Due to the influence of the Indian monsoon, the Kangri Karpo Mountains in the south-east of the Tibetan Plateau is in the most humid and one of the most important and concentrated regions containing maritime (temperate) glaciers. Glacier mass loss in the Kangri Karpo is an important contributor to global mean sea level rise, and changes run-off distribution, increasing the risk of glacial-lake outburst floods (GLOFs). Because of its inaccessibility and high labour costs, information about the Kangri Karpo glaciers is still limited. Using geodetic methods based on digital elevation models (DEMs) derived from 1980 topographic maps from the Shuttle Radar Topography Mission (SRTM) (2000) and from TerraSAR-X/TanDEM-X (2014), this study has determined glacier elevation changes. Glacier area and length changes between 1980 and 2015 were derived from topographical maps and Landsat TM/ETM+/OLI images. Results show that the Kangri Karpo contained 1166 glaciers with an area of 2048.50 ± 48.65 km² in 2015. Ice cover diminished by 679.51 ± 59.49 km² (24.9 ± 2.2 %) or 0.71 ± 0.06 % a⁻¹ from 1980 to 2015, although nine glaciers advanced. A glacierized area of 788.28 km², derived from DEM differencing, experienced a mean mass loss of 0.46 ± 0.08 m w.e. a⁻¹ from 1980 to 2014. Shrinkage and mass loss accelerated significantly from 2000 to 2015 compared to 1980–2000, consistent with a warming climate.

The change in snow cover under climate change is poorly understood in Tianshan Mountains. Here, we investigate the spatiotemporal characteristics and trends of snow-covered area (SCA) and snow-covered days (SCD) in the Tianshan Mountains by using the cloud-removed MODIS fractional snow cover datasets from 2001–2015. The possible linkage between the snow cover and temperature and precipitation changes over the Tianshan Mountains is also investigated. The results are as follows: (1) The distribution of snow cover over the Tianshan Mountains exhibits a large spatiotemporal heterogeneity. The areas with SCD greater than 120 days are distributed in the principal mountains with elevations of above 3000 m. (2) In total, 26.39% (5.09% with a significant decline) and 34.26% (2.81% with a significant increase) of the study area show declining and increasing trend in SCD, respectively. The SCD mainly decreases in Central and Eastern Tianshan (decreased by 11.88% and 8.03%, respectively), while it increases in Northern and Western Tianshan (increased by 9.36% and 7.47%). (3) The snow cover variations are linked to the temperature and precipitation changes. Temperature tends to be the major factor effecting the snow cover changes in the Tianshan Mountains during 2001–2015.

Multi-temporal glacier inventories provide key information about the glaciers, their characteristics, and changes and are inevitable for glacier modelling and investigating geodetic mass changes. However, to date, no consistent multi-temporal glacier inventory for the whole of the Karakoram exists, negatively affecting the monitoring of spatio-temporal variations in glaciers' geometric parameters and their related applications. We used a semi-automatic method combining automatic segmentation and manual correction and produced a multi-temporal Karakoram glacier inventory (KGI) compiled from Landsat TM/ETM+/OLI (Thematic Mapper, Enhanced Thematic Mapper Plus, and Operational Land Imager) images for the 1990s, 2000s, 2010s, and 2020s. Our assessments using independent multiple digitisation of 37 glaciers show that the KGI is sufficiently accurate, with an overall uncertainty of ±3.68 %. We also performed uncertainty evaluation for the contiguous glacier polygons using a buffer of half a pixel, which resulted in an average mapping uncertainty of ±5.21 %. We calculated more than 20 attributes for each glacier, including coordinates, area, supraglacial debris area, date information, and topographic parameters derived from the ASTER GDEM (Advanced Spaceborne Thermal Emission and Reflection Radiometer global digital elevation model). According to KGI-2020s, approximately 10 500 alpine glaciers (>0.01 km² each) cover an area of 22 510±828 km² of which 10.18±0.38 % (2290±84 km²) is covered by supraglacial debris. Over the past 3 decades, the glaciers experienced a loss of clean ice and/or snow area but a gain in supraglacial debris. Supraglacial debris cover has increased by 17.63±1.44 % (343.30±27.95 km²), while non-debris-covered glaciers decreased by 1.56±0.24 % (319.85±49.92 km²). The total glacier area was relatively stable and showed only a slight insignificant increase of 23.45±28.85 km² (0.10±0.13 %). The glacier area has declined by 3.27±0.24 % in the eastern Karakoram, while the glacier area slightly increased in central (0.65±0.10 %) and western Karakoram (1.26±0.11 %). Supraglacial debris has increased over the whole of Karakoram, especially in areas above 4200 m a.s.l. (above sea level), showing an upward shift. The glacier area changes were characterised by strong spatial heterogeneity, influenced by surging and advancing glaciers. However, due to global warming, the glaciers are on average retreating. This is in particular true for small and debris-free glaciers. The multi-temporal KGI data are available at the National Cryosphere Desert Data Center of China: https://doi.org/10.12072/ncdc.glacier.db2386.2022 (F. Xie et al., 2022).

Previous studies have shown that glacier changes were heterogeneous in the western Karakoram, with the coexistence of retreating, advancing, and surging glaciers. However, it remains unclear that the mechanisms driving these changes. Based on the Shuttle Radar Topography Mission (SRTM) DEM and TerraSAR-X/TanDEM-X images (2014), this study presents glacier surface height changes in the Hunza Basin of the western Karakoram, employing the method of differential synthetic aperture radar interferometry (DInSAR). A slight negative glacier mass balance was observed in the Hunza Basin during 2000–2014. Surge-type glaciers would not have an obvious effect on overall mass balance in regional assessments over long-time scales. Further, glacier surface velocities in the Hunza Basin were estimated from Landsat images for the period of 1990–2018 by utilizing published data sets and Landsat images. Compared to the annual glacier surface velocities, 22 surge events were observed in seven surge-type glaciers in the Hunza Basin. Glacier flow can be attributed to thermally and hydrologically control, and the geomorphological characteristics of different individuals. This study gives us a new insight into the situation of the “Karakoram anomaly” under the background of glacier mass loss in the high mountains of Asia (HMA).