Glaciers distinct from the Greenland and Antarctic ice sheets cover an area of approximately 706,000 square kilometres globally 1 , with an estimated total volume of 170,000 cubic kilometres, or 0.4 metres of potential sea-level-rise equivalent 2. Retreating and thinning glaciers are icons of climate change 3 and affect regional runoff 4 as well as global sea level 5,6. In past reports from the Intergovernmental Panel on Climate Change, estimates of changes in glacier mass were based on the multiplication of averaged or interpolated results from available observations of a few hundred glaciers by defined regional glacier areas 7-10. For data-scarce regions, these results had to be complemented with estimates based on satellite altimetry and gravimetry 11. These past approaches were challenged by the small number and heterogeneous spatiotemporal distribution of in situ measurement series and their often unknown ability to represent their respective mountain ranges, as well as by the spatial limitations of satellite altimetry (for which only point data are available) and gravimetry (with its coarse resolution). Here we use an extrapolation of glaciological and geodetic observations to show that glaciers contributed 27 ± 22 millimetres to global mean sea-level rise from 1961 to 2016. Regional specific-mass-change rates for 2006-2016 range from −0.1 metres to −1.2 metres of water equivalent per year, resulting in a global sea-level contribution of 335 ± 144 gigatonnes, or 0.92 ± 0.39 millimetres, per year. Although statistical uncertainty ranges overlap, our conclusions suggest that glacier mass loss may be larger than previously reported 11. The present glacier mass loss is equivalent to the sea-level contribution of the Greenland Ice Sheet 12 , clearly exceeds the loss from the Antarctic Ice Sheet 13 , and accounts for 25 to 30 per cent of the total observed sea-level rise 14. Present mass-loss rates indicate that glaciers could almost disappear in some mountain ranges in this century, while heavily glacierized regions will continue to contribute to sea-level rise beyond 2100. Changes in glacier volume and mass are observed by geodetic and glaciological methods 15. The glaciological method provides glacier-wide mass changes by using point measurements from seasonal or annual in situ campaigns, extrapolated to unmeasured regions of the glacier. The geodetic method determines glacier-wide volume changes by repeated mapping and differencing of glacier surface elevations from in situ, airborne and spaceborne surveys, usually over multiyear to decadal periods. In this study, we used glaciological and geodetic data from the World Glacier Monitoring Service (WGMS) 16 , complemented by new and as-yet-unpublished geodetic assessments for glaciers in Africa,
Abstract. Knowledge of the ice thickness distribution of glaciers and ice caps is an important prerequisite for many glaciological and hydrological investigations. A wealth of approaches has recently been presented for inferring ice thickness from characteristics of the surface. With the Ice Thickness Models Intercomparison eXperiment (ITMIX) we performed the first coordinated assessment quantifying individual model performance. A set of 17 different models showed that individual ice thickness estimates can differ considerably – locally by a spread comparable to the observed thickness. Averaging the results of multiple models, however, significantly improved the results: on average over the 21 considered test cases, comparison against direct ice thickness measurements revealed deviations on the order of 10 ± 24 % of the mean ice thickness (1σ estimate). Models relying on multiple data sets – such as surface ice velocity fields, surface mass balance, or rates of ice thickness change – showed high sensitivity to input data quality. Together with the requirement of being able to handle large regions in an automated fashion, the capacity of better accounting for uncertainties in the input data will be a key for an improved next generation of ice thickness estimation approaches.
Abstract. Knowledge of supra-glacial debris cover and its changes remain incomplete in the Greater Caucasus, in spite of recent glacier studies. Here we present data of supra-glacial debris cover for 659 glaciers across the Greater Caucasus based on Landsat and SPOT images from the years 1986, 2000 and 2014. We combined semi-automated methods for mapping the clean ice with manual digitization of debris-covered glacier parts and calculated supra-glacial debris-covered area as the residual between these two maps. The accuracy of the results was assessed by using high-resolution Google Earth imagery and GPS data for selected glaciers. From 1986 to 2014, the total glacier area decreased from 691.5±29.0 to 590.0±25.8 km2 (15.8±4.1 %, or ∼0.52 % yr−1), while the clean-ice area reduced from 643.2±25.9 to 511.0±20.9 km2 (20.1±4.0 %, or ∼0.73 % yr−1). In contrast supra-glacial debris cover increased from 7.0±6.4 %, or 48.3±3.1 km2, in 1986 to 13.4±6.2 % (∼0.22 % yr−1), or 79.0±4.9 km2, in 2014. Debris-free glaciers exhibited higher area and length reductions than debris-covered glaciers. The distribution of the supra-glacial debris cover differs between the northern and southern and between the western, central and eastern Greater Caucasus. The observed increase in supra-glacial debris cover is significantly stronger on the northern slopes. Overall, we have observed up-glacier average migration of supra-glacial debris cover from about 3015 to 3130 m a.s.l. (metres above sea level) during the investigated period.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.