Soil freeze-thaw state influences multiple terrestrial ecosystem processes, such as soil hydrology and carbon cycling. However, knowledge of historical long-term changes in the timing, duration, and temperature of freeze-thaw processes remains insufficient, and studies exploring the combined or individual contributions of climatic factors-such as air temperature, precipitation, snow depth, and wind speed-are rare, particularly in current thermokarst landscapes induced by abrupt permafrost thawing. Based on ERA5-Land reanalysis, MODIS observations, and integrated thermokarst landform maps, we found that: 1) Hourly soil temperature from the reanalysis effectively captured the temporal variations of in-situ observations, with Pearson' r of 0.66-0.91. 2) Despite an insignificant decrease in daily freeze-thaw cycles in 1981-2022, other indicators in the Qinghai-Tibet Plateau (QTP) changed significantly, including delayed freezing onset (0.113 d yr- 1), advanced thawing onset (-0.22 d yr- 1), reduced frozen days (-0.365 d yr- 1), increased frozen temperature (0.014 degrees C yr- 1), and decreased daily freeze-thaw temperature range (-0.015 degrees C yr- 1). 3) Total contributions indicated air temperature was the dominant climatic driver of these changes, while indicators characterizing daily freeze-thaw cycles were influenced mainly by the combined effects of increased precipitation and air temperature, with remarkable spatial heterogeneity. 4) When regionally averaged, completely thawed days increased faster in the thermokarstaffected areas than in their primarily distributed grasslands-alpine steppe (47.69%) and alpine meadow (22.64%)-likely because of their stronger warming effect of precipitation. Locally, paired comparison within 3 x 3 pixel windows from MODIS data revealed consistent results, which were pronounced when the thermokarst-affected area exceeded about 38% per 1 km2. Conclusively, the warming and wetting climate has significantly altered soil freeze-thaw processes on the QTP, with the frozen soil environment in thermokarstaffected areas, dominated by thermokarst lakes, undergoing more rapid degradation. These insights are crucial for predicting freeze-thaw dynamics and assessing their ecological impacts on alpine grasslands.

Climate change impacts water supply dynamics in the Upper Rio Grande (URG) watersheds of the US Southwest, where declining snowpack and altered snowmelt patterns have been observed. While temperature and precipitation effects on streamflow often receive the primary focus, other hydroclimate variables may provide more specific insight into runoff processes, especially at regional scales and in mountainous terrain where snowpack is a dominant water storage. The study addresses the gap by examining the mechanisms of generating streamflow through multi-modal inferences, coupling the Bayesian Information Criterion (BIC) and Bayesian Model Averaging (BMA) techniques. We identified significant streamflow predictors, exploring their relative influences over time and space across the URG watersheds. Additionally, the study compared the BIC-BMA-based regression model with Random Forest Regression (RFR), an ensemble Machine Learning (RFML) model, and validated them against unseen data. The study analyzed seasonal and long-term changes in streamflow generation mechanisms and identified emergent variables that influence streamflow. Moreover, monthly time series simulations assessed the overall prediction accuracy of the models. We evaluated the significance of the predictor variables in the proposed model and used the Gini feature importance within RFML to understand better the factors driving the influences. Results revealed that the hydroclimate drivers of streamflow exhibited temporal and spatial variability with significant lag effects. The findings also highlighted the diminishing influence of snow parameters (i. e., snow cover, snow depth, snow albedo) on streamflow while increasing soil moisture influence, particularly in downstream areas moving towards upstream or elevated watersheds. The evolving dynamics of snowmelt-runoff hydrology in this mountainous environment suggest a potential shift in streamflow generation pathways. The study contributes to the broader effort to elucidate the complex interplay between hydroclimate variables and streamflow dynamics, aiding in informed water resource management decisions.

