Large ensemble modeling of the last deglacial retreat of the West Antarctic Ice Sheet: Comparison of simple and advanced statistical techniques

David Pollard, Won Chang, Murali Haran, Patrick Applegate, Robert DeConto

Research output: Contribution to journalArticle

36 Scopus citations

Abstract

A 3-D hybrid ice-sheet model is applied to the last deglacial retreat of the West Antarctic Ice Sheet over the last ∼ 20000yr. 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.

Original languageEnglish (US)
Pages (from-to)1697-1723
Number of pages27
JournalGeoscientific Model Development
Volume9
Issue number5
DOIs
StatePublished - May 4 2016

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Earth and Planetary Sciences(all)

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