Yucheng Lin, Xuebin Zhang, Nicholas R. Golledge, Robert E. Kopp, John A. Church, Yi Jin, Chen Zhao, Chris R. Stokes
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引用次数: 0
Abstract
The Antarctic Ice Sheet is the largest source of uncertainty in sea-level rise projections, with uncertainties propagating through emissions scenarios, atmosphere–ocean general circulation models, ice-sheet dynamics and sea-level physics. In ice-sheet model intercomparison exercises, these uncertainties—typically attributed to intermodel differences—stem from modelling choices that may bias ensembles towards commonly adopted approaches regardless of observational consistency. Here we quantify how each individual physical assumption cascades into projection uncertainty using a machine-learning emulation framework, which also enables Bayesian calibration against satellite observations to reduce projection bias. Our results suggest it is very likely (≥0.92 probability) that the Antarctic Ice Sheet is committed to twenty-first-century mass loss, even under aggressive emissions-reduction scenarios. Higher emissions drive greater Antarctic mass loss by 2100 (≥0.89 probability), directly elevating near-term coastal risks. Under very high-emissions scenarios, we identify cascading mechanisms that could produce up to 25.4 cm of sea-level rise by 2100 (95th percentile; median = 15.7 cm) while remaining consistent with satellite observations. Effective management of these risks to densely populated coastal communities requires rapid emissions reductions and improved constraints on climate model selection, sliding laws and ice-shelf melt parameterizations.
期刊介绍:
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