Permafrost Ground Research Articles

Development of heat and mass transfer modulus to Feflow code for calculation of brine loaded to permafrost ground

The article discusses the application of FreezeThaw75 module, developed by one of the authors to calculate heat and mass transfer taking into account water–ice and ice–water–water phase transitions. Numerical simulations are compared with the analytical solution and other software codes. The module was tested at one of the injection sites in Daldino-Alakitskii district of Yakutia. FreezeThaw75 module was developed in relation to Feflow v7.4–7.5 model environment. The module was tested on a model of brine injection into frozen rocks. The model simultaneously takes into account the movement of groundwater flow, heat and mass transfer and phase transitions. A feature of the calculations in the developed model is the consideration of large injected volumes of highly mineralized brines.It influences the degradation of permafrost and takes into account the cryohydrogeological conditions of the site. Brines are injected into permafrost rocks with a high absorption capacity especially in areas confined to zones of tectonic disturbances. The developed module can adjust the predicted potential of the operated injection sites. It can also act as an additional element of control over the injection process and the formation of an artificial aquifer in the permafrost rocks.

No deceleration signs in the permafrost ground subsidence four years after the 2019 fire in Northwest Territories, Canada

Abstract The circum-arctic permafrost environment is often disturbed by wildfires but could also show resilience to these disturbances. However, the increased frequency and extent of wildfires, coupled with unprecedented hot weather, have introduced greater uncertainties in the post-fire permafrost dynamics. We need to address emerging questions, e.g., How will permafrost respond to the joint effect of hot anomalies and wildfires? To what extent will post-wildfire deformation evolve? How will permafrost resilience to wildfires vary? Utilizing Interferometric Synthetic Aperture Radar (InSAR) time series analysis, we investigated the post-wildfire ground deformation around a 2019 fire scar in the lower Mackenzie Valley, Northwest Territories, Canada, where dramatic heat anomalies and severe wildfires have been recorded in recent years. The resilience of permafrost to wildfires appears to be weakened by the continuous and rapid warming after the fire, as evidenced by the year-on-year acceleration in subsidence rates. Such acceleration was never reported by previous findings that typically observed deceleration in subsidence rates four to five years after wildfires. The deformation along the line of sight (LOS) of the satellite demonstrates significant permafrost degradation induced by wildfires and exacerbated by climate warming, and the cumulative subsidence was detected up to 25 cm in the LOS direction in the upland areas and up to 10 cm in the lowland areas four years after the fire. The difference in deformation magnitude could be attributed to local factors, including ground ice, topography, and vegetation. Our study highlights the increasingly severe threat to circum-arctic permafrost due to the combined effects of wildfires and extreme heat anomalies.

Estimation of Permafrost Ground Ice to 10 m Depth on the Qinghai‐Tibet Plateau

ABSTRACTPermafrost ground ice melting could alter hydrological processes in cold regions by releasing water. Currently, there is a lack of gridded data of ground ice from the Qinghai‐Tibet Plateau (QTP). Using 664 borehole sample records, we applied a random forest (RF) method to predict the ground ice content of permafrost between 2 and 10 m depth in three layers (2–3, 3–5, and 5–10 m) at a spatial resolution of 1 km. The RF predictions demonstrated an R2 value exceeding 0.80 for all three layers with a negligible positive overestimation (0.98%–1.85%). The ground ice content of the first layer (2–3 m) can be predicted primarily using climate variables, but the contribution of terrain and soil variables increases as the depth increases. The total water storage of ground ice across the QTP permafrost (2–10 m depth) is approximately 3330.0 km3, with 403.5 km3 in the 2–3 m layer, 857.2 km3 in the 3–5 m layer, and 2069.3 km3 in the 5–10 m layer. This study generated for the first time a gridded dataset of the shallow permafrost ground ice content across the entire QTP which can be used to improve simulations of hydrological processes in the permafrost regions.

