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ABSTRACT In cold regions across the globe, snowpack dynamics play a fundamental role in regulating hydrological regimes, influencing water resource availability, and triggering natural hazards such as floods, landslides, and debris flows. As climate warming accelerates, particularly in high‐latitude and high‐altitude areas, the need for accurate snow accumulation and snowmelt estimation has become increasingly critical for both environmental management and disaster risk reduction. To overcome the limitations of traditional constant‐density assumptions, this study presents an improved snow accumulation and snowmelt estimation approach incorporating temporal snow density variability and compaction effects. Subsequently, a comparative assessment of six widely used snow density estimation models is conducted based on the observed snow depth and density measurements. Results demonstrate that snow density estimation requires partitioning the entire snow cover duration into two distinct phases, that is, snowpack season and snowmelt season, and accurate snow density estimation must separately account for compaction effects induced by snow depth and duration of snow cover during the snowpack season and snowmelt season. That is, during the snowpack season, the increases in snow density are mainly caused by the gravitational compaction of overlying fresh snow layers, while during the snowmelt season, the snow density enhancement is predominantly governed by the duration of snow cover. Afterward, based on the proposed snow accumulation and snowmelt estimation approach, the impacts of temperature rise induced by climate change on snowpack dynamics were systematically investigated. Results indicate that the rising temperatures contribute to a reduction in snow depth during the snowpack season, primarily in the initial unstable phase of snowpack formation. Conversely, during the snowmelt season, temperature increases exert a more pronounced influence on snowmelt dynamics. Analysis of meteorological data from Nakayama Pass, Hokkaido, Japan, indicates that for every 1.0°C increase in temperature, the duration of snow cover at this location will be reduced by approximately 14.5 days, which may have implications for understanding snowpack responses to climate warming in other snow‐dominated regions. The findings of this study provide critical assessment benchmarks and modeling support for evaluating snowmelt‐induced disasters, including but not limited to floods, landslides, and debris flows.

In this study, we established an annually resolved chronology for the upper 98.5 m of a 210.5 m deep ice core (Styx-M core) drilled at the Styx Glacier plateau (SGP) in northern Victoria Land, East Antarctica, to reconstruct the multi-centennial variations of the snow accumulation rate (SAR). The core was dated via the annual layer counting of highly resolved impurities exhibiting seasonal cycles. The layer counting result was constrained using multiple temporal markers, including the 239Pu peaks that resulted from atmospheric weapon tests as well as five large volcanic eruptions in recorded history. These approaches show that the Styx-M core chronology covered 755 years (1259–2014 CE), with the estimated dating uncertainties of ±8 years. The annual accumulation record was derived using the depth-age scale and depth-density relationships of the core. This record revealed a long-term trend of a ∼30% increase in the SARs over the past 755 years, overlapping the pronounced inter-decadal and multi-decadal fluctuations. Further study will be needed to reveal the complex interaction of oceanic and atmospheric processes controlling the temporal fluctuations of SARs in the coastal areas of northern Victoria Land, combining multiple proxy records in the Styx-M core.

SWAP land surface model, developed by the authors of this article, was used to carry out many-year calculations of snow cover characteristics for forest and field areas in the main regions of Asian Russia: West Siberia, East Siberia, and Far East for a historic period (1967−2019). The comparison of simulation results with the appropriate data of route snow surveys at meteorological stations in the Asian part of RF showed that SWAP adequately reproduces the dynamics of snow water equivalent, snow depth and density in open areas and under forest canopy at the chosen sites. For all sites located in snow survey areas, climatic values of the characteristics of snow cover formation regime were obtained for two types of the land surface (forest and field) and two climatic periods (1967−1992 and 1993−2019) and used to identify trends in changes in these characteristics in the historic period. It was shown that the direction of changes in the climatic values of snow cover characteristics in forest and field areas in West Siberia, East Siberia, and Far East is the same and corresponds to projections for the XXI century derived from climate models.

