Glaciers distinct from the Greenland and Antarctic ice sheets cover an area of approximately 706,000 square kilometres globally1, with an estimated total volume of 170,000 cubic kilometres, or 0.4 metres of potential sea-level-rise equivalent2. Retreating and thinning glaciers are icons of climate change3 and affect regional runoff4 as well as global sea level5,6. 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 areas7,8,9,10. For data-scarce regions, these results had to be complemented with estimates based on satellite altimetry and gravimetry11. 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 reported11. The present glacier mass loss is equivalent to the sea-level contribution of the Greenland Ice Sheet12, clearly exceeds the loss from the Antarctic Ice Sheet13, and accounts for 25 to 30 per cent of the total observed sea-level rise14. 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.
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The temporal variabilities for the glaciological clusters as well as the regional and global mass-change results have been deposited in the Zenodo repository (https://doi.org/10.5281/zenodo.1492141). The full sample of glaciological and geodetic observations for individual glaciers is publicly available from the WGMS (https://doi.org/10.5904/wgms-fog-2018-11).
The analytical scripts are available from the authors on request.
RGI Consortium Randolph Glacier Inventory (v.6.0): A Dataset of Global Glacier Outlines. Global Land Ice Measurements from Space, Boulder, Colorado USA (RGI Technical Report, 2017) https://doi.org/10.7265/N5-RGI-60.
Huss, M. & Farinotti, D. Distributed ice thickness and volume of all glaciers around the globe. J. Geophys. Res. 117, F04010 (2012).
Bojinski, S. et al. The concept of essential climate variables in support of climate research, applications, and policy. Bull. Am. Meteorol. Soc. 95, 1431–1443 (2014).
Huss, M. & Hock, R. Global-scale hydrological response to future glacier mass loss. Nat. Clim. Chang. 8, 135–140 (2018).
Marzeion, B., Cogley, J. G., Richter, K. & Parkes, D. Attribution of global glacier mass loss to anthropogenic and natural causes. Science 345, 919–921 (2014).
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).
Cogley, J. G. Geodetic and direct mass-balance measurements: comparison and joint analysis. Ann. Glaciol. 50, 96–100 (2009).
Kaser, G., Cogley, J. G., Dyurgerov, M. B., Meier, M. F. & Ohmura, A. Mass balance of glaciers and ice caps: consensus estimates for 1961–2004. Geophys. Res. Lett. 33, L19501 (2006).
Dyurgerov, M. B. & Meier, M. F. Glaciers and the Changing Earth System: A 2004 Snapshot. Report INSTAAR/OP-58 (Instaar, 2005).
Ohmura, A. in The State of the Planet: Frontiers and Challenges in Geophysics Vol. 150 (eds Sparks, R. S. J. & Hawkesworth, C. J.) 239–257 (American Geophysical Union, 2004).
Gardner, A. S. et al. A reconciled estimate of glacier contributions to sea level rise: 2003 to 2009. Science 340, 852–857 (2013).
Khan, S. A. et al. Greenland ice sheet mass balance: a review. Rep. Prog. Phys. 78, 046801 (2015).
IMBIE. Mass balance of the Antarctic Ice Sheet from 1992 to 2017. Nature 558, 219–222 (2018).
Watson, C. S. et al. Unabated global mean sea-level rise over the satellite altimeter era. Nat. Clim. Chang. 5, 565–568 (2015).
Working Group on Mass-Balance Terminology and Methods of the International Association of Cryosphere Glossary of Glacier Mass Balance and Related Terms (UNESCO Digital Library, 2011) https://unesdoc.unesco.org/ark:/48223/pf0000192525.
World Glacier Monitoring Service (WGMS) Global Glacier Change Bulletin No. 2 (2014–2015) (WGMS, 2017) https://doi.org/10.5904/wgms-fog-2017-10.
Brun, F., Berthier, E., Wagnon, P., Kääb, A. & Treichler, D. A spatially resolved estimate of High Mountain Asia glacier mass balances from 2000 to 2016. Nat. Geosci. 10, 668–673 (2017); correction 11, 543 (2018).
Kääb, A., Treichler, D., Nuth, C. & Berthier, E. Contending estimates of 2003–2008 glacier mass balance over the Pamir–Karakoram–Himalaya. Cryosphere 9, 557–564 (2015).
Mernild, S. H., Lipscomb, W. H., Bahr, D. B., Radić, V. & Zemp, M. Global glacier changes: a revised assessment of committed mass losses and sampling uncertainties. Cryosphere 7, 1565–1577 (2013).
