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Monitoring changes in glacial dynamics is essential for understanding the environmental response to accelerated climate warming in the Arctic. However, geodetic surveys in polar regions continue to present considerable challenges because of the harsh environmental conditions and the polar night. This study records a 14-year-long time series (2006–2019) of global navigation satellite system (GNSS) surveys of the positions of 16 ablation stakes distributed across Hansbreen, a tidewater glacier in southern Svalbard. The measurements were conducted with an exceptionally high temporal resolution, from about 1 week to about 1 month, and covering altitudes ranging from 20 to 490 m a.s.l. The position of one stake was surveyed every day. The primary data products consist of the stake coordinates and velocities. Time series of annual and seasonal velocities are also provided. This dataset may be a subject of further studies of glacier dynamics in relation to the long-term and seasonal impact of climate change on ice flow in the region. It also offers unique material for tuning numerical models of glacier dynamics and for validating satellite-derived products such as velocity and digital elevation models. The dataset described here has been made publicly available through the Zenodo repository: 10.5281/zenodo.8289380 (Błaszczyk et al., 2023). [ABSTRACT FROM AUTHOR]

Monitoring changes in glacial dynamics is essential for understanding the environmental response to a ccelerated climate warming in the Arctic. However, geodetic surveys in polar regions continue to present considerable challenges because of the harsh environmental condit ions and the polar night. This study records a 14--year--long time series (2006-2019) of GNSS surveys of the positions of 16 ablat ion stakes distributed across Hansbreen, a tidewater glacier in southern Svalbard. The measurements were conducted with an exceptionally high temporal resolution, from about one week to about one month, and covering altitudes ranging from 0 to 490 m asl. The position of one stake was surveyed every day. The primary data products consist of the stake coordinates and velocities. Time series of annual and seasonal velocities are also provided. This dataset may be a subject of further studies of glacier dynamics in relation to the long--term and seasonal impact of climate change on ice flow in the region. It also offers unique material for tuning numerical models of glacier dynamics and for validating satellite--derived products such as velocity and digital elevation models. The dataset described here has been made publicly available through the Zenodo repository: https://doi.org/10.5281/zenodo.8289380 (Błaszczyk et al., 2023). [ABSTRACT FROM AUTHOR]

Background: Arctic snowpack microbial communities are continually subject to dynamic chemical and microbial input from the atmosphere. As such, the factors that contribute to structuring their microbial communities are complex and have yet to be completely resolved. These snowpack communities can be used to evaluate whether they fit niche-based or neutral assembly theories. Methods: We sampled snow from 22 glacier sites on 7 glaciers across Svalbard in April during the maximum snow accumulation period and prior to the melt period to evaluate the factors that drive snowpack metataxonomy. These snowpacks were seasonal, accumulating in early winter on bare ice and firn and completely melting out in autumn. Using a Bayesian fitting strategy to evaluate Hubbell's Unified Neutral Theory of Biodiversity at multiple sites, we tested for neutrality and defined immigration rates at different taxonomic levels. Bacterial abundance and diversity were measured and the amount of potential ice-nucleating bacteria was calculated. The chemical composition (anions, cations, organic acids) and particulate impurity load (elemental and organic carbon) of the winter and spring snowpack were also characterized. We used these data in addition to geographical information to assess possible niche-based effects on snow microbial communities using multivariate and variable partitioning analysis. Results: While certain taxonomic signals were found to fit the neutral assembly model, clear evidence of niche-based selection was observed at most sites. Inorganic chemistry was not linked directly to diversity, but helped to identify predominant colonization sources and predict microbial abundance, which was tightly linked to sea spray. Organic acids were the most significant predictors of microbial diversity. At low organic acid concentrations, the snow microbial structure represented the seeding community closely, and evolved away from it at higher organic acid concentrations, with concomitant increases in bacterial numbers. Conclusions: These results indicate that environmental selection plays a significant role in structuring snow microbial communities and that future studies should focus on activity and growth. A4vcHcKNh9Gahh9Z6pYiCt Video Abstract [ABSTRACT FROM AUTHOR]

