The Tibetan Plateau (TP), often referred to as the 'Asian Water Tower', plays a critical role in regulating the hydrological cycle and influencing global climate patterns. Its unique topography and climatic conditions result in pronounced seasonal freeze-thaw (FT) dynamics of the land surface, which are critical for understanding permafrost ecosystem responses to climate change. However, existing studies on FT dynamics over the TP are limited by either short observational periods or deficiency in accuracy, failing to capture the long-term FT processes comprehensively. This study presents a novel satellite-based approach for monitoring the FT dynamics over the TP from 1979 to 2022, utilizing passive microwave observations. We developed a new algorithm that integrates discriminant function algorithm (DFA) with a seasonal threshold algorithm (STA), employing the freeze-thaw index (FTI) as the classification variable to determine optimal FT thresholds. The strong performance of the algorithm was confirmed by in-situ validation, with an overall accuracy of 91.46%, a Kappa coefficient of 0.83, and an F1-score of 0.92, outperforming other remote sensing-derived FT products such as SMAP (OA = 89.44%, Kappa = 0.79, F1 = 0.89). Results reveal significant changes in surface freeze-thaw dynamics over the past four decades. Between 1988-2022, frozen days exhibited a significant decreasing trend of -0.19 daysyear(-)(1), primarily attributed to the delayed freeze onset (0.19 daysyear(-)(1)), while thaw onset showed no significant trend. Spatially, permafrost regions experienced a more pronounced decrease in frozen days and earlier thaw onset compared to seasonally frozen regions. Moreover, marked interannual trend differences in FT processes were observed across elevation gradients, with higher elevations showing more negative trends in frozen days and thaw onset. This study provides a reliable and up-to-date analysis of surface FT process changes over the TP, informed by long-term satellite-based observational perspectives. These analyses revealed marked spatial heterogeneity in surface FT dynamics across the TP region, underscoring the impacts of climate change on the cryosphere and hydrology.

Black carbon (BC), a major light-absorbing aerosol emitted from South Asian biomass burning, can be efficiently transported to the Tibetan Plateau (TP), substantially accelerating snowmelt. However, the relative contributions of different biomass burning sources and their future impacts on TP snowpack remain poorly quantified. Using the Community Integrated Earth System Model (CIESM), this study conducted a suite of sensitivity experiments to systematically quantify the impacts of BC emissions from South Asian biomass burning on snow cover fraction (SCF) and snow depth (SD) over the TP, and assessed the synergistic effects of sulfur dioxide (SOS) through aerosol-radiation interactions. The results show that BC emitted from South Asian biomass burning significantly enhances snowmelt over the TP. The strongest impacts occur in spring, during which SCF and SD are decreased by 9.7% and 4.6 cm, respectively. Source attribution reveals that forest fires dominate TP spring snowmelt, contributing 42.1% and 41.1% to the decreases in SCF and SD, respectively. Agricultural waste burning is the primary contributor in autumn, accounting for 67.7% and 46.0% of the decrease in SCF and SD, respectively. Under the SSP1-2.6 and SSP5-8.5 scenarios, BC emissions from South Asian biomass burning will lead to a 6.9% and 3.5 cm reduction, and an 11.5% and 7.3 cm reduction, respectively, in SCF and SD in spring over the TP in 2060. We show that SOS substantially amplifies BC-induced snowmelt through the aerosol lensing effect, reducing the annual mean SCF and SD from 5.2% to 6.4% and from 2.7 cm to 4.3 cm in 2020, respectively. These findings highlight the critical roles of source-specific emission control and multi-pollutant mitigation strategies in alleviating cryospheric degradation and safeguarding water resources in the Asian Water Tower.

