Permafrost soils contain approximately twice the amount of carbon as the atmosphere and this carbon could be released with Arctic warming, further impacting climate. Mosses are major component of Arctic tundra ecosystems, but the environmental drivers controlling heat penetration though the moss layer and into the soil and permafrost are still debated, especially at fine spatial scales where microtopography impacts both vegetation and soil moisture. This study measured soil temperature profiles (1-15 cm), summer thaw depth, water table depth, soil moisture, and moss thickness at a fine spatial scale (2 m) together with meteorological variables to identify the most important controls on the development of the thaw depth during two Arctic summers. We found a negative relationship between the green moss thickness (up to 3 cm) and the soil temperatures at 15 cm, suggesting that mosses insulated the soil even at high volumetric water contents (>70%) in the top 5 cm. A drier top (2-3 cm) green moss layer better insulated deep (15 cm) soil layers by reducing soil thermal conductivity, even if the moss layers immediately below the top layer were saturated. The thickness of the top green moss layer had the strongest relationships with deeper soil temperatures, suggesting that the top layer had the most relevant role in regulating heat transfer into deeper soils. Further drying of the top green moss layer could better insulate the soil and prevent permafrost thawing, representing a negative feedback on climate warming, but damage or loss of the moss layer due to drought or fire could reduce its insulating effects and release carbon stored in the permafrost, representing a positive feedback to climate warming.

Slope failures resulting from thaw slumps in permafrost regions, have developed widely under the influence of climate change and engineering activities. The shear strength at the interface between the active layer and permafrost (IBALP) at maximum thawing depth is a critical factor to evaluate stability of permafrost slopes. Traditional direct shear, triaxial shear, and large-scale in-situ shear experiments are unsuitable for measuring the shear strength parameter of the IBALP. Based on the characteristics of thaw slumps in permafrost regions, this study proposes a novel test method of self-weight direct shear instrument (SWDSI), and its principle, structure, measurement system and test steps are described in detail. The shear strength of the IBALP under maximum thaw depth conditions is measured using this method. The results show that under the condition that the permafrost layer is thick underground ice and the active layer consists of silty clay with 20% water content, the test results are in good agreement with the results of field large-scale direct shear tests and are in accordance with previous understandings and natural laws. The above analysis indicates that the method of the SWDSI has a reliable theoretical basis and reasonable experimental procedures, and meets the needs of stability assessment of thaw slumps in permafrost regions. The experimental data obtained provide important parameter support for the evaluation of related geological hazards.

Here, we present the result of different models for active layer thickness (ALT) in an area of the Italian Central Alps where a few information about the ALT is present. Looking at a particular warm year (2018), we improved PERMACLIM, a model used to calculate the Ground Surface Temperature (GST) and applied two different versions of Stefan's equation to model the ALT. PERMACLIM was updated refining the temporal basis (daily respect the monthly means) of the air temperature and the snow cover. PERMACLIM was updated also to minimize the bias of the snow cover in summer months using the PlanetScope images. Moreover, the contribution of the solar radiation was added to the air temperature to improve the summer GST. The modelled GST showed a good calibration and, among the two versions of Stefan's equation, the first (ALT1) indicates a maximum active layer thickness of 7.5 m and showed a better accuracy with R2 of 0.93 and RMSE of 0.32 m. The model underlined also the importance of better definition of the thermal conductivity of the ground that can strongly influence the ALT.

Permafrost is undergoing widespread degradation affected by climate change and anthropogenic factors, leading to seasonal freezing and thawing exhibiting interannual, and fluctuating differences, thereby impacting the stability of local hydrological processes, ecosystems, and infrastructure. To capture this seasonal deformation, scholars have proposed various InSAR permafrost deformation models. However, due to spatial-temporal filtering smoothing high-frequency deformation and the presence of approximate assumptions in permafrost models, such differences are often difficult to accurately capture. Therefore, this paper applies an InSAR permafrost monitoring method based on moving average models and annual variations to detect freezing and thawing deformation in the Russian Novaya Zemlya region from 2017 to 2021 using Sentinel-1 data. Most of the study area's deformation rates remained between 10 and 10 mm/yr, while in key oil extraction areas, they reached -20 mm/yr. Seasonal deformation amplitudes were relatively stable in urban areas, but reached 90 mm in regions with extensive development of thermokarst lakes, showing a significant increasing trend. To validate the accuracy of the new method in capturing seasonal deformations, we used seasonal deformations obtained from different methods to retrieval the Active Layer Thickness (ALT), and compared them with field ALT measurement data. The results showed that the new method had a smaller RMSE and improved accuracy by 5% and 30% in two different ALT observation areas, respectively, compared to previous methods. Additionally, by combining the spatial characteristics of seasonal deformation amplitudes and ALT, we analyzed the impact of impermeable surfaces, confirming that human-induced surface hardening alters the feedback mechanism of perennial frozen soil to climate.

