Rock glaciers (RGs) manifest the creep of mountain permafrost occurring in the past or at present. Their presence and dynamics are indicators of permafrost distribution and changes in response to climate forcing. There is a complete lack of knowledge about RGs in the Western Kunlun Mountains, one of the driest mountain ranges in Asia, where extensive permafrost is rapidly warming. In this study, we first mapped and quantified the kinematics of active RGs based on satellite Interferometric Synthetic Aperture Radar (InSAR) and Google Earth images. Then, we trained DeepLabv3+, a deep learning network for semantic image segmentation, to automate the mapping task. The well‐trained model was applied for a region‐wide extensive delineation of RGs from Sentinel‐2 images to map the landforms that were previously missed due to the limitations of the InSAR‐based identification. Finally, we mapped 413 RGs across the Western Kunlun Mountains: 290 of them were active RGs mapped manually based on InSAR and 123 of them were newly identified and outlined by deep learning. The RGs are categorized by their spatial connection to the upslope geomorphic units. All the RGs are located at altitudes between 3,390 and 5,540 m with an average size of 0.26 km² and a mean slope angle of 17°. Characteristics of the inventoried RGs provided insights into permafrost distribution in the Western Kunlun Mountains. The median and maximum surface downslope velocities of the active ones are 17 ± 1 and 127 ± 6 cm yr⁻¹, respectively.

Rock glaciers are distinctive debris landforms found worldwide in cold mountainous regions. They express the long‐term movement of perennially frozen ground. Rock Glacier Velocity (RGV), defined as the time series of the annualized surface velocity of a rock glacier unit or a part of it, has been accepted as an Essential Climate Variable Permafrost Quantity in 2022. This review aims to highlight the relationship between rock glacier velocity and climatic factors, emphasizing the scientific relevance of interannual rock glacier velocity in generating RGV products within the context of observed rock glacier kinematics. Under global warming, rock glacier velocity exhibits widespread (multi‐)decennial acceleration. This acceleration varies regionally in onset timing (from the 1950s to the 2010s) and magnitude (up to a factor of 10), and has been observed in regions such as the European Alps, High Mountain Asia, and the Andes. Despite different local conditions, a synchronous interannual velocity pattern prevails in the European Alps since the 2000s, highlighting the primary influence of climate. A common pattern is the seasonal velocity rhythm, which peaks in late summer to autumn and declines in spring. RGV assesses permafrost evolution via (multi‐)decennial and interannual changes in rock glacier velocity, influenced by air temperature shifts with varying time lags and snow cover effects. Although not integrated into the RGV products, seasonal variations should be examined. This rhythmic behavior is attributed to alterations in pore water pressure influenced by air temperature, snow cover, and ground water conditions.

Rock glaciers – periglacial landforms commonly found in high-mountain systems – are of significant scientific value for inferring the presence of permafrost, understanding mountain hydrology, and assessing climate impacts on high-mountain environments. However, inventories remain patchy in many alpine regions, and as a result they are poorly understood for some areas of High Mountain Asia such as the Tibetan Plateau. To address this gap, we compiled a comprehensive inventory of rock glaciers for the Tibetan Plateau, i.e., TPRoGI (v1.0), developed using an innovative deep learning method. This inventory consists of a total of 44 273 rock glaciers, covering approximately 6000 km ² , with a mean area of 0.14 km ² . They are predominantly situated at elevations ranging from 4000 to 5500 m a.s.l., with a mean of 4729 m a.s.l. They tend to occur on slopes with gradients between 10 and 25°, with a mean of 17.7°. Across the plateau, rock glaciers are widespread in the northwestern and southeastern areas, with dense concentrations in the Western Pamir and Nyainqêntanglha, while they are sparsely distributed in the inner part. Our inventory serves as a benchmark dataset, which will be further maintained and updated in the future. This dataset constitutes a significant contribution towards understanding, future monitoring, and assessment of permafrost on the Tibetan Plateau in the context of climate change. The dataset is available at https://doi.org/10.5281/zenodo.10732042 (Sun et al., 2024a).

Meltwater from the cryosphere contributes a significant fraction of the freshwater resources in the countries receiving water from the Third Pole. Within the ESA-MOST Dragon 4 project, we addressed in particular changes of glaciers and proglacial lakes and their interaction. In addition, we investigated rock glaciers in permafrost environments. Here, we focus on the detailed investigations which have been performed in the Poiqu River Basin, central Himalaya. We used in particular multi-temporal stereo satellite imagery, including high-resolution 1960/70s Corona and Hexagon spy images and contemporary Pleiades data. Sentinel-2 data was applied to assess the glacier flow. The results reveal that glacier mass loss continuously increased with a mass budget of −0.42 ± 0.11 m w.e.a⁻¹ for the period 2004–2018. The mass loss has been primarily driven by an increase in summer temperature and is further accelerated by proglacial lakes, which have become abundant. The glacial lake area more than doubled between 1964 and 2017. The termini of glaciers that flow into lakes moved on average twice as fast as glaciers terminating on land, indicating that dynamical thinning plays an important role. Rock glaciers are abundant, covering approximately 21 km², which was more than 10% of the glacier area (approximately 190 km²) in 2015. With ongoing glacier wastage, rock glaciers can become an increasingly important water resource.

Active rock glaciers are viscous flow features embodying ice-rich permafrost and other ice masses. They contain significant amounts of ground ice and serve as potential freshwater reservoirs as mountain glaciers melt in response to climate warming. However, current knowledge about ice content in rock glaciers has been acquired mainly from in situ investigations in limited study areas, which hinders a comprehensive understanding of ice storage in rock glaciers situated in remote mountains over local to regional scales. This study proposes a novel approach for assessing the hydrological value of rock glaciers in a more quantitative way and presents exploratory results focusing on a small region. We develop an empirical rheological model to infer ice content of rock glaciers using readily available input data, including rock glacier planar shape, surface slope angle, active layer thickness, and surface velocity. The model is calibrated and validated using observational data from the Chilean Andes and the Swiss Alps. We apply the model to five rock glaciers in the Khumbu and Lhotse valleys, northeastern Nepal. The velocity constraints applied to the model are derived from interferometric synthetic aperture radar (InSAR) measurements. The volume of rock glacier is estimated based on an existing scaling approach. The inferred volumetric ice fraction in the Khumbu and Lhotse valleys ranges from 70 ± 8 % to 74 ± 8 %, and the water volume equivalents lie between 1.4 ± 0.2 and $\mathrm{5.9}\pm \mathrm{0.6}\times {\mathrm{10}}^{\mathrm{6}}$ m³ for the coherently moving parts of individual rock glaciers. Due to the accessibility of the model inputs, our approach is applicable to permafrost regions where observational data are lacking, which is valuable for estimating the water storage potential of rock glaciers in remote areas.