Search Results (42)

The Laptev Sea, as a marginal sea and a key source of sea ice for the Arctic Ocean, has a profound influence on the dynamic processes of sea ice evolution. Under a 2 °C global warming scenario, the accelerated ablation of Arctic sea ice is projected to greatly impact Arctic warming. The ocean regulates global climate through its interactions with the atmosphere, where sea surface temperature (SST) serves as a crucial parameter in exchanging energy, momentum, and gases. SST is also a key driver of sea ice concentration (SIC). In this paper, we analyze the spatiotemporal variability of SST and SIC, along with their interrelationships in the Laptev Sea, using daily optimum interpolation SST datasets from NCEI and daily SIC datasets from the University of Bremen for the period 2004–2023. The results show that: (1) Seasonal variations are observed in the influence of SST on SIC. SIC exhibited a decreasing trend in both summer and fall with pronounced interannual variability as ice conditions shifted from heavy to light. (2) The highest monthly averages of SST and SIC were in July and September, respectively, while the lowest values occurred in August and November. (3) The most pronounced trends for SST and SIC appeared both in summer, with rates of +0.154 °C/year and −0.095%/year, respectively. Additionally, a pronounced inverse relationship was observed between SST and SIC across the majority of the Laptev Sea with correlation coefficients ranging from −1 to 0.83. Full article

The modern Arctic is characterized by a decreased ice cover and significant interannual variability. However, the reaction of the High Arctic ecosystem to such changes is still being determined. This study tested the hypothesis that the key drivers of changes in phytoplankton are the position and intensity of Atlantic water (AW) flow. The research was conducted in August 2017 in the northern part of the Barents Sea and in August 2020 in the Nansen Basin. In 2017, the Nansen Basin was ice covered; in 2020, the Nansen Basin had open water up to 83° N. A comparative analysis of phytoplankton composition, dominant species, abundance, and biomass at the boundary of the ice and open water in the marginal ice zone (MIZ) as well as in the open water was carried out. The total biomass of the phytoplankton in the photic layer of MIZ is one and a half orders of magnitude greater than in open water. In 2017, the maximum abundance and biomass of phytoplankton in the MIZ were formed by cold-water diatoms Thalassiosira spp. (T. gravida, T. rotula, T. hyalina, T. nordenskioeldii), associated with first-year ice. They were confined to the northern shelf of the Barents Sea. The large diatom Porosira glacialis grew intensively in the MIZ of the Nansen Basin under the influence of Atlantic waters. A seasonal thermocline, above which the concentrations of silicon and nitrogen were close to zero, and deep maxima of phytoplankton abundance and biomass were recorded in the open water. Atlantic species—haptophyte Phaeocystis pouchettii and large diatom Eucampia groenlandica—formed these maxima. P. pouchettii were observed in the Nansen Basin in the Atlantic water (AW) flow (2020); E. groenlandica demonstrated a high biomass (4848 mg m⁻³, 179.5 mg C m⁻³) in the Franz Victoria trench (2017). Such high biomass of this species in the northern Barents Sea shelf has not been observed before. The variability of the phytoplankton composition and biomass in the Franz Victoria trench and in the Nansen Basin is related to the intensity of the AW, which comes from the Frame Strait as the Atlantic Water Boundary Current. Full article

The dynamic changes of sea ice exhibit spatial clustering, and this clustering has characteristics extending from its origin, through its development, and to its dissipation. Current research on sea ice change primarily focuses on spatiotemporal variation trends and remote correlation analysis, and lacks an analysis of spatiotemporal evolution characteristics. This study utilized monthly sea ice concentration (SIC) data from the National Snow and Ice Data Center (NSIDC) for the period from 1979 to 2022, utilizing classical spatiotemporal clustering algorithms to analyze the clustering patterns and evolutionary characteristics of SIC anomalies in key Arctic regions. The results revealed that the central-western region of the Barents Sea was a critical area where SIC anomaly evolutionary behaviors were concentrated and persisted for longer durations. The relationship between the intensity and duration of SIC anomaly events was nonlinear. A positive correlation was observed for shorter durations, while a negative correlation was noted for longer durations. Anomalies predominantly occurred in December, with complex evolution happening in April and May of the following year, and concluded in July. Evolutionary state transitions mainly occurred in the Barents Sea. These transitions included shifts from the origin state in the northwestern margin to the dissipation state in the central-north Barents Sea, from the origin state in the central-north to the dissipation state in the central-south, and from the origin state in the northeastern to the dissipation state in the central-south Barents Sea and southeastern Kara Sea. Various evolutionary states were observed in the same area on the southwest edge of the Barents Sea. These findings provide insights into the evolutionary mechanism of sea ice anomalies. Full article