Snow cover variation significantly impacts alpine vegetation dynamics on the Tibetan Plateau (TP), yet this effect under climate change remains underexplored. This study uses a survival analysis model to assess the influence of snow on vegetation green-up dynamics, while controlling for key temperature and water availability factors. This analysis integrates multi-source data, including satellite-derived vegetation green-up dates (GUDs), snow depth, accumulated growing degree days (AGDD), downward shortwave radiation (SRAD), precipitation, and soil moisture. Our survival analysis model effectively simulated GUD on the TP, achieving an R of 0.62 (p < 0.01), a root mean square error (RMSE) of 11.20 days, and a bias of -1.41 days for 2020 GUD predictions. It outperformed both the model excluding snow depth and a linear regression model. By isolating snow's impact, we found it exerts a stronger influence on vegetation GUD than precipitation in snow-covered areas of the TP. Furthermore, snow depth effects varied seasonally: a 1-cm increase in preseason snow depth reduced green-up rates by 8.48% before 156(th) day but increased them by 4.74% afterward. This indicates that deeper preseason snow cover delays GUD before June, but advances it from June onward, rather than having a uniform effect. These findings highlight the critical role of snow and underscore the need to incorporate its distinct effects into vegetation phenology models in alpine regions.

The global climate is becoming warmer and wetter, and the physical properties of saline soil are easily affected by the external climate changes, which can lead to complex water-heat-salt-mechanics (WHSM) coupling effect within the soil. However, in the context of climate change, the current research on the surface energy balance process and laws of water and salt migration in saline soil are not well understood. Moreover, testing systems for studying the impact of external meteorological factors on the properties of saline soil are lacking. Therefore, this study developed a testing system that can simulate the environmental coupling effect of the WHSM in saline soil against a background of climate change. Based on meteorological data from the Hexi District in the seasonal permafrost region of China, the testing system was used to clarify the characteristics of surface energy and WHSM coupling changes in sulfate saline soil in Hexi District during the transition of the four seasons throughout the year. In addition, the reliability of the testing system was also verified using testing data. The results showed that the surface albedo of sulfate saline soil in the Hexi region was the highest in winter, with the highest exceeding 0.4. Owing to changes in the external environment, the heat flux in the sulfate saline soil in spring, summer, and early autumn was positive, while the heat flux in late autumn and winter was mainly negative. During the transition of the four seasons throughout the year in the Hexi region, the trends of soil temperature, volumetric water content, and conductivity were similar, first increasing and then decreasing. As the soil depth increased, the influence of external environmental factors on soil temperature, volumetric water content, and conductivity gradually weakened, and the hysteresis effect became more pronounced. Moreover, owing to the influence of external environmental temperature, salt expansion in the positive temperature stage accounts for approximately five times the salt-frost heave deformation in the negative temperature stage, indicating that the deformation of sulfate saline soil in the Hexi region is mainly caused by salt expansion. Therefore, to reduce the impact of external climate change on engineering buildings and agriculture in salted seasonal permafrost regions, appropriate measures and management methods should be adopted to minimize salt expansion and soil salinization.

Precipitation comes in various phases, including rainfall, snowfall, sleet, and hail. Shifts of precipitation phases, as well as changes in precipitation amount, intensity, and frequency, have significant impacts on regional climate, hydrology, ecology, and the energy balance of the land-atmosphere system. Over the past century, certain progress has been achieved in aspects such as the observation, discrimination, transformation, and impact of precipitation phases. Mainly including: since the 1980s, studies on the observation, formation mechanism, and prediction of precipitation phases have gradually received greater attention and reached a certain scale. The estimation of different precipitation phases using new detection theories and methods has become a research focus. A variety of discrimination methods or schemes, such as the potential thickness threshold method of the air layer, the temperature threshold method of the characteristic layer, and the near-surface air temperature threshold method, have emerged one after another. Meanwhile, comparative studies on the discrimination accuracy and applicability assessment of multiple methods or schemes have also been carried out simultaneously. In recent years, the shift of precipitation from solid to liquid (SPSL) in the mid-to-high latitudes of the Northern Hemisphere has become more pronounced due to global warming and human activities. It leads to an increase in rain-on-snow (ROS) events and avalanche disasters, affecting the speed, intensity, and duration of spring snow-melting, accelerating sea ice and glacier melting, releasing carbon from permafrost, altering soil moisture, productivity, and phenological characteristics of ecosystems, and thereby affecting their structures, processes, qualities, and service functions. Although some progress has been made in the study of precipitation phases, there remains considerable research potential in terms of completeness of basic data, reliability of discrimination schemes, and the mechanistic understanding of the interaction between SPSL and other elements or systems. The study on shifts of precipitation phases and their impacts will play an increasingly important role in assessing the impacts of global climate change, water cycle processes, water resources management, snow and ice processes, snow and ice-related disasters, carbon emissions from permafrost, and ecosystem safety.