This paper explores the potential of ground-penetrating radar (GPR) monitoring for an advanced understanding of snow cover processes and structure. For this purpose, the study uses the Hansbreen (SW Spitsbergen) records that are among the longest and the most comprehensive snow-cover GPR monitoring records available on Svalbard. While snow depth (HS) is frequently the only feature derived from high-frequency radio-echo sounding (RES), this study also offers an analysis of the physical characteristics (grain shape, size, hardness, and density) of the snow cover structure. We demonstrate that, based on GPR data (800 MHz) and a single snow pit, it is possible to extrapolate the detailed features of snow cover to the accumulation area. Field studies (snow pits and RES) were conducted at the end of selected accumulation seasons in the period 2008–2019, under dry snow conditions and HS close to the maximum. The paper shows that although the snow cover structure varies in space and from season to season, a single snow pit site can represent the entire center line of the accumulation zone. Numerous hard layers (HLs) (up to 30% of the snow column) were observed that reflect progressive climate change, but there is no trend in quantity, thickness, or percentage contribution in total snow depth in the study period. HLs with strong crystal bonds create a "framework" in the snowpack, which reduces compaction and, consequently, the ice formation layers slow down the rate of snowpack metamorphosis. The extrapolation of snow pit data through radar profiling is a novel solution that can improve spatial recognition of snow cover characteristics and the accuracy of calculation of snow water equivalent (SWE). [ABSTRACT FROM AUTHOR]

Snow cover is a key element in the water cycle, global heat balance and in the condition of glaciers. Characterised by high temporal and spatial variability, it is subject to short- and long-term changes in climatic conditions. This paper presents a unique dataset of snow measurements on Hansbreen, an Arctic glacier in Svalbard. The dataset includes 79 archived snow profiles performed from 1989 to 2021. It presents all available observations of physical properties for snow cover, such as grain shape and size, hardness, wetness, temperature and density, supplemented with organised metadata. All data has been revised and unified with current protocols and the present International Classification for Seasonal Snow on the Ground, allowing comparison of data from different periods and locations. The information included is essential for estimations of glacier mass balance or snow depth using indirect methods, such as ground-penetrating radar. A wide range of input data makes this dataset valuable to the greater community involved in the study of snow cover evolution and modelling related to glaciology, ecology and hydrology of glacierised areas. Measurement(s) snow cover, snow stratigraphy Technology Type(s) snow pit analyses, automatic weather stations Factor Type(s) Hansbreen Sample Characteristic - Environment seasonal snow cover, cryosphere, polar environment Sample Characteristic - Location glacier, Hansbreen, Hornsund, Spitsbergen, Svalbard, Arctic [ABSTRACT FROM AUTHOR]

In recent years extreme winter warming events have been reported in arctic areas. These events are characterized as extraordinarily warm weather episodes, occasionally combined with intense rainfall, causing ecological disturbance and challenges for arctic societies and infrastructure. Ground-ice formation due to winter rain or melting prevents ungulates from grazing, leads to vegetation browning, and impacts soil temperatures. The authors analyze changes in frequency and intensity of winter warming events in the Nordic arctic region-northern Norway, Sweden, and Finland, including the arctic islands Svalbard and Jan Mayen. This study identifies events in the longest available records of daily temperature and precipitation, as well as in future climate scenarios, and performs analyses of long-term trends for climate indices aimed to capture these individual events. Results show high frequencies of warm weather events during the 1920s-30s and the past 15 years (2000-14), causing weak positive trends over the past 90 years (1924-2014). In contrast, strong positive trends in occurrence and intensity for all climate indices are found for the past 50 years with, for example, increased rates for number of melt days of up to 9.2 days decade−1 for the arctic islands and 3-7 days decade−1 for the arctic mainland. Regional projections for the twenty-first century indicate a significant enhancement of the frequency and intensity of winter warming events. For northern Scandinavia, the simulations indicate a doubling in the number of warming events, compared to 1985-2014, while the projected frequencies for the arctic islands are up to 3 times higher. [ABSTRACT FROM AUTHOR]

