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Climate warming can lead to permafrost degradation, potentially resulting in slope failures such as retrogressive thaw slumps (RTSs). The formation of and changes in RTSs could exacerbate the degradation of permafrost and the environment in general. The mechanisms of RTS progression and the potential consequences on the analogous freeze–thaw cycle are not well understood, owing partly to necessitating field work under harsh conditions and with high costs. Here, we used multi-source remote sensing and field surveys to quantify the changes in an RTS on Eboling Mountain in the Qilian Mountain Range in west-central China. Based on optical remote sensing and SBAS-InSAR measurements, we analyzed the RTS evolution and the underlying drivers, combined with meteorological observations. The RTS expanded from 56 m2 in 2015 to 4294 m2 in 2022, growing at a rate of 1300 m2/a to its maximum in 2018 and then decreasing. Changes in temperature and precipitation play a dominant role in the evolution of the RTS, and the extreme weather in 2016 may also be a primary contributor to the accelerated growth, with an average deformation of −8.3 mm during the thawing period, which decreased slope stability. The RTS evolved more actively during the thawing and early freezing process, with earthquakes having potentially contributed further to RTS evolution. We anticipate that the rate of RTS evolution is likely to increase in the coming years. [ABSTRACT FROM AUTHOR]

The maximum annual freeze depth (MFD) is a primary indicator of the thermal state of frozen ground, affecting ecosystems, hydrological processes, vegetation growth, infrastructure, and human activities in cold regions. It is thus important to quantify the past, present, and future spatial and temporal variability of MFD at the hemispheric scale. We develop a data‐driven MFD simulation method within a machine learning framework, integrating MFD observations from meteorological stations and several environmental predictors, to analyze past and future scenarios in the Northern Hemisphere (NH). Based on ERA5 reanalysis estimates and historical to future CMIP6 scenarios, the NH MFD averaged 133 cm (ERA5) and 131 cm (CMIP6) during 1981–2010, and will vary 81–112 cm during 2015–2100 depending on the emission scenario. During 1950–2013, MFD decreased by 0.37 cm/a (ERA5) versus 0.22 cm/a (CMIP6), and is projected to decrease 0.16–0.69 cm/a by 2100. During 1981–2010, MFD decreased by an average of 19.1% (ERA5) and 13.9% (CMIP6), with a net change of −17 cm (ERA5) and −13 cm (CMIP6). Depending on the emission scenario, MFD will decrease 11% (−12 cm) to 42% (−19 cm) between 2015 and 2099 relative to the 1981–2010. Warming, increased moisture, warmer cold seasons, warmer warm seasons, shallower snow depths, and increased vegetation cover all lead to a reduction in MFD. The results from this novel machine learning approach provide useful insights regarding the fate of future frozen ground changes. Plain Language Summary: Seasonally frozen ground covers approximately half of the exposed ground surface in the Northern Hemisphere and is found in areas of intense human activity. There, the moisture retention and occurrence of freezing and thawing significantly impact agricultural production and infrastructure. Maximum freeze depth is a key indicator of the status of seasonally frozen ground. We simulate and predict the spatial distribution of maximum freeze depth at the hemispheric scale and quantify the variability of maximum freeze depth over past and future periods. Depending on the choice of future emission scenario, average maximum freeze depth in the Northern Hemisphere will decrease by 11% (−12 cm) to 42% (−19 cm) between 2015 and 2099, relative to the base period (1981–2010). Key Points: A novel machine learning approach is used to calculate 250 years of maximum freeze depth for Northern Hemisphere seasonally frozen groundUnder the SSP5‐8.5 scenario, the maximum freeze depth in the Northern Hemisphere will decrease by 42% by 2099The maximum freeze depth decreases the most in the snow climate zone [ABSTRACT FROM AUTHOR]

Climate warming and anthropogenic disturbances result in permafrost degradation in cold regions, including in the Qilian Mountains. These changes lead to extensive hillslope thermokarst (HT) formation, such as retrogressive thaw slumps, active-layer detachment slides, and thermal erosion gullies. These in turn cause, e.g., degradation of local vegetation, economic losses, infrastructure damages, and threats to human safety. However, despite its importance, there is currently no thermokarst inventory for the Qilian Mountains. Through manual visual interpretation and field validation, we therefore produce the first quantification of HT features. We count a total of 1064 HT features, with 67 % located in the upper reaches of the Heihe River Basin, which encompasses ~13 % of the Qilian Mountains region. We furthermore document that 82 % of the HT was initiated in the last 10 years. The thermokarst terrain is observed primarily in areas with shallow active layer depth, on northern shaded slopes of 3–25°, with low solar radiation and moderate elevations ranging from 3200 to 4000 m. This first inventory of HT features is an important and missing piece in documenting changes on the Qinghai-Tibetan Plateau, and this new dataset also provides an important basis for further studies on, e.g., quantitative assessment losses caused by HT. The datasets are available from the National Tibetan Plateau/Third Pole Environment Data Center and can be downloaded from https://doi.org/10.11888/Cryos.tpdc.300805 (Peng and Yang, 2023). [ABSTRACT FROM AUTHOR]