Glaciers provide multiple ecosystem services (ES) to human society. Due to the continued global warming, the valuation of glacier ES is of urgent importance because this knowledge can support the protection of glaciers. However, a systematic valuation of glacier ES is still lacking, particularly from the perspective of ES contributors. In this study, we introduce the concept of emergy to establish a methodological framework for accounting glacier ES values, and take the Tibetan Plateau (TP) as a case study to comprehensively evaluate the spatiotemporal characteristics of glacier ES during the early 21st century. The results show that the total glacier ES values on the TP increased from 2.36E+24 sej/yr in the 2000s to 2.40E+24 sej/yr in the 2010s, with an overall growth rate of 1.6%. The values of the various services in the 2010s are ranked in descending order: climate regulation (1.59E+24 sej/yr, 66.1%), runoff regulation (4.40E+23 sej/yr, 18.4%), hydropower generation (1.88E+23 sej/ yr, 7.8%). Significantly higher glacier ES values were recorded in the marginal TP than in the endorheic area. With the exception of climate regulation and carbon sequestration, all other service values increased during the study period, partially cultural services, which have experienced rapid growth in tandem with social development. The results of this study will help establish the methodological basis for the assessment of regional and global glacier ES, as well as a scientific basis for the regional protection of glacier resources.

Understanding the dynamics of soil respiration (Rs) in response to freeze-thaw cycles is crucial due to permafrost degradation on the Qinghai-Tibet Plateau (QTP). We conducted continuous in situ observations of Rs using an Li-8150 automated soil CO2 flux system, categorizing the freeze-thaw cycle into four stages: completely thawed (CT), autumn freeze-thaw (AFT), completely frozen (CF), and spring freeze-thaw (SFT). Our results revealed distinct differences in Rs magnitudes, diurnal patterns, and controlling factors across these stages, attributed to varying thermal regimes. The mean Rs values were as follows: 2.51 (1.10) mu mol center dot m(-2)center dot s(-1) (CT), 0.37 (0.04) mu mol center dot m(-2)center dot s(-1) (AFT), 0.19 (0.06) mu mol center dot m(-2)center dot s(-1) (CF), and 0.68 (0.19) mu mol center dot m(-2)center dot s(-1) (SFT). Cumulatively, the Rs contributions to annual totals were 89.32% (CT), 0.79% (AFT), 5.01% (CF), and 4.88% (SFT). Notably, the temperature sensitivity (Q10) value during SFT was 2.79 times greater than that in CT (4.63), underscoring the significance of CO2 emissions during spring warming. Soil temperature was the primary driver of Rs in the CT stage, while soil moisture at 5 cm depth and solar radiation significantly influenced Rs during SFT. Our findings suggest that global warming will alter seasonal Rs patterns as freeze-thaw phases evolve, emphasizing the need to monitor CO2 emissions from alpine meadow ecosystems during spring.

