Search Results (47)

Arctic sea ice variations exhibit relatively strong statistical associations with precipitation variability over northeastern and southern China. Using Arctic Ocean reanalysis data from the EU Copernicus Project, this study examines the time-lagged statistical relationships between winter Arctic sea ice conditions and subsequent spring precipitation variability over China through wavelet analysis and Granger causality tests. Singular value decomposition (SVD) identifies the Barents, Kara, East Siberian, and Chukchi Seas as key regions exhibiting strong associations with spring precipitation anomalies. Increased winter sea ice in the East Siberian and Chukchi Seas generates positive geopotential height anomalies over the Arctic and negative anomalies over Northeast Asia, adjusting upper-level jet streams and influencing precipitation patterns in Northeast China. Conversely, increased sea ice in the Barents–Kara Seas leads to persistent negative geopotential height anomalies simultaneously occurring over both the Arctic and South China regions, enhancing southern jet stream activity and intensifying warm-moist airflow at the 850 hPa level, thus favoring precipitation in southern China. Compared to considering only climate factors such as the Pacific Decadal Oscillation (PDO), El Niño–Southern Oscillation (ENSO), and Arctic Oscillation (AO), the inclusion of Arctic sea ice significantly enhances the influence of multiple climate factors on precipitation variability in China. Full article

Siliceous plankton are vital for understanding modern and past marine environments. However, few studies have been carried out on silicoflagellates, a group of siliceous phytoplankton. The determination of reliable environmental reconstructions using silicoflagellates is hindered by the lack of consensus on the optimal counting number. In this study, sinking particles and surface sediments collected from the Chukchi Sea, western Arctic Ocean, were used to investigate the composition of silicoflagellates and to determine the optimal counting number of silicoflagellate assemblages. The silicoflagellate assemblage in the western Arctic is dominated by Octactis speculum, followed by Staphanocha medianoctisol in secondary abundance, while Octactis octonaria and Stephanocha quinquangella are present in very low frequencies. Employing an analysis of relative abundances and their corresponding coefficient of variations (CVs) for different silicoflagellate species across a counting gradient, we established an optimal counting number of 100–200 silicoflagellate skeletons for samples with high abundance. In contrast, the entire sample slide should be counted due to the low absolute abundance of silicoflagellates in surface sediments. Full article

Low-frequency ocean noise (50–500 Hz) was recorded by a single omnidirectional hydrophone in the open waters of the Chukchi Plateau from 31 August 2021 to 6 September 2021 (local time). After other non-wind interference was filtered out, wind-generated noise source levels (NSLs) were extracted from the wind-generated noise. The correlation coefficients between the one-third octave wind-generated NSLs and sea surface wind speed exceed 0.84, an improvement of approximately 10% compared to those between the raw data and the wind speed. For 200–500 Hz, the wind-generated NSLs are highly consistent with Wilson’s (1983) estimated curve. The 50–300 Hz results closely match those of Chapman and Cornish (1993) from vertical line array (VLA) measurements. Both demonstrate the feasibility of extracting wind-generated NSLs by utilizing a single omnidirectional hydrophone in the Chukchi Plateau’s open waters. Furthermore, the research results of wind speed dependence and frequency dependence can be applied to calculate wind-generated NSLs in the Chukchi Plateau. Wind-derived ocean ambient noise data are useful for background correction in underwater target detection, recognition, tracking, and positioning. Full article