Erosion along the coastline of the Alaskan Arctic poses an existential threat to several communities. Rising air temperatures have been implicated in accelerating erosion rates through permafrost thaw, decreasing sea ice cover (increasing ocean fetch and wave energy), and shortening the duration of a shore-fast ice buffer, which all mean that erosion rates are higher in summer than they are in winter. However, the resolution of available satellite imagery has historically been too low to allow for the quantification of seasonal erosion rates across large areas of the Arctic, and so erosion rates are generally measured at annual to decadal time scales. This study uses PlanetScope high-resolution satellite imagery to calculate seasonal erosion rates in the Alaskan Arctic. Erosion rates as high as 38 cm/day (equivalent to 140 m/year) were measured using twice-annual images from 2017–2023 on two stretches of Alaska’s Beaufort Sea coast: Drew Point and Cape Halkett. The highest erosion rates are measured in the summer, with winter erosion rates consistently below 10 cm/day (usually within error margin of zero) and summer erosion rates exceeding 20 cm/day in three out of the seven years of data. Summer erosion rates are shown to correlate well with local air temperatures in July–September, July sea surface temperatures, and with Beaufort Sea sea ice area in May–August. Wind speeds and number of windy days do not correlate well with summer erosion rates. This study demonstrates the feasibility of using PlanetScope imagery to calculate erosion rates at seasonal time resolution without field measurements and shows the magnitude of difference between summer and winter season erosion rates. Full article

Two coupled climate models that participated in the CMIP6 project (Coupled Model Intercomparison Project Phase 6), the Earth System Model of Chinese Academy of Sciences version 2 (CAS-ESM2-0), and the Nanjing University of Information Science and Technology Earth System Model version 3 (NESM3) were assessed in terms of the impact of four new sea ice parameterization schemes. These four new schemes are related to air–ice heat flux, radiation penetration and absorption, melt ponds, and ice–ocean flux, respectively. To evaluate the effectiveness of these schemes, key sea ice variables with and without these new schemes, such as sea ice concentration (SIC) and sea ice thickness (SIT), were compared against observation and reanalysis products from 1980 to 2014. The simulations followed the design of historical experiments within the CMIP6 framework. The results revealed that both models demonstrated improvements in simulating Arctic SIC and SIT when the new parameterization schemes were implemented. The model bias of SIC in some marginal sea ice zones of the Arctic was reduced, especially during March. The SIT was increased and the transpolar gradient of SIT was reproduced. The changes in spatial patterns of SIC and SIT after adding new schemes bear similarities between the two coupled models. This suggests that the new schemes have the potential for broad application in climate models for simulation and future climate scenario projection, especially for those with underestimated SIT. Full article

The seasonally ice-covered marine region of the European Arctic has experienced warming and sea ice loss in the last two decades. During expeditions in August 2020 and 2021, new data on size-fractioned primary production (PP), chlorophyll a concentration, phytoplankton biomass and composition and carbon fixation rates in the dark were obtained in the marginal ice zone (MIZ) of the Barents Sea, Nansen Basin and Greenland Sea to better understand the response of Arctic ecosystems to ongoing climate changes. Four different situations were observed in the study region: (i) a bloom of the large-cell diatom Podosira glacialis, whose biomass was trapped in a strong halocline at the edge of a dense ice cover; (ii) a bloom of the chain-like colonies of Thalassiosira diatoms on the shelf in mixed waters in fields of shallow ice that could be supported by “fresh” elements in the polynya condition, as well as by terrestrial run-off and drifting ices; at the late stage, this bloom was accompanied by intensive growth of Phaeocystis pouchetti; (iii) dominance of small-cell phytoplankton under weakened stratification and the significant influence of the Atlantic water, depleted of microelements and silicates; (iv) dominance of dinoflagellates of eutrophic water in the contact zone between the water masses of Arctic origin and Atlantic origin in clear water under conditions of increased light intensity. The >10 µm phytoplankton cell size group increased its relative contribution to PP as a response to stratification, light and nutrient load associated with sea ice conditions. Small phytoplankton with sizes < 2 µm formed the basis of total PP in the MIZ regardless of the state of the sea ice. Full article