This study presents the first comprehensive year-long analysis of aerosol light-scattering properties and type classification at a continental background site in northwestern Greece, addressing a critical observational gap in the southern Balkans, while identifies the dominant seasonal aerosol regimes and their controlling processes in this climatically transitional region. Continuous measurements of scattering and absorption coefficients were conducted in 2023 at the University of Western Macedonia. The annual mean scattering coefficient at 525 nm (bsca,525) was 32.9 Mm-1, with a summer maximum (41.8 Mm-1) linked to secondary aerosol formation and dust resuspension, and a spring minimum (27.7 Mm-1) coinciding with wet removal. The scattering Angstro & uml;m exponent (SAE450-525) averaged 1.65, peaking in spring-summer and reaching a minimum in autumn, reflecting seasonal shifts in particle size. The mean single scattering albedo (SSA525) was 0.88 +/- 0.06 with weak spectral dependence, consistent with moderately absorbing aerosols; the asymmetry factor peaked in summer (g525: 0.67; annual mean: 0.60). Diurnal cycles revealed midday scattering enhancements likely attributed to new particle formation in summer, and SSA reductions during morning (traffic effect) and evening in winter due to residential wood burning (RWB) emissions. Aerosol-type classification combined SAE, SSA, and the absorption Angstro & uml;m exponent (AAE) to distinguish dominant regimes. BC-dominated aerosols prevailed annually (38%), with winter influenced by BC/BrC mixtures from RWB (68%), summer by BC-dominated types (79%), and autumn by coarse BC-dust mixtures (32%). Atmospheric conditions reflected mostly low-to-moderate aerosol burden, while episodic pollution events in winter indicate fresh RWB emissions. Compared with urban Mediterranean sites, aerosols in Kozani are generally more scattering and less absorbing, presenting similar characteristics with regional/background sites in Europe. These findings provide a reference dataset for southeastern Europe, reduce uncertainties in aerosol radiative forcing, and offer a benchmark for assessing the impacts of biomass burning in a recognized climate-change hotspot.

The Tibetan Plateau (TP), known as the 'Asian Water Tower', poses significant challenges for hydrological modeling due to its complex cryospheric processes and parametric uncertainties. To address these challenges, we developed an integrated evaluation framework that combines spatiotemporal performance metrics with three global sensitivity analysis methods, based on the Variable Infiltration Capacity (VIC) model. Four alpine river basins were used as case studies to assess the impact of 33 parameters on nine hydro-energy variables across daily, seasonal, and spatial scales. Key drivers of spatial heterogeneity in parameter sensitivities were identified. The results indicate that snow albedo, leaf area index, and the soil drainage parameter broadly influence multiple processes. Runoff and baseflow sensitivities vary spatiotemporally. Random Forest-based SHapley Additive Explanations analysis reveals an east-west gradient in parameter sensitivity, driven by temperature, precipitation, and radiation. Two-step parameter optimization improves the average daily simulation efficiency and spatial consistency for land surface temperature and snow cover fraction by 33% and 30%, respectively, without compromising runoff accuracy. Transferring parameter sensitivities to similar basins confirms the framework's robustness and generalizability. This study underscores the importance of non-runoff parameters, enhances simulation performance, and provides insights into seasonal hydrological variability for more robust model applications across the TP.

Arctic landscapes could add 55-230 Pg of carbon (in CO2 equivalent) to the atmosphere, through CO2 and CH(4 )emissions, by the end of this century. These estimates could be quantified more accurately by constraining the contribution of rapid thawing processes such as thermokarst landscapes to permafrost carbon loss, and by investigating the exposed organic carbon (OC) interacting with mineral surfaces or metallic cations, i.e., the nature of these interactions and what controls their relative abundance. Here, we investigate two contrasted types of hillslope thermokarst landscapes: an Active Layer Detachment (ALD) which is a one-time event, and a Retrogressive Thaw Slump (RTS) which repeats annually during summer months in the Cape Bounty Arctic Watershed Observatory (Melville Island, Canada). We analyzed mineralogy, total and soluble element concentrations, total OC and mineral-OC interactions within the headwalls of both disturbances, and within corresponding undisturbed profiles. Our results show that small fragments of biopolymers stabilized by chemical bonds account for 13 +/- 5 % of total OC in the form of organo-metallic complexes and up to 6 +/- 2 % associated with poorly crystalline iron oxides. If we add the mechanisms of physical protection of particulate organic matter in aggregates and larger molecules stabilized by chemical bonds, we reach 64 +/- 10 % of the total OC being stabilized. Importantly, we observe a decrease in the proportion of mineral-bound OC in the deeper layers exposed by the retrogressive thaw slump: the proportion of organo-metallic complexes drops from 18 % in surface samples (2-22 cm) to 1 % in the deepest samples (50-70 cm). These results therefore suggest that the OC exposed by thermokarst disturbances at Cape Bounty is protected by interactions with minerals to a certain extent, but that deep thaw features could expose OC more readily accessible to degradation.