The Chukchi Sea is an open estuary in the southwestern Arctic. Its near-surface salinities are higher than those of the surrounding open Arctic waters due to the key inflow of saltier and warmer Pacific waters through the Bering Strait. This salinity distribution may suggest that interannual changes in the Bering Strait mass transport are the sole and dominant factor shaping the salinity distribution in the downstream Chukchi Sea. Using satellite sea surface salinity (SSS) retrievals and altimetry-based estimates of the Bering Strait transport, the relationship between the Strait transport and Chukchi Sea SSS distributions is analyzed from 2010 onward, focusing on the ice-free summer to fall period. A comparison of five different satellite SSS products shows that anomalous SSS spatially averaged over the Chukchi Sea during the ice-free period is consistent among them. Observed interannual temporal change in satellite SSS is confirmed by comparison with collocated ship-based thermosalinograph transect datasets. Bering Strait transport variability is known to be driven by the local meridional wind stress and by the Pacific-to-Arctic sea level gradient (pressure head). This pressure head, in turn, is related to an Arctic Oscillation-like atmospheric mean sea level pattern over the high-latitude Arctic, which governs anomalous zonal winds over the Chukchi Sea and affects its sea level through Ekman dynamics. Satellite SSS anomalies averaged over the Chukchi Sea show a positive correlation with preceding months’ Strait transport anomalies. This correlation is confirmed using two longer (>40-year), separate ocean data assimilation models, with either higher- (0.1°) or lower-resolution (0.25°) spatial resolution. The relationship between the Strait transport and Chukchi Sea SSS anomalies is generally stronger in the low-resolution model. The area of SSS response correlated with the Strait transport is located along the northern coast of the Chukotka Peninsula in the Siberian Coastal Current and adjacent zones. The correlation between wind patterns governing Bering Strait variability and Siberian Coastal Current variability is driven by coastal sea level adjustments to changing winds, in turn driving the Strait transport. Due to the Chukotka coastline configuration, both zonal and meridional wind components contribute. Full article

Atmospheric sounding using the Tu-134 Optik aircraft-laboratory was conducted in September 2020 over the seas of the Russian sector of the Arctic Ocean, namely the Barents, Kara, Laptev, East Siberian, Chukchi and Bering seas. Unique samples of atmospheric aerosols at altitudes from 200 and up to 10,000 m were taken, including samples for the identification of cultivated microorganisms and their genetic analysis. Data on the concentration and diversity of bacteria and fungi isolated from 24 samples of atmospheric aerosols are presented; the main phenotypic and genomic characteristics were obtained for 152 bacterial cultures; and taxonomic belonging was determined. The concentration of cultured microorganisms detected in aerosols of different locations was similar, averaging 5.5 × 10³ CFU/m³. No dependence of the number of isolated microorganisms on the height and location of aerosol sampling was observed. The presence of pathogenic and condto shitionally pathogenic bacteria, including those referred to in the genera Staphylococcus, Kocuria, Rothia, Comamonas, Brevundimonas, Acinetobacter, and others, as well as fungi represented by the widely spread genera Aureobasidium, Aspergillus, Alternaria, Penicillium, capable of causing infectious and allergic diseases were present in most analyzed samples. Obtained data reveal the necessity of systematic studies of atmospheric microbiota composition to combat emerging population diseases. Full article

The interannual features of the salinity in the Chukchi Sea during the ice-free period of a year are investigated on the base of Soil Moisture Active Passive (SMAP) satellite measurements and GLORYS12v1 reanalysis data. Analysis of salinity measurements revealed two types of Bering Summer Waters (BSW) propagation: “western” and “eastern”. The first is characterized by the penetration of Pacific waters into the northwest part of the sea, as well as the propagation of BSW to 180°W and 72.5°N. During the “eastern” type, salty waters are pressed to the eastern part of the shelf. Their area decreases and the northern boundary of the BSW area shifts to 174–176°W. Areas with low salinity, ~29 psu, are observed in the western part of the sea. Our study reveals that the formation of these types is affected not only by the inflow of Pacific waters through the Bering Strait but also by the East Siberian Current (ESC). Both factors are related and lead to correlated changes in the salinity of the Chukchi Sea waters. ESC carries Arctic freshwaters from west to east and leads to a decrease in salinity in the western part of the sea. At the same time, southward ESC caused the blockage of the northward currents in the Bering Strait and a decrease in the influx of saline Pacific waters in the southern part of the Chukchi Sea. The intensification of ESC occurred in 1994, 2002, 2012, and 2016, when the volume transport of ESC increased by approximately 0.2 Sv, while the influx through the Bering Strait decreased. As a result, in the years with intense ESC, the spatial structure of the salinity of the Chukchi Sea changed significantly and the shelf-averaged salinity decreased by 0.3–0.5 psu. Full article

