Uncertainty Quantification for Large-Scale Ice Sheet Modeling

GSTDTAP > 地球科学

DOI	10.2172/1237006
报告编号	DOE-UTAUSTIN--0002710
来源ID	OSTI ID: 1237006
	Uncertainty Quantification for Large-Scale Ice Sheet Modeling
	Ghattas, Omar
	2016-02-05
出版年	2016
页数	11
语种	英语
国家	美国
领域	地球科学
英文摘要	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.
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来源平台	US Department of Energy (DOE)
引用统计
文献类型	科技报告
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/7410
专题	地球科学
推荐引用方式 GB/T 7714	Ghattas, Omar. Uncertainty Quantification for Large-Scale Ice Sheet Modeling,2016.