The study investigates the influence of air temperature on the variability in the timing of stable ice formation and final ice clearance in different regions of the White Sea under current climate change. The relevance of the study derives from the need to update the methods used in the statistical forecasting of the dates of the main ice-regime phases. This is particularly important in view of the planned construction of a new seaport near the town of Belomorsk. The study is based on marine and meteorological observations for 1980–2019 covering the main regions of the White Sea. Correlation and regression analyses were performed to assess the relationships between the dates of the main ice-regime phases and air temperature. The temperature characteristics considered for the periods of ice formation and ice decay included the dates of air temperature transition through 0 °C, mean monthly air temperatures, and accumulated sums of negative and positive air temperatures. The correlation coefficients between the dates of stable ice formation and those of air temperature transition through 0 °C to negative values were generally low in most regions (R = 0.22–0.54), although at individual observation sites they reached R = 0.65–0.75. The strongest relationships for the timing of stable ice formation were found with accumulated negative air temperatures during the autumn–winter period (R = 0.68–0.77). The timing of final ice clearance was most closely related to accumulated positive air temperatures in spring (R = 0.66–0.75) and to the dates of air temperature transition through 0 °C to positive values (R = 0.61–0.74). The strength of the relationships identified varied depending on the physical and geographical characteristics of the different regions of the White Sea. The derived regression equations can be used in the development of modern methods for medium- and long-term forecasting of the timing of the main ice-regime phases. The results are of practical importance for the hydrometeorological support of marine activities in the White Sea.

In the context of a changing climate, a comprehensive assessment is required of the impact of climatic conditions on the comfort of the living environment. This study evaluates changes in bioclimatic indices assessed on the basis of model reanalysis across the marine and land Arctic within the boundaries of the WMO Arctic Regional Climate Center — Network under ongoing climate change. Data from two periods were used: the WMO reference period (1991–2020) and the recent five-year period (2021–2025). Three indices were analyzed: the Bodman severity index, Effective Temperature (ET), and Net Effective Temperature (NET). For eight Arctic regions, long-term means, linear trends (1991–2025), and shifts in the shares of severity/comfort categories between the two periods were calculated. For the Arctic as a whole, the Bodman index averages 5.8 points (extremely severe conditions) in winter and 2.4 points (slightly severe) in summer. ET averages –17.7 °C (discomfort) in winter and 4.8 °C (partial discomfort) in summer. NET averages –44.4 °C (very cold) in winter and –10.5 °C (very cold) in summer, so standard NET thresholds proved unsuitable for the Arctic conditions. Trends for all the indices predominantly indicate increasing comfort, except for zero trends in the Bodman index for several regions. The average number of very cold days per year (calculated using NET) is 349, with a trend of 1.5 days/decade (3.1 days/decade when permanently cold areas are excluded), indicating a growing number of warmer days. During 2021–2025, most of the regions showed a shift toward milder Bodman severity categories, with increased shares of less severe categories and reduced shares of the harshest ones. The work presents a new zoning: the delineating of the Arctic zone is based on the combination of the effective temperature and Bodman index values. The results may be useful for economic planning and adaptation strategies in the region.

The Russian Barentsburg Hydrometeorological Observatory has provided the longest series of continuous instrumental air temperature observations on Spitsbergen Archipelago, starting in 1932. To extend this record further back in time, measurements from the Norwegian Green Harbour station (1911–1930) can be utilized. However, despite the proximity of the two sites (about 1.5 km), a direct merger of the data is invalid owing to substantial microclimatic differences. These differences stem from the unequal distances of the sites from Grønfjorden and from their distinct topographic settings — a low-lying area at the foot of a slope at Green Harbour versus a steep slope at Barentsburg. A method is presented for reconciling mean monthly air temperature values recorded at the Norwegian meteorological station Green Harbor (Spitsbergen Archipelago, Grønfjorden Bay, Cape Finneset) for the period 1911–1930 with observations from the Barentsburg Hydrometeorological Observatory. The corrections applied to the mean monthly temperatures at Green Harbor were negative for temperatures above –5 °C, owing to the warming influence of Grønfjorden, which is most pronounced at this site because of its cape location. At lower temperatures, the corrections become positive, presumably as a result of the formation of stable snow-ice cover (fast ice) in the fjord. The appearance of ice significantly restricts heat transfer from the seawater to the surface atmosphere, while the ice-covered surface itself becomes an area for the accumulation of cold air draining from the adjacent slopes and for its subsequent radiative cooling. Once Grønfjorden freezes, an inverted temperature profile develops along the slope. The resulting composite series of monthly mean air temperatures for Barentsburg was repeatedly tested for homogeneity using the standard normal homogeneity test (SNHT) across time windows of varying widths. No inhomogeneity was detected at the junction points between the calculated and measured data. 