Thawing-triggered slope failures and landslides are becoming an increasing concern in cold regions due to the ongoing climate change. Predicting and understanding the behaviour of frozen soils under these changing conditions is therefore critical and has led to a growing interest in the research community. To address this challenge, we present the first mesh-free smoothed particle hydrodynamics (SPH) computational framework designed to handle the multi-phase and multi-physic coupled thermo-hydro-mechanical (THM) process in frozen soils, namely the THM-SPH computational framework. The frozen soil is considered a tri-phase mixture (i.e., soil, water and ice), whose governing equations are then established based on u-p-T formulations. A critical-state elasto-plastic Clay and Sand Model for Frozen soils (CASM-F), formulated in terms of solid-phase stress, is then introduced to describe the transition response and large deformation behaviour of frozen soils due to thawing action for the first time. Several numerical verifications and demonstrations highlight the usefulness of this advanced THM-SPH computational framework in addressing challenging problems involving thawing-induced large deformation and failures of slopes. The results indicate that our proposed single-layer, fully coupled THM-SPH model can predict the entire failure process of thawing-induced landslides, from the initiation to post-failure responses, capturing the complex interaction among multiple coupled phases. This represents a significant advancement in the numerical modelling of frozen soils and their thawing-induced failure mechanisms in cold regions.

When developing Arctic territories, studying and forecasting the state of cryogenic landscapes in the context of climate change plays an important role. General conclusions about permafrost degradation do not fully capture changes at regional and local levels, as the direction and pace of landscape transformation depend on many factors, including the specific characteristics of the terrain. Permafrost degradation and changes in the depth of the active layer thickness (ALT) can be accompanied by alterations in ground vegetation cover (GVC) and surface moisture, which can be recorded through remote sensing (RS) data. However, there is a knowledge gap regarding the use of RS data to identify long-term trends in the phytocenotic properties of GVC and soil moisture at different geomorphological levels, as well as to determine the relationship between these trends and changes in ALT. In this study, based on Landsat data from 1985 to 2024, changes in GVC and soil moisture across various geomorphological levels were identified in a local area of the Yamal Peninsula. The analysis used the NDVI vegetation index, the NDWI moisture index, and the WI (Wetness Index) temperature-vegetation index, which reflects the moisture content of GVC and soil. The general trend observed is an increase in the growth rates of these indices as the geomorphological levels rise from the floodplain to Terrace IV. A comparison of these observed trends in the NDVI, NDWI, and WI indices with in situ geocryological observations shows the potential of using these indices as indicators of ALT change.

Highlights What are the main findings? Permafrost in the Muri area responded to human disturbance without significant spatial expansion during 2000-2024. The semi-arid climate, rough terrain, thin root zone and gappy vertical structure underneath were the major factors. What are the implications of the main findings? Annual ALT estimated from 2000 to 2024 filled the data gap of high-resolution ALT in the Muri area. Knowledge was provided for a better understanding of alpine permafrost development.Highlights What are the main findings? Permafrost in the Muri area responded to human disturbance without significant spatial expansion during 2000-2024. The semi-arid climate, rough terrain, thin root zone and gappy vertical structure underneath were the major factors. What are the implications of the main findings? Annual ALT estimated from 2000 to 2024 filled the data gap of high-resolution ALT in the Muri area. Knowledge was provided for a better understanding of alpine permafrost development.Abstract Alpine permafrost plays a vital role in regional hydrology and ecology. Alpine permafrost is highly sensitive to climate change and human disturbance. The Muri area, which is located in the headwaters of the Datong River, northeast of the Tibetan Plateau, has undergone decadal mining, and the permafrost stability there has attracted substantial concerns. In order to decipher how and to what extent the permafrost in the Muri area has responded to the decadal mining in the context of climate change, daily MODIS land surface temperatures (LSTs) acquired during 2000-2024 were downscaled to 30 m x 30 m. The active layer thickness (ALT)-ground thaw index (DDT) coefficient was derived from in situ ALT measurements. An annual ALT of 30 m x 30 m spatial resolution was subsequently estimated from the downscaled LST for the Muri area using the Stefan equation. Validation of the LST and ALT showed that the root of mean squared error (RMSE) and the mean absolute error (MAE) of the downscaled LST were 3.64 degrees C and -0.1 degrees C, respectively. The RMSE and MAE of the ALT estimated in this study were 0.5 m and -0.25 m, respectively. Spatiotemporal analysis of the downscaled LST and ALT found that (1) during 2000-2024, the downscaled LST and estimated ALT delineated the spatial extent and time of human disturbance to permafrost in the Muri area; (2) human disturbance (i.e., mining and replantation) caused ALT increase without significant spatial expansion; and (3) the semi-arid climate, rough terrain, thin root zone and gappy vertical structure beneath were the major controlling factors of ALT variations. ALT, estimated in this study with a high resolution and accuracy, filled the data gaps of this kind for the Muri area. The ALT variations depicted in this study provide references for understanding alpine permafrost evolution in other areas that have been subject to human disturbance and climate change.

