Substantial degradation can occur to warm permafrost due to changes in surface conditions resulting from infrastructure development and climate warming. The associated geohazards, including differential settlement, slope instability, and liquefaction of degraded, unconsolidated materials in seismically active warm permafrost regions, pose substantial threats to the built infrastructure. Among them, seismic hazards of degraded permafrost have received little attention. This paper aims to provide a case study of an airport built on warm permafrost about 80 years ago, focusing on climate changes, permafrost degradation, and observed seismic hazards during a strong earthquake. The study site, that is, the Northway Airport, is located in a discontinuous permafrost area in Interior Alaska. Geotechnical data from 1973, 1991, and 2005 were compiled and analyzed to reveal permafrost degradation at various surface conditions, and are compared with the well-known degradation data from a site in Fairbanks. Furthermore, the responses of the airport runway during the 2002 Denali earthquake (Mw = 7.9), including liquefaction and lateral spreading displacements, are described and analyzed. And the seismic hazards of civilian airports built on permafrost across Alaska are surveyed. Distinct trends are revealed in two periods, namely, from 1943 to 1975 and from 1976 to 2021, for air temperature, precipitation, and wind speed. Permafrost tables were observed to drop with time at various rates for different surface conditions. Liquefaction and lateral spreading were observed extensively during the earthquake. The locations of observed liquefaction at the airport are mapped, and the lateral spreading displacements are estimated based on available photos. The standard penetration test data collected during geotechnical investigations are analyzed, and a liquefiable layer is identified at the talik between the active layer and the permafrost table. Moreover, 55% of Alaska's civilian airports are in permafrost areas. Among them, two-thirds fall within seismic zones with a risk level of 3 or above. This study demonstrates the high seismic risks of degraded permafrost and its potential impact on the built infrastructure.

Recent research on the Himalayan cryosphere has increasingly been focused on climate uncertainty and regional variations, considering features such as glacier recession, lake expansion, outburst floods, and regional hazards. The Bhilangana river basin, located in the central Himalayas, is predominantly characterized by increased elevation-dependent warming and declining seasonal precipitation. Our study shows that high-elevation temperature increased from 2000 to 2022 (0.05(degrees)C/year, p = 20 m/sec). Quantification of the regional hazard reveals potentially severe downstream challenges for low-to-medium-scale hydropower stations, local settlements, and road and railway bridges near Devling and Ghuttu villages.

Climate change is causing permafrost in the Qinghai-Tibet Plateau to degrade, triggering thermokarst hazards and impacting the environment. Despite their ecological importance, the distribution and risks of thermokarst lakes are not well understood due to complex influencing factors. In this study, we introduced a new interpretable ensemble learning method designed to improve the global and local interpretation of susceptibility assessments for thermokarst lakes. Our primary aim was to offer scientific support for precisely evaluating areas prone to thermokarst lake formation. In the thermokarst lake susceptibility assessment, we identified ten conditioning factors related to the formation and distribution of thermokarst lakes. In this highly accurate stacking model, the primary learning units were the random forest (RF), extremely randomized trees (EXTs), extreme gradient boosting (XGBoost), and categorical boosting (CatBoost) algorithms. Meanwhile, gradient boosted decision trees (GBDTs) were employed as the secondary learning unit. Based on the stacking model, we assessed thermokarst lake susceptibility and validated accuracy through six evaluation indices. We examined the interpretability of the stacking model using three interpretation methods: accumulated local effects (ALE), local interpretable model-agnostic explanations (LIME), and Shapley additive explanations (SHAP). The results showed that the ensemble learning stacking model demonstrated superior performance and the highest prediction accuracy. Approximately 91.20% of the total thermokarst hazard points fell within the high and very high susceptible areas, encompassing 20.08% of the permafrost expanse in the QTP. The conclusive findings revealed that slope, elevation, the topographic wetness index (TWI), and precipitation were the primary factors influencing the assessment of thermokarst lake susceptibility. This comprehensive analysis extends to the broader impacts of thermokarst hazards, with the identified high and very high susceptibility zones affecting significant stretches of railway and highway infrastructure, substantial soil organic carbon reserves, and vast alpine grasslands. This interpretable ensemble learning model, which exhibits high accuracy, offers substantial practical significance for project route selection, construction, and operation in the QTP.