Bottom sediments of Arctic lakes are widely used as archives of environmental change and indicators of trace element accumulation. However, the interpretation of integrated geochemical pollution indices may be complicated in regions with complex geological settings, where natural lithogenic and post-sedimentary processes significantly influence sediment chemistry. The aim of this study was to assess the ecological and geochemical condition of present-day bottom sediments from ten small lakes located on the Rybachy and Sredny peninsulas(Murmansk Region, Russian Arctic) and to identify the factors controlling their chemical composition. The study combined X-ray fluorescence analysis with integrated geochemical indices (Igeo, PLI and RI) and factor analysis of potentially toxic elements. Most of the lakes were characterized by moderate contamination according to the Pollution Load Index (PLI = 1.4–1.8) and low ecological risk according to the Potential Ecological Risk Index (RI). The highest index values were recorded in Lakes Skorbeevskoe, Pitevoe and Palvi. The principal contribution to the pollution indices was provided by Sb, Bi, Pb, Ni, Tl and Cd. Factor analysis distinguished three independent geochemical associations corresponding to lithogenic–diagenetic, ore-related and mixed mechanisms of trace element accumulation. The elevated concentrations of Cd and Pb in Lake Pitevoe were due to phosphate-bearing rocks and sphalerite within the catchment area, whereas the geochemical anomalies in Lake Palvi were controlled by early diagenetic redistribution of elements and the formation of a manganese redox barrier. The findings demonstrate that the elevated values of integrated geochemical indices may reflect not only recent anthropogenic inputs but also natural geological and post-sedimentary processes. Therefore, reliable environmental assessment of Arctic lake sediments requires an integrated interpretation of geochemical indices that takes into account lithology, sediment stratigraphy and diagenetic transformations, thereby reducing the risk of inaccurate contamination assessment.

Instrumental data on sublimation from the snow cover surface in the high-latitude Arctic remain scarce. Existing estimates indicate a wide range of sublimation losses, varying from 10 to 90 % of the total cold-season precipitation depending on local climatic and landscape conditions. The paper presents the results of two-year (2024–2025) instrumental observations of sublimation from the snow cover in the high-latitude Arctic, specifically in the area of the research station “Ice Base Cape Baranova” (Severnaya Zemlya archipelago). The aim of the study is to summarize experimental data, assess the key factors influencing the evaporation process under Arctic conditions, and determine regional characteristics of moisture loss from snow. The observations were conducted according to the methodology of the FSBI State Hydrological Institute using standard GGI 500-6 evaporimeters and additional instruments made of solid polycarbonate. To exclude anthropogenic influence, the evaporation site was located 500 m away from the research station’s meteorological site. It was found that during the pre-spring period, the average daily sublimation rate was 0.15 mm/day, with daytime sublimation at 0.12 mm/day and nighttime at 0.05 mm/night. For the winter and pre-spring periods of 2025, the total sublimation was negative (–3.52 mm, indicating condensation). During the spring transition period and snowmelt in 2025, sublimation reached 13.03 mm, which is 46.5 % higher than in the same periods of 2024 (6.06 mm). To fill the gaps in the observation series caused by adverse weather conditions, a semi-empirical method by P.P. Kuzmin and a statistical multiple linear regression model E = f(U, B) were used, where U is wind speed and B is radiation balance. The correlation coefficient between the instrumental data and model calculations was 0.840. It was shown that P.P. Kuzmin’s method overestimates sublimation (up to 42.52 mm for the entire period of 2025) compared to the model (32.16 mm). The results obtained allow the refinement of water balance calculations in the Arctic regions and can be used in water-balance and climatic research.

Stamukhas are dangerous ice formations typical of the shallow parts of freezing seas. In conditions of poor visibility, stamukhas pose a threat to shipping, and when they run afloat and drift, they also pose a threat to offshore infrastructure. Regular monitoring of stamukhas and obtaining comprehensive information about their location and size is essential for the safety of maritime operations in the Russian Arctic. A method for identifying stamukhas using satellite imagery developed at the Arctic and Antarctic Research Institute (AARI) enabled the collection of information on the location and horizontal dimensions of 2,975 stamukhas in the Pechora Sea, Kara Sea, Laptev Sea, East Siberian Sea, and Chukchi Sea over the five-year period 2020–2024. These findings were compared with archival data on the location and draft of stamukhas based on aerial ice reconnaissance in the same seas from 1959 to 1995. The following features were identified of the stamukha distribution regime in the Russian Arctic seas. In recent years, most of the water areas under consideration have shown a general trend for a shift in the distribution of stamukhas toward shallower depths. At the same time, the distribution range of stamukhas at depths greater than 20 meters has decreased. This is apparently due to both changes in the ice regime as a result of general climate change in recent decades in the Arctic, and to bottom processes of sediment accumulation, which contribute to the formation of shoals and banks, and the expansion of shallow zones. According to modern satellite data, the predominant range of depths for the formation of stamukhas in the Pechora and Chukchi Seas is 4-8 m, in the Kara and Laptev Seas — 8–12 m, and in the East Siberian Sea — 12–16 m. Currently, the perennial stamukhas and extended multi-row barriers of stamukhas, typical of the 20th century, are absent from the waters of the Russian Arctic seas. It has been established that after the destruction of fast ice in the summer, the overwhelming majority of stamukhas last no more than five days. Despite the low values of the correlation coefficients obtained between the draft and the horizontal dimensions of stamukhas, a general increase in the values of the length, width, and elongation coefficient of stamukhas is observed with the increasing depth of their formation.