A study of thermal modeling parameters and their impact on modelled permafrost responses to climate warming

Climate warming is causing significant changes in the Arctic, leading to increased temperatures and permafrost instability. The active layer has been shown to be affected by climate change, where warmer ground surface temperatures result in progressive permafrost thaw and a deepening active layer. This study assessed the effects of thermal modeling parameters on permafrost ground response to climate warming using the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and TEMP/W software. We analyzed how variations in depth, water content, and soil type affect predictions of future active layer depths and settlement under various climate scenarios using the soil characteristics along Hudson Bay Railway corridor. The results indicate that, for fine-grained soils, the depth of the model is a more significant parameter than for coarse-grained soils. The water content of all soil types is a critical factor in determining the time at which permafrost thaws and the depth at which the active layer is located, as higher water content leads to larger active layer changes and more settlement in most cases. Our findings have important implications for infrastructure and land use management in the Arctic region.

Analysis on the synergistic variation of soil freezing and pile foundation bearing capacity in permafrost regions

The construction of bored piles in permafrost regions disturbs the thermal stability of frozen soil, leading to decreased early bearing capacity of the pile foundation. As the permafrost ground temperature influences the area, the pile-soil gradually undergoes refreezing, resulting in a continuous enhancement of the pile foundation's bearing capacity. To study the synergistic variation law of soil refreezing and bearing capacity of bridge pile foundation in permafrost regions, two test piles with a length of 15 m and a diameter of 1.2 m were poured based on the actual bridge engineering construction project in the permafrost region of Daxing’an mountains, China. The intelligent temperature monitoring system was set up inside and in the area where the test pile was located. Combined with the collected temperature data, the refreezing state of pile-soil was comprehensively judged. The self-balancing method was employed to assess the bearing capacity of pile foundation before and after refreezing, unveiling the variation patterns in friction resistance at different soil layers and pile-end resistance. On this basis, a finite element model was established to analyze the interaction between pile side friction and pile tip resistance at varying depths of frozen soil. The test and analysis results revealed that the permafrost temperature in the pile foundation area was −1.9℃.Following pile-soil refreezing, the ultimate bearing capacity of the pile foundation increased by 2232 kN, and the growth rate was 42.9%. The friction resistance of each soil (rock) layer on the pile side increased, with the growth rate ranging from 15% −75%.

Multisite evaluation of physics-informed deep learning for permafrost prediction in the Qinghai-Tibet Plateau

Prediction of the permafrost ground temperature is challenging due to its complex nonlinear process. Coupling physical models and machine learning has shown great potential in big data analysis, but its performance in permafrost prediction is still unclear. In this study, we proposed a physics-informed deep learning framework (i.e., PI-LSTM) to predict permafrost ground temperature profiles. The framework combines physical information with a long short-term memory (LSTM) network by two-stage training (pretraining and fine-tuning). The output of a Geophysical Institute Permafrost Laboratory 2 (GIPL2) model was used to pretrain the LSTM model. Borehole ground temperature measurements were used to fine-tune the pretrained LSTM model. Validation at multiple sites in various situations in the Qinghai-Tibet Plateau (QTP) shows that the accuracy and efficiency of the PI-LSTM model are dramatically higher than those of the original LSTM or GIPL2 model. Depending on the fine-tuning data sampling frequencies, the performance of the PI-LSTM model improved by an average of 27% (6–56%) and 69% (64–71%) compared to the LSTM and GIPL2 models, respectively. Even when only one year of observations was used to fine-tune the model, the RMSE of the simulated near-surface ground temperature profiles in the next decade did not substantially decline. The incorporation of physical information also contributes to the simulation efficiency. The PI-LSTM model converges faster than the LSTM model, and the training epochs are reduced by 70% (67–73%) during the fine-tuning step. This study demonstrates that integrating physical information into deep learning is promising for improving permafrost predictions.

Measurement of Excess Pore-Water Pressure in Frozen Soil at Subfreezing Temperatures Close to 0°C

Response of pore-water pressure has crucial effect on the engineering geological performance of permafrost ground. However, there is a dearth of literature on the measurement of pore-water pressure in frozen soils due to challenges with regard to technical and operational method. To validate the generation of pore-water pressure and to reveal its variation property in frozen soils at subfreezing temperatures close to 0°C, a miniature pressure transducer was utilized to conduct a number of confined compression tests. Double-wall structure avoided damage to the transducer during frozen soil sampling. The transducer at sample bottom perceived a pressure fluctuation as varying air pressure imposed on sample surface, proving the connectivity among the pores in frozen soils with a hysteretic effect on pressure transmission. Pore-water pressure experienced a progressive increase followed by a slow dissipation under invariable load and temperature conditions when water drainage was permitted, while a monotonic increase in pressure was observed for an undrained sample. With decreasing temperature, a smaller peak and a more dilatory dissipation were displayed. When the sample was exposed to a stepwise warming process, a similar performance for the pressure was obtained with abrupt rise at the turning point of temperature.

