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.

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.

The distribution and variation of active layer thickness (ALT) are crucial indicators for assessing the stability and environmental conditions of permafrost regions, which significantly impact regional hydrology, ecology, climate change, engineering construction, and disaster risk assessment. Based on the measured ALT data and Stefan equation, this study investigated the spatial distribution characteristics of ALT in the Tuotuo River region and explored the factors influencing its variability. The results showed that the ALT in the Tuotuo River area ranged from 0.15 to 5.18 m, with an average value of 2.65 m. The spatial distribution showed that the ALT was thinner in the southern region, which exhibited strong spatial heterogeneity, while the northeastern region generally had thicker ALT. Additionally, mountain areas tended to have thinner ALT, whereas plains showed thicker ALT. There was a good linear correlation between the simulated and measured ALT values, and the R 2 was up to 80%. The ALT in the Tuotuo River area was mainly controlled by air temperature and surface water thermal conditions. Among all factors, soil water content was identified as the key determinant. Topographic factors influenced ALT distribution and variation mainly through their impact on soil water content.

Understanding the evolution of permafrost extent and active layer thickness (ALT) surrounding Antarctica is critical to global climate change and ecosystem transformations in the polar regions. However, due to the remoteness and harsh environment of Antarctica, most studies lack long-term and a regional perspective on the variations of ALT in Antarctica, resulting in hindering accurate assessment of ALT dynamics. In this study, based on MODIS land surface temperature (LST) and soil climate station data, we used the Stefan model to reconstruct ALT in the ice-free area of the McMurdo Dry Valleys (MDV) in East Antarctica from 2003 to 2022. The modeled ALT was verified against ground observations showing a good correlation (R) of 0.72 (p < 0.001), with an RMSE of 12.66 cm. The results indicate that the ALT exhibits a decreasing trend from coastal to inland, ranging from a maximum of 60 cm near the coastal area to zero in the polar plateau. Furthermore, within the inland valleys, deeper ALT values are mainly distributed in the lower elevation areas, reaching up to 60 cm at the lowest altitudes. During the period from 2003 to 2022, the interannual variability in ALT was notable, especially in coastal areas, with a maximum amplitude close to 30 cm in the years 2012 and 2016. Our study proved that the Stefan model with parameters estimated by MODIS LST and soil climate station data has good potential to reconstruct large-scale ALT in the ice-free area of Antarctica.

Permafrost is one of the crucial components of the cryosphere, covering about 25% of the global continental area. The active layer thickness (ALT), as the main site for heat and water exchange between permafrost and the external atmosphere, its changes significantly impact the carbon cycle, hydrological processes, ecosystems, and the safety of engineering structures in cold regions. This study constructs a Stefan CatBoost-ET (SCE) model through machine learning and Blending integration, leveraging multi-source remote sensing data, the Stefan equation, and measured ALT data to focus on the ALT in the Qinghai-Tibet Plateau (QTP). Additionally, the SCE model was verified via ten-fold cross-validation (MAE: 20.713 cm, RMSE: 32.680 cm, R2: 0.873, and MAPE: 0.104), and its inversion of QTP's ALT data from 1958 to 2022 revealed 1998 as a key turning point with a slow growth rate of 0.25 cm/a before 1998 and a significantly increased rate of 1.26 cm/a afterward. Finally, based on multiple model input factor analysis methods (SHAP, Pearson correlation, and Random Forest Importance), the study analyzed the ranking of key factors influencing ALT changes. Meanwhile, the importance of Stefan equation results in SCE model is verified. The research results of this paper have positive implications for eco-hydrology in the QTP region, and also provide valuable references for simulating the ALT of permafrost.

The extent of wildfires in tundra ecosystems has dramatically increased since the turn of the 21st century due to climate change and the resulting amplified Arctic warming. We simultaneously studied the recovery of vegetation, subsurface soil moisture, and active layer thickness (ALT) post-fire in the permafrost-underlain uplands of the Yukon-Kuskokwim Delta in southwestern Alaska to understand the interaction between these factors and their potential implications. We used a space-for-time substitution methodology with 2017 Landsat 8 imagery and synthetic aperture radar products, along with 2016 field data, to analyze tundra recovery trajectories in areas burned from 1953 to 2017. We found that spectral indices describing vegetation greenness and surface albedo in burned areas approached the unburned baseline within a decade post-fire, but ecological succession takes decades. ALT was higher in burned areas compared to unburned areas initially after the fire but negatively correlated with soil moisture. Soil moisture was significantly higher in burned areas than in unburned areas. Water table depth (WTD) was 10 cm shallower in burned areas, consistent with 10 cm of the surface organic layer burned off during fire. Soil moisture and WTD did not recover in the 46 years covered by this study and appear linked to the long recovery time of the organic layer.

Whilst permafrost change is widely concerned in the context of global warming, lack of observations becomes one of major limitations for conducting large-scale and long-term permafrost change research. Reanalysis/assimilation data in theory can make up for the lack of observations, but how they characterize permafrost extent and active layer thickness remains unclear. Here, we investigate the near-surface permafrost extent and active layer thickness characterized by seven reanalysis/assimilation datasets (CFSR, MERRA-2, ERA5, ERA5-Land, GLDAS-CLSMv20, GLDAS-CLSMv21, and GLDAS-Noah). Results indicate that most of reanalysis/assimilation data have limited abilities in characterizing near-surface permafrost extent and active layer thickness. GLDAS-CLSMv20 is overall optimal in terms of comprehensive performance in characterizing both present-day near-surface permafrost extent and active layer thickness change. The GLDAS-CLSMv20 indicates that near-surface permafrost extent decreases by -0.69 x 106 km2 decade-1 and active layer deepens by 0.06 m decade-1 from 1979 to 2014. Change in active layer is significantly correlated to air temperature, precipitation, and downward longwave radiation in summer, but the correlations show regional differences. Our study implies an imperative to advance reanalysis/assimilation data's abilities to reproduce permafrost, especially for reanalysis data.