Prediction under uncertainty : from models for marine-terminating glaciers to Bayesian computation

Thesis: Ph. D. in Computational Science and Engineering, Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2018 Cataloged from PDF version of thesis. Includes bibliographical references (pages 255-266). The polar ice sheets have enormous potential impact on future gl...

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Bibliographic Details
Main Author: Davis, Andrew D.(Andrew Donaldson)
Other Authors: Youssef Marzouk and Patrick Heimbach., Massachusetts Institute of Technology. Department of Aeronautics and Astronautics., Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Format: Thesis
Language:English
Published: Massachusetts Institute of Technology 2018
Subjects:
Online Access:https://hdl.handle.net/1721.1/121812
Description
Summary:Thesis: Ph. D. in Computational Science and Engineering, Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2018 Cataloged from PDF version of thesis. Includes bibliographical references (pages 255-266). The polar ice sheets have enormous potential impact on future global mean sea level rise. Recent observations suggest they are losing mass to the ocean at an accelerated rate. Skillful prediction of the ice sheets' future mass loss remains difficult, however; observations of key variables are insufficient and physical processes are poorly understood. Even when a relatively accurate dynamical model is available, computational limitations make it difficult to characterize uncertainties associated with the model's predictions. To address this prediction challenge, this thesis presents complementary developments in glaciology and in Bayesian computation. In particular, (i) we develop new models of marine-terminating glaciers whose dynamics are controlled by an extended set of physical processes and geometric constraints; and (ii) we develop new sampling algorithms to efficiently characterize selected marginals of a high-dimensional probability distribution describing uncertain parameters. The latter algorithms have broader utility in Bayesian modeling and inference with computationally intensive models. We begin by studying laterally confined ice streams that terminate in the ocean, where they may form floating ice shelves. Such marine-terminating outlet glaciers are the main conduits by which Greenland and Antarctica drain their ice mass into the ocean. Ice shelves play an important role in buttressing the grounded inland ice. The seaward ice flow is typically accompanied by acceleration and thinning. Increased thinning eventually leads to flotation of the ice supported by buoyant forces from the ocean. The transition region from grounded to floating ice is referred to as the grounding line (or zone), and the mass transport across the grounding line as the output flux. ...