Growing interest in finding the optimal route through the arctic ocean, and sea ice concentration is also emerging as a factor to be considered. In this paper, an algorithm to calculate the sea ice concentration was developed based on the images taken during the Arctic voyage of the Korean icebreaker ARAON in July 2019. A sea ice concentration calculation program was developed using the image processing functions in open-source image processing library, called OpenCV. To develop the algorithm, parameter studies were conducted on red, green, blue (RGB) color space and hue, saturation, value (HSV) color space, and k-means clustering. To verify the algorithm for sea ice concentration calculation, it was applied to images taken during Araon’s Arctic voyages. Lens curvature and view point were corrected through camera calibration. To improve the accuracy of sea ice concentration calculation, a binarization model based on random forest was proposed. A parameter study for training image numbers and tree numbers was conducted to establish the random forest model. The calculated sea ice concentrations by random forest and k-means clustering were compared and discussed. 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

Ambient noise plays a crucial role in influencing the observation quality at seismic stations. By studying the distribution patterns of ambient noise, we can gain initial insights into the noise conditions within a specific research area. This paper investigates the properties of ambient noise in different frequency bands under environmental settings in the Chukchi Sea region, utilizing data collected from ocean bottom seismometers (OBSs) deployed during the Ninth Chinese National Arctic Scientific Survey. The probability density function (PDF) method is used to reveal the distinctive features of ambient noise. In addition, by comparing the crowed number values of ambient noise in the Chukchi Sea area with the global new low-noise model (NLNM) and new high-noise model (NHNM), a more comprehensive understanding of the patterns, distribution characteristics, and sources of ambient noise in the Arctic Chukchi Sea area is gained. The study suggests that the overlying sea ice in the Arctic Chukchi Sea area can suppress the microseismic band ambient noise, and the overall level of ambient noise in the Chukchi Sea area lies between the land seismic ambient noise level and the ambient noise level in the middle- and low-latitude sea areas. Meanwhile, an abnormal power spectrum caused by different levels of natural earthquakes is observed. This study fills the gap by using seafloor seismic instruments to investigate ambient noise in the Chukchi Sea area. Full article

The main parameters of wind waves in the World Ocean are connected with global climate change. Renewable energy technologies, intensive shipping, fishery, marine infrastructure, and many different human marine activities in the coastal zone and open sea need knowledge about the wind-wave climate. The main motivation of this research is to share various wind wave parameters with high spatial resolution in the coastal zone via a modern cartographic web atlas. The developed atlas contains information on 13 Russian Seas, including the Azov, Black, Baltic, Caspian, White, Barents, Kara, Laptev, East Siberian, Chukchi, Bering Seas, the Sea of Okhotsk, and the Sea of Japan/East Sea. The analysis of wave climate was based on the results of wave modeling by WAVEWATCH III with input NCEP/CFSR wind and ice data. The web atlas was organized using the classic three-tier architecture, which includes a data storage subsystem (database server), a data analysis and publishing subsystem (GIS server), and a web application subsystem that provides a user interface for interacting with data and map services (webserver). The web atlas provides access to the following parameters: mean and maximum significant wave height, wave length and period, wave energy flux, wind speed, and wind power. The developed atlas allows changing the map scale (zoom) for detailed analysis of wave parameters in the coastal zones where the wave model spatial resolution is 300–1000 m. Full article

An analysis of archival and literary materials, as well as recently collected data in coastal areas at 14 locations in the Eurasian seas showed that the diversity of biomass-dominating key bryozoan species is low, totaling 26 species, less than 1/15 of the total bryozoan fauna richness. Their number decreases eastward from 17 species with an average total biomass of >16 g/m² in the Barents Sea to three species with an average biomass of about 3 g/m² in the East Siberian Sea. In the Chukchi Sea, their number and average biomass increase to 10 species and ~12 g/m², respectively. Average biomass strongly correlates with the number of species in each sea. Furthermore, variation in biomass is significantly correlated with the composition of bottom sediments and, in some locations, with depth. The marked decrease in the number of key species along the vector from Barents→Kara→Laptev→East Siberian Sea is due to a decline in the number of boreal and boreal–Arctic bryozoans of Atlantic origin. In contrast, the appearance of boreal and boreal–Arctic Pacific species is responsible for the increase in key species in the Chukchi Sea. Full article