High Mountain Asia (HMA) shows a remarkable warming tendency and divergent trend of regional precipitation with enhanced meteorological extremes. The rapid thawing of the HMA cryosphere may alter the magnitude and frequency of nature hazards. We reviewed the influence of climate change on various types of nature hazards in HMA region, including their phenomena, mechanisms and impacts. It reveals that: 1) the occurrences of extreme rainfall, heavy snowfall, and drifting snow hazards are escalating; accelerated ice and snow melting have advanced the onset and increased the magnitude of snowmelt floods; 2) due to elevating trigger factors, such as glacier debuttressing and the rapid shift of thermal and hydrological regime of bedrock/snow/ice interface or subsurface, the mass flow hazards including bedrock landslide, snow avalanche, ice-rock avalanches or glacier detachment, and debris flow will become more severe; 3) increased active-layer detachment and retrogressive thaw slumps slope failures, thaw settlement and thermokarst lake will damage many important engineering structures and infrastructure in permafrost region; 4) multi-hazards cascading hazard in HMA, such as the glacial lake outburst flood (GLOF) and avalanche-induced mass flow may greatly enlarge the destructive power of the primary hazard by amplifying its volume, mobility, and impact force; and 5) enhanced slope instability and sediment supply in the highland areas could impose remote catastrophic impacts upon lowland regions, and threat hydropower security and future water shortage. In future, ongoing thawing of HMA will profoundly weaken the multiple-phase material of bedrock, ice, water, and soil, and enhance activities of nature hazards. Compounding and cascading hazards of high magnitude will prevail in HMA. As the glacier runoff overpasses the peak water, low flow or droughts in lowland areas downstream of glacierized mountain regions will became more frequent and severe. Addressing escalating hazards in the HMA region requires tackling scientific challenges, including understanding multiscale evolution and formation mechanism of HMA hazard-prone systems, coupling thermo-hydro-mechanical processes in multi-phase flows, predicting catastrophes arising from extreme weather and climate events, and comprehending how highland hazards propagate to lowlands due to climate change.

Over the past decades, the cryosphere has changed significantly in High Mountain Asia (HMA), leading to multiple natural hazards such as rock-ice avalanches, glacier collapse, debris flows, landslides, and glacial lake outburst floods (GLOFs). Monitoring cryosphere change and evaluating its hydrological effects are essential for studying climate change, the hydrological cycle, water resource management, and natural disaster mitigation and prevention. However, knowledge gaps, data uncertainties, and other substantial challenges limit comprehensive research in climate-cryosphere-hydrology-hazard systems. To address this, we provide an up-to-date, comprehensive, multidisciplinary review of remote sensing techniques in cryosphere studies, demonstrating primary methodologies for delineating glaciers and measuring geodetic glacier mass balance change, glacier thickness, glacier motion or ice velocity, snow extent and water equivalent, frozen ground or frozen soil, lake ice, and glacier-related hazards. The principal results and data achievements are summarized, including URL links for available products and related data platforms. We then describe the main challenges for cryosphere monitoring using satellite-based datasets. Among these challenges, the most significant limitations in accurate data inversion from remotely sensed data are attributed to the high uncertainties and inconsistent estimations due to rough terrain, the various techniques employed, data variability across the same regions (e.g., glacier mass balance change, snow depth retrieval, and the active layer thickness of frozen ground), and poor-quality optical images due to cloudy weather. The paucity of ground observations and validations with few long-term, continuous datasets also limits the utilization of satellite-based cryosphere studies and large-scale hydrological models. Lastly, we address potential breakthroughs in future studies, i.e., (1) outlining debris-covered glacier margins explicitly involving glacier areas in rough mountain shadows, (2) developing highly accurate snow depth retrieval methods by establishing a microwave emission model of snowpack in mountainous regions, (3) advancing techniques for subsurface complex freeze-thaw process observations from space, (4) filling knowledge gaps on scattering mechanisms varying with surface features (e.g., lake ice thickness and varying snow features on lake ice), and (5) improving and cross-verifying the data retrieval accuracy by combining different remote sensing techniques and physical models using machine learning methods and assimilation of multiple high-temporal-resolution datasets from multiple platforms. This comprehensive, multidisciplinary review highlights cryospheric studies incorporating spaceborne observations and hydrological models from diversified techniques/methodologies (e.g., multi-spectral optical data with thermal bands, SAR, InSAR, passive microwave, and altimetry), providing a valuable reference for what scientists have achieved in cryosphere change research and its hydrological effects on the Third Pole.