Origin of CO2, CH4, and N2O trapped in ice wedges in central Yakutia and their relationship

AbstractPermafrost thawing as a result of global warming is expected to foster the biological remineralization of intact organic carbon and nitrogen and release greenhouse gas (GHG) into the atmosphere, which will have positive feedback for future global warming. However, GHG budgets and their controls in permafrost ground ice are not yet fully understood. This study aims to better understand the control mechanisms of GHG in ground ice by using new gas and chemistry data. In this study, we present new data on carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) mixing ratios in three different ice wedges, Churapcha, Syrdakh, and Cyuie, located in central Yakutia, Siberia. The GHG mixing ratios in the studied ice wedges range from 0.0% to 13.8% CO2, 1.3–91.2 ppm CH4, and 0% and 0–1414 N2O. In particular, all three ice wedges demonstrate that ice‐wedge samples enriched in CH4 were depleted in N2O mixing ratios and vice versa. N2–O2–Ar compositions indicate that the studied ice wedges were most likely formed by dry snow or hoarfrost, not by freezing of snow meltwater, and the O2‐consuming biological metabolism was active. Most of the observed GHG mixing ratios cannot be explained without microbial metabolism. The inhibitory impact of denitrification products of nitrate (including N2O) could be an important control of the ice‐wedge CH4 mixing ratio.

Landscape influence on permafrost ground ice geochemistry in a polar desert environment, Resolute Bay, Nunavut

Arctic permafrost is degrading and is thus releasing nutrients, solutes, sediment and water into soils and freshwater ecosystems. The impacts of this degradation depends on the geochemical characteristics and in large part on the spatial distribution of ground ice and solutes, which is not well-known in the High Arctic polar desert ecosystems. This research links ground ice and solute concentrations, to establish a framework for identifying locations vulnerable to permafrost degradation. It builds on landscape classifications and cryostratigraphic interpretations of permafrost history. Well-vegetated wetland sites with syngenetic permafrost aggradation show a different geochemical signature from polar desert and epigenetic sites. In wetlands, where ground ice contents were high (<97% volume), total dissolved solute concentrations were relatively low (mean 283.0 ± 327.8 ppm), reflecting a carbonate terrestrial/freshwater setting. In drier sites with epigenetic origin, such as polar deserts, ice contents are low (<47% volume), solute concentrations were high (mean 3248.5 ± 1907.0 ppm, max 12055 ppm) and dominated by Na+ and Cl− ions, reflecting a post-glacial marine inundation during permafrost formation. Dissolved organic carbon and total dissolved nitrogen concentrations usually increased at the top of permafrost and could not be as clearly associated with permafrost history. The research shows that the geochemistry of polar desert permafrost is highly dependent on permafrost history, and it can be estimated using hydrogeomorphological terrain classifications. The lower ice content of polar desert sites indicates that these areas are more vulnerable to thaw relative to the ice-rich wetland sites, and the elevated solute concentrations indicate that these areas could mobilise substantial solutes to downstream environments, should they become hydrologically connected with future warming.

Brief communication: Unravelling the composition and microstructure of a permafrost core using X-ray computed tomography

Abstract. The microstructure of permafrost ground contains clues to its formation and hence its preconditioning to future change. We applied X-ray computed microtomography (CT) to obtain high-resolution data (Δx=50 µm) of the composition of a 164 cm long permafrost core drilled in a Yedoma upland in north-eastern Siberia. The CT analysis allowed the microstructures to be directly mapped and volumetric contents of excess ice, gas inclusions, and two distinct sediment types to be quantified. Using laboratory measurements of coarsely resolved core samples, we statistically estimated the composition of the sediment types and used it to indirectly quantify volumetric contents of pore ice, organic matter, and mineral material along the core. We conclude that CT is a promising method for obtaining physical properties of permafrost cores which opens novel research potentials.

