Permafrost in the Northern Hemisphere has been degrading under climate change, affecting climatic, hydrological, and ecological systems. To reveal the temporal and spatial characteristics of permafrost degradation under climate change, we quantified permafrost thermal states and active layer thicknesses using observational data covering various periods and different areas of the Northern Hemisphere. The soil temperatures at 20 cm depth in the circumpolar Arctic permafrost regions were much lower than in the Qinghai-Tibet Plateau. The thaw period is 114 days in the circumpolar permafrost regions compared to 167 days in the Qinghai-Tibet Plateau. The active layer thickness (ALT) was largest in transitional permafrost regions and sporadic permafrost regions, and lowest in the high latitude permafrost regions and continuous permafrost regions, and the ALT generally exhibited an increasing trend. The average ALT was 1.7 m, and increased by 3.6 cm per year in the Northern Hemisphere. The mean annual ground temperature (MAGT) was largest in the high-altitude permafrost regions and isolated permafrost regions, and lowest in the high latitude permafrost regions and continuous permafrost regions. The warming rate of the MAGT was largest in the high latitude regions and lowest in the high altitude regions, and gradually increased from isolated permafrost regions to continuous permafrost regions, with an average warming rate of 0.3 degrees C per decade for the whole Northern Hemisphere. These findings provide important information for understanding the variability in permafrost degradation processes across different regions under climate change.

The comprehensive understanding of the occurred changes of permafrost, including the changes of mean annual ground temperature (MAGT) and active layer thickness (ALT), on the Qinghai-Tibet Plateau (QTP) is critical to project permafrost changes due to climate change. Here, we use statistical and machine learning (ML) modeling approaches to simulate the present and future changes of MAGT and ALT in the permafrost regions of the QTP. The results show that the combination of statistical and ML method is reliable to simulate the MAGT and ALT, with the root-mean-square error of 0.53 degrees C and 0.69 m for the MAGT and ALT, respectively. The results show that the present (2000-2015) permafrost area on the QTP is 1.04 x 10(6) km(2) (0.80-1.28 x 10(6) km(2)), and the average MAGT and ALT are -1.35 +/- 0.42 degrees C and 2.3 +/- 0.60 m, respectively. According to the classification system of permafrost stability, 37.3% of the QTP permafrost is suffering from the risk of disappearance. In the future (2061-2080), the near-surface permafrost area will shrink significantly under different Representative Concentration Pathway scenarios (RCPs). It is predicted that the permafrost area will be reduced to 42% of the present area under RCP8.5. Overall, the future changes of MAGT and ALT are pronounced and region-specific. As a result, the combined statistical method with ML requires less parameters and input variables for simulation permafrost thermal regimes and could present an efficient way to figure out the response of permafrost to climatic changes on the QTP.

Permafrost in Northeastern China is not only controlled by latitude and elevation, but also locally environmental factors, such as vegetation cover and human activities. During 2009-2022, thinning active layer, increasing annual maximum frost depth in talik zones and lowering ground temperature above the depth of dividing point (DDP) between permafrost cooling and warming have been observed in many places, possibly due to the global warming hiatus (GWH). However, the responses of permafrost below DDP did not show a clear trend to the GWH, despite an evident ground warming. The warming and degradation of permafrost below DDP in the Da Xing'anling Mountains are more strongly influenced by the overall climate warming than by regional GWH. This study improves our understanding of changing permafrost temperature and its drivers. It also helps to provide data support and references for the management of the ecological and hydrological environment of the northern Da Xing'anling Mountains and the Heilongjiang-Amur River Basin.

This research presents a comprehensive environmental assessment of a small mountain permafrost catchment of the Anmangynda River in the Upper Kolyma Highland (Northeastern Asia) over the period of 2021-2023. The study reveals significant diversity in climatic, geocryological, and hydrogeological conditions within this confined area, emphasizing the need for extensive field data collection and monitoring in vast permafrost regions with limited data availability. Key findings include variations in ground temperature, maximum seasonal thaw depth, and depths of zero annual amplitudes of ground temperature at different elevations and landscape types. Groundwater and surface flow dynamics within spring aufeis basins exhibit complex geocryological regimes influenced by icing processes. The presence of aufeis and its impact on local hydrology highlight the ecological significance of this phenomenon. Future research should focus on long-term trends in permafrost dynamics and their relationship with climate change, as well as the ecological effects of aufeis formation on local ecosystems. The study underscores the importance of a multi-faceted approach to environmental assessment, incorporating various environmental parameters and processes, to gain a comprehensive understanding of the intricate interactions within the cryosphere and their responses to changing climate conditions. Such knowledge is essential for addressing broader questions related to climate change, ecosystem resilience, and sustainable resource management in Northeastern Siberia.