The boreal winter 2019/2020 was very irregular in Europe. While there was very little snow in Central Europe, the opposite was the case in northern Fenno-Scandia, particularly in the Arctic. The snow cover was more persistent here and its rapid melting led to flooding in many places. Since the last severe spring floods occurred in the region in 2018, this raises the question of whether more frequent occurrences can be expected in the future. To assess the variability of snowmelt related flooding we used snow cover maps (derived from the DLR's Global SnowPack MODIS snow product) and freely available data on runoff, precipitation, and air temperature in eight unregulated river catchment areas. A trend analysis (Mann-Kendall test) was carried out to assess the development of the parameters, and the interdependencies of the parameters were examined with a correlation analysis. Finally, a simple snowmelt runoff model was tested for its applicability to this region. We noticed an extraordinary variability in the duration of snow cover. If this extends well into spring, rapid air temperature increases leads to enhanced thawing. According to the last flood years 2005, 2010, 2018, and 2020, we were able to differentiate between four synoptic flood types based on their special hydrometeorological and snow situation and simulate them with the snowmelt runoff model (SRM). [ABSTRACT FROM AUTHOR]

Compared to other Arctic ice masses, Svalbard glaciers are low-elevated with flat interior accumulation areas, resulting in a marked peak in their current hypsometry (area-elevation distribution) at ~450 m above sea level. Since summer melt consistently exceeds winter snowfall, these low-lying glaciers can only survive by refreezing a considerable fraction of surface melt and rain in the porous firn layer covering their accumulation zones. We use a high-resolution climate model to show that modest atmospheric warming in the mid-1980s forced the firn zone to retreat upward by ~100 m to coincide with the hypsometry peak. This led to a rapid areal reduction of firn cover available for refreezing, and strongly increased runoff from dark, bare ice areas, amplifying mass loss from all elevations. As the firn line fluctuates around the hypsometry peak in the current climate, Svalbard glaciers will continue to lose mass and show high sensitivity to temperature perturbations. Svalbard glaciers are among the lowest ice masses in the Arctic, with a peak in glacier area below 450 m elevation. Using a high-resolution climate model, here the authors show that a modest warming in the mid-1980s propagated meltwater runoff above the glacier area peak, amplifying Svalbard mass loss from all elevations. [ABSTRACT FROM AUTHOR]

The primary environmental concern related to nuclear power is the production of radioactive waste hazardous to humans and the environment. The main scientific and technological problems to address this are related to the storage and disposal of the nuclear waste and monitoring the dispersion of radioactive species into the environment. In this work, we determined an anomalously high 14C activity, well above the modern natural background, on surface and seasonal snow sampled in early May 2019 on glaciers in the Hornsund fjord area (Svalbard). Due to the lack of local sources, the high snow concentrations of 14C suggest long-range atmospheric transport of nuclear waste particles from lower latitudes, where nuclear power plants and treatment stations are located. The analysis of the synoptic and local meteorological data allowed us to associate the long-range transport of this anomalous 14C concentration to an intrusion event of a warm and humid air mass that likely brought pollutants from Central Europe to the Arctic in late April 2019. Elemental and organic carbon, trace element concentration data, and scanning electron microscopy morphological analysis were performed on the same snow samples to better constrain the transport process that might have led to the high 14C radionuclide concentrations in Svalbard. In particular, the highest 14C values found in the snowpack (> 200 percent of Modern Carbon, pMC) were associated with the lowest OC/EC ratios (< 4), an indication of an anthropogenic industrial source, and with the presence of spherical particles rich in iron, zirconium, and titanium which, altogether, suggest an origin related to nuclear waste reprocessing plants. This study highlights the role of long-range transport in exposing Arctic environments to human pollution. Given that the frequency and intensity of these atmospheric warming events are predicted to increase due to ongoing climate change, improving our knowledge of their possible impact to Arctic pollution is becoming urgent. [Display omitted] • Atmospheric transport of 14C to the Arctic during warm intrusion events. • Deposition of nuclear waste residuals onto the Arctic snowpack. • Rain on snow event affected the spatial distribution of deposition. • Air mass back trajectories tracked the source in central Europe. [ABSTRACT FROM AUTHOR]