Interdecadal glacier inventories in the Karakoram since the 1990s

Abstract

Abstract. 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).

A comprehensive and version-controlled database of glacial lake outburst floods in High Mountain Asia

“…The database was developed keeping in mind interoperability with other datasets, enabling future local and regional risk assessments, as well as investigations on how the occurrence of GLOFs can be explained on a regional, rather than an individual level. Multiple datasets related to the cryosphere are readily accessible, including historic glacier outlines (Pfeffer, 2017;Soheb et al, 2022;Xie et al, 2023), elevation change (Brun et al, 2017;Hugonnet et al, 2021), glacial lakes (Chen et al, 2021;Wang et al, 2020), and permafrost extents (Obu, 2021). These datasets can be easily combined with the GLOF inventory for comprehensive analysis.…”

“…Exploiting other spatial datasets, this can help in evaluating possible drivers as well as impacts. Repeat spatial products related to the cryosphere available in HMA include decadal glacier outlines (He and Zhou, 2022;Lee et al, 2021;Xie et al, 2023) and distributed data on ice mass loss (Brun et al, 2017;Hugonnet et al, 2021), permafrost probability (Obu, 2021), and snow cover (Muhammad and Thapa, 2021). Such datasets can be compared with recorded GLOF events and lakes that have not resulted in GLOFs to evaluate potential drivers.…”

A Geodetic-Data-Calibrated Ice Flow Model to Simulate Historical and Future Response of Glaciers in Southeastern Tibetan Plateau

“…For example, the Nyainqêntanglha region has experienced the most notable glacier mass loss [16]. However, the glacier mass balance in the Karakoram and Pamir regions is relatively small, occasionally even exhibiting a positive value [17,18]. This heterogeneity can be attributed to factors such as regional atmospheric circulation patterns [19], sensitivity to a warming climate [20], and changes in the seasonality and intensity of the summer monsoon [21,22].…”

Mapping Seasonal Snow Melting in Karakoram Using SAR and Topographic Data

“…Situated at the center of the Hindukush-Karakoram-Himalaya (HKH) mountain system, the Karakoram is renowned for hosting some of the world's highest peaks and harboring the largest alpine glacier system outside the polar regions (Nie et al, 2021). Across its expansive landscape, snow and ice reserves are substantial, encompassing an area exceeding 20,000 km 2 , with seasonal snow covering nearly 90% of this expanse (Lund et al, 2020;Hasson et al, 2014;Xie et al, 2023). In the expansive and challenging terrain of the Karakoram region, ground-based observation methods struggle to effectively cover the vast and rugged terrain, and hence remote sensing techniques have become the primary approach for snow cover mapping.…”