Uncertainty Quantification for Large-Scale Ice Sheet Modeling

This report summarizes our work to develop advanced forward and inverse solvers and uncertainty quantification capabilities for a nonlinear 3D full Stokes continental-scale ice sheet flow model. The components include: (1) forward solver: a new state-of-the-art parallel adaptive scalable high-order-...

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Main Author: Ghattas, Omar
Language:unknown
Published: 2016
Subjects:
97 MATHEMATICS AND COMPUTING
58 GEOSCIENCES
Ice Sheet
Online Access:http://www.osti.gov/servlets/purl/1237006
https://www.osti.gov/biblio/1237006
https://doi.org/10.2172/1237006
id ftosti:oai:osti.gov:1237006
record_format openpolar
spelling ftosti:oai:osti.gov:1237006 2023-07-30T04:04:10+02:00 Uncertainty Quantification for Large-Scale Ice Sheet Modeling Ghattas, Omar 2016-03-15 application/pdf http://www.osti.gov/servlets/purl/1237006 https://www.osti.gov/biblio/1237006 https://doi.org/10.2172/1237006 unknown http://www.osti.gov/servlets/purl/1237006 https://www.osti.gov/biblio/1237006 https://doi.org/10.2172/1237006 doi:10.2172/1237006 97 MATHEMATICS AND COMPUTING 58 GEOSCIENCES 2016 ftosti https://doi.org/10.2172/1237006 2023-07-11T09:04:45Z This report summarizes our work to develop advanced forward and inverse solvers and uncertainty quantification capabilities for a nonlinear 3D full Stokes continental-scale ice sheet flow model. The components include: (1) forward solver: a new state-of-the-art parallel adaptive scalable high-order-accurate mass-conservative Newton-based 3D nonlinear full Stokes ice sheet flow simulator; (2) inverse solver: a new adjoint-based inexact Newton method for solution of deterministic inverse problems governed by the above 3D nonlinear full Stokes ice flow model; and (3) uncertainty quantification: a novel Hessian-based Bayesian method for quantifying uncertainties in the inverse ice sheet flow solution and propagating them forward into predictions of quantities of interest such as ice mass flux to the ocean. Other/Unknown Material Ice Sheet SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy)
institution Open Polar
collection SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy)
op_collection_id ftosti
language unknown
topic 97 MATHEMATICS AND COMPUTING
58 GEOSCIENCES
spellingShingle 97 MATHEMATICS AND COMPUTING
58 GEOSCIENCES
Ghattas, Omar
Uncertainty Quantification for Large-Scale Ice Sheet Modeling
topic_facet 97 MATHEMATICS AND COMPUTING
58 GEOSCIENCES
description This report summarizes our work to develop advanced forward and inverse solvers and uncertainty quantification capabilities for a nonlinear 3D full Stokes continental-scale ice sheet flow model. The components include: (1) forward solver: a new state-of-the-art parallel adaptive scalable high-order-accurate mass-conservative Newton-based 3D nonlinear full Stokes ice sheet flow simulator; (2) inverse solver: a new adjoint-based inexact Newton method for solution of deterministic inverse problems governed by the above 3D nonlinear full Stokes ice flow model; and (3) uncertainty quantification: a novel Hessian-based Bayesian method for quantifying uncertainties in the inverse ice sheet flow solution and propagating them forward into predictions of quantities of interest such as ice mass flux to the ocean.
author Ghattas, Omar
author_facet Ghattas, Omar
author_sort Ghattas, Omar
title Uncertainty Quantification for Large-Scale Ice Sheet Modeling
title_short Uncertainty Quantification for Large-Scale Ice Sheet Modeling
title_full Uncertainty Quantification for Large-Scale Ice Sheet Modeling
title_fullStr Uncertainty Quantification for Large-Scale Ice Sheet Modeling
title_full_unstemmed Uncertainty Quantification for Large-Scale Ice Sheet Modeling
title_sort uncertainty quantification for large-scale ice sheet modeling
publishDate 2016
url http://www.osti.gov/servlets/purl/1237006
https://www.osti.gov/biblio/1237006
https://doi.org/10.2172/1237006
genre Ice Sheet
genre_facet Ice Sheet
op_relation http://www.osti.gov/servlets/purl/1237006
https://www.osti.gov/biblio/1237006
https://doi.org/10.2172/1237006
doi:10.2172/1237006
op_doi https://doi.org/10.2172/1237006
_version_ 1772815394597240832

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