The Arctic has been warming much faster than the global average, known as Arctic amplification. The active layer is seasonally frozen in winter and thaws in summer. In the 2017 Arctic Boreal Vulnerability Experiment (ABoVE) airborne campaign, airborne L- and P- band synthetic aperture radar (SAR) was used to acquire a dataset of active layer thickness (ALT) and vertical soil moisture profile, at 30 m resolution for 51 swaths across the ABoVE domain. Using a thawing degree day (TDD) model, ALT=K root TDD, we estimated ALT along the ABoVE swaths employing the 2-m air temperature from ERA5. The coefficient (K) calibrated has an R2=0.9783. We also obtained an excellent fit between ALT and K root(TDD/theta) where theta is the soil moisture from ERA5 (R2=0.9719). Output based on shared-social economic pathway (SSP) climate scenarios SSP 1-2.6, SSP 2-4.5, and SSP 5-8.5 from seven global climate models (GCMs), statistically downscaled to 25-km resolution, was used to project the impacts of climate warming on ALT. Assuming ALT=K root TDD, the projections of UKESM1-0-LL GCM resulted in the largest projected ALT, up to about 0.7 m in 2080s under SSP5-8.5. Given that the mean observed ALT of the study sites is about 0.482 m, this implies that ALT will increase by 0.074 to 0.217 m (15% and 45%) in 2080s. This will have substantial impacts on Arctic infrastructure. The projected settlement Iset (cm) of 1 to 7 cm will also impact the infrastructure, especially by differential settlement due to the high spatial variability of ALT and soil moisture, given at local scale the actual thawing will partly depend on thaw sensitivity of the material and potential thaw strain, which could vary widely from location to location.

Permafrost is both a product of climate change and an indicator of its progression. Rising air temperature has led to permafrost degradation, resulting in the melting of ground ice and the release of carbon to the atmosphere, creating a positive feedback loop. Extreme weather events, particularly extreme rainfall, have been increasing, yet the effects of extreme rainfall on permafrost remain unclear. Here, we use long-term observational data to investigate the effects of extreme rainfall on the hydrothermal properties of the active layer at two sites in China's upper Heihe River Basin, EBoA and PT5. Two methods are applied: hierarchical linear regression and a relative variation ratio. The results for both sites indicate that when rainfall exceeds 10 mm, soil temperatures increase. This suggests warming effects of extreme rainfall on the active layer that maybe attributable to reduced heat loss from decreased actual evapotranspiration, as well as increased thermal conductivity and heat transfer due to elevated soil moisture during extreme rainfall events. Future studies investigating the effects of extreme rainfall via irrigation experiments and physical modeling could benefit our results as a reference for the design of controlled experiments.

Small modular reactors (SMRs) are an alternative for clean energy solutions in Canada's remote northern communities, owing to their safety, flexibility, and reduced capital requirements. Currently, these communities are heavily reliant on fossil fuels, and the transition to cleaner energy sources, such as SMRs, becomes imperative for Canada to achieve its ambitious net-zero emissions target by 2050. However, applying SMR technology in permafrost regions affected by climate change presents unique challenges. The degradation of permafrost can lead to significant deformations and settlements, which can result in increased maintenance expenses and reduced structural resilience of SMR infrastructure. In this paper, we studied the combined effect of climate nonstationarity in terms of ground surface temperature and heat dissipation from SMR reactor cores for the first time in two distinct locations in Canada's North: Salluit in Quebec and Inuvik in the Northwest Territories. It was shown that these combined effects can make significant changes to the ground thermal conditions within a radius of 15-20 m around the reactor core. The change in the ground thermal conditions poses a threat to the integrity of the permafrost table. The implementation of mitigation strategies is imperative to maintain the structural integrity of the nuclear infrastructure in permafrost regions. The thermal modeling presented in this study paves the way for the development of advanced coupled thermo-hydromechanical models to examine the impact of SMRs and climate nonstationarity on permafrost degradation.