Marzeion, B., Kaser, G., Maussion, F. & Champollion, N. Limited influence of climate change mitigation on short-term glacier mass loss. Nat. Clim. Chang. 8, 305–308 (2018).
Huss, M. & Hock, R. A new model for global glacier change and sea-level rise. Front. Earth Sci. 3, https://doi.org/10.3389/feart.2015.00054 (2015).
Huss, M., Hock, R., Bauder, A. & Funk, M. Conventional versus reference-surface mass balance. J. Glaciol. 58, 278–286 (2012).
Paul, F. The influence of changes in glacier extent and surface elevation on modeled mass balance. Cryosphere 4, 569–581 (2010).
Vaughan, D. G. et al. in Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) (eds Stocker, T. F. et al.) 317–382 (Cambridge Univ. Press, Cambridge, 2013).
Cogley, J. G. Glacier shrinkage across High Mountain Asia. Ann. Glaciol. 57, 41–49 (2016).
Zemp, M. et al. Reanalysing glacier mass balance measurement series. Cryosphere 7, 1227–1245 (2013).
Marzeion, B., Leclercq, P. W., Cogley, J. G. & Jarosch, A. H. Global reconstructions of glacier mass change during the 20th century are consistent. Cryosphere 9, 2399–2404 (2015).
Huss, M. Density assumptions for converting geodetic glacier volume change to mass change. Cryosphere 7, 877–887 (2013).
Fountain, A. G. & Vecchia, A. How many stakes are required to measure the mass balance of a glacier? Geogr. Ann. Ser. A 81, 563–573 (1999).
Lliboutry, L. Multivariate statistical analysis of glacier annual balances. J. Glaciol. 13, 371–392 (1974).
Cox, L. H. & March, R. S. Comparison of geodetic and glaciological mass-balance techniques, Gulkana Glacier, Alaska, U.S.A. J. Glaciol. 50, 363–370 (2004).
Thibert, E., Blanc, R., Vincent, C. & Eckert, N. Glaciological and volumetric mass-balance measurements: error analysis over 51 years for Glacier de Sarennes, French Alps. J. Glaciol. 54, 522–532 (2008).
Huss, M., Bauder, A. & Funk, M. Homogenization of long-term mass-balance time series. Ann. Glaciol. 50, 198–206 (2009).
Andreassen, L. M., Elvehøy, H., Kjøllmoen, B. & Engeset, R. V. Reanalysis of long-term series of glaciological and geodetic mass balance for 10 Norwegian glaciers. Cryosphere 10, 535–552 (2016).
Thomson, L. I., Zemp, M., Copland, L., Cogley, J. G. & Ecclestone, M. A. Comparison of geodetic and glaciological mass budgets for White Glacier, Axel Heiberg Island, Canada. J. Glaciol. 63, 55–66 (2016).
Wang, P., Li, Z., Li, H., Wang, W. & Yao, H. Comparison of glaciological and geodetic mass balance at Urumqi Glacier No. 1, Tian Shan, Central Asia. Global Planet. Change 114, 14–22 (2014).
Basantes-Serrano, R. et al. Slight mass loss revealed by reanalyzing glacier mass-balance observations on Glaciar Antisana 15α (inner tropics) during the 1995–2012 period. J. Glaciol. 62, 124–136 (2016).
Fischer, M., Huss, M. & Hoelzle, M. Surface elevation and mass changes of all Swiss glaciers 1980–2010. Cryosphere 9, 525–540 (2015).
Vijay, S. & Braun, M. Elevation change rates of glaciers in the Lahaul-Spiti (Western Himalaya, India) during 2000–2012 and 2012–2013. Remote Sens. 8, 1038 (2016).
Le Bris, R. & Paul, F. Glacier-specific elevation changes in parts of western Alaska. Ann. Glaciol. 56, 184–192 (2015).
Falaschi, D., Bravo, C., Masiokas, M., Villalba, R. & Rivera, A. First glacier inventory and recent changes in glacier area in the Monte San Lorenzo region (47°S), Southern Patagonian Andes, South America. Arct. Antarct. Alp. Res. 45, 19–28 (2013).
Larsen, C. F., Motyka, R. J., Arendt, A. A., Echelmeyer, K. A. & Geissler, P. E. Glacier changes in southeast Alaska and northwest British Columbia and contribution to sea level rise. J. Geophys. Res. 112, F01007 (2007).