Ensemble simulations with the Northern Hemisphere ice sheets model are performed for the last glacial cycle (last 123 kyr). The time dependence of the atmospheric forcing is reconstructed based on two sets of borehole data — EPICA (The European Project for Ice Coring in Antarctica; the data exhibit weak millennium-scale variabilitу) and NGRIP (North Greenland Ice Core Project; the data show strong temperature variability at the indicated timescale). The time dependence is combined with the long-term means from theERA5 reanalysis(for the present-day state) and with the IPSL-CM4-V1-MR model output for the Last Glacial Maximum. We found that the simulated trajectory in MIS3 (Marine Isotope Stage 3; ~60–30 kyr before present) is very sensitive to the relatively small perturbation of thus constructed paleoscenarios. This sensitivity is exhibited both for EPICA(after perturbing the data by the stochastic autoregressive processes with decorrelation timescale up to 2 kyr) and NGRIP data (after removing the millenium-scale variability from the data by applying the Savitzky– Golay filter). In particular, depending on the existence of such variability in the forcing dataset and provided that this variability is strong enough, an artificial interglacial is developed during MIS3. The physical reason for the development of this interglacial is the location of the system trajectory near the glacial termination threshold owing to the specific Earth orbit parameter configuration in the time interval indicated. We conclude that both the EPICA and NGRIP data can be used to force the Northern Hemisphere ice sheet model in the last glacial cycle. However, it is sensible to exclude the millennium-scale variability from the NGRIP data before applying them to paleoscenario reconstruction. In addition, high sensitivity of the model to the applied forcing during MIS3 might indicate the trajectory splitting in the vicinity of the attractor basin boundary in this time interval.

Using Bennett Island (East Siberian Sea) as a case study, the role of shortwave radiation was examined in shaping the spatial distribution of the mass balance of Arctic ice caps. The aim of the study was to quantitatively assess the influence of spatial variability in insolation on glacier surface lowering. Changes in the surface elevation of four ice caps on Bennett Island, with a total area of approximately 56 km², over the period 2012–2022 were previously derived from multi-temporal ArcticDEM data. On average, the elevation change amounted to −6.27 ± 0.12 m, corresponding to a mass balance of −5.33 ± 0.39 m w. e. The mean incoming clear-sky shortwave radiation flux for a typical ablation season (76 frost-free days per year, based on ERA5-Land reanalysis data for 1994–2024) was modeled in SAGA GIS, taking into account both astronomical and terrain-related factors. The resulting distribution of values is characterized by spatial heterogeneity and direct dependencies on exposure and slope shading. The spatial variability of clear-sky insolation across the ice caps ranged from 360 to 520 W/m². For two of the ice caps, a statistically significant positive relationship between surface lowering and insolation was identified, with a linear trend of 0.013–0.021 m of additional melt per 1 W/m². Also, for two larger domes, a positive trend of ice melt was revealed, which equals 1.115–1.750 m per 100 m of altitude. It was shown that for smaller ice caps, the maximum differences in clear-sky insolation (160 W/m²) were equivalent to the effect of an elevation gradient of 100–200 m. For the largest ice cap, Toll, the influence of insolation could not be evaluated: due to horizontal ice motion, surface lowering derived using the geodetic method did not directly correspond to the actual melt. Therefore, further investigation required in situ mass balance measurements using the glaciological method. 

In Antarctica, despite the absence of permanent populations and economic activities typical of other continents, elevated levels of hazardous pollutants including lead are recorded in various environmental components. Brought through transboundary air transport, local sources of emissions, discharges, waste, and due to logistics and tourism, lead also enters the continent as part of various materials and products necessary for the operation of research stations and the survival of polar explorers. The article examines the entry of lead into Antarctica in vehicles. Almost all internal combustion engine vehicles contain batteries that operate on a lead-acid system. Furthermore, heavy metals, including lead, are found in paintwork, brake pads and other components. The main focus in the article is on lead-acid batteries and paint coatings, and describes the possible pathways by which they may migrate into the environment. To carry out an assessment, available data on the vehicles used at year-round and seasonal Antarctic stations were collected. The vehicles were divided into five groups based on their function and engine power. For each group, the mass of batteries and coatings containing lead and specific factors of lead content per unit were calculated. According to the estimates obtained, the batteries of vehicles at Antarctic stations contain 25 729 kg of lead, and the paint coatings — 26.4 kg. The distribution of lead over the Antarctic regions is described. The highest amount of lead in vehicles are found in two areas: Queen Maud Land, where there are 7 year-round and 5 seasonal research stations, and Victoria Land with two year-round stations. Preliminary estimates are given of the annual volume of lead waste as a result of battery replacement. The paper discusses ways in which lead can enter the Antarctic environment at the end of the service life of batteries and/or vehicles, following their loss, or in the course of storage. Further steps to assess the impact of lead in vehicles on the Antarctic environment are outlined.