Urban snow management systems are typically treated as logistical operations to remove and dispose of excess snow. However, the Sapporo Glacier concept reframes municipal snow management within a cryospheric systems framework, transforming urban snow accumulation into a controlled cryospheric process that interacts with climate and urban energy systems. This paper presents a hypothesis-driven scoping concept, the Sapporo Glacier, as a conceptual framework for Urban Cryosphere Engineering, which seeks to design and control the long-term storage, insulation, and metamorphism of urban snow using bounded, first-order physical reasoning rather than site-calibrated performance prediction to create a glacier possessing glacier ice (as classically defined) and measurable flow. Using Sapporo City’s existing snow-depot infrastructure as a reference model, the framework integrates physical modeling (degree-day method and simplified energy-balance considerations), surface control through organic mulch, and seasonal monitoring to delineate feasible design regimes for optimizing the thermal state of accumulated snow. Beyond technical feasibility, it emphasizes socio-environmental integration, envisioning snow storage as both a climate-adaptive infrastructure and a cultural landscape that connects citizens to seasonal cycles. Importantly, meltwater released from such an urban glacier during summer may generate a localized, testable nearshore thermal signal, enabling empirical evaluation of coastal cryosphere–ocean interactions. This hypothesis-driven, conceptual approach aims to establish an interdisciplinary foundation for future empirical studies and design experiments, rather than to deliver predictive site-specific outcomes, toward the realization of urban glaciers as sustainable and ecological elements of city life.

A procedure for calculating various characteristics of snow cover formation, based on the use of the land surface model SWAP was tested on forest areas of the European Russia for a historical period (1967−2019). The comparison of simulation results with appropriate observation data showed the good quality of reproduction of snow formation processes at these objects. Changes of the climatic values of snow cover formation characteristics in the historical period were analyzed to reveal tendencies in these changes in forest areas in the region. Thus, it was found that, despite the decrease in the duration of snow cover, there is increase in snowpack, in particular, in the maximal snow water equivalent. The difference between the characteristics of snow cover formation in the field and forest areas of European Russia was assessed. The mean values of the snow accumulation coefficient over the forest area relative to the field was found to be greater than 1.0. At the same time, the climatic changes in the historical period lead to a decrease of this characteristic in time.

During winters, the high-speed train travels in the northern of China is struck by to the snow, ice and coldness, massive snow accumulating on the bogies. To understand the cause of snow packing on the high-speed train’s bogies clearly, the 3-D unsteady Reynolds-averaged Navier-Stokes equations with a RNG double-equations turbulence model and a DPM discrete phase model were used to investigate the flow field carried snow particles in a single high-speed train bogie region and monitor the movement of snow particles. And, the numerical simulation was verified by the wind tunnel test. The results show that when air flows into the region, the airflow will rise and impact on the wheels, brakes, electromotors and other parts of bogie regions. The snow particles will follow the air, while the air direction changes sharply the particles will keep the movement due to the inertia. Afterwards, the snow packs on the bogie. In front of the bogies the streamlines of the air and the particle path lines are basically the same. However, due to the inertia of mass particles, the following characteristics of the snow particles with the air are not obvious in the bogie leeward side. Different structures of the end plates will affect the snow accumulation in the bogie regions.

In this paper, a new installation of flat plate deflector which attached on the bottom of the bogie frame is proposed and its anti-snow accumulation performance with different attack angles is numerically studied. The wind-snow two-phase flow in the bogie region is simulated based on the Reynolds Averaged Navier-Stokes (RANS) equations combined with the Realizable \"k-ε\" turbulence model and the Lagrangian particle phase method. The adopted numerical simulation methodology is verified and validated by comparing with previous wind tunnel tests. In this paper, three typical attack angles (30°, 60°, 90°) for deflector are studied. The results show that: the 30° case has a medium influence on the flow field and reduces snow accumulation by 35.14%; the 60° case guides the high-speed airflow downward and has the best effect with 62.46% reduction in snow accumulation; the 90° case has the smallest reduction with 20.30% in the mass. Overall, all deflectors with three different installation angles can reduce the mass of snow accumulated on the bogie surface.