In polar regions, positive feedback of snow and ice albedo can intensify global warming. While recent significant decreases in Arctic surface ice albedo have drawn considerable attention, Antarctic surface albedo variability remains underexplored. Here, satellite albedo product CLARA-A2.1-SAL is first validated and then used to investigate spatial and temporal trends in the summer albedo over the Antarctic from 1982 to 2018, along with their association with Antarctic sea ice changes. The SAL product matches well surface albedo observations from eight stations, suggesting its robust performance in Antarctica. Summer surface albedo averaged over the entire ice sheet shows a downward trend since 1982, albeit not statistically significant. In contrast, a significant upward trend is observed in the sea ice region. Spatially, for ice sheet surface albedo, positive trends occur in the eastern Antarctica Peninsula and the margins of East Antarctica, whereas other regions exhibit negative trends, most prominently in the Ross and Ronne ice shelves. For sea ice albedo, positive trends are observed in the Ross Sea and the Weddell Sea, but negative trends are observed in the Bellingshausen and the Amundsen Seas. Between 2016 and 2018, an unusual decrease in the sea ice extent significantly affected both sea ice and Antarctic ice sheet (AIS) surface albedo changes. However, for the 1982–2015 period, while the effect of sea ice on its own albedo is significant, its impact on ice sheet albedo is less apparent. Air temperature and snow depth also contribute much to sea ice albedo changes. However, on ice sheet surface albedo, the influence of temperature and snow accumulation appears limited. Full article

Microplastic pollution has emerged as a global environmental concern, exhibiting wide distribution within marine ecosystems, including the Arctic Ocean. Limited Arctic microplastic data exist from beached plastics, seabed sediments, floating plastics, and sea ice. However, no studies have examined microplastics in the sea ice of the Canadian Arctic Archipelago and Tallurutiup Imanga National Marine Conservation Area, and few have explored Arctic marginal seas’ water column. The majority of the microplastic data originates from the Eurasian Arctic, with limited data available from other regions of the Arctic Ocean. This study presents data from two distinct campaigns in the Canadian Arctic Archipelago and Western Arctic marginal seas in 2019 and 2020. These campaigns involved sampling from different regions and matrices, making direct comparisons inappropriate. The study’s primary objective is to provide insights into the spatial and vertical distribution of microplastics. The results reveal elevated microplastic concentrations within the upper 50 m of the water column and significant accumulation in the sea ice, providing evidence to support the designation of sea ice as a microplastic sink. Surface seawater exhibits a gradient of microplastic counts, decreasing from the Chukchi Sea towards the Beaufort Sea. Polyvinyl chloride polymer (~60%) dominated microplastic composition in both sea ice and seawater. This study highlights the need for further investigations in this region to enhance our understanding of microplastic sources, distribution, and transport. Full article

Our study shows that, during 2001–2017, when the sea ice was melting rapidly, cyclone days accounted for more than 50% of the total autumn days at the sounding stations in the Arctic marginal seas north of the Eurasian continent and almost 50% of the total autumn days at the sounding station on the northern coast of Canada. It is necessary to investigate the influence of Arctic cyclones on the cloud fraction in autumn when the sea ice refreezes from its summer minimum and the infrared cloud radiative effect becomes increasingly important. Cyclones at the selected stations are characterized by a narrow maximum rising zone with vertically consistent high relative humidity (RH) and a broad region outside the high RH zone with low RH air from the middle troposphere covering the low troposphere’s high relative humidity air. Consequently, on approximately 40% of the cyclone days, the cloud formation condition was improved from the near surface to the upper troposphere due to the cooling of strong rising warm humid air. Therefore, cyclones lead to middle cloud increases and sometimes high cloud increases, since the climatological Arctic autumn clouds are mainly low clouds. On approximately 60% of the cyclone days, only low cloud formed, but the low cloud formation condition was suppressed due to the mixing ratio decrease induced by cold dry air sinking. As a result, cyclones generally lead to a decrease in low clouds. However, the correlation between the cyclones and low clouds is complex and varies with surface ice conditions. Full article

