Versions Compared

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.

                    

Page Properties


Poster Title

Probabilistic Sea-Level Projections from Ice Sheet and Earth System Models 2: Ice Sheet Model Optimization, V&V, and UQ

AuthorsKate Evans (Unlicensed), jdjakem@sandia.gov (Unlicensed), Joseph H. Kennedy (Unlicensed), Esmond G. Ng (Unlicensed), Mauro Perego, Stephen Price, Georg Stadler (Unlicensed), Irina Tezaur
AuthorKate Evans (Unlicensed)
Session TypeE3SM Session
Session IDE4
Submission TypeposterPoster
GroupNGD/Ecosystem: SciDAC ProSPect
ExperimentCryosphere (v2-v4)
Poster Link




Abstract

The contribution to sea-level rise from ice sheets is increasing. Observed acceleration in the rate of ice loss from the Greenland and Antarctic ice sheets is a concern, particularly for the West Antarctic Ice Sheet, which is largely grounded below sea level. This geometric configuration makes it Antarctica susceptible to a dynamic instability that could result in a catastrophic collapse of one or more ice shelves as a result of relatively small perturbations at the ice sheet's margins. While Ice ice sheet models have become significantly more advanced over the past decade, they are still incomplete in many ways, and thus lead to large uncertainties when applied towards ; hence, there are large uncertainties in these models' projections of future sea-level rise. The goal of the ProSPect SciDAC partnership is to address current limitations to of DOE ice sheet and Earth system models that limit their use for making accurate sea-level projections. These include inadequate or missing model physics, incomplete couplings between models, and deficiencies in methods for model initialization, validation, and uncertainty quantification (UQ). This poster focuses on recent ProSPect efforts towards: (1) improved model initialization using PDE-constrained optimization methods constrained by the ice sheet flow model and observations, (2) Verification and Validation through ongoing development of the Land Ice V&V toolkit (LIVVkit), and (3) and the development and initial applications deployment of an end-to-end Uncertainty Quantification framework using UQ framework consisting of the solution of an approximate Bayesian inference problem followed by forward simulations of posterior samples.

...