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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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
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author Davis, Andrew D.(Andrew Donaldson)
author2 Youssef Marzouk and Patrick Heimbach.
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics.
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
author_facet Davis, Andrew D.(Andrew Donaldson)
author_sort Davis, Andrew D.(Andrew Donaldson)
collection DSpace@MIT (Massachusetts Institute of Technology)
description 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. ...
format Thesis
genre Antarc*
Antarctica
Greenland
Ice Shelves
genre_facet Antarc*
Antarctica
Greenland
Ice Shelves
geographic Greenland
geographic_facet Greenland
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language English
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op_relation https://hdl.handle.net/1721.1/121812
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op_rights MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
publishDate 2018
publisher Massachusetts Institute of Technology
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spelling ftmit:oai:dspace.mit.edu:1721.1/121812 2025-04-20T14:23:42+00:00 Prediction under uncertainty : from models for marine-terminating glaciers to Bayesian computation Davis, Andrew D.(Andrew Donaldson) Youssef Marzouk and Patrick Heimbach. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics 2018 266 pages application/pdf https://hdl.handle.net/1721.1/121812 eng eng Massachusetts Institute of Technology https://hdl.handle.net/1721.1/121812 1103712369 MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 Aeronautics and Astronautics Thesis 2018 ftmit 2025-03-21T06:47:43Z 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. ... Thesis Antarc* Antarctica Greenland Ice Shelves DSpace@MIT (Massachusetts Institute of Technology) Greenland
spellingShingle Aeronautics and Astronautics
Davis, Andrew D.(Andrew Donaldson)
Prediction under uncertainty : from models for marine-terminating glaciers to Bayesian computation
title Prediction under uncertainty : from models for marine-terminating glaciers to Bayesian computation
title_full Prediction under uncertainty : from models for marine-terminating glaciers to Bayesian computation
title_fullStr Prediction under uncertainty : from models for marine-terminating glaciers to Bayesian computation
title_full_unstemmed Prediction under uncertainty : from models for marine-terminating glaciers to Bayesian computation
title_short Prediction under uncertainty : from models for marine-terminating glaciers to Bayesian computation
title_sort prediction under uncertainty : from models for marine-terminating glaciers to bayesian computation
topic Aeronautics and Astronautics
topic_facet Aeronautics and Astronautics
url https://hdl.handle.net/1721.1/121812