Permafrost degradation on the Qinghai-Tibet Plateau (QTP) has significant impacts on climate, hydrology, and engineering and environmental systems. To understand the temporal and spatial characteristics of permafrost on the QTP, we quantified the variation in active layer thickness (ALT), permafrost thermal state, and future permafrost change under different scenarios using observational data, reanalysis data, and the numerical permafrost model. Generally, ALT ranged from 0.5 to 6.0 m with an average of 2.39 m, and mean annual ground temperature (at a depth of zero annual amplitude for ground temperature) mainly ranged between 0 and -3 degrees C with an average of -0.85 degrees C. The soil temperatures in different layers based on the ERA5-Land data revealed even stronger increasing trends, for example, 0.245, 0.245, 0.244, and 0.238 degrees C/decade at depths of 0-7, 7-28, 28-100, and 100-289 cm from 1980 to 2021, compared to those during the period from 1960 to 2021, which were 0.153, 0.156, 0.155, and 0.149 degrees C/decade, respectively. The average warming trends in annual mean soil temperature were 0.153 and 0.243 degrees C/decade from 1960 to 2021 and 1980 to 2021, respectively. The average rate of thickening of the ALT among the 10 active layer observation sites was 2.84 cm/year. There was a significant warming trend in ground temperature above similar to 15 m with warming of 0.063 to 0.120, 0.026 to 0.182, 0.101 to 0.314, and 0.189 to 0.303 degrees C/decade at the QTB01, QTB06, QTB08, and XDTGT sites, respectively, and yearly minimum ground temperatures exhibited stronger warming trends than maximum ground temperatures. In addition, the simulation revealed significant increases in ground temperature at the Xidatan (XDT) and Tanggula (TGL) sites under both historical and future Representative Concentration Pathway (RCP) scenarios, but the increases in ground temperature were significantly greater at TGL than XDT. These findings provide important information for understanding the variability in permafrost degradation processes and improving simulations of permafrost change under climate change on the QTP.

Subsurface processes significantly influence surface dynamics in permafrost regions, necessitating utilizing diverse geophysical methods to reliably constrain permafrost characteristics. This research uses multiple geophysical techniques to explore the spatial variability of permafrost in undisturbed tundra and its degradation in disturbed tundra in Utqia & gdot;vik, Alaska. Here, we integrate multiple quantitative techniques, including multichannel analysis of surface waves (MASW), electrical resistivity tomography (ERT), and ground temperature sensing, to study heterogeneity in permafrost's geophysical characteristics. MASW results reveal active layer shear wave velocities (Vs) between 240 and 370 m/s, and permafrost Vs between 450 and 1,700 m/s, typically showing a low-high-low velocity pattern. Additionally, we find an inverse relationship between in situ Vs and ground temperature measurements. The Vs profiles along with electrical resistivity profiles reveal cryostructures such as cryopeg and ice-rich zones in the permafrost layer. The integrated results of MASW and ERT provide valuable information for characterizing permafrost heterogeneity and cryostructure. Corroboration of these geophysical observations with permafrost core samples' stratigraphies and salinity measurements further validates these findings. This combination of geophysical and temperature sensing methods along with permafrost core sampling confirms a robust approach for assessing permafrost's spatial variability in coastal environments. Our results also indicate that civil infrastructure systems such as gravel roads and pile foundations affect permafrost by thickening the active layer, lowering the Vs, and reducing heterogeneity. We show how the resulting Vs profiles can be used to estimate key parameters for designing buildings in permafrost regions and maintaining existing infrastructure in polar regions.

