Rapid climate change in the Northern Hemisphere cryosphere threatens ancient permafrost carbon. Once thawed, permafrost carbon may migrate to surface waters. However, the magnitude of permafrost carbon processed by northern freshwater remains uncertain. Here, we compiled '1800 radiocarbon data of aquatic dissolved organic carbon (DOC) and particulate organic carbon (POC) in the Arctic and Qinghai -Tibet Plateau (QTP) to explore the fate of permafrost carbon under climate warming over the past 30 years. We showed that the contribution of aged carbon has significantly increased since 2015. Approximately 70 % of DOC and POC was derived from aged carbon for QTP rivers. In Arctic waters, an average of '67 % of POC was derived from aged carbon, however, '75 % of DOC was derived from modern carbon, mainly due to low temperatures and protection by vegetation limiting the export of aged DOC. For both regions, DOC 14 C age was positively correlated with the active layer thickness, whereas the POC 14 C age was positively correlated with the mean annual ground temperature, suggesting that gradual thaw accelerated the mobilization of aged DOC while abrupt thaw facilitated the export of aged POC. Furthermore, POC 14 C age was positively correlated with the soil organic carbon density, which was attributed to well-developed pore networks facilitated aged carbon output. This study suggests that permafrost carbon release is affected by both permafrost thermal properties and soil organic carbon density, which should be considered in evaluation of permafrost carbon -climate feedback.

Accurate soil thermal conductivity (STC) data and their spatiotemporal variability are critical for the accurate simulation of future changes in Arctic permafrost. However, in-situ measured STC data remain scarce in the Arctic permafrost region, and the STC parameterization schemes commonly used in current land surface process models (LSMs) fail to meet the actual needs of accurate simulation of hydrothermal processes in permafrost, leading to considerable errors in the simulation results of Arctic permafrost. This study used the XGBoost method to simulate the spatial-temporal variability of the STC in the upper 5 cm active layer of Arctic permafrost during thawing and freezing periods from 1980 to 2020. The findings indicated STC variations between the thawing and freezing periods across different years, with values ranging from-0.4 to 0.28 W & sdot;m-1 & sdot;K-1. The mean STC during the freezing period was higher than that during the thawing period. Tundra, forest, and barren land exhibited the greatest sensitivity of STC to freeze-thaw transitions. This is the first study to explore the long-term spatiotemporal variations of STC in Arctic permafrost, and these findings and datasets can provide useful support for future research on Arctic permafrost evolution simulations.

Global warming is accelerating the glacier and snow shrinkage in the Tien Shan. This study assesses the impacts of meltwater changes on soil moisture and hydrological processes using VIC-CAS, a glacier-expanded Variable Infiltration Capacity model, refined by improving the glacier-melt algorithm and incorporating a snowmelt pathway-tracking scheme. Projections were conducted across six glacierized basins in the Northern Tien Shan, with model calibration and validation using remote-sensing snow/glacier data and observed streamflow. By the late century (2080-2100), snowmelt runoff will decrease by one-third to two-thirds owing to decreasing snowfall. In the Bayingou River Basin (BRB), comprising large glaciers, glacier retreat is slow, and glacier runoff will increase until the 2060s. In contrast, glacier runoff in the other five basins, having surpassed the glacier runoff tipping points, will decline substantially. Glacier runoff remains the primary driver of annual streamflow variability with the BRB showing little change, while the other basins experience a one-fourth decrease in annual streamflow by the late 21st century. Reduced summer meltwater will exacerbate water scarcity, with summer streamflow declining by over one-third in basins with declining glacier runoff, and by nearly 10 % in the BRB. In mountainous areas above 2000 m, increased evapotranspiration is projected to reduce annual mean soil moisture by 10.5-16.3 % by the late century, with a more substantial decrease of 12.4-20 % during July-September due to reduced snowmelt. Continued glacier and snow shrinkage will intensify hydrological and ecological droughts, posing major challenges for water resource management and ecological protection.

The thermal coupling between the atmosphere and the subsurface on the Qinghai-Tibetan Plateau (QTP) governs permafrost stability, surface energy balance, and ecosystem processes, yet its spatiotemporal dynamics under accelerated warming are poorly understood. This study quantifies soil-atmosphere thermal coupling ((3) at the critical 0.1 m root-zone depth using in-situ data from 99 sites (1980-2020) and a machine learning framework. Results show significantly weaker coupling in permafrost (PF) zones (mean (3 = 0.42) than in seasonal frost (SF) zones (mean (3 = 0.50), confirming the powerful thermal buffering of permafrost. Critically, we find a widespread trend of weakening coupling (decreasing (3) at 66.7 % of sites, a phenomenon most pronounced in SF zones. Our driver analysis reveals that the spatial patterns of (3 are primarily controlled by surface insulation from summer rainfall and soil moisture. The temporal trends, however, are driven by a complex and counter-intuitive interplay. Paradoxically, rapid atmospheric warming is the strongest driver of a strengthening of coupling, likely due to the loss of insulative snow cover, while trends toward wetter conditions drive a weakening of coupling by enhancing surface insulation. Spatially explicit maps derived from our models pinpoint hotspots of accelerated decoupling in the eastern and southern QTP, while also identifying high-elevation PF regions where coupling is strengthening, signaling a loss of protective insulation and increased vulnerability to degradation. These findings highlight a dynamic and non-uniform response of land-atmosphere interactions to climate change, with profound implications for the QTP's cryosphere, hydrology, and ecosystems.

