Light-absorbing impurities (LAIs), such as mineral dust (MD), organic carbon (OC), and black carbon (BC), deposited in snow, can reduce snow albedo and accelerate snowmelt. The Ili Basin, influenced by its unique geography and westerly atmospheric circulation, is a critical region for LAI deposition. However, quantitative assessments on the impact of LAIs on snow in this region remain limited. This study investigated the spatial distribution of LAIs in snow and provided a quantitative evaluation of the effects of MD and BC on snow albedo, radiative forcing, and snowmelt duration through sampling analysis and model simulations. The results revealed that the Kunes River Basin in the eastern Ili Basin exhibited relatively high concentrations of MD. In contrast, the southwestern Tekes River Basin showed relatively high concentrations of OC and BC. Among the impurities, MD plays a dominant role in the reduction of snow albedo and has a greater effect on the absorption of solar radiation by snow than BC, while MD is the most important light-absorbing impurity responsible for the reduction in the number of snow-melting days in the Ili Basin. Under the combined influence of MD and BC, the snowmelt period in the Ili Basin was reduced by 2.19 +/- 1.43 to 7.31 +/- 4.76 days. This study provides an initial understanding of the characteristics of LAIs in snow and their effects on snowmelt within the Ili Basin, offering essential basic data for future research on the influence of LAIs on snowmelt runoff and hydrological processes in this region.

Global climate change exerts profound effects on snow cover, with consequential impacts on microbial activities and the stability of soil organic carbon (SOC) within aggregates. Northern peatlands are significant carbon reservoirs, playing a critical role in mitigating climate change. However, the effects of snow variations on microbial-mediated SOC stability within aggregates in peatlands remain inadequately understood. Here, an in-situ field experiment manipulating snow conditions (i.e., snow removal and snow cover) was conducted to investigate how snow variations affect soil microbial community and the associated SOC stability within soil aggregates (> 2, 0.25-2, and < 0.25 mm) in a peatland of Northeast China. The results showed that snow removal significantly increased the SOC content and stability within aggregates. Compared to the soils with snow cover, snow removal resulted in decreased soil average temperatures in the topsoil (0-30 cm depth) and subsoil (30-60 cm depth) (by 1.48 and 1.34 degrees C, respectively) and increased freeze-thaw cycles (by 11 cycles), consequently decreasing the stability of aggregates in the topsoil and subsoil (by 23.68% and 6.85%, respectively). Furthermore, more recalcitrant carbon and enhanced SOC stability were present in microaggregates (< 0.25 mm) at two soil depths. Moreover, reductions in bacterial diversity and network stability were observed in response to snow removal. Structural equation modeling analysis demonstrated that snow removal indirectly promoted (P < 0.01) SOC stability by regulating carbon to nitrogen (C:N) ratio within aggregates. Overall, our study suggested that microaggregate protection and an appropriate C:N ratio enhanced carbon sequestration in response to climate change.

The complex failure behavior of ice under cyclic loading holds significant relevance for understanding the behavior of nearshore sea ice cover, ice shelves, and ice pavements or runways. Experimental evidence demonstrates that the strength of freshwater ice, whether in compression or flexure, can either increase or decrease after cyclic loading. To explore this further, new cyclicmonotonic loading experiments were conducted on snow-sintered ice using four-point bending and unconfined compression tests subjected to various temperatures, monotonic strain rates, and cycling conditions. The results show that the average non-cycled flexural and compressive strength of snow-sintered ice at -10 degrees C is higher than that of water-frozen freshwater ice. The cycled flexural and compressive strength of snow-sintered ice under cyclic loading is highly sensitive to strain rate and accumulated strain. Notably, brittle failure was delayed under cyclic compressive loading at strain rates as high as 10-1 s-1. However, as the number of cycles increases, accumulated strain leads to a decrease in strength. Cyclic loading altered the ductile-tobrittle transition rate and secant modulus, shedding light on the mechanisms behind high-strainrate, low-cycle strengthening effects in ice.