A Review of Satellite Synthetic Aperture Radar Interferometry Applications in Permafrost Regions: Current status, challenges, and trends

With climate change and the increment of human activities, global permafrost is undergoing degradation, threatening the stability of engineering and the ecological environment of the permafrost region. With the advantages of all-day, all-weather, wide-coverage, and high-accuracy monitoring, synthetic aperture radar interferometry (InSAR) is becoming a substantial tool for permafrost monitoring, and many studies with InSAR in permafrost regions have been conducted in the recent 20 years. In this article, the basic principles of time–series InSAR are introduced first. Then, the development and applications of InSAR in permafrost, such as the coherence analysis of permafrost ground surface, the deformation of permafrost and infrastructure, and active layer thickness (ALT) retrieval, are given. Next, the existing problems, including temporal decorrelation, atmospheric delay, deformation models, and the effect of soil moisture and phase unwrapping (PU), are discussed.

A large frozen debris avalanche entraining warming permafrost ground—the June 2021 Assapaat landslide, West Greenland

A large landslide (frozen debris avalanche) occurred at Assapaat on the south coast of the Nuussuaq Peninsula in Central West Greenland on June 13, 2021, at 04:04 local time. We present a compilation of available data from field observations, photos, remote sensing, and seismic monitoring to describe the event. Analysis of these data in combination with an analysis of pre- and post-failure digital elevation models results in the first description of this type of landslide. The frozen debris avalanche initiated as a 6.9 * 106 m3 failure of permafrozen talus slope and underlying colluvium and till at 600–880 m elevation. It entrained a large volume of permafrozen colluvium along its 2.4 km path in two subsequent entrainment phases accumulating a total volume between 18.3 * 106 and 25.9 * 106 m3. About 3.9 * 106 m3 is estimated to have entered the Vaigat strait; however, no tsunami was reported, or is evident in the field. This is probably because the second stage of entrainment along with a flattening of slope angle reduced the mobility of the frozen debris avalanche. We hypothesise that the initial talus slope failure is dynamically conditioned by warming of the ice matrix that binds the permafrozen talus slope. When the slope ice temperature rises to a critical level, its shear resistance is reduced, resulting in an unstable talus slope prone to failure. Likewise, we attribute the large-scale entrainment to increasing slope temperature and take the frozen debris avalanche as a strong sign that the permafrost in this region is increasingly at a critical state. Global warming is enhanced in the Arctic and frequent landslide events in the past decade in Western Greenland let us hypothesise that continued warming will lead to an increase in the frequency and magnitude of these types of landslides. Essential data for critical arctic slopes such as precipitation, snowmelt, and ground and surface temperature are still missing to further test this hypothesis. It is thus strongly required that research funds are made available to better predict the change of landslide threat in the Arctic.

Permafrost Ground Ice Melting and Deformation Time Series Revealed by Sentinel-1 InSAR in the Tanggula Mountain Region on the Tibetan Plateau

In this study, we applied small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) to monitor the ground surface deformation from 2017 to 2020 in the permafrost region within an ~400 km × 230 km area covering the northern and southern slopes of Mt. Geladandong, Tanggula Mountains on the Tibetan Plateau. During SBAS-InSAR processing, we inverted the network of interferograms into a deformation time series using a weighted least square estimator without a preset deformation model. The deformation curves of various permafrost states in the Tanggula Mountain region were revealed in detail for the first time. The study region undergoes significant subsidence. Over the subsiding terrain, the average subsidence rate was 9.1 mm/a; 68.1% of its area had a subsidence rate between 5 and 20 mm/a, while just 0.7% of its area had a subsidence rate larger than 30 mm/a. The average peak-to-peak seasonal deformation was 19.7 mm. There is a weak positive relationship (~0.3) between seasonal amplitude (water storage in the active layer) and long-term deformation velocity (ground ice melting). By examining the deformation time series of subsiding terrain with different subsidence levels, we also found that thaw subsidence was not restricted to the summer and autumn thawing times but could last until the following winter, and in this circumstance, the winter uplift was greatly weakened. Two import indices for indicating permafrost deformation properties, i.e., long-term deformation trend and seasonal deformation magnitude, were extracted by direct calculation and model approximations of deformation time series and compared with each other. The comparisons showed that the long-term velocity by different calculations was highly consistent, but the intra-annual deformation magnitudes by the model approximations were larger than those of the intra-annual highest-lowest elevation difference. The findings improve the understanding of deformation properties in the degrading permafrost environment.

