR]

A cyclone is an intensive synoptic activity that occurs frequently over Baffin Bay. By modifying the large‐scale distribution pattern of sea level pressure, a passing cyclone can serve as an important regulator of sea ice outflow via the Davis Strait. We obtain a nearly 40‐year‐long record (1979/1980–2017/2018) of the sea ice area flux (SIAF) through the Davis Strait and Arctic cyclone activities in winter. A case study and statistical results indicate that the sea ice concentration and motion fields can be greatly altered by the occurrence of cyclones, thereby contributing to changes in sea ice export. Moreover, the effects of cyclones on sea ice export in Baffin Bay are dependent on the spatial distribution pattern of the storms. In terms of the cyclone center count and intensity, the key regions with significant impacts on sea ice export out of Baffin Bay are identified, one around Baffin Island (80°W–60°W, 60°N–70°N) and the other over the southern Labrador Peninsula (70°W–50°W, 40°N–60°N). A robust correlation exists between the winter‐accumulated SIAF via the Davis Strait and the average winter cyclone intensity (center count) in the critical regions with R = −0.57 (+0.49), affirming the vital role of cyclone activity in modulating the interannual variability of sea ice export in Baffin Bay. Key Points: The wintertime sea ice area flux through the Davis Strait and cyclone activities nearby over the period 1979/1980–2017/2018 are acquiredStrong winds induced by cyclones can change the characteristics of sea ice and thus can impact sea ice export through the Davis StraitThe effects of cyclones on sea ice export through the Davis Strait are spatially dependent, and the key regions are identified [ABSTRACT FROM AUTHOR]

In comparison with seasonal sea ice (first-year ice, FY ice), multiyear (MY) sea ice is thicker and has more opportunity to survive through the summer melting seasons. Therefore, the variability of wintertime MY ice plays a vital role in modulating the variations in the Arctic sea ice minimum extent during the following summer. As a response, the ice-ocean-atmosphere interactions may be significantly affected by the variations in the MY ice cover. Satellite observations are characterized by their capability to capture the spatiotemporal changes of Arctic sea ice. During the recent decades, many active and passive sensors onboard a variety of satellites (QuikSCAT, ASCAT, SSMIS, ICESat, CryoSat-2, etc.) have been used to monitor the dramatic loss of Arctic MY ice. The main objective of this study is to outline the advances and remaining challenges in monitoring the MY ice changes through the utilization of multiple satellite observations. We summarize the primary satellite data sources that are used to identify MY ice. The methodology to classify MY ice and derive MY ice concentration is reviewed. The interannual variability and trends in the MY ice time series in terms of coverage, thickness, volume, and age composition are evaluated. The potential causes associated with the observed Arctic MY ice loss are outlined, which are primarily related to the export and melting mechanisms. In addition, the causes to the MY ice depletion from the perspective of the oceanic water inflow from Pacific and Atlantic Oceans and the water vapor intrusion, as well as the roles of synoptic weather, are analyzed. The remaining challenges and possible upcoming research subjects in detecting the rapidly changing Arctic MY ice using the combined application of multisource remote sensing techniques are discussed. Moreover, some suggestions for the future application of satellite observations on the investigations of MY ice cover changes are proposed. [ABSTRACT FROM AUTHOR]

The Pacific sector of the Arctic Ocean (PA, hereafter) is a region sensitive to climate change. Given the alarming changes in sea ice cover during recent years, knowledge of sea ice loss with respect to ice advection and melting processes has become critical. With satellite-derived products from the National Snow and Ice Center (NSIDC), a 38-year record (1979–2016) of the loss in sea ice area in summer within the Pacific-Arctic (PA) sector due to the two processes is obtained. The average sea ice outflow from the PA to the Atlantic-Arctic (AA) Ocean during the summer season (June–September) reaches 0.173×106 km 2 , which corresponds to approximately 34 % of the mean annual export (October to September). Over the investigated period, a positive trend of 0.004×106 km 2 yr -1 is also observed for the outflow field in summer. The mean estimate of sea ice retreat within the PA associated with summer melting is 1.66×106 km 2 , with a positive trend of 0.053×106 km 2 yr -1. As a result, the increasing trends of ice retreat caused by outflow and melting together contribute to a stronger decrease in sea ice coverage within the PA (0.057×106 km 2 yr -1) in summer. In percentage terms, the melting process accounts for 90.4 % of the sea ice retreat in the PA in summer, whereas the remaining 9.6 % is explained by the outflow process, on average. Moreover, our analysis suggests that the connections are relatively strong (R=0.63), moderate (R=-0.46), and weak (R=-0.24) between retreat of sea ice and the winds associated with the dipole anomaly (DA), North Atlantic Oscillation (NAO), and Arctic Oscillation (AO), respectively. The DA participates by impacting both the advection (R=0.74) and melting (R=0.55) processes, whereas the NAO affects the melting process (R=-0.46). [ABSTRACT FROM AUTHOR]