Girod, L., Nuth, C., Kääb, A., McNabb, R. W. & Galland, O. MMASTER: improved ASTER DEMs for elevation change monitoring. Remote Sens. 9, 704 (2017).
Nuth, C. & Kääb, A. Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change. Cryosphere 5, 271–290 (2011).
Shean, D. High Mountain Asia 8-meter DEMs Derived from Cross-track Optical Imagery (v.1.0) (NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDS DAAC), 2017) https://doi.org/10.5067/GSACB044M4PK.
McNabb, R., Nuth, C., Kääb, A. & Girod, L. Sensitivity of geodetic glacier mass balance estimation to DEM void interpolation. Cryosphere 13, 895–910 https://doi.org/10.5194/tc-13-895-2019 (2019).
Korsgaard, N. J. et al. Digital elevation model and orthophotographs of Greenland based on aerial photographs from 1978–1987. Sci. Data 3, 160032 (2016).
Pfeffer, W. T. et al. The Randolph Glacier Inventory: a globally complete inventory of glaciers. J. Glaciol. 60, 537–552 (2014).
GLIMS Glacier Database (GLIMS and National Snow and Ice Data Center (NSIDC), 2005) https://doi.org/10.7265/N5V98602.
Rastner, P. et al. The first complete inventory of the local glaciers and ice caps on Greenland. Cryosphere 6, 1483–1495 (2012).
Huber, J., Cook, A. J., Paul, F. & Zemp, M. A complete glacier inventory of the Antarctic Peninsula based on Landsat 7 images from 2000 to 2002 and other preexisting data sets. Earth Syst. Sci. Data 9, 115–131 (2017).
Fountain, A. G., Basagic, H. J., IV & Niebuhr, S. Glaciers in equilibrium, McMurdo Dry Valleys, Antarctica. J. Glaciol. 62, 976–989 (2016).
Mernild, S. H. et al. Glacier changes in the circumpolar Arctic and sub-Arctic, mid-1980s to late-2000s/2011. Geogr. Tidsskr. J. Geogr. 115, 39–56 (2015).
Hannesdóttir, H., Björnsson, H., Pálsson, F., Aðalgeirsdóttir, G. & Guðmundsson, S. Changes in the southeast Vatnajökull ice cap, Iceland, between ~1890 and 2010. Cryosphere 9, 565–585 (2015).
Khromova, T. et al. Impacts of climate change on the mountain glaciers of Russia. Reg. Environ. Change 18, 1–19 (2019).
Global Terrestrial Network for Glaciers GTN-G Glacier Regions (GTN-G, 2017) https://doi.org/10.5904/gtng-glacreg-2017-07.
Radić, V. & Hock, R. Regional and global volumes of glaciers derived from statistical upscaling of glacier inventory data. J. Geophys. Res. 115, F001373 (2010).
Dyurgerov, M. B. Glacier Mass Balance and Regime: Data of Measurements and Analysis. Occasional Paper No. 55 (Institute of Arctic and Alpine Research, Univ. Colorado, 2002).
Letréguilly, A. & Reynaud, L. Space and time distribution of glacier mass-balance in the Northern Hemisphere. Arct. Alp. Res. 22, 43–50 (1990).
Cogley, J. G. & Adams, W. P. Mass balance of glaciers other than the ice sheets. J. Glaciol. 44, 315–325 (1998).
Krzywinski, M. & Altman, N. Analysis of variance and blocking. Nat. Methods 11, 699–700 (2014).
Eckert, N., Baya, H., Thibert, E. & Vincent, C. Extracting the temporal signal from a winter and summer mass-balance series: application to a six-decade record at Glacier de Sarennes, French Alps. J. Glaciol. 57, 134–150 (2011).
Puga, J. L., Krzywinski, M. & Altman, N. Bayesian statistics. Nat. Methods 12, 377–378 (2015); corrigendum 12, 1098 (2015).
Cogley, J. G. Area of the ocean. Mar. Geod. 35, 379–388 (2012).
GCOS The Global Observing System for Climate: Implementation Needs (World Meteorological Organization, 2016).