This study presents the first high-resolution Regional Climate Model 5 (RegCM5) analysis of the unprecedented May-June 2024 heatwave in India, evaluating the role of absorbing aerosols-black carbon (BC) and dust-in amplifying extreme heat. Heatwaves have a severe impact on health, mortality, and agriculture, with absorbing aerosols exacerbating warming. MERRA-2 Aerosol Optical Depth (AOD) anomalies show that BC peaked at +0.027 in May, weakening in June, while dust remained higher (up to +0.36), intensifying over the Indo-Gangetic Plain (IGP) and northwestern India. RegCM5 simulations, validated against India Meteorological Department (IMD) observational data, indicate that these aerosols amplified surface temperature anomalies, with BC-induced warming exceeding +4 degrees C in northern India during May, while dust produced stronger anomalies, surpassing +5 degrees C in the IGP and Rajasthan in June. BC-induced warming was vertically distributed and more pronounced under clear skies, whereas dust-induced warming was surface-concentrated and persisted longer in regions with higher dust concentrations. Both aerosols increased net shortwave radiation (SWR; >300 W m(-2) for BC, similar to 270 W m(-2) for dust) and upward longwave radiation (ULR; >130 W m(-2)), inducing surface energy imbalances. This radiative forcing caused lower-tropospheric warming (up to +3 degrees C at 925 hPa for BC and 850 hPa for dust) and humidity deficits (-0.009 kg/kg), which stabilised the atmosphere, suppressed convection, and delayed monsoon onset. These findings highlight aerosol-radiation interactions as critical drivers of heatwave onset and persistence, emphasizing the need for their integration into regional climate models and early warning systems.

Infrastructure in northern regions is increasingly threatened by climate change, mainly due to permafrost thaw. Prediction of permafrost stability is essential for assessing the long-term stability of such infrastructure. A key aspect of geotechnical problems subject to climate change is addressing the surface energy balance (SEB). In this study, we evaluated three methodologies for applying surface boundary conditions in longterm thermal geotechnical analyses, including SEB heat flux, n-factors, and machine learning (ML) models by using ERA5-Land climate reanalysis data until 2100. We aimed to determine the most effective approach for accurately predicting ground surface temperatures for climate-resilient design of northern infrastructure. The evaluation results indicated that the ML-based approach outperformed both the SEB heat flux and n-factors methods, demonstrating significantly lower prediction errors. The feasibility of long-term thermal analysis of geotechnical problems using ML-predicted ground surface temperatures was then demonstrated through a permafrost case study in the community of Salluit in northern Canada, for which the thickness of the active layer and talik were calculated under moderate and extreme climate scenarios by the end of the 21st century. Finally, we discussed the application and limitations of surface boundary condition methodologies, such as the limited applicability of the n-factors in long-term analysis and the sensitivity of the SEB heat flux to inputs and thermal imbalance. The findings highlight the importance of selecting suitable boundary condition methodologies in enhancing the reliability of thermal geotechnical analyses in cold regions.

Frozen soils, including seasonally frozen ground and permafrost, are rapidly changing under a warming climate, with cascading effects on water, energy, and carbon cycles. We synthesize recent advances in the physics, observation, and modeling of frozen-soil hydrology, emphasizing freeze-thaw dynamics, infiltration regimes and preferential flow, groundwater-permafrost interactions (including talik development and advective heat), and resulting shifts in streamflow seasonality. Progress in in situ sensing, geophysics, and remote sensing now resolves unfrozen water, freezing fronts, and active-layer dynamics across scales, while land-surface and tracer-aided hydrological models increasingly represent phase change, macropore bypass, and vapor transport. Thaw-induced activation of subsurface pathways alters recharge and baseflow, influences vegetation and biogeochemistry, and modulates greenhouse-gas emissions. Key uncertainties persist in scaling micro-scale processes, parameterizing ice-impeded hydraulics, and representing abrupt thaw and wetland dynamics. We outline a tiered modeling framework, priority observations, and integration of vegetation-hydrology-carbon processes to improve projections of cold-region water resources and climate feedbacks.