Classifying a given landscape on the basis of its susceptibility to surface processes is a standard procedure in low to mid-latitudes. Conversely, these procedures have hardly been explored in periglacial regions. However, global warming is radically changing this situation and will change it even more in the future. For this reason, un-derstanding the spatial and temporal dynamics of geomorphological processes in peri-arctic environments can be crucial to make informed decisions in such unstable environments and shed light on what changes may follow at lower latitudes. For this reason, here we explored the use of data-driven models capable of recognizing locations prone to develop retrogressive thaw slumps (RTSs) and/or active layer detachments (ALDs). These are cryo-spheric hazards induced by permafrost degradation, and their development can negatively affect human set-tlements or infrastructure, change the sediment budget and release greenhouse gases. Specifically, we test a binomial Generalized Additive Modeling structure to estimate the probability of RST and ALD occurrences in the North sector of the Alaskan territory. The results we obtain show that our binary classifiers can accurately recognize locations prone to RTS and ALD, in a number of goodness-of-fit (AUCRTS = 0.83; AUCALD = 0.86), random cross-validation (mean AUCRTS = 0.82; mean AUCALD = 0.86), and spatial cross-validation (mean AUCRTS = 0.74; mean AUCALD = 0.80) routines. Overall, our analytical protocol has been implemented to build an open-source tool scripted in Python where all the operational steps are automatized for anyone to replicate the same experiment. Our protocol allows one to access cloud-stored information, pre-process it, and download it locally to be integrated for spatial predictive purposes.

The thawing of permafrost in the Arctic has led to an increase in coastal land loss, flooding, and ground subsidence, seriously threatening civil infrastructure and coastal communities. However, a lack of tools for synthetic hazard assessment of the Arctic coast has hindered effective response measures. We developed a holistic framework, the Arctic Coastal Hazard Index (ACHI), to assess the vulnerability of Arctic coasts to permafrost thawing, coastal erosion, and coastal flooding. We quantified the coastal permafrost thaw potential (PTP) through regional assessment of thaw subsidence using ground settlement index. The calculations of the ground settlement index involve utilizing projections of permafrost conditions, including future regional mean annual ground temperature, active layer thickness, and talik thickness. The predicted thaw subsidence was validated through a comparison with observed long-term subsidence data. The ACHI incorporates the PTP into seven physical and ecological variables for coastal hazard assessment: shoreline type, habitat, relief, wind exposure, wave exposure, surge potential, and sea-level rise. The coastal hazard assessment was conducted for each 1 km2 coastline of North Slope Borough, Alaska in the 2060s under the Representative Concentration Pathway 4.5 and 8.5 forcing scenarios. The areas that are prone to coastal hazards were identified by mapping the distribution pattern of the ACHI. The calculated coastal hazards potential was subjected to validation by comparing it with the observed and historical long-term coastal erosion mean rates. This framework for Arctic coastal assessment may assist policy and decision-making for adaptation, mitigation strategies, and civil infrastructure planning.

