Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Ice velocity and thickness of the world’s glaciers

An Author Correction to this article was published on 12 December 2022

This article has been updated

Abstract

The effect of climate change on water resources and sea-level rise is largely determined by the size of the ice reservoirs around the world and the ice thickness distribution, which remains uncertain. Here, we present a comprehensive high-resolution mapping of ice motion for 98% of the world’s total glacier area during the period 2017–2018. We use this mapping of glacier flow to generate an estimate of global ice volume that reconciles ice thickness distribution with glacier dynamics and surface topography. After reallocating volume connected to the Antarctic ice sheet, the results suggest that the world’s glaciers have a potential contribution to sea-level rise of 257 ± 85 mm, which is 20% less than previously estimated. At low latitudes, our findings highlight notable changes in freshwater resources, with 34% more ice in the Himalayas and 27% less ice in the tropical Andes of South America, affecting water availability for local populations. This mapping of glacier flow and thickness redefines our understanding of global ice-volume distribution and has implications for the prediction of glacier evolution around the world, since accurate representations of glacier geometry and dynamics are of prime importance to glacier modelling.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Ice velocity of the world’s glaciers.
Fig. 2: Comparison of glacier thickness distribution.
Fig. 3: Impact of the velocity-derived thicknesses on water resources.

Similar content being viewed by others

Data availability

Thickness and ice velocity datasets are publicly available at https://doi.org/10.6096/1007. GLACIOCLIM data available at https://glacioclim.osug.fr/; GlaThiDa data available at https://www.gtn-g.ch/data_catalogue_glathida/; RGI available at https://www.glims.org/RGI/; river basins and population data available at www.worldpop.org and https://www.bafg.de.

Change history

References

  1. Hock, R. et al. in Special Report on the Ocean and Cryosphere in a Changing Climate (eds Pörtner, H.-O. et al.) Ch. 2 (IPCC, 2019).

  2. Hugonnet, R. et al. Accelerated global glacier mass loss in the early twenty-first century. Nature 592, 726–731 (2021).

    Article  Google Scholar 

  3. Zemp, M. et al. Global glacier mass changes and their contributions to sea-level rise from 1961 to 2016. Nature 568, 382–386 (2019).

    Article  Google Scholar 

  4. Hock, R. et al. GlacierMIP—a model intercomparison of global-scale glacier mass-balance models and projections. J. Glaciol. 65, 453–467 (2019).

    Article  Google Scholar 

  5. McGranahan, G., Balk, D. & Anderson, B. The rising tide: assessing the risks of climate change and human settlements in low elevation coastal zones. Environ. Urban. 19, 17–37 (2007).

    Article  Google Scholar 

  6. Welty, E. et al. Worldwide version-controlled database of glacier thickness observations. Earth Syst. Sci. Data 12, 3039–3055 (2020).

  7. Huss, M. & Farinotti, D. Distributed ice thickness and volume of all glaciers around the globe. J. Geophys. Res. Earth Surf. 117, f04010 (2012).

    Article  Google Scholar 

  8. Linsbauer, A., Paul, F. & Haeberli, W. Modeling glacier thickness distribution and bed topography over entire mountain ranges with GlabTop: application of a fast and robust approach. J. Geophys. Res. Earth Surf. 117, F03007 (2012).

  9. Farinotti, D. et al. A consensus estimate for the ice thickness distribution of all glaciers on Earth. Nat. Geosci. 12, 168–173 (2019).

    Article  Google Scholar 

  10. Huss, M. & Hock, R. A new model for global glacier change and sea-level rise. Front. Earth Sci. 3, 54 (2015).

  11. Grinsted, A. An estimate of global glacier volume. Cryosphere 7, 141–151 (2013).

    Article  Google Scholar 

  12. Farinotti, D. et al. How accurate are estimates of glacier ice thickness? Results from ITMIX, the Ice Thickness Models Intercomparison eXperiment. Cryosphere 11, 949–970 (2017).

    Article  Google Scholar 

  13. Farinotti, D., Huss, M., Bauder, A., Funk, M. & Truffer, M. A method to estimate the ice volume and ice-thickness distribution of alpine glaciers. J. Glaciol. 55, 422–430 (2009).

    Article  Google Scholar 

  14. Marzeion, B., Jarosch, A. H. & Hofer, M. Past and future sea-level change from the surface mass balance of glaciers. Cryosphere 6, 1295–1322 (2012).