Mountain Permafrost Hydrology—A Practical Review Following Studies from the Andes

Climate change is expected to reduce water security in arid mountain regions around the world. Vulnerable water supplies in semi-arid zones, such as the Dry Andes, are projected to be further stressed through changes in air temperature, precipitation patterns, sublimation, and evapotranspiration. Together with glacier recession this will negatively impact water availability. While glacier hydrology has been the focus of scientific research for a long time, relatively little is known about the hydrology of mountain permafrost. In contrast to glaciers, where ice is at the surface and directly affected by atmospheric conditions, the behaviour of permafrost and ground ice is more complex, as other factors, such as variable surficial sediments, vegetation cover, or shallow groundwater flow, influence heat transfer and time scales over which changes occur. The effects of permafrost on water flow paths have been studied in lowland areas, with limited research in the mountains. An understanding of how permafrost degradation and associated melt of ground ice (where present) contribute to streamflow in mountain regions is still lacking. Mountain permafrost, particularly rock glaciers, is often conceptualized as a (frozen) water reservoir; however, rates of permafrost ground ice melt and the contribution to water budgets are rarely considered. Additionally, ground ice and permafrost are not directly visible at the surface; hence, uncertainties related to their three-dimensional extent are orders of magnitude higher than those for glaciers. Ground ice volume within permafrost must always be approximated, further complicating estimations of its response to climate change. This review summarizes current understanding of mountain permafrost hydrology, discusses challenges and limitations, and provides suggestions for areas of future research, using the Dry Andes as a basis.

Magnitudes and patterns of large-scale permafrost ground deformation revealed by Sentinel-1 InSAR on the central Qinghai-Tibet Plateau

Permafrost on the Qinghai-Tibet Plateau (QTP) undergoes significant thawing and degradation, which affects the hydrological processes, ecosystems and infrastructure stability. The ground deformation, a key indicator of permafrost degradation, can be quantified via geodetic observations, especially using multi-temporal InSAR techniques. The previous InSAR studies, however, either rely on data-driven models or Stefan-equation-based models, which are both lacking of consideration of the spatial-temporal variations of freeze-thaw processes. Furthermore, the magnitudes and patterns of the permafrost-related ground deformation over large scales (e.g., 1×105km2 or larger) is still insufficiently quantified or poorly understood. In this study, to account for the spatial heterogeneity of freeze-thaw processes, we develop a permafrost-tailored InSAR approach by incorporating a MODIS-land-surface-temperature-integrated ground deformation model to reconstruct the seasonal and long-term deformation. Utilizing the approach to Sentinel-1 SAR images on the vast regions of about 140,000km2 of the central QTP during 2014–2019, we observe widespread seasonal deformation up to about 80mm with a mean value of about 10mm and linear subsidence up to 20mm/year. We apply the geographical detector to determine the controlling factors on the permafrost-related deformation. We find that the slope angle is the primary controller on the seasonal deformation: strong magnitudes and variations of seasonal deformation are most pronounced in flat or gentle-slope regions. The aspect angle, vegetation and soil bulk density exhibit a certain correlation with seasonal deformation as well. Meanwhile, we find that a linear subsidence is higher in the regions with high ground ice content and warm permafrost. It indicates that warm and ice-rich permafrost regions are more vulnerable to extensive long-term subsidence. We also observe that the cold permafrost regions experience lower linear subsidence even with high ground ice content, which indicate ice loss is limited. Thus, we infer that under continuously warming, the transition from cold permafrost to warm permafrost may lead to more extensive ground ice melting. Moreover, the strong subsidence/uplift signals surrounding some lakes suggesting that the change of local hydrological conditions may induce localized permafrost degradation/aggradation. Our study demonstrates the capability of the permafrost-tailored InSAR approach to quantify the permafrost freeze-thaw dynamics as well as their spatial-temporal patterns over large scales in vast permafrost areas.