The Ku-band scatterometer called CSCAT onboard the Chinese–French Oceanography Satellite (CFOSAT) is the first spaceborne rotating fan-beam scatterometer (RFSCAT). A new algorithm for classification of Arctic sea ice types on CSCAT measurement data using a random forest classifier is presented. The random forest classifier is trained on the National Snow and Ice Data Center (NSIDC) weekly sea ice age and sea ice concentration product. Five feature parameters, including the mean value of horizontal and vertical polarization backscatter coefficient, the standard deviation of horizontal and vertical polarization backscatter coefficient and the copol ratio, are innovatively extracted from orbital measurement for the first time to distinguish water, first-year ice (FYI) and multi-year ice (MYI). The overall accuracy and kappa coefficient of sea ice type model are 93.35% and 88.53%, respectively, and the precisions of water, FYI, and MYI are 99.67%, 86.60%, and 79.74%, respectively. Multi-source datasets, including daily sea ice type from the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF), NSIDC weekly sea ice age, multi-year ice concentration (MYIC) provided by the University of Bremen, and SAR-based sea ice type released by Copernicus Marine Environment Monitoring Service (CMEMS) have been used for comparison and validation. It is shown that the most obvious difference in the distribution of sea ice types between the CSCAT results and OSI SAF sea ice type are mainly concentrated in the marginal zones of FYI and MYI. Furthermore, compared with OSI SAF sea ice type, the area of MYI derived from CSCAT is more homogeneous with less noise, especially in the case of younger multiyear ice. In the East Greenland region, CSCAT identifies more pixels as MYI with lower MYIC values, showing better accuracy in the identification of areas with obvious mobility of MYI. In conclusion, this research verifies the capability of CSCAT in monitoring Arctic sea ice classification, especially in the spatial homogeneity and detectable duration of sea ice classification. Given the high accuracy and processing speed, the random forest-based algorithm can offer good guidance for sea ice classification with FY-3E/RFSCAT, i.e., a dual-frequency (Ku and C band) scatterometer called WindRAD. Full article

To understand the Arctic environment, which is closely related to sea ice and to reduce potential risks, reliable sea ice forecasts are indispensable. A practical, lightweight yet effective assimilation scheme of sea ice concentration based on Optimal Interpolation is designed and adopted in an operational global 1/10° surface wave-tide-circulation coupled ocean model (FIO-COM10) forecasting system to improve Arctic sea ice forecasting. Twin numerical experiments with and without data assimilation are designed for the simulation of the year 2019, and 5-day real-time forecasts for 2021 are implemented to study the sea ice forecast ability. The results show that the large biases in the simulation and forecast of sea ice concentration are remarkably reduced due to satellite observation uncertainty levels by data assimilation, indicating the high efficiency of the data assimilation scheme. The most significant improvement occurs in the marginal ice zones. The sea surface temperature bias averaged over the marginal ice zones is also reduced by 0.9 °C. Sea ice concentration assimilation has a profound effect on improving forecasting ability. The Root Mean Square Error and Integrated Ice-Edge Error are reduced to the level of the independent satellite observation at least for 24-h forecast, and sea ice forecast by FIO-COM10 has better performance than the persistence forecasts in summer and autumn. Full article

Since the mid-1990s, there has been a marked decrease in the sea ice extent (SIE) in the Arctic Ocean. After reaching an absolute minimum in September 2012, the seasonal variations in the SIE have settled at a new level, which is almost one-quarter lower than the average climatic norm of 1979–2022. Increased melting and accelerated ice export from marginal seas ensure an increase in the open water area, which affects the lower atmosphere and the surface layer of the ocean. Scientists are cautiously predicting a transition to a seasonally ice-free Arctic Ocean as early as the middle of this century, which is about 50 years earlier than was predicted just a few years ago. Such predictions are based on the fact that the decrease in sea ice extent and ice thinning that occurred at the beginning of this century, initially caused by an increase in air temperature, triggered an increase in the thermal and dynamic contribution of the ocean to the further reduction in the ice cover. This paper reviews published evidence of such changes and discusses possible mechanisms behind the observed regional anomalies of the Arctic Sea ice cover parameters in the last decade. Full article