Brown carbon (BrC) significantly influences climate by absorbing solar radiation, but the critical lack of molecular-level evidence from real-world vehicle emissions hinders accurate assessment of its radiative forcing in climate models. In this study, PM2.5 samples were collected in three urban tunnels in Northwest China and analyzed using ultrahigh-resolution mass spectrometry and UV-vis spectroscopy to elucidate the molecular composition, optical properties, and simple forcing efficiency (SFE) of vehicle-emitted water-soluble BrC. The results reveal that nitrogen-containing organics dominated vehicular BrC molecular formulas (33.5-43.9%), with unique molecular fingerprints distinct from other sources. The light absorption coefficient at 365 nm (b(365)) ranged from 3.07 to 5.86 Mm(-1), optical-based classification of the vehicular water-soluble BrC in the weak and moderate absorption category. The estimated SFE (1.17 to 2.37 W/g) indicates a non-negligible warming effect. Diurnal and spatial gradients in molecular unsaturation and optical properties highlighted divergent oxidative atmospheric processing by center dot OH and NO3 center dot radicals. Daytime BrC showed elevated aromaticity and nonmonotonic light absorption evolution, whereas nighttime oxidation drove persistent absorption enhancement. This study delivers field molecular evidence for vehicular water-soluble BrC and its in-tunnel chemical evolution, advancing the constraint of urban aerosol climatic impacts and supporting refined climate mitigation and air quality regulation.

Microplastic and nanoplastic particles (MNPs) are pervasive in the atmosphere, yet their direct radiative forcing (DRF) remains poorly constrained. Using a radiative transfer model combined with experimentally derived optical properties and simulated atmospheric distributions, we show that coloured MNPs exhibit strong light absorption, with a mean refractive index of 1.49-0.22i at 550 nm and absorption coefficients 74.8 times higher than those of pristine particles. Atmospheric ageing produces minimal net optical change, as yellowing-induced absorption in white particles is largely offset by bleaching of red ones. Modelled global surface concentrations reach 4.18 MP m(-3) for microplastics and 3.67 ng m(-3) for nanoplastics. Resulting simulations yield mean DRF of 0.039 +/- 0.019 W m(-2) for MNPs, equivalent to 16.2% of black carbon forcing. Regional DRF peaks over the North Pacific Subtropical Gyre (similar to 1.34 W m(-2)), exceeded located black carbon by 4.7-fold, highlighting MNPs as previously unrecognized climate forcing agents.

Northern peatlands are important sources of methane (CH4) in the atmosphere. However, the magnitude of CH4 emissions and their response to environmental factors are poorly constrained within the Hudson Bay Lowlands (HBL), the largest contiguous peatland complex in North America. This study investigated seasonal (April-November) eddy covariance-derived ecosystem scale CH4 emissions and their predictors from 16 site-years over four different HBL peatlands. Average seasonal emissions were greatest at a permafrost-free treed fen over 7 years (6.0 g CH4 m-2; wettest and warmest peatland) and about 40% lower at a co-located bog over 6 years (3.8 g CH4 m-2). Emissions were least at a permafrost peat plateau 250 km to the north near the Hudson Bay coast over 1 year (2.6 g CH4 m-2; driest and coolest peatland) and about 60% higher at a co-located thawed peatland over 2 years (4.1 g CH4 m-2). The combined temporal and spatial variability was not well explained by average air temperature or water table depth but instead was related to measures of soil temperature, soil moisture, and gross primary productivity, which were also significantly and positively correlated. At the daily scale, hysteresis was observed in the exponential CH4 flux-soil temperature relationship. Water table depth was an important predictor of day-to-day variations in CH4 flux. Results from these paired peatlands suggest that warming will generally increase CH4 emissions in the HBL, which may be moderated by peat drying or exacerbated by peat plateau collapse and wetting in permafrost-affected peatlands.

Climate warming advances the start of the growing season and enhances carbon uptake on the Qinghai-Tibet Plateau, primarily through the direct effects of air temperature and precipitation. However, the role of spring soil moisture dynamics driven by freeze-thaw processes remains underexplored. Here, using multi-source data from 32 Qinghai-Tibet Plateau sites (2003-2024), we develop a framework to decouple and quantify the moisture-limit relief from freeze-thaw-driven soil moisture return (E-SMR) and concurrent precipitation effect (E-prec). Across study sites, soil moisture return contributes 20.7% +/- 2.1% (mean +/- SD) of the start of the growing season advance since 2003, surpassing the precipitation effect and air temperature, underscoring the role of pre-freezing moisture return in advancing start of the growing season in the following spring. At sites with active layer thickness exceeding 2.2 m, the E-SMR exhibits similar to 31% higher sensitivity to surface soil moisture compared to sites with thinner active layer thickness. As active layer thickness deepens, the influence of soil moisture dynamics in the middle and lower active layers, associated with permafrost degradation, may gradually weaken in regulating start of the growing season. Our findings identify freeze-thaw soil moisture dynamics as an important, previously underappreciated control on start of the growing season and spring carbon uptake on the warming Qinghai-Tibet Plateau.