    Article  Google Scholar 

  15. Radić, V. et al. Regional and global projections of twenty-first century glacier mass changes in response to climate scenarios from global climate models. Clim. Dyn. 42, 37–58 (2014).

    Article  Google Scholar 

  16. Zorzut, V. et al. Slope estimation influences on ice thickness inversion models: a case study for Monte Tronador glaciers, North Patagonian Andes. J. Glaciol. https://doi.org/10.1017/jog.2020.64 (2020).

  17. Werder, M. A., Huss, M., Paul, F., Dehecq, A. & Farinotti, D. A Bayesian ice thickness estimation model for large-scale applications. J. Glaciol. 66, 137–152 (2020).

    Article  Google Scholar 

  18. Millan, R. et al. Vulnerability of Southeast Greenland glaciers to warm Atlantic water from Operation IceBridge and Ocean Melting Greenland data. Geophys. Res. Lett. 45, 2688–2696 (2018).

    Article  Google Scholar 

  19. Morlighem, M. et al. BedMachine v3: complete bed topography and ocean bathymetry mapping of Greenland from multibeam echo sounding combined with mass conservation. Geophys. Res. Lett. 44, 11051–11061 (2017).

    Article  Google Scholar 

  20. Larsen, C. F. et al. Surface melt dominates Alaska glacier mass balance. Geophys. Res. Lett. 42, 5902–5908 (2015).

  21. Millan, R., Mouginot, J. & Rignot, E. Mass budget of the glaciers and ice caps of the Queen Elizabeth Islands, Canada, from 1991 to 2015. Environ. Res. Lett. 12, 024016 (2017).

    Article  Google Scholar 

  22. Mouginot, J. & Rignot, E. Ice motion of the Patagonian Icefields of South America: 1984–2014. Geophys. Res. Lett. 42, 1441–1449 (2015).

    Article  Google Scholar 

  23. Dehecq, A. et al. Twenty-first century glacier slowdown driven by mass loss in High Mountain Asia. Nat. Geosci. 12, 22–27 (2019).

    Article  Google Scholar 

  24. Gardner, A. S., Fahnestock, M. & Scambos, T. ITS_LIVE Regional Glacier and Ice Sheet Surface Velocities (NSIDC, 2020).

  25. Millan, R. et al. Mapping surface flow velocity of glaciers at regional scale using a multiple sensors approach. Remote Sens. 11, 2498 (2019).

    Article  Google Scholar 

  26. Randolph Glacier Inventory 6.0 (RGI Consortium, 2017); https://doi.org/10.7265/N5-RGI-60

  27. Michel, R. & Rignot, E. Flow of glaciar Moreno, Argentina, from the repeat-pass shuttle imaging radar images: comparison of the phase correlation method with radar interferometry. J. Glaciol. 45, 93–100 (1999).

  28. Mouginot, J., Rignot, E., Scheuchl, B. & Millan, R. Comprehensive annual ice sheet velocity mapping using Landsat-8, Sentinel-1, and RADARSAT-2 data. Remote Sens. 9, 364 (2017).

    Article  Google Scholar 

  29. Cuffey, K. & Paterson, W. S. B. The Physics of Glaciers (Butterworth-Heinemann/Elsevier, 2010).

  30. Gaillardet, J. et al. OZCAR: the French network of critical zone observatories. Vadose Zone J. 17, 180067 (2018).

    Article  Google Scholar 

  31. Lambrecht, A., Mayer, C., Aizen, V., Floricioiu, D. & Surazakov, A. The evolution of Fedchenko glacier in the Pamir, Tajikistan, during the past eight decades. J. Glaciol. 60, 233–244 (2014).

    Article  Google Scholar 

  32. Björnsson, H. & Pálsson, F. Radio-echo soundings on Icelandic temperate glaciers: history of techniques and findings. Ann. Glaciol. https://doi.org/10.1017/aog.2020.10 (2020).

  33. Dowdeswell, J. A. et al. Form and flow of the Academy of Sciences Ice Cap, Severnaya Zemlya, Russian High Arctic. J. Geophys. Res. Solid Earth https://doi.org/10.1029/2000JB000129 (2002).

  34. Azam, M. F. et al. From balance to imbalance: a shift in the dynamic behaviour of Chhota Shigri glacier, western Himalaya, India. J. Glaciol. 58, 315–324 (2012).

    Article  Google Scholar 

  35. Wagnon, P. et al. Seasonal and annual mass balances of Mera and Pokalde glaciers (Nepal Himalaya) since 2007. Cryosphere 7, 1769–1786 (2013).

