Projections of changes in Antarctic Ice Sheet (AIS) surface mass balance indicate a negative contribution to sea level because of the expected increase in precipitation due to the higher moisture holding capacity of warmer air1. Observations over the past decades, however, are unable to constrain the relation between temperature and accumulation changes because both are dominated by strong natural variability2,3,4,5. Here we derive a consistent continental-scale increase in accumulation of approximately 5 ± 1% K−1, through the assessment of ice-core data (spanning the large temperature change during the last deglaciation, 21,000 to 10,000 years ago), in combination with palaeo-simulations, future projections by 35 general circulation models (GCMs), and one high-resolution future simulation. The ice-core data and modelling results for the last deglaciation agree, showing uniform local sensitivities of ∼6% K−1. The palaeo-simulation allows for a continental-scale aggregation of accumulation changes reaching 4.3% K−1. Despite the different timescales, these sensitivities agree with the multi-model mean of 6.1 ± 2.6% K−1 (GCM projections) and the continental-scale sensitivity of 4.9% K−1 (high-resolution future simulation). Because some of the mass gain of the AIS is offset by dynamical losses induced by accumulation6,7, we provide a response function allowing projections of sea-level fall in terms of continental-scale accumulation changes that compete with surface melting and dynamical losses induced by other mechanisms6,8,9.
Access optionsAccess options
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Subscribe to Journal
Get full journal access for 1 year
only $16.58 per issue
All prices are NET prices.
VAT will be added later in the checkout.
The authors thank B. Lemieux-Dudon for providing Antarctic ice-core accumulation rate data. The authors acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for the Coupled Model Intercomparison Project, and thank the climate modelling groups for producing and making available their model output. P.U.C. was supported by the US NSF Antarctic Glaciology Program (grant number ANT-1043517). This research used resources of the Oak Ridge Leadership Computing Facility, located in the National Center for Computational Sciences at Oak Ridge National Laboratory, which is supported by the Office of Science of the Department of Energy under contract DE-AC05-00OR22725. F.H. is supported by the US NSF (AGS-1203430) and the US NOAA Climate and Global Change Postdoctoral Fellowship program. The research was supported by the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety, Germany (11_II_093_Global_A_SIDS and LDCs). S.R.M.L. and M.R.v.d.B. acknowledge support from the Netherlands Polar Program of the Netherlands Organization for Scientific Research, section Earth and Life Sciences (NWO/ALW/NPP) and the Ice2Sea project, funded by the European Commission 7th Framework Programme through grant number 226375.