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A 3-D hybrid ice-sheet model is applied to the last deglacial retreat of the West Antarctic Ice Sheet over the last  ∼  20 000 yr. A large ensemble of 625 model runs is used to calibrate the model to modern and geologic data, including reconstructed grounding lines, relative sea-level records, elevation–age data and uplift rates, with an aggregate score computed for each run that measures overall model–data misfit. Two types of statistical methods are used to analyze the large-ensemble results: simple averaging weighted by the aggregate score, and more advanced Bayesian techniques involving Gaussian process-based emulation and calibration, and Markov chain Monte Carlo. The analyses provide sea-level-rise envelopes with well-defined parametric uncertainty bounds, but the simple averaging method only provides robust results with full-factorial parameter sampling in the large ensemble. Results for best-fit parameter ranges and envelopes of equivalent sea-level rise with the simple averaging method agree well with the more advanced techniques. Best-fit parameter ranges confirm earlier values expected from prior model tuning, including large basal sliding coefficients on modern ocean beds.







Creative Commons License

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.


This work was supported in part by the following grants from the National Science Foundation: NSF-DMS-1418090 and the Network for Sustainable Climate Risk Management (SCRiM) under NSF cooperative agreement GEO1240507 (DP, MH); PLIOMAX OCE-1202632, OPP-1341394, and ANT-1443190 (DP); NSF Statistical Methods in the Atmospheric Sciences Network 1106862, 1106974, and 1107046 (WC).