    Article  Google Scholar 

  36. Millan, R. et al. Ice thickness and bed elevation of the northern and southern Patagonian icefields. Geophys. Res. Lett. https://doi.org/10.1029/2019GL082485 (2019).

  37. Morlighem, M. et al. Deep glacial troughs and stabilizing ridges unveiled beneath the margins of the Antarctic ice sheet. Nat. Geosci. https://doi.org/10.1038/s41561-019-0510-8 (2019).

  38. Huss, M. & Hock, R. Global-scale hydrological response to future glacier mass loss. Nat. Clim. Change 8, 135–140 (2018).

    Article  Google Scholar 

  39. Soruco, A. et al. Contribution of glacier runoff to water resources of La Paz city, Bolivia (16° S). Ann. Glaciol. 56, 147–154 (2015).

    Article  Google Scholar 

  40. Lutz, A. F., Immerzeel, W. W., Shrestha, A. B. & Bierkens, M. F. P. Consistent increase in High Asia’s runoff due to increasing glacier melt and precipitation. Nat. Clim. Change 4, 587–592 (2014).

    Article  Google Scholar 

  41. Dussaillant, I. et al. Two decades of glacier mass loss along the Andes. Nat. Geosci. 12, 802–808 (2019).

    Article  Google Scholar 

  42. World Imagery (Esri, accessed 19 May 2019); https://www.arcgis.com/home/item.html?id=10df2279f9684e4a9f6a7f08febac2a9

  43. Meier, F. & Post, A. What are glacier surges? Can. J. Earth Sci. 6, 807–817 (1969).

  44. Abrams, M., Crippen, R. & Fujisada, H. ASTER Global Digital Elevation Model (GDEM) and ASTER Global Water Body Dataset (ASTWBD). Remote Sens. 12, 1156 (2020).

  45. TanDEM-X - Digital Elevation Model (DEM) - Global, 90m (German Aerospace Center, 2018); https://doi.org/10.15489/JU28HC7PUI09

  46. Porter, C. et al. ArcticDEM (Polar Geospatial Center, 2018); https://doi.org/10.7910/DVN/OHHUKH

  47. Bamber, J. L., Hardy, R. J. & Joughin, I. An analysis of balance velocities over the Greenland ice sheet and comparison with synthetic aperture radar interferometry. J. Glaciol. 46, 67–74 (2000).

Download references

Acknowledgements

R.M. acknowledges support from a post-doctoral fellowship awarded by the French Centre National d’Etudes Spatiales (CNES). J.M. and A.R. acknowledge support from the CNES MaiSON project and Labex OSUG@2020 (Investissements d’avenir - ANR10 LABX56). M.M. acknowledges support from MEASURES‐3 project (NASA grant 80NSSC18M0083). We gratefully acknowledge CNES, ESA, Copernicus Program, NASA and Deutsches Zentrum für Luft- und Raumfahrt e.V. for providing the observation used in this paper (Landsat 8, ASTER, Sentinel-1 and 2, TanDEM-X, Venµs). We thank the RGI and GlaThiDa, the Service National d’Observation GLACIOCLIM, the worldpop and BFG for the glacier basins, ice thickness, river basins and population data. The computing/storage resources (about 4 MCPU-hours and 100 Tb) used for this work were provided by high-performance clusters from GRICAD (Grenoble Alpes Recherche - Infrastructure de Calcul Intensif et de Données). Maps in Fig. 3 were created using ArcGIS software by Esri. ArcGIS and ArcMap are the intellectual property of Esri and are used herein under license. Copyright © Esri. All rights reserved. For more information about Esri software, please visit www.esri.com.

Author information

Authors and Affiliations

Authors

Contributions

R.M., J.M., A.R. and M.M. conceived and designed the research. R.M. and J.M. performed the experiments. R.M., J.M. and A.R. analysed the data. R.M., J.M., A.R. and M.M. wrote the paper.

Corresponding author

Correspondence to Romain Millan.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Geoscience thanks Leigh Stearns, Adrian Luckman and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Tom Richardson.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–13 and Tables 1–3.

Supplementary Table 4

Median value of the creep parameter A for all processed regions s−1 Pa−3.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Millan, R., Mouginot, J., Rabatel, A. et al. Ice velocity and thickness of the world’s glaciers. Nat. Geosci. 15, 124–129 (2022). https://doi.org/10.1038/s41561-021-00885-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41561-021-00885-z

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing