The Greenland ice sheet (GrIS) is a growing contributor to global sea-level rise1, with recent ice mass loss dominated by surface meltwater runoff2,3. Satellite observations reveal positive trends in GrIS surface melt extent4, but melt variability, intensity and runoff remain uncertain before the satellite era. Here we present the first continuous, multi-century and observationally constrained record of GrIS surface melt intensity and runoff, revealing that the magnitude of recent GrIS melting is exceptional over at least the last 350 years. We develop this record through stratigraphic analysis of central west Greenland ice cores, and demonstrate that measurements of refrozen melt layers in percolation zone ice cores can be used to quantifiably, and reproducibly, reconstruct past melt rates. We show significant (P < 0.01) and spatially extensive correlations between these ice-core-derived melt records and modelled melt rates5,6 and satellite-derived melt duration4 across Greenland more broadly, enabling the reconstruction of past ice-sheet-scale surface melt intensity and runoff. We find that the initiation of increases in GrIS melting closely follow the onset of industrial-era Arctic warming in the mid-1800s, but that the magnitude of GrIS melting has only recently emerged beyond the range of natural variability. Owing to a nonlinear response of surface melting to increasing summer air temperatures, continued atmospheric warming will lead to rapid increases in GrIS runoff and sea-level contributions.
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Ice-core melt records, the derived runoff reconstructions, and other records from cores NU, GC and GW are available via the NSF Arctic Data Center (http://arcticdata.io) and from the corresponding author upon request. Additionally, source data for Figs. 2, 4 are provided in the online version of this paper. RACMO2 model outputs5 as well as downscaled 1-km surface mass balance data are available from B.P.Y.N. and M.R.v.d.B. upon request. MAR model outputs6 are available from X.F. upon request. Greenland air-temperature data51 are available from http://www.dmi.dk/laer-om/generelt/dmi-publikationer/tekniske-rapporter/. Sea-ice data29,30 are available from https://nsidc.org/data/g10010and https://www.nature.com/articles/nature10581. Arctic air-temperature reconstruction data21 are available from https://www.nature.com/articles/nature19082. Satellite melt data4,41 are available from http://www.cryocity.org.
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Funding was provided by US National Science Foundation (NSF) awards OPP-1205196 and PLR-1418256 to S.B.D., ARC-1205062 to B.E.S. and OPP-1205008 to M.J.E. L.D.T. acknowledges institutional support from Rowan University and the Doherty Postdoctoral Scholarship at Woods Hole Oceanographic Institution. M.B.O. acknowledges support from the Department of Defense Office of Naval Research, National Defense Science and Engineering Graduate (NDSEG) Fellowship, 32 CFR 168a. Collection, analysis and interpretation of core D5 was supported by NSF grant 0352511 to J.R.McC. B.P.Y.N. and M.R.v.d.B. acknowledge support from the Polar Program of the Netherlands Organization for Scientific Research (NWO/NPP) and the Netherlands Earth System Science Centre (NESSC). For running the MAR model, computational resources have been provided by the Consortium des Équipements de Calcul Intensif (CÉCI), funded by the Fonds de la Recherche Scientifique de Belgique (FRS–FNRS) under grant number 2.5020.11 and the Tier-1 supercomputer (Zenobe) of the Fédération Wallonie Bruxelles infrastructure funded by the Walloon Region under grant agreement number 1117545. We thank M. Waszkiewicz and IDPO/IDDO for ice core drilling support. We thank the NSF Ice Core Facility (formerly NICL), A. York, M. Bingham, M. Hatch, S. Zarfos, Z. Li, and Milton Academy students for ice core sampling and processing support. We thank R. Banta for help with the D5 core, and A. Arienzo and N. Chellman for help in analysing the NU core. We thank M. Tedesco for providing the satellite melt duration data used in Fig. 3d. Maps in Figs. 1a, 3 and Extended Data Figs. 3, 4 were created with the NCAR Command Language (https://www.ncl.ucar.edu), and maps in Fig. 1b and Extended Data Fig. 6 were created with Esri ArcGIS. We acknowledge the use of Rapid Response imagery in Fig. 1b from the Land, Atmosphere Near real-time Capability for EOS (LANCE) system operated by the NASA/GSFC/Earth Science Data and Information System (ESDIS) with funding provided by NASA/HQ.
Nature thanks J. Briner and B. Vinther for their contribution to the peer review of this work.