High Mountain Asia hosts the largest glacier concentration outside the polar regions. These glaciers are important contributors to streamflow in one of the most populated areas of the world. Past studies have used methods that can provide only regionally averaged glacier mass balances to assess the glacier contribution to rivers and sea level rise. Here we compute the mass balance for about 92% of the glacierized area of High Mountain Asia using time series of digital elevation models derived from satellite stereo-imagery. We calculate a total mass change of −16.3 ± 3.5 Gt yr⁻¹ (−0.18 ± 0.04 m w.e. yr⁻¹) between 2000 and 2016, which is less negative than most previous estimates. Region-wide mass balances vary from −4.0 ± 1.5 Gt yr⁻¹ (−0.62 ± 0.23 m w.e. yr⁻¹) in Nyainqentanglha to +1.4 ± 0.8 Gt yr⁻¹ (+0.14 ± 0.08 m w.e. yr⁻¹) in Kunlun, with large intra-regional variability of individual glacier mass balances (standard deviation within a region ∼0.20 m w.e. yr⁻¹). Specifically, our results shed light on the Nyainqentanglha and Pamir glacier mass changes, for which contradictory estimates exist in the literature. They provide crucial information for the calibration of the models used for projecting glacier response to climatic change, as these models do not capture the pattern, magnitude and intra-regional variability of glacier changes at present. Publisher Correction (18 June 2018)

We present glacier thickness changes over the entire Pamir–Karakoram–Himalaya arc based on ICESat satellite altimetry data for 2003–2008. We highlight the importance of C-band penetration for studies based on the SRTM elevation model. This penetration seems to be of potentially larger magnitude and variability than previously assumed. The most negative rate of region-wide glacier elevation change (<−1 m yr⁻¹) is observed for the eastern Nyainqêntanglha Shan. Conversely, glaciers of the western Kunlun Shan are slightly gaining volume, and Pamir and Karakoram seem to be on the western edge of this mass-gain anomaly rather than its centre. For the Ganges, Indus and Brahmaputra basins, the glacier mass change reaches −24 ± 2 Gt yr⁻¹, about 10% of the current glacier contribution to sea-level rise. For selected catchments, we estimate glacier imbalance contributions to river run-off from a few percent to greater than 10%.

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.

Glaciers distinct from the Greenland and Antarctic ice sheets are currently losing mass rapidly with direct and severe impacts on the habitability of some regions on Earth as glacier meltwater contributes to sea-level rise and alters regional water resources in arid regions. In this review, we present the different techniques developed during the last two decades to measure glacier mass change from space: digital elevation model (DEM) differencing from stereo-imagery and synthetic aperture radar interferometry, laser and radar altimetry and space gravimetry. We illustrate their respective strengths and weaknesses to survey the mass change of a large Arctic ice body, the Vatnajökull Ice Cap (Iceland) and for the steep glaciers of the Everest area (Himalaya). For entire regions, mass change estimates sometimes disagree when a similar technique is applied by different research groups. At global scale, these discrepancies result in mass change estimates varying by 20%–30%. Our review confirms the need for more thorough inter-comparison studies to understand the origin of these differences and to better constrain regional to global glacier mass changes and, ultimately, past and future glacier contribution to sea-level rise.

A mantel of debris cover often accumulates across the surface of glaciers in active mountain ranges with exceptionally steep terrain, such as the Andes, Himalaya, and New Zealand Alps. Such a supraglacial debris layer has a major influence on a glacier's surface energy budget, enhancing radiation absorption, and melt when the layer is thin, but insulating the ice when thicker than a few cm. Information on spatially distributed debris surface temperature has the potential to provide insight into the properties of the debris, its effects on the ice below and its influence on the near-surface boundary layer. Here, we deploy an unmanned aerial vehicle (UAV) equipped with a thermal infrared sensor on three separate missions over one day to map changing surface temperatures across the debris-covered Lirung Glacier in the Central Himalaya. We present a methodology to georeference and process the acquired thermal imagery, and correct for emissivity and sensor bias. Derived UAV surface temperatures are compared with distributed simultaneous in situ temperature measurements as well as with Landsat 8 thermal satellite imagery. Results show that the UAV-derived surface temperatures vary greatly both spatially and temporally, with −1.4 ± 1.8, 11.0 ± 5.2, and 15.3 ± 4.7℃ for the three flights (mean ± sd), respectively. The range in surface temperatures over the glacier during the morning is very large with almost 50 °C. Ground-based measurements are generally in agreement with the UAV imagery, but considerable deviations are present that are likely due to differences in measurement technique and approach, and validation is difficult as a result. The difference in spatial and temporal variability captured by the UAV as compared with much coarser satellite imagery is striking and it shows that satellite derived temperature maps should be interpreted with care. We conclude that UAVs provide a suitable means to acquire surface temperature maps of debris-covered glacier surfaces at high spatial and temporal resolution, but that there are caveats with regard to absolute temperature measurement.