Recently, the Greenland Ice Sheet (GrIS) has become the main source of barystatic sea-level rise1,2. The increase in the GrIS melt is linked to anticyclonic circulation anomalies, a reduction in cloud cover and enhanced warm-air advection3,4,5,6,7. The Climate Model Intercomparison Project fifth phase (CMIP5) General Circulation Models (GCMs) do not capture recent circulation dynamics; therefore, regional climate models (RCMs) driven by GCMs still show significant uncertainties in future GrIS sea-level contribution, even within one emission scenario5,8,9,10. Here, we use the RCM Modèle Atmosphèrique Règional to show that the modelled cloud water phase is the main source of disagreement among future GrIS melt projections. We show that, in the current climate, anticyclonic circulation results in more melting than under a neutral-circulation regime. However, we find that the GrIS longwave cloud radiative effect is extremely sensitive to the modelled cloud liquid-water path, which explains melt anomalies of +378 Gt yr–1 (+1.04 mm yr–1 global sea level equivalent) in a +2 °C-warmer climate with a neutral-circulation regime (equivalent to 21% more melt than under anticyclonic circulation). The discrepancies between modelled cloud properties within a high-emission scenario introduce larger uncertainties in projected melt volumes than the difference in melt between low- and high-emission scenarios11.
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The monthly means from 1980 to 2100 of all three MAR RCP 8.5 simulations used in this study are available via ftp://ftp.climato.be/fettweis/MARv3.9/Greenland/. If daily outputs are required, they can be requested from X.F. (firstname.lastname@example.org) and S.H.
All the code used for the analysis in this study is available upon request from the corresponding author.
The authors declare no competing interests.
Peer review information: Nature Climate Change thanks Ruth Mottram, Matthew Shupe and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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This work was supported by the National Environment Research Council (grant no. ME/M021025/1) and received funding from the European Research Council under the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 694188. This work was also supported by the Fonds de la Recherche Scientifique (FNRS) and the Fonds Wetenschappelijk Onderzoek-Vlaanderen (FWO) under the EOS Project n° O0100718F. For the MAR simulations, computational resources were provided by the Consortium des Equipements de Calcul Intensif, funded by the Fonds de la Recherche Scientifique de Belgique (F.R.S.-FNRS) under grant no. 2.5020.11, and the Tier-1 supercomputer (Zenobel) of the Fèdèration Wallonie-Buxelles, and infrastructure was funded by the Walloon Region under grant agreement no. 1117545. X.F. is a research associate of the F.R.S.-FNRS. S.H. would like to thank M. McCrystall for valuable discussions on the topic.
Supplementary Tables 1 and 2, and Supplementary Figs. 1 and 2.