Abstract
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 language | English |
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Article number | e2022GL099058 |
Journal | Geophysical Research Letters |
Volume | 49 |
Issue number | 19 |
DOIs | |
State | Published - Oct 16 2022 |
Keywords
- Bayesian calibration
- Greenland
- data assimilation
- ice sheet modeling
- sea level rise
- uncertainty quantification