Climate change is reducing snowpack across temperate regions with negative consequences for human and natural systems. Because forest canopies create microclimates that preserve snowpack, managing forests to support snow refugia-defined here as areas that remain relatively buffered from contemporary climate change over time that sustain snow quality, quantity, and/or timing appropriate to the landscape-could reduce climate change impacts on snow cover, sustaining the benefits of snow. We review the current understanding of how forest canopies affect snow, finding that while closed-conifer forests and snow interactions have been extensively studied in western North America, there are knowledge gaps for deciduous and mixed forests with dormant season leaf loss. We propose that there is an optimal, intermediate zone along a gradient of dormant season canopy cover (DSCC; the proportion of the ground area covered by the canopy during the dormant season), where peak snowpack depth and the potential for snow refugia will be greatest because the canopy-mediated effects of snowpack sheltering (which can preserve snowpack) outweigh those of snowfall interception (which can limit snowpack). As an initial test of our hypothesis, we leveraged snowpack measurements in the northeastern United States spanning the DSCC gradient (low, 50% DSCC), including from 2 sites in Old Town, Maine; 12 sites in Acadia National Park, Maine; and 30 sites in the northern White Mountains of New Hampshire. Medium DSCC forests (typically mature mixed coniferous-deciduous forests) exhibited the deepest peak snowpacks, likely due to reduced snowfall interception compared to high DSCC forests and reduced snowpack loss compared to low DSCC forests. Many snow accumulation or snowpack studies focus on the contrast between coniferous and open sites, but our results indicate a need for enhanced focus on mixed canopy sites that could serve as snow refugia. Measurements of snowpack depth and timing across a wider range of forest canopies would advance understanding of canopy-snow interactions, expand the monitoring of changing winters, and support management of forests and snow-dependent species in the face of climate change.

Snow cover is a critical factor controlling plant performance, such as survival, growth, and biomass, and vegetation cover in regions with seasonal snow (e.g., high-latitude and high-elevation regions), due to its influence on the timing and length of the growing season, insulation effect during winter, and biotic and abiotic environmental factors. Therefore, changes in snow cover driven by rising temperatures and shifting precipitation patterns are expected to alter plant performance and vegetation cover. Despite the rapid increase in research on this topic in recent decades, there is still a lack of studies that quantitatively elucidate how plant performance and vegetation cover respond to shifting snow cover across snowy regions. Additionally, no comprehensive study has yet quantitatively examined these responses across regions, ecosystems, and plant functional types. Here, we conducted a meta-analysis synthesizing data from 54 snow cover manipulation studies conducted in both the field and laboratory across snowy regions to detect how plants performance and vegetation cover respond to decreased or increased snow cover. Our results demonstrate that plant survival, aboveground biomass, and belowground biomass exhibited significant decreases in response to decreased snow cover, with rates of survival having the greatest decrease. In response to increased snow cover, plant survival, growth, biomass and vegetation cover tended to increase, except for plant belowground length growth and biomass, which showed significant decreases. Additionally, our quantitative analysis of plant responses to changes in snow cover across regions, ecosystems, and plant functional types revealed that cold regions with thin snow cover, tundra and forest ecosystems, and woody species are particularly vulnerable to snow cover reduction. Overall, this study demonstrates the strong controls that snow cover exerts on plant performance, providing insights into the dynamics of snow-covered ecosystems under changing winter climatic conditions.

In alpine tundra regions, snowmelt plays a crucial role in creating spatial heterogeneity in soil moisture and nutrients across various terrains, influencing vegetation distribution. With climate warming, snowmelt has advanced, lengthening the growing season while also increasing the risk of frost damage to evergreen dwarf shrubs like Rhododendron aureum in alpine tundra regions. To understand these long-term effects, we used remote sensing imagery to analyze nearly four decades (1985-2022) of snowmelt date and the distribution change of R. aureum in Changbai Mountain, East China's only alpine tundra. Results show that snowmelt advanced by 1-3 days/10 years, with faster rates at higher elevations and shady slopes (0.4-0.6 days/10 years more than sunny slopes), while R. aureum increased more on shady slopes under such conditions. Our study demonstrates that these shifts in snowmelt date vary significantly across topographies and reveals how topography and snowmelt changes interact to shape the distribution of evergreen shrubs under climate warming.

The finite element method is used to investigate the ultimate lateral pressure of snowflake pile group in undrained clay in this paper. The parametric analyses are performed to study the effects of the geometry of cross-section, the pile-soil adhesion coefficient, the loading direction, and the normalized pile spacing on the ultimate lateral pressure and the damage mechanism of the snowflake pile. The analysis results show that the ultimate lateral pressure of snowflake pile group decreases with the increasing of the length-thickness ratio of the pile flange and increases with the increasing of the pile-soil adhesion coefficient. When the loading direction is considered, the snowflake pile group with the number of piles of 4 is less affected by the loading direction, it has a larger ultimate lateral pressure. The ultimate lateral pressure of the pile group significantly decreases with the increasing of the number of piles. When the pile spacing is smaller, the decreasing of the ultimate lateral pressure is more obvious with the increasing of the number of piles. On the basis of finite element analysis, the empirical formula of ultimate lateral pressure of snowflake pile group is proposed and calibrated with the finite element results.

