Calibrated Mass Loss Predictions for the Greenland Ice Sheet

A. Aschwanden, D. J. Brinkerhoff

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11 Scopus citations


The potential contribution of ice sheets remains the largest source of uncertainty in predicting sea-level due to the limited predictive skill of numerical ice sheet models, yet effective planning necessitates that these predictions are credible and accompanied by a defensible assessment of uncertainty. While the use of large ensembles of simulations allows probabilistic assessments, there is no guarantee that these simulations are aligned with observations. Here, we present a probabilistic prediction of 21st century mass loss from the Greenland Ice Sheet calibrated with observations of surface speeds and mass change using a novel two-stage surrogate-based approach. Our results suggest a sea-level contribution ranging from 4 to 30 cm at the year 2100, proviso the assumption that our chosen ice sheet model’s physics represent reality.

Original languageEnglish
Article numbere2022GL099058
JournalGeophysical Research Letters
Issue number19
StatePublished - Oct 16 2022


  • Bayesian calibration
  • Greenland
  • data assimilation
  • ice sheet modeling
  • sea level rise
  • uncertainty quantification


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