A blocking high in the Ural Mountains, which is recognized as the third major blocking high area in the northern hemisphere, describes a deep warm high-pressure system superimposed on the westerly belt. Based on the ERA-5 daily reanalysis data (the fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis global climate dataset) and using the Tibaldi and Molteni (TM) method, we selected 43 blocking high events in the Ural Mountains during the extended winters of 1979–2020 and analyzed their atmospheric circulation characteristics and influencing factors. Our findings revealed a downward trend in the frequency of occurrence of blocking highs in the Ural Mountains in winter, most of them were short-lived; furthermore, the frequency and duration of these occurrences generally followed a 3–4 years oscillating cycle. The synthetic results of the geopotential height (HGT) anomaly field and the surface air temperature (SAT) anomaly field of these 43 extended wintertime blocking high events in the Ural Mountains region showed that during the development of a blocking high, the central intensity of the positive anomalies in the Ural Mountains region first increased and then weakened, while the central intensity and meridional span of the negative anomalies in the Eurasian mid-latitudes of the SAT anomaly field increased continuously. In addition, abnormally high sea surface temperature (SST) in the North Atlantic sea area and abnormal reduction of sea ice (SI) in the Barents-Kara Sea and the Chukchi Sea in autumn had a significant impact on the wintertime formation of Ural Mountains blocking highs. In contrast, in autumn, the abnormal reduction of SI in the Barents-Kara and Chukchi Seas might also have led to the westward positioning of Ural Mountains blocking highs. 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

In the Russian Arctic seas and adjacent areas of the Arctic basin, 120 sites of siboglinid records are currently known. Individuals belonging to 15 species have been collected. The largest number (49.2%) of records were made in the Barents Sea, followed by the Laptev Sea (37.5%) and the Arctic basin (10 records; 8.3%). No siboglinids have been reported from the Chukchi Sea. The largest number of species has been identified in both the Laptev Sea and Arctic basin (seven species each). Seventy-eight percent of the records were discovered at water depths down to 400 m. Many of the siboglinid records in the Arctic seas of Russia are associated with areas of high hydrocarbon concentrations. In the Barents Sea, Nereilinum murmanicum has been collected near the largest gas fields. The records of Oligobrachia haakonmosbiensis, N. murmanicum, Siboglinum ekmani, Siboglinum hyperboreum, Siboglinum norvegicum, as well as two undetermined species of siboglinids are associated with the marginal areas of bottom gas hydrates where methane emissions can occur. The Arctic seas of Russia feature vast areas of permafrost rocks containing gas hydrates flooded by the sea. Under the influence of river runoff, gas hydrates dissociate, and methane emissions occur. Crispabrachia yenisey and Galathealinum karaense were found in the Yenisei estuary, and O. haakonmosbiensis was found in the Lena estuary. Full article

Monitoring the status of Arctic marine ecosystems is aided by multi-sensor oceanographic moorings that autonomously collect data year-round. In the northeast Chukchi Sea, an ASL Environmental Sciences Acoustic Zooplankton Fish Profiler (AZFP) collected data from the upper 30 m of the water column every 10–20 s from 2014 to 2020. We here describe the processing of the AZFP’s 455 kHz acoustic backscatter return signal for the purpose of developing methods to assist in characterizing local sea ice conditions. By applying a self-organizing map (SOM) machine learning algorithm to 15-min ensembles of these data, we are able to accurately differentiate between the presence of open water and sea ice, and thereby characterize statistical properties surface wave height envelopes and ice draft. The ability to algorithmically identify small-scale features within the information-dense acoustic dataset enables efficient and rich characterizations of environmental conditions, such as frequency of sparse ice floes in otherwise open water and brief open-water leads amidst the ice pack. Corrections for instrument tilt, speed of sound, and water level allow us to resolve the sea surface reflection interface to within approximately 0.06 ± 0.09 m. By automating the acoustic data processing and alleviating labor- and time-intensive analyses, we extract additional information from the AZFP backscatter data, which is otherwise used for assessing fish and zooplankton densities and behaviors. Beyond applications to new datasets, the approach opens possibilities for the efficient extraction of new information from existing upward-looking sonar records that have been collected in recent decades. Full article