Carbon Polygons and Carbon Offsets: Current State, Key Challenges and Pedological Aspects

Russia holds the largest store of carbon in soils, forests and permafrost grounds. Carbon, stored in a stabilized form, plays an important role in the balance of the global biogeochemical cycle and greenhouse gases. Thus, recalcitrance of soil organic matter to mineralization results in a decrease in current emissions of carbon dioxide into the atmosphere. At the same time, stabilization of organic matter in the form of humus due to organo–mineral interactions leads to the sequestration of carbon from the atmosphere into soils and biosediments. Thus, global carbon balance is essentially determined by soil cover state and stability. Currently, Russia is faced with a set of problems regarding carbon offsets and the carbon economy. One of the methods used to evaluate carbon stocks in ecosystems and verify offsets rates is carbon polygons, which are currently being organized, or are under organization, in various regions of Russia. This discussion addresses the current issues surrounding the methods and methodology of carbon polygons and their pedological organization and function.

Consequences of permafrost degradation for Arctic infrastructure – bridging the model gap between regional and engineering scales

Abstract. Infrastructure built on perennially frozen ice-rich ground relies heavily on thermally stable subsurface conditions. Climate-warming-induced deepening of ground thaw puts such infrastructure at risk of failure. For better assessing the risk of large-scale future damage to Arctic infrastructure, improved strategies for model-based approaches are urgently needed. We used the laterally coupled 1D heat conduction model CryoGrid3 to simulate permafrost degradation affected by linear infrastructure. We present a case study of a gravel road built on continuous permafrost (Dalton highway, Alaska) and forced our model under historical and strong future warming conditions (following the RCP8.5 scenario). As expected, the presence of a gravel road in the model leads to higher net heat flux entering the ground compared to a reference run without infrastructure and thus a higher rate of thaw. Further, our results suggest that road failure is likely a consequence of lateral destabilisation due to talik formation in the ground beside the road rather than a direct consequence of a top-down thawing and deepening of the active layer below the road centre. In line with previous studies, we identify enhanced snow accumulation and ponding (both a consequence of infrastructure presence) as key factors for increased soil temperatures and road degradation. Using differing horizontal model resolutions we show that it is possible to capture these key factors and their impact on thawing dynamics with a low number of lateral model units, underlining the potential of our model approach for use in pan-Arctic risk assessments. Our results suggest a general two-phase behaviour of permafrost degradation: an initial phase of slow and gradual thaw, followed by a strong increase in thawing rates after the exceedance of a critical ground warming. The timing of this transition and the magnitude of thaw rate acceleration differ strongly between undisturbed tundra and infrastructure-affected permafrost ground. Our model results suggest that current model-based approaches which do not explicitly take into account infrastructure in their designs are likely to strongly underestimate the timing of future Arctic infrastructure failure. By using a laterally coupled 1D model to simulate linear infrastructure, we infer results in line with outcomes from more complex 2D and 3D models, but our model's computational efficiency allows us to account for long-term climate change impacts on infrastructure from permafrost degradation. Our model simulations underline that it is crucial to consider climate warming when planning and constructing infrastructure on permafrost as a transition from a stable to a highly unstable state can well occur within the service lifetime (about 30 years) of such a construction. Such a transition can even be triggered in the coming decade by climate change for infrastructure built on high northern latitude continuous permafrost that displays cold and relatively stable conditions today.