Unlike the rapid decline of Arctic sea ice in the warming climate, Antarctic sea‐ice extent exhibits a modest positive trend in the period of near four decades. In recent years, the fluctuation in Antarctic sea ice has been strengthened, including a decrease toward the lowest sea‐ice extent in February 2011 for the period of 1978–2016 and a strong rebound in the summer of 2012. The sea‐ice recovery mainly occurs in the Weddell Sea, Bellingshausen Sea, Amundsen Sea, southern Ross Sea, and the eastern Somov Sea. This study offers a new mechanism for this summertime sea‐ice rebound. We demonstrate that cloud‐fraction anomalies in winter 2011 contributed to the positive Antarctic sea‐ice anomaly in summer 2012. The results show that the negative cloud‐fraction anomalies in winter 2011 related to the large‐scale atmospheric circulation resulted in a substantial negative surface‐radiation budget, which cooled the surface and promoted more sea‐ice growth. The sea‐ice growth anomalies due to the negative cloud forcing propagated by sea‐ice motion vectors from September 2011 to January 2012. The distribution of the sea‐ice anomalies corresponded well with the sea‐ice concentration anomalies in February 2012 in the Weddell Sea and eastern Somov Sea. Thus, negative cloud‐fraction anomalies in winter can play a vital role in the following summer sea‐ice distribution. Key Points: Wintertime cloud fraction anomalies in 2011 contributed significantly to the summertime sea‐ice rebound in 2012 in the AntarcticLess cloud fraction in winter 2011 related to large‐scale atmospheric circulation resulted in a strong negative surface‐radiation budgetCloud forcing in winter 2011 cooled the surface, promoted more sea‐ice growth, and resulted in more sea‐ice survival in summer 2012 [ABSTRACT FROM AUTHOR]

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 km 2 and 55.2(±17.8)×103 km 2. 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 km 2. 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 km 2 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. [ABSTRACT FROM AUTHOR]

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 ${\text{4.68}}\times {\text{10}}^{3}\,{\text{km}}^{3}$ during autumn (October–November) and about 87% (or ${\text{4.11}}\times {\text{10}}^{3}\,{\text{km}}^{3}$ ) is caused by the removal in multiyear ice (two years and older). In spring (February–March), the net ice depletion amounts to ${\text{1.46}}\times {\text{10}}^{3}\,{\text{km}}^{3}$ , with the multiyear ice loss of ${\text{3.74}}\times {\text{10}}^{3}\,{\text{km}}^{3}$ and seasonal ice increment of ${\text{2.24}}\times {\text{10}}^{3}\,{\text{km}}^{3}$. 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. [ABSTRACT FROM AUTHOR]

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 (November-December) and 12 W m (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. [ABSTRACT FROM AUTHOR]

By combing ice motion and concentration fields, we obtain the estimates of ice area flux passing the Fram Strait over a 25-year period (1988–2012). Mean monthly area flux exhibits a prominent cycle with the peak in March \rm(78 \times 10^3\,\textkm^2\text/month) and the trough in August \rm(5 \times 10^3\,\textkm^2/\textmonth). Mean net annual ice area flux \rm(644.1 \times 10^3\,\textkm^2\,\textkm^2\rm) is primarily/slightly attributable to winter (October–May)/summer (June–September) outflow of \rm598.7\times 10^3\,\textkm^2 \rm(or\; 93.0\%)/ 45.4 \times 10^3\,\textkm^2 (\rmor 7\%) . However, these quantities need to be considered with great prudence since comparisons with preceding studies indicate distinct difference may exist between calculated Fram Strait sea ice outflow based on varied ice motion datasets. In particular, major bias emerged during winter rather than summer. Trends are also affected due to this bias. Despite the clear disparity in magnitude, we found a good agreement with preceding estimates in terms of temporal variability. The linkage between ice area flux via the Fram Strait and various atmospheric circulation indices, such as the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), a west-east dipole anomaly pattern (DA), as well as a seesaw structure between Beaufort and Barents Sea (BBO), was examined. Results show that atmospheric circulation patterns linked to the DA and BBO possess a relatively stronger influence on Fram Strait ice export over the 25-year period. By contrast, the AO- and NAO-related atmospheric circulation pattern exhibit weaker connections with ice outflow through the strait. In addition, correlation analysis further justify the robust connection with a cross-strait surface level pressure gradient index. Depending on months, it is suggested that a manifold of aforementioned atmospheric indices may jointly or alone impose a significant influence on sea ice export through the Fram Strait. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]

The affiliations of the authors of this article unfortunately contained a mistake. [ABSTRACT FROM AUTHOR]

The Arctic Ocean has experienced rapid warming and sea ice loss in recent decades, becoming the first open-ocean basin to experience widespread aragonite undersaturation [saturation state of aragonite (Warag) < 1]. However, its trend toward long-term ocean acidification and the underlying mechanisms remain undocumented. Here, we report rapid acidification there, with rates three to four times higher than in other ocean basins, and attribute it to changing sea ice coverage on a decadal time scale. Sea ice melt exposes seawater to the atmosphere and promotes rapid uptake of atmospheric carbon dioxide, lowering its alkalinity and buffer capacity and thus leading to sharp declines in pH and Warag. We predict a further decrease in pH, particularly at higher latitudes where sea ice retreat is active, whereas Arctic warming may counteract decreases in Warag in the future. [ABSTRACT FROM AUTHOR]