We thank the national correspondents and principal investigators of the WGMS network as well as the Global Land Ice Measurements from Space (GLIMS) and RGI communities for free and open access to their data sets. We thank B. Armstrong for polishing the language. Arctic digital elevation model (DEM) strips were provided by the Polar Geospatial Center under National Science Foundation (NSF) Office of Polar Programs (OPP) awards 1043681, 1559691 and 1542736. This study was enabled by support from the Federal Office of Meteorology and Climatology MeteoSwiss within the framework of the Global Climate Observing System (GCOS) Switzerland, the Cryospheric Commission of the Swiss Academy of Science, the Copernicus Climate Change Service (C3S) implemented by the European Centre for Medium-range Weather Forecasts (ECMWF) on behalf of the European Commission, the European Space Agency (ESA) projects Glaciers_cci (4000109873/14/I-NB) and Sea-Level Budget Closure CCI (4000119910/17/I-NB), and Irstea Grenoble as part of LabEx OSUG@2020.
Nature thanks A. Rowan and the other anonymous reviewer(s) for their contribution to the peer review of this work.
The authors declare no competing interests.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
a–s, For each of the 19 first-order regions, glacier hypsometry from RGI 6.0 (blue)1 is overlaid with glacier hypsometry of both the geodetic (grey) and the glaciological (black) samples used here. Values for the total number (N) and total area (S) of glaciers are given for each region, together with the relative coverage of both the glaciological and the geodetic samples. Plots are ordered according to the region numbers in RGI 6.0 (see Table 1); m a.s.l., metres above sea level.
a, b, Cumulative mass changes in m w.e. (a) and Gt (b) are shown for the 19 regions. Specific mass changes (a) indicate the observed glacier thickness changes. Total glacier mass changes (b, left vertical axis) correspond to the regional contributions to global mean sea-level rise (b, right vertical axis). As an example, cumulative specific mass changes were most negative in the Southern Andes with an average regional glacier thickness change of approximately −40 m w.e. (a), resulting in a cumulative mass change of −1,200 Gt (b). Glaciers in Alaska experience less negative specific mass changes (a) but contribute much more to global sea-level rise (b) because of the larger regional glacier area.
Shown are relative contributions (%) of the different sources to the overall regional error bars (Fig. 3b). Taking Alaska as an example, the overall error estimate is dominated by the glaciological and the geodetic errors with contributions of 47% and 37%, respectively, whereas the errors for extrapolation (10%), glacier area (5%), and second-order crossed uncertainties (less than 1%) are of less importance. A special case is Central Europe: the large number of high-quality observations from airborne surveys comes with reported geodetic uncertainties that are one order of magnitude smaller than the spaceborne estimates in other regions. As a result, the overall error bars are much smaller (Fig. 3) and the relative contributions from other error sources become larger. In the Southern Andes, the relative contribution of the geodetic error is reduced by the large sample size, while glaciological and interpolation errors feature large absolute values.
a, b, Annual specific mass-change rates in m w.e. yr−1 (a) and in Gt yr−1 (b), as shown in Fig. 3 but for the period 2003–2009. The estimates and related error bars (corresponding to 95% confidence intervals) found here are shown in blue. The results from IPCC AR511,24 are shown in red, differentiating between those based on glaciological and geodetic observations (crosses) and those based on ICESat and/or the Gravity Recovery and Climate Experiment (GRACE; diamonds). Global mass change rates are −260 ± 28 Gt yr−1 and −307 ± 148 Gt yr−1, as estimated by IPCC AR511,24 and this study, respectively.
Extended Data Fig. 6 Temporal variability in the glaciological mass balance for Alaska and British Columbia, 1961–2016.
a, b, Annual (a; m w.e. yr−1) and cumulative (b; m w.e.) values for the cluster’s smooth trend (g(t); blue lines) and annual deviations (g(t) + z(t); orange lines), as reconstructed from the variance decomposition (see Methods, equations (1) and (2)) on the basis of glaciological measurements from 19 glaciers (Extended Data Table 2, cluster C01).
Extended Data Fig. 7 Calibration of temporal variability from glaciological sample to geodetic values of individual glaciers.
Schematic representation of the approach to calibrate the cumulative temporal variability (black line; m w.e.), as derived from the variance decomposition (see Extended Data Fig. 6), to geodetic values of individual glaciers (blue and purple lines; m w.e.). For Glacier 1 and Glacier 2, the mean annual deviations between the glaciological balance of the cluster and the glacier-individual geodetic balances were 0.1 m w.e. yr−1 and −0.2 m w.e. yr−1, respectively, over corresponding survey periods between t0 and t1 (see Methods, equation (3)).
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Zemp, M., Huss, M., Thibert, E. et al. Global glacier mass changes and their contributions to sea-level rise from 1961 to 2016. Nature 568, 382–386 (2019). https://doi.org/10.1038/s41586-019-1071-0
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