Mountains are highly diverse in areal extent, geological and climatic context, ecosystems and human activity. As such, mountain environments worldwide are particularly sensitive to the effects of anthropogenic climate change (global warming) as a result of their unique heat balance properties and the presence of climatically-sensitive snow, ice, permafrost and ecosystems. Consequently, mountain systems-in particular cryospheric ones-are currently undergoing unprecedented changes in the Anthropocene. This study identifies and discusses four of the major properties of mountains upon which anthropogenic climate change can impact, and indeed is already doing so. These properties are: the changing mountain cryosphere of glaciers and permafrost; mountain hazards and risk; mountain ecosystems and their services; and mountain communities and infrastructure. It is notable that changes in these different mountain properties do not follow a predictable trajectory of evolution in response to anthropogenic climate change. This demonstrates that different elements of mountain systems exhibit different sensitivities to forcing. The interconnections between these different properties highlight that mountains should be considered as integrated biophysical systems, of which human activity is part. Interrelationships between these mountain properties are discussed through a model of mountain socio-biophysical systems, which provides a framework for examining climate impacts and vulnerabilities. Managing the risks associated with ongoing climate change in mountains requires an integrated approach to climate change impacts monitoring and management.

Permafrost degradation poses serious threats to both natural and human systems through its influence on ecological-hydrological processes, infrastructure stability, and the climate system. The Arctic and the Third Pole (Tibetan Plateau, TP hereafter) are the two northern regions on Earth with the most extensive permafrost areas. However, there is a lack of systematic comparisons of permafrost characteristics and its climate and ecoenvironment between these two regions and their susceptibility to disturbances. This study provides a comprehensive review of the climate, ecosystem characteristics, ground temperature, permafrost extent, and active-layer thickness, as well as the past and future changes in permafrost in the Arctic and the TP. The potential consequences associated with permafrost degradation are also examined. Lastly, possible connections between the two regions through land-ocean-atmosphere interactions are explored. Both regions have experienced dramatic warming in recent decades, characterized by Arctic amplification and elevation-dependent warming on the TP. Permafrost temperatures have increased more rapidly in the Arctic than on the TP, and will likely be reinforced under a future high emission scenario. Near-surface permafrost extents are projected to shrink in both regions in the coming decades, with a more dramatic decline in the TP. The active layer on the TP is thicker and has substantially deepened, and is projected to thicken more than in the Arctic. Widespread permafrost degradation increases geohazard risk and has already wielded considerable effects on the human and natural systems. Permafrost changes have also exerted a pronounced impact on the climate system through changes in permafrost carbon and land-atmosphere interactions. Future research should involve comparative studies of permafrost dynamics in both regions that integrate long-term observations, high-resolution satellite measurements, and advanced Earth System models, with emphasis on linkages between the two regions.

Climate warming could accelerate frozen ground degradation on the Qinghai-Tibet Plateau (QTP). Quantitative analysis of the impacts of thaw-induced hazards of the frozen ground on human activities in cold regions has become one of the most important issues in current research. To identify adverse impacts of these thawing hazards on human activities, this study explores a spatially explicit, temporally consistent and quantitative method to map human activity intensity (HAI). Four categories of variables are selected to represent some of the most important human activities on the QTP, including land use, road distribution, population density, and grazing density. By improving the human footprint index method, HAI maps of the QTP in 1995, 2005, and 2015 are created, and then quantitative analysis of the HAI under different thawing hazard levels in the frozen ground of QTP is done. The results show that, for the above three periods, the mean HAI values on the QTP are 0.10, 0.11, and 0.12, respectively. Moreover, during 1995-2015, the intensity and extent of human activities increase by 15.35% and 40.64%, respectively. The superposition results of the HAI and frozen ground thawing hazard maps show that a seasonally frozen ground region has relatively larger HAI, and its mean value is more than twice that of the permafrost region. For permafrost regions, the medium-hazard area has the highest HAI (0.09), which possibly has great impacts on the linear infrastructure. The establishment of a thawing disaster warning map can effectively shield high thaw settlement hazard areas without human activities and thus can present a more accurate early warning. These results can provide important scientific references for the disaster prevention and mitigation work in frozen ground regions, including risk assessment and infrastructure maintenance.