Knowledge about the long-term response of High Mountain Asian glaciers to climatic variations is paramount because of their important role in sustaining Asian river flow. Here, a satellite-based time series of glacier mass balance for seven climatically different regions across High Mountain Asia since the 1960s shows that glacier mass loss rates have persistently increased at most sites. Regional glacier mass budgets ranged from −0.40 ± 0.07 m w.e.a⁻¹ in Central and Northern Tien Shan to −0.06 ± 0.07 m w.e.a⁻¹ in Eastern Pamir, with considerable temporal and spatial variability. Highest rates of mass loss occurred in Central Himalaya and Northern Tien Shan after 2015 and even in regions where glaciers were previously in balance with climate, such as Eastern Pamir, mass losses prevailed in recent years. An increase in summer temperature explains the long-term trend in mass loss and now appears to drive mass loss even in regions formerly sensitive to both temperature and precipitation.

Glaciers are indicators of ongoing anthropogenic climate change¹. Their melting leads to increased local geohazards², and impacts marine³ and terrestrial^4,5 ecosystems, regional freshwater resources⁶, and both global water and energy cycles^7,8. Together with the Greenland and Antarctic ice sheets, glaciers are essential drivers of present^9,10 and future^11–13 sea-level rise. Previous assessments of global glacier mass changes have been hampered by spatial and temporal limitations and the heterogeneity of existing data series^14–16. Here we show in an intercomparison exercise that glaciers worldwide lost 273 ± 16 gigatonnes in mass annually from 2000 to 2023, with an increase of 36 ± 10% from the first (2000–2011) to the second (2012–2023) half of the period. Since 2000, glaciers have lost between 2% and 39% of their ice regionally and about 5% globally. Glacier mass loss is about 18% larger than the loss from the Greenland Ice Sheet and more than twice that from the Antarctic Ice Sheet¹⁷. Our results arise from a scientific community effort to collect, homogenize, combine and analyse glacier mass changes from in situ and remote-sensing observations. Although our estimates are in agreement with findings from previous assessments^14–16 at a global scale, we found some large regional deviations owing to systematic differences among observation methods. Our results provide a refined baseline for better understanding observational differences and for calibrating model ensembles^12,16,18, which will help to narrow projection uncertainty for the twenty-first century^11,12,18.

Thinning rates for the debris-covered Gangotri Glacier and its tributary glaciers during the period 1968–2014, length variation and area vacated at the snout from 1965 to 2015, and seasonal variation of ice-surface velocity for the last two decades have been investigated in this study. It was found that the mass loss of Gangotri and its tributary glaciers was slightly less than those reported for other debris-covered glaciers in the Himalayan regions. The average velocity during 2006–14 decreased by ~6.7% as compared with that during 1993–2006. The debris-covered area of the main trunk of Gangotri Glacier increased significantly from 1965 until 2015 with the maximum rate of increase (0.8 ± 0.2 km² a⁻¹) during 2006–15. The retreat (~9.0 ± 3.5 m a⁻¹) was less in recent years (2006–2015) but the down-wasting (0.34 ± 0.2 m a⁻¹) in the same period (2006–2014) was higher than that (0.20 ± 0.1 m a⁻¹) during 1968–2006. The study reinforced the established fact that the glacier length change is a delayed response to climate change and, in addition, is affected by debris cover, whereas glacier mass balance is a more direct and immediate response. Therefore, it is recommended to study the glacier mass balance and not only the glacier extent, to conclude about a glacier's response to climate change.

Glacial lake outburst floods (GLOFs) are a major concern throughout High Mountain Asia, where societal impacts can extend far downstream. This is particularly true for transboundary Himalayan basins, where risks are expected to further increase as new lakes develop. Given the need for anticipatory approaches to disaster risk reduction, this study aims to demonstrate how the threat from a future lake can be feasibly assessed alongside that of worst-case scenarios from current lakes, as well as how this information is relevant for disaster risk management. We have focused on two previously identified dangerous lakes (Galongco and Jialongco), comparing the timing and magnitude of simulated worst-case outburst events from these lakes both in the Tibetan town of Nyalam and downstream at the border with Nepal. In addition, a future scenario has been assessed, whereby an avalanche-triggered GLOF was simulated for a potential large new lake forming upstream of Nyalam. Results show that large ($>\mathrm{20}\times {\mathrm{10}}^{\mathrm{6}}$ m³) rock and/or ice avalanches could generate GLOF discharges at the border with Nepal that are more than 15 times larger than what has been observed previously or anticipated based on more gradual breach simulations. For all assessed lakes, warning times in Nyalam would be only 5–11 min and 30 min at the border. Recent remedial measures undertaken to lower the water level at Jialongco would have little influence on downstream impacts resulting from a very large-magnitude GLOF, particularly in Nyalam where there has been significant development of infrastructure directly within the high-intensity flood zone. Based on these findings, a comprehensive approach to disaster risk management is called for, combining early warning systems with effective land use zoning and programmes to build local response capacities. Such approaches would address the current drivers of GLOF risk in the basin while remaining robust in the face of worst-case, catastrophic outburst events that become more likely under a warming climate.

The Corona KH-4 reconnaissance satellite missions acquired panoramic stereo imagery with high spatial resolution of 1.8–7.5 m from 1962 to 1972. The potential of 800000+ declassified Corona images has not been leveraged due to the complexities arising from handling of panoramic imaging geometry, film distortions, and limited availability of the metadata required for georeferencing of the Corona imagery. This article presents the Corona Stereo Pipeline (CoSP): A pipeline for processing of Corona KH-4 stereo panoramic imagery. CoSP utilizes the deep learning-based feature matcher SuperGlue to automatically match feature points between Corona KH-4 images and recent satellite imagery to generate ground control points (GCPs). To model the imaging geometry and the scanning motion of the panoramic KH-4 cameras, a rigorous camera model consisting of modified collinearity equations with time-dependent exterior orientation parameters is employed. Using the entire frame of the Corona image, bundle adjustment with well-distributed GCPs results in an average standard deviation (SD) or $\sigma _{0}$ of less than two pixels. We evaluate fiducial marks on the Corona films and show that pre-processing the Corona images to compensate for film bending improves the 3-D reconstruction accuracy. The distortion pattern of image residuals of GCPs and $y$ -parallax in epipolar resampled images suggest that film distortions due to long-term storage likely cause systematic deviations of up to six pixels. Compared to the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM), the Corona DEM computed using CoSP achieved a normalized median absolute deviation (NMAD) of elevation differences of $\approx $ 4 m over an area of approximately 4000 km2 after a tile-based fine coregistration of the DEMs. We further assess CoSP on complex scenes involving high relief and glacierized terrain and show that the resulting DEMs can be used to compute long-term glacier elevation changes over large areas.