Hydrologically-induced landslides are ubiquitous natural hazards in the Himalayas, posing severe threat to human life and infrastructure. Yet, landslide assessment in the Himalayas is extremely challenging partly due to complex and drastically changing climate conditions. Here we establish a mechanistic hydromechanical landslide modeling framework that incorporates the impacts of key water fluxes and stocks on landslide triggering and risk evolution in mountain systems, accounting for potential climate change conditions for the period 1991-2100. In the drainage basin of the largest river in the northern Himalayas- the Yarlung Zangbo River Basin (YZRB), we estimate that rainfall, glacier/snow melt and permafrost thaw contribute similar to 38.4%, 28.8%, and 32.8% to landslides, respectively, for the period 1991-2019. Future climate change will likely exacerbate landslide triggering primarily due to increasing rainfall, whereas the contribution of glacier/snow melt decreases owing to deglaciation and snow cover loss. The total Gross Domestic Productivity risk is projected to increase continuously throughout the 21st century, while the risk to population shows a general declining trend. The results yield novel insights into the climatic controls on landslide evolution and provide useful guidance for disaster risk management and resilience building under future climate change in the Himalayas.

We present an innovative approach to understanding permafrost degradation processes through the application of new environment-based particle image velocimetry (E-PIV) to time-lapse imagery and correlation with synchronous temperature and rainfall measurements. Our new approach to extracting quantitative vector movement from dynamic environmental conditions that can change both the position and the color balance of each image has optimized the trade-off between noise reduction and preserving the authenticity of movement data. Despite the dynamic polar environments and continuous landscape movements, the E-PIV provides the first quantitative real-time associations between environmental drivers and the responses of permafrost degradation mechanism. We analyze four event-based datasets from an island southwest of Tuktoyaktuk, named locally as Imnaqpaaluk or Peninsula Point near Tuktoyaktuk, NWT, Canada, spanning a 5-year period from 2017 to 2022. The 2017 dataset focuses on the interaction during a hot dry summer between slope movement and temperature changes, laying the foundation for subsequent analyses. In 2018, two datasets significantly expand our understanding of typical failure mechanisms in permafrost slopes: one investigates the relationship between slope movement and rainfall, while the other captures an overhang collapse, providing a rare quantitative observation of an acute landscape change event. The 2022 dataset revisits the combination of potential rain and air temperature-related forcing to explore the environment-slope response relationship around an ice wedge, a common feature of ice-rich permafrost coasts. These analyses reveal both a direct but muted association with air temperatures and a detectable delayed slope response to the occurrence of rainfall, potentially reflective of the time taken for the warm rainwater to infiltrate through the active layer and affect the frozen ground. Whilst these findings also indicate that other factors are likely to influence permafrost degradation processes, the associations have significant implications given the projections for a warmer, wetter Arctic. The ability to directly measure permafrost slope responses offers exciting new potential to quantitatively assess the sensitivity of different processes of degradation for the first time, improving the vulnerability components of hazard risk assessments, guiding mitigation efforts, and better constraining future projections of erosion rates and the mobilization of carbon-rich material.

This study investigates black carbon (BC) concentrations in the seasonal snowpack on the Godwin-Austen Glacier and in surface snow at K2 Camps 1 and 2 (Karakoram Range), assessing their impact on snowmelt during the 2019 ablation season. Potential BC and moisture sources were identified through back-trajectory analysis and atmospheric reanalyses. Variations in water stable isotopes (delta 1(8)O and delta 2H) in the snowpack were analysed to confirm its representativeness as a climatic record for the 2018-19 accumulation season. The average BC concentration in the snow pits (12 ng g-1) generated 66 mm w.e. (or 53 mm w.e. excluding the basal zone) of meltwater. Surface snow at K2 Camp 1 showed BC concentrations of 7 ng g-1, consistent with those on the snowpack surface, suggesting it may reflect local BC levels in late February 2019. In contrast, higher concentrations at K2 Camp 2 (26 ng g-1) were potentially linked to expedition activities.