Widespread dieback of natural Mongolian pine (Pinus sylvestris var. mongolica) forests in Hulunbuir sandy land since 2018 has raised concerns about their sustainability in afforestation programs. We hypothesized that this dieback is driven by two interrelated mechanisms: (1) anthropogenic fire suppression disrupting natural fire regime, and (2) climate change-induced winter warming reducing snow cover duration and depth. To test these, we quantified dieback using Green Normalized Difference Vegetation Index (GNDVI) across stands with varying fire histories via UAV-based multispectral imagery, alongside long-term climatic observations (1960-2024) of temperature, precipitation, and snow dynamics from meteorological stations combined with remote sensing datasets. Results showed that an abrupt change point in 2018 for both annual precipitation and mean temperature was identified, coinciding with dieback. Significant negative linear relationship between GNDVI (forest health) and last fire interval indicated prolonged fire exclusion exacerbating dieback, possibly via pathogen/pest accumulation. Winter temperature rose significantly during 1960-2023, with notable acceleration following abrupt change point in 1987. Concurrently, winters during 2018-2023 exhibited pronounced warming, with snow cover duration reduced by 23 days and snow depth diminished by 7.6 cm. These conditions reduced snowmelt -derived soil moisture (critical water source) recharge in early spring, exacerbating drought stress during critical growth periods and predisposing trees to pest and disease infestations. Our results support both hypotheses, demonstrating that dieback is synergistically driven by fire regime alteration and climate-mediated snowpack reductions. Converting pure pine forests into mixed pine-broadleaf forests via differentiated water sources was proposed to restore ecological resilience in sandy ecosystems.

The Three-Rivers Headwater Region (TRHR) is located on the Tibetan Plateau, within a transitional zone between seasonally frozen ground and continuous permafrost. Over 70 % of the region is predominantly covered by alpine grasslands, a vulnerable ecosystem increasingly threatened by ongoing permafrost degradation. This study utilized satellite data to analyze permafrost degradation by measuring active layer thickness (ALT) and the soil non-frozen period (NFP), and to investigate their impacts on alpine grassland growth. Results showed significant permafrost degradation from 2000 to 2020, with ALT thickening at a rate of 7.79 cm/decade (p < 0.05) and NFP lengthening by 1.1 days/yr (p < 0.05). Simultaneously, grassland vegetation exhibited a significant greening trend (0.0014 yr(-1), p < 0.01). Using the partial least squares (PLS) regression method, the study evaluated the relationships between grassland dynamics and permafrost degradation, while jointly accounting for climate variables (temperature, precipitation, and sunshine duration). ALT thickening was the dominant explanatory variable for grassland growth in 11.09 % of the region, and it was positively correlated in relatively cold western and alpine areas, but negatively correlated in the relatively warm eastern and central regions. NFP extension was the dominant explanatory variable for grassland growth in 10.38 % of the region, although its positive correlation weakened as climate conditions transitioned from relatively cold-dry to relatively warm-wet. Although permafrost degradation was positively correlated with grassland greening in relatively cold regions, the diminishing benefit of NFP extension and the adverse effects of ALT thickening may increasingly undermine grassland stability in relatively warm regions under further climate warming.

The changing Arctic climate is affecting groundwater flow and storage in supra-permafrost aquifers due to groundwater recharge changes and thaw-driven alterations to aquifer properties and connectivity. Changes to shallow subsurface hydrological processes can drive extensive ecological and biogeochemical changes in addition to potential surface hydrologic regime shifts. This study uses a pan-Arctic geospatial approach to classify shallow, unconfined Arctic aquifers (supra-permafrost aquifers) as topography-limited (TL) (characterized by low permeability, wet climate, and/or low slopes) or recharge-limited (high permeability, dry climate and/or steep slopes) based on the water table ratio framework. Under current conditions, the continuous and discontinuous permafrost zones were determined to be predominantly (65%) TL, with an average net decrease of 5.6% by the year 2100 under RCP2.6 and RCP8.5 conditions. This apparent stability masks local-scale heterogeneity, with change in aquifer function projected at dispersed locations throughout the Arctic, and in clustered hot spots in Siberia and the central Canadian Arctic. Coastal zones around the Arctic are more TL (94%) compared to the overall average, leaving them especially vulnerable to ocean-driven impacts on groundwater such as subsurface seawater intrusion or groundwater flooding. Arctic coasts in Siberia and eastern Canada are also particularly susceptible to water table rise due to high relative sea-level rise which may exceed the active layer thickness and result in substantive changes to saturation. Classification results are sensitive to input values, particularly hydraulic conductivity, which remains a source of uncertainty in the analysis. Despite the sparsity of Arctic data, the available open-source datasets provide valuable insight into broad spatiotemporal trends in aquifer function and highlight particularly vulnerable regions and geographic areas where uncertainty should drive additional data collection and study. These results provide new context for conceptualizing changes to shallow Arctic aquifers as the climate evolves in the 21st century.