Arctic permafrost is rapidly degrading in response to global warming. Its thermodynamic evolution governs carbon emissions, hydrological shifts, and terrain stability, with critical consequences for both natural systems and built infrastructure. Accurate prediction of the thermodynamic behavior of permafrost remains elusive, hindered by limited observations and underdeveloped methodologies. Here, we introduce a digital twin framework that integrates differentiable modeling (DM) with high spatial resolution distributed temperature sensing (DTS) data to predict and infer key permafrost characteristics-ground temperature, unfrozen water content, thermal conductivity, and heat capacity. By leveraging a neural-network-based parameterization, our framework fuses observational data with physical heat transfer equations, enabling real-time calibration and updating of the spatiotemporally varying soil thermodynamic characteristics. Applied to permafrost beneath a road embankment in Utqia & gdot;vik, Alaska, the digital twin accurately reconstructs the spatiotemporal evolution of soil temperature fields and captures spatial variability in permafrost thermodynamic properties. The prediction results were further validated against shear-wave velocity distributions inferred from distributed acoustic sensing (DAS), temperature data obtained from borehole thermistors, and thermodynamic properties measured by laboratory testing, demonstrating the framework's robustness. This work advances the predictive understanding of permafrost dynamics under climate change and establishes a generalizable pathway for digital twin applications in Arctic science.

Black carbon (BC) aerosols are short-lived climate pollutants with important, but uncertain, climate impacts. In this Review, we synthesize observations of atmospheric BC concentrations, sources, optical properties, lifetimes and climate effects, drawing comparisons with atmospheric model simulations. Isotopic fingerprinting reveals regional differences in BC sources, with biomass burning contributing 93 +/- 3% in sub-Saharan Africa, 56 +/- 7% in South Asia and 28 +/- 5% in East Asia. Atmospheric BC loadings have declined in South America, East Asia, Europe and North America, and stabilized in Africa and South Asia owing to clean air policies and advances in technology and practices. The optical properties of BC influence its climate effects. The global-mean mass absorption coefficient (MAC550) of atmospheric BC is 12.3 +/- 5.8 m2 g-1, being highest in Africa, Europe and South Asia. MAC550 is enhanced near universally by 1.6 +/- 0.4 owing to ageing during long-range transport. In major emission regions, the aerosol absorption optical depth and the direct aerosol radiative forcing ratio between the bottom and the top of the atmosphere are lower in model simulations than in observations by factors of 2 and 1.5, respectively. Relative to long-term observations, model simulations estimate higher BC deposition fluxes but lower concentrations and sunlight absorption. These discrepancies have implications for the accuracy of model representations of humidity, clouds, precipitation and climate forcing. Future research should prioritize comparisons of emission inventory and model estimates with observations to enhance model accuracy and guide mitigation efforts.

Study region The eastern Qilian Mountains, located on the northeastern margin of the Tibetan Plateau, span elevations from similar to 2600 to 5300 m around the Menyuan area. It is characterized by cold, alpine climatic conditions and hosts both permafrost and seasonally frozen ground, which are highly sensitive to climate change and have important hydrological and ecological implications. Study focus This study develops an enhanced multi-temporal InSAR framework to monitor frozen ground dynamics in the eastern Qilian Mountains using Sentinel-1 data from 2014 to 2024, with a particular focus on the permafrost-seasonally frozen ground transition zone around Menyuan. It addresses key challenges in permafrost monitoring by implementing a co-seismic deformation separation model, a Common Scene Stack (CSS)-based atmospheric correction method, and a time-series decomposition model with linearly varying annual amplitude to capture evolving freeze-thaw behavior under climate change. New hydrological insights for the region The results reveal clear hydrological and thermal contrasts between permafrost and seasonally frozen ground. Seasonally frozen ground exhibits higher seasonal deformation amplitudes, more rapid interannual changes, and shorter thermal response lags compared to permafrost, reflecting its more dynamic hydrothermal regime. The estimated freeze-thaw layer thickness ranges from 0 to 5.3 m, with thinning trends in seasonally frozen ground at lower elevations and slight thickening of active layers in high-elevation permafrost. These findings highlight ongoing frozen ground degradation and provide new insights into subsurface water-energy interactions and long-term cryospheric responses to climate warming in alpine environments.