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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]

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]

With the new-generation reanalysis product (ERA5), the spatiotemporal characteristics of poleward atmospheric moisture and energy transport over the past four decades (1979–2020) were examined. The main channels of atmospheric transport entering the Arctic in the Northern Hemisphere include the Chukchi Sea at 170° W, Baffin Bay at 50° W, North Atlantic at 0° E, and central Siberia at 90° E. Summer (winter) is characterized by high moisture (energy) transport across 70° N. No clear trend in moisture transport was found, whereas the winter and spring energy transport are declining significantly at a rate of −7.31 × 105 W/m/a (99% confidence) and −6.04 × 105 W/m/a (95% confidence), respectively. Meanwhile, an increasing trend was found in summer (4.48 × 105 W/m/a, 95% confidence) and autumn (3.61 × 105 W/m/a, not significant). The relationship between atmospheric moisture and energy transport and different large-scale atmospheric circulation patterns, including the Arctic Oscillation (AO), North Atlantic Oscillation (NAO), and Dipole Anomaly (DA), was explored. Among them, DA was identified as the most favorable pattern in relation to moisture and/or energy intrusion into the Arctic. As a result, the surface air temperature increases are more pronounced over most of the central Arctic under the regulation of DA. [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]

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]

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]