Snowmelt is a very important component of freshwater resources in the polar environment. Seasonal fluctuations in the water supply to glacial drainage systems influence glacier dynamics and indirectly affect water circulation and stratification in fjords. Here, we present spatial distribution of the meltwater production from the snow cover on Hansbreen in southern Spitsbergen. We estimated the volume of freshwater coming from snow deposited over this glacier. As a case study, we used 2014 being one of the warmest season in the 21st century. The depth of snow cover was measured using a high frequency Ground Penetrating Radar close to the maximum stage of accumulation. Simultaneously, a series of studies were conducted to analyse the structure of the snowpack and its physical properties in three snow pits in different glacier elevation zones. These data were combined to construct a snow density model for the entire glacier, which together with snow depth distribution represents essential parameters to estimate glacier winter mass balance. A temperature index model was used to calculate snow ablation, applying an average temperature lapse rate and surface elevation changes. Applying variable with altitude degree day factor, we estimated an average daily rate of ablation between 0.023 m d-1 °C-1 (for the ablation zone) and 0.027 m d-1 °C-1 (in accumulation zone). This melting rate was further validated by direct ablation data at reference sites on the glacier. An average daily water production by snowmelt in 2014 ablation season was 0.0065 m w.e. (water equivalent) and 41.52·106 m3 of freshwater in total. This ablation concerned 85.5% of the total water accumulated during winter in snow cover. Extreme daily melting exceeded 0.020 m w.e. in June and September 2014 with a maximum on 6th July 2014 (0.027 m w.e.). The snow cover has completely disappeared at the end of ablation season on 75.8% of the surface of Hansbreen.

Using a high-durability designed plasma electrode (PA), the plasma actuation effect on both a two-dimensional backward-facing step flow (standard model) and an arc-shaped three-dimensional backward-facing step flow (arc model) was investigated experimentally. First, we searched for plasma operation control conditions suitable for the two-dimensional backward-facing step flow by carrying out experiments using a medium-sized circulating wind tunnel. Next, using the natural-snow wind tunnel of the Hokkaido University of Science, we examined whether an AC-driven PA can control snowfall flow. It became clear for the first time that the amount of snow accumulation can be reduced by more than 20% when the PA is driven at a dimensionless frequency of fH/U = 0.32, where f is the pulsed modulation frequency, H is the step height, and U is the mainstream velocity, and the duty ratio D (the time ratio of PA_ON to the total time when controlled by the pulsed modulation frequency) is equal to 1.0%. It was also confirmed that by masking the arc-shaped electrode parallel to the mainstream and using only the part perpendicular to the mainstream of the PA electrode, the amount of accumulated snow could be reduced by up to 20%. It has become clear that high-durability designed plasma electrodes can control the snowfall flow and reduce the amount of accumulated snow.

Coupled hydrological and atmospheric modeling is an efficient method for snowmelt runoff forecast in large basins. We use short-range precipitation forecasts of mesoscale atmospheric Weather Research and Forecasting (WRF) model combining them with ground-based and satellite observations for modeling snow accumulation and snowmelt processes in the Votkinsk reservoir basin (184,319 km 2 ). The method is tested during three winter seasons (2012–2015). The MODIS-based vegetation map and leaf area index data are used to calculate the snowmelt intensity and snow evaporation in the studied basin. The GIS-based snow accumulation and snowmelt modeling provides a reliable and highly detailed spatial distribution for snow water equivalent (SWE) and snow-covered areas (SCA). The modelling results are validated by comparing actual and estimated SWE and SCA data. The actual SCA results are derived from MODIS satellite data. The algorithm for assessing the SCA by MODIS data (ATBD-MOD 10) has been adapted to a forest zone. In general, the proposed method provides satisfactory results for maximum SWE calculations. The calculation accuracy is slightly degraded during snowmelt periods. The SCA data is simulated with a higher reliability than the SWE data. The differences between the simulated and actual SWE may be explained by the overestimation of the WRF-simulated total precipitation and the unrepresentativeness of the SWE measurements (snow survey).