In cold regions characterized by perennially frozen soil, climate warming has caused permafrost degradation, which is manifested by surface deformation and deepening of the active layer. Interferometric synthetic aperture radar (InSAR) is a common method to obtain large‐scale surface deformation, especially in mountainous terrain where it is difficult to install a large number of monitoring sites. Here, we used Sentinel‐1A SAR data acquired from March 2017 to March 2021 to monitor surface deformation and estimate active layer thickness (ALT) using two methods—temperature‐based and soil moisture‐based—in the permafrost regions of the Heihe River Basin on the northeast Qinghai‐Tibetan Plateau. We find that the seasonal deformation amplitude ranges 10–60 mm, and the annual mean vertical deformation trend ranges from −40 to 30 mm/a. We verify the ALT estimates with observations and find that the method based on soil moisture has higher accuracy and is therefore more applicable in this particular study area. The ALT gradually decreases from the southeast to the northwest, ranging from 0.3 to 6.5 m, with an average value of 2.47 m. These results contribute to better quantifying the response of permafrost change and to understanding the spatial distribution of ALT on a large scale, serving as guidance for engineering and other applications. Plain Language Summary: The effects of global warming have led to the degradation of permafrost. To quantify changes in permafrost, we use InSAR (Interferometric Synthetic Aperture Radar) technology to monitor the surface deformation in permafrost area. The main manifestation of permafrost degradation is the deepening of the active layer (AL). Therefore, we investigate the feasibility of obtaining AL thickness in the permafrost zone based on InSAR. Mean AL thickness in the Heihe River Basin is 2.47 m and ranges 0.3–6.5 m. Compared with temperature‐based inversion models, the inversion model for ALT based on the soil moisture content has a higher accuracy. Key Points: Surface deformation based on interferometric synthetic aperture radar can be used to quantify active‐layer thickness (ALT) with high resolutionMean active layer thickness in the Heihe River Basin is 2.47 m and ranges from 0.3 to 6.5 mThe inversion model for ALT based on the soil moisture content has a higher accuracy when combined with the temperature‐based inversion model [ABSTRACT FROM AUTHOR]

Surface air temperatures are significant indicators of environmental and climatic change that affect a diverse set of physical systems including permafrost. Most temperature products, such as gridded or reanalysis data, are still at a relatively low spatial resolution, limiting the ability to simulate heterogeneous permafrost changes and leading to large uncertainties. Here we apply a downscaling method based on elevation to obtain high‐resolution surface air temperatures from the sixth Coupled Model Intercomparison Project in Northern Hemisphere permafrost regions. Root‐mean‐square errors and mean absolute errors after downscaling are reduced by 34 and 37%, respectively, relative to meteorological site data and gridded observations from the Climatic Research Unit. Compared to the downscaled surface air temperature data, nondownscaled model projections overestimate by 0.12–0.39°C in the discontinuous, isolated, and sporadic permafrost regions and underestimate up to 0.18°C in the continuous permafrost region under different emission scenarios. The warming rates in Northern Hemisphere permafrost regions were 0.093°C/10 year during the historical (1850–2014) period and are projected to be 0.22°C/10 year for SSP1‐2.6, 0.48°C/10 year for SSP2‐4.5, 0.75°C/10 year for SSP3‐7.0, and 0.95°C/10 year for SSP5‐8.5 during 2015–2100, which is 1.4–1.6 times the warming of nonpermafrost regions. Warming rates in high latitudes are 1.2–1.7 times higher than those in high‐elevation regions. Continuous permafrost regions' warming will be 1.2–1.4 times higher than in other permafrost regions. For permafrost with high ground ice content, warming will be 1.1 times greater than in permafrost regions with medium or low ground ice content. [ABSTRACT FROM AUTHOR]

It’s important to understand the role of permafrost in the future climate and water resources management, for huge storage of soil organic carbon and ground ice in the permafrost. To date, large uncertainties still exist in permafrost simulations for many reasons. One reason is being a lack of long-term meteorological, permafrost and carbon observations. Here, we therefore present datasets for air temperatures, precipitation, soil temperature and moisture, active layer thickness, ground temperatures at different depths, soil organic carbon contents, and ecosystem carbon emission rates for the Qilian Mountains of the Northeastern Qinghai-Tibetan Plateau during 2011–2020. The data come from 5 automatic meteorological stations, 21 boreholes with depths from 11.5 to 149.3 m, and 12 active layer monitoring sites, which are used to obtain the hydrothermal and thermal states, and climate change in the study area. Soil organic carbon contents is available from 10 deep boreholes, down to a depth of 20 m. Ecosystem respiration rates are obtained from the prevalent vegetation types of alpine wet meadow, meadow, and steppe for the growing seasons. This decade’s high-quality datasets are expected to serve as useful inputs for earth system models, and are for researchers working in those disciplines including geophysics, ecology, and hydrology in alpine environments. [ABSTRACT FROM AUTHOR]