We evaluated the morphology, geomorphic settings, and micrometeorological controls of sorted polygons, stripes, lobate patterns, and turf-banked terraces in two summit areas of Daisetsu Mountain, Japan, using orthophoto images and digital surface models generated from unmanned aerial vehicle observations and structure-from-motion techniques and in situ records of air temperature, wind speed/direction and ground temperatures. The sorted polygons on flat terrain are equiform and large (3.5 m in mean length), but on gentle slopes, they are elliptical and small (2.9 m). Sorted stripes and lobate patterns occur on slope steeper than 3.5 degrees-4.5 degrees. The form transition of sorted patterned grounds is considered due to activities of frost heave and thaw settlement, gelifluction, and frost creep, as well as the spatial pattern of soil wetness. In the windward slopes steeper than 3.5 degrees-4.5 degrees, the ground materials move downslope, forming lobate patterns and sorted stripes. On the flat surfaces and leeward slopes, snow accumulation prevents soils from cooling in winter, provides snowmelts to the soils, and thus thickens the seasonal thawing during summer, allowing sorting at greater depths and enlarging the diameters of the frost patterned forms. Snow redistribution and snowmelt infiltration produce locally moist soils, creating favorable environments for plant growth on leeward, that is, eastward sides of microtopography. Soil movements along slopes are dammed on the slope covered with dense vegetation cover where risers of turf-banked terrace are formed. This is the explanation why the turf-banked terraces are typically facing slightly eastward from principal slope direction.

Black carbon (BC) affects the Arctic climate via aerosol-radiation-cloud interaction and snow/ice albedo feedback. Fires have become a substantial source of the Arctic BC in recent years, while the radiative effects of BC in the Arctic due to the recent extreme fires remain unclear. In this study, the atmospheric and snow radiative forcing of BC in the Arctic due to the extreme fires in summer 2019 were investigated based on numerical simulations, and the effects on meteorological variables and snow albedo were explored. Biomass burning BC in summer 2019 caused negative radiative forcing at the bottom of the atmosphere in Greenland and the central Arctic Ocean, and it caused positive radiative forcing in Europe, central Siberia, and northern Canada, with values that can reach 9 W/m2 and 18 W/m2, respectively. The radiative forcing was spatially heterogeneous, which was mainly induced by the dominant role of semi-direct and indirect radiative effects of BC related to cloud changes. The air temperature in the higher troposphere increased in the central Arctic Ocean and Greenland, and the near-surface air temperature increased in Europe, central Siberia, and northern Canada. The responses of wind field and relative humidity were mainly linked with the air temperature changes, and the cyclone activity anomaly can be observed in the central Arctic. Biomass burning BC caused positive snow radiative forcing in Greenland of 0.4-1.4 W/m2, and the maximum snow albedo reduction was about 0.005. Overall, this study highlights the importance of BC from fires on the Arctic climate.

Polychlorinated biphenyls (PCBs) are classified as persistent organic pollutants (POPs) due to their potential threat to both ecosystems and human health. The Tibetan Plateau (TP), characterized by its low temperatures, pristine ecological conditions, and remoteness from anthropogenic influences, serves as the investigation region. This study analyzed water samples from the temperature glacial watershed and employed the risk assessment method established by the United States Environmental Protection Agency (US EPA) to assess both carcinogenic and non-carcinogenic risks of PCBs in five age groups. The total concentrations of PCBs (& sum;3PCBs) varied from 738 to 1914 ng/L, with a mean value of 1058 ng/L, which was comparable to or exceeded levels reported in the surface water around the TP. Notably, the riverine sites located near the villages and towns exhibited the highest pollution levels. Our analyses indicated that glacier melting, long-range atmospheric transport (LRAT), reductive dechlorination processes, and various anthropogenic activities might be potential sources of PCB emission in the Meili Snow Mountains. According to the established national and international water quality standards, as well as toxic equivalency concentrations (TEQs) for dioxin-like PCBs (DL PCBs), the PCB concentrations detected in this study could result in serious biological damage and adverse ecological toxicological effects. However, the PCBs in all samples posed a negligible cancer risk to five age groups, and a non-carcinogenic risk to adults. These findings contribute valuable insights into the risks and sources of PCBs and may serve as a foundational reference for subsequent study of these compounds in the Meili Snow Mountains area of the southeastern TP.