The increasing influence of Atlantic inflows in the Arctic Ocean in recent decades has had a potential impact on regional biogeochemical cycles of major and trace elements. The warm and salty Atlantic water, entering the Eurasian Basin through the Norwegian Sea margin and the Barents Sea, affects particle transport, sink, phyto-, and zooplankton community structure and could have far-reaching consequences for the marine ecosystems. This study discusses the elemental composition of suspended particulate matter and fluffy-layer suspended matter derived from samples collected in the Barents Sea and northern Norwegian Sea in August 2017. The mosaic distribution of SPM elemental composition is mainly determined by two factors: (i) The essential spatial variability of biological processes (primary production, abundance, and phytoplankton composition) and (ii) differences in the input of terrigenous sedimentary matter to the sea area from drainage sources (weak river runoff, melting of archipelago glaciers, etc.). The distribution of lithogenic, bioessential, and redox-sensitive groups of elements in the particulate matter was studied at full-depth profiles. Marine cycling of strontium in the Barents Sea is shown to be significantly affected by increasing coccolithophorid bloom, which is associated with Atlantic water. Mn, Cu, Cd, and Ba significantly enrich the suspended particulate matter of the benthic nepheloid layer relative to the fluffy layer particulate matter within the benthic boundary layer. Full article

As the Arctic Ocean continues to warm, both the extent and thickness of sea ice have dramatically decreased over the past few decades. These changes in ice have an impact on sea ice motion, including sea ice inertial oscillations (SIIO). However, the spatial pattern and temporal variations of Arctic SIIO remain poorly understood. In this study, the spatiotemporal characteristics of Arctic SIIO between 1979 and 2019 are revealed based on the sea ice drifting buoy dataset from the International Arctic Buoy Program (IABP). The results indicate the significant enhancement of SIIO during 1979–2019, with the trend of 7.84 × 10⁻³ (±3.34 × 10⁻³) a⁻¹ (a⁻¹ means per year) in summer and 1.92 × 10⁻³ (±0.80 × 10⁻³) a⁻¹ in winter. Compared with the first 30 years, the magnitude of SIIO in 2009–2019 increases by 66% in summer and 21% in winter. Spatially, the remarkable enhancement of SIIO during 2009–2019 is found in most of the Arctic Ocean. Especially in summer, SIIO are significantly intensified in marginal seas, including the Beaufort Sea, East Siberian Sea and Laptev Sea, which is mainly correlated with the decrease of sea ice concentration in recent years. This study is anticipated to provide insights for spatiotemporal variation of Arctic sea ice inertial motion in recent decades. Full article

Polar lows (PLs) are intense mesoscale weather systems that often cause severe storm winds in the Nordic Seas but were considered as being exceedingly rare in the Pacific Arctic region before sea ice decline. Here, we explore four PLs observed on 18–22 October 2017 in the Chukchi and Beaufort Seas—an area with an exceptionally sparse observation network. The study is based on the combined use of the satellite microwave measurements, as well as infrared imagery, the ERA5, MERRA-2 and NCEP-CFSv2 reanalysis data sets. An unusually strong PLs pair developed near the marginal ice zone during a marine-cold air outbreak in anomalously low sea ice extent conditions. PLs pair moved southward as a mesocyclonic system called the “merry-go-round”, under the upper-level tropospheric vortex with a cold core. Multi-sensor satellite measurements show that, in the mature stage, a PL pair had near-surface wind speeds (W) close to hurricane force—over 30 m/s. Comparison analysis of W distributions within the strongest PL showed that all reanalysis data sets reasonably reproduce the PL median wind speed but underestimate its extreme values by 15–23%. The reanalysis data sets detected only two PLs with horizontal scales of over 220 km. Tracks of identified PLs for all data sets are in good agreement with the ones obtained from satellite images capturing the main features of the mesoscale weather system propagation. For the track of the strongest PL event, ERA5 exhibited the most accordance with satellite observations with a tracking error of 50–60 km. Full article