Permafrost in the Qinghai-Tibet Plateau (QTP) is sensitive to climate warming, but the associated degradation risk still lacks accurate evaluation. To address this issue, machine learning (ML) models are established to simulate the mean annual ground temperature (MAGT) and active layer thickness (ALT), and climate data from shared socioeconomic pathways (SSPs) are prepared for evaluation in the future period. Based on the projections, permafrost is expected to remain relatively stable under the SSP1-2.6 scenario, and large-scale permafrost degradation will occur after the 2050s, resulting in area losses of 30.15% (SSP2-4.5), 58.96% (SSP3-7.0), and 65.97% (SSP5-8.5) in the 2090s relative to the modeling period (2006-2018). The average permafrost MAGT (ALT) is predicted to increase by 0.50 degrees C (59 cm), 0.67 degrees C (89 cm), and 0.79 degrees C (97 cm) in the 2090s with respect to the modeling period under the SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. Permafrost in the Qilian Mountains and Three Rivers Source region are fragile and vulnerable to degradation. In the future period, permafrost on the sunny slopes is more prone to degradation and the sunny-shade slope effect of permafrost distribution will be further enhanced under climate warming. The lower limit of permafrost distribution is expected to rise by about 100 m in the 2050s under the SSP2-4.5 scenario. These findings can provide valuable insights about future permafrost changes in the QTP. In the past decades, the Qinghai-Tibet Plateau (QTP) warmed at more than twice the global average, and permafrost degradation within this process has become widely acknowledged. To project the possible changes, a combination of climate data from global climate model, machine learning model, and permafrost field observation data were used, based on a comprehensive review of previous studies. The findings indicate that permafrost in the QTP is not expected to undergo significant degradation under the SSP1-2.6 scenario. However, noticeable permafrost degradation is projected to occur after the 2050s under the SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, particularly in the Qilian Mountains and Three Rivers Source region. It is predicted that permafrost on sunny slopes is more susceptible to degradation under climate warming, and the permafrost area difference between the sunny and shade slopes will be further expanded. The mean annual air temperature of the QTP will rise by about 1.5 degrees C in the 2050s under the SSP2-4.5 scenario relative to the average between 2006 and 2018, which may lead to a 100 m rise on the low limit of permafrost distribution. Permafrost area of the Qinghai-Tibet Plateau (QTP) is expected to lose by 30.15% (SSP2-4.5) to 65.97% (SSP5-8.5) in the 2090sPermafrost in the Qilian Mountains and Three Rivers Source region are fragile and vulnerable to degradationThe lower limit of permafrost distribution in the QTP is forecasted to rise by about 100 m in the 2050s under the SSP2-4.5 scenario

Ground temperature measurements are crucial for a better understanding of changes in the natural environment, especially in the Arctic. Previous measurement systems provided accurate measurements; however, their most significant disadvantage was the relatively low spatial resolution, including in the vertical profile. The aim of this work was to develop and initially validate a new, original temperature measurement system based on the photonic sensing technique of optical frequency-domain reflectometry (OFDR). The system consists of a fibre-optic sensor, an interrogator, and an automatic data acquisition system. Such fibre-optic sensors allow a significant increase in spatial resolution. Data on precise temperature distribution in the ground profile will allow for a detailed determination of the changes in the thickness of the permafrost active layer (PAL) and, as a consequence, a better description of the current state of the permafrost and the layers above it in relation to their progressive degradation. In the longer term, it will make a better prediction of the pace of possible changes in the polar environment and will open up previously unavailable opportunities in the field of climate change monitoring and forecasting.

Downward solar radiation (DSR) and air temperature (Ta) have significant influences on the thermal state of frozen ground. These parameters are also important forcing terms for physically based land surface models (LSMs). However, the quantitative influences of inaccuracies in DSR and Ta products on simulated frozen ground temperatures remain unclear. In this study, three DSR products (CMFD-SR, Tang-SR, and GLDAS-SR) and two Ta products (CMFD-Ta and GLDAS-Ta) were used to force an LSM model in an alpine watershed in Northwest China, to investigate the sensitivity of simulated ground temperatures to different DSR and Ta products. Compared to a control model (CTRL) forced by in situ observed DSR, ground temperatures simulated by the experimental model forced by GLDAS-SR are obviously decreased because GLDAS-SR is much lower than in situ observations. Instead, simulation results in models forced by CMFD-SR and Tang-SR are much closer to those of CTRL. Ta products led to significant errors in simulated ground temperatures. In conclusion, both CMFD-SR and Tang-SR could be used as good alternatives to in situ observed DSR for forcing a model, with acceptable errors in simulation results. However, more care need to be paid for models forced by Ta products instead of Ta observations, and conclusions should be carefully drawn.

This paper presents the results of 30 years of permafrost thermal monitoring in the Tiksi area in the eastern Russian Arctic. At a stone ridge site, the mean annual temperatures in the upper 30 m of the ground have increased by 1-2.4 degrees C compared to the first years of observations, with trends of degrees C/yr. At the same time, its change was uneven. In the last 20 years, the rate of increase has increased compared with the first decade of observations. At wet tundra sites in the foothill plain, the mean annual temperatures at the top of permafrost have increased by 2.4-2.6 degrees C between 2005 and 2022 at rates of 0.11-0.15 degrees C/yr, and the active layer thicknesses have increased at rates of 0.05-0.41 cm/yr.