Modern methods of cooling permafrost ground beds of multi-storey residential buildings

Abstract
 Introduction. The bearing capacity of soil in the frozen state is much higher than its bearing capacity at positive temperatures. Therefore, it makes sense to use frozen soil as the footing of a building in permafrost regions. However, the preservation of soil in the frozen state in a built-up area is a challenging engineering problem despite low average annual air temperatures (below –4 °C).
 Materials and methods. The co-authors employed numerical methods to study the temperature regime of the footing using TEMRA software. This software was developed at MISI – MGSU (State Registration Certificate 2016618937); it solves non-stationary thermophysical problems by the enthalpy method with regard for the phase transitions of the bound moisture in the temperature range.
 Results. Two approaches are used to preserve building footings in the frozen state: natural seasonal surface cooling and deep cooling, on the one hand, and reducing the thermal effect produced by the building on footing soils, on the other hand. In the first case, the surface under the building is cooled with air in the winter season using the cold ventilated space under the building, the so-called “ventilated basement”. Deep cooling is carried out using Seasonal Cooling Devices (SCD) that employs air-soil heat exchange with the help of pipes, filled with the heat transfer agent during the winter period. A change in the average annual air temperature inside the ventilated basement and seasonal insulation of its walls or the ground bed can reduce the thermal effect, produced by the building.
 Conclusions. The most effective way to keep ground beds of multi-storey residential buildings frozen is the thermal insulation of the footing surface in combination with deep liquid cooling devices.

Top-of-permafrost ground ice indicated by remotely sensed late-season subsidence

Abstract. Ground ice is foundational to the integrity of Arctic ecosystems and infrastructure. However, we lack fine-scale ground ice maps across almost the entire Arctic, chiefly because there is no established method for mapping ice-rich permafrost from space. Here, we assess whether remotely sensed late-season subsidence can be used to identify ice-rich permafrost. The idea is that, towards the end of an exceptionally warm summer, the thaw front can penetrate materials that were previously perennially frozen, triggering increased subsidence if they are ice rich. Focusing on northwestern Alaska, we test the idea by comparing the Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) late-season subsidence observations to permafrost cores and an independently derived ground ice classification. We find that the late-season subsidence in an exceptionally warm summer was 4–8 cm (5th–95th percentiles) in the ice-rich areas, while it was low in ice-poor areas (−1 to 2 cm; 5th–95th percentiles). The distributions of the late-season subsidence overlapped by 2 %, demonstrating high sensitivity and specificity for identifying top-of-permafrost excess ground ice. The strengths of late-season subsidence include the ease of automation and its applicability to areas that lack conspicuous manifestations of ground ice, as often occurs on hillslopes. One limitation is that it is not sensitive to excess ground ice below the thaw front and thus the total ice content. Late-season subsidence can enhance the automated mapping of permafrost ground ice, complementing existing (predominantly non-automated) approaches based on largely indirect associations with vegetation and periglacial landforms. Thanks to its suitability for mapping ice-rich permafrost, satellite-observed late-season subsidence can make a vital contribution to anticipating terrain instability in the Arctic and sustainably stewarding its ecosystems.

Permafrost thaw and ground settlement considering long-term climate impact in northern Alaska

Alaska’s North Slope is predicted to experience twice the warming expected globally. When summers are longer and winters are shortened, ground surface conditions in the Arctic are expected to change considerably. This is significant for Arctic Alaska, a region that supports surface infrastructure such as energy extraction and transport assets (pipelines), buildings, roadways, and bridges. Climatic change at the ground surface has been shown to impact soil layers beneath through the harmonic fluctuation of the active layer, and warmer air temperature can result in progressive permafrost thaw, leading to a deeper active layer. This study attempts to assess climate change based on the climate model data from the fifth phase of the Coupled Model Intercomparison Project and its impact on a permafrost environment in Northern Alaska. The predicted air temperature data are analyzed to evaluate how the freezing and thawing indices will change due to climate warming. A thermal model was developed that incorporated a ground surface condition defined by either undisturbed intact tundra or a gravel fill surface and applied climate model predicted air temperatures. Results indicate similar fluctuation in active layer thickness and values that fall within the range of minimum and maximum readings for the last quarter-century. It is found that the active layer thickness increases, with the amount depending on climate model predictions and ground surface conditions. These variations in active layer thickness are then analyzed by considering the near-surface frozen soil ice content. Analysis of results indicates that thaw strain is most significant in the near-surface layers, indicating that settlement would be concurrent with annual thaw penetration. Moreover, ice content is a major factor in the settlement prediction. This assessment methodology, after improvement, and the results can help enhance the resilience of the existing and future new infrastructure in a changing Arctic environment.