Calibrating an Ice Sheet Model Using High-Dimensional Binary Spatial Data

Rapid retreat of ice in the Amundsen Sea sector of West Antarctica may cause drastic sea level rise, posing significant risks to populations in low-lying coastal regions. Calibration of computer models representing the behavior of the West Antarctic Ice Sheet is key for informative projections of fu...

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Main Authors: Won Chang, Murali Haran, Patrick Applegate, David Pollard
Format: Article in Journal/Newspaper
Language:unknown
Subjects:
Online Access:http://hdl.handle.net/10.1080/01621459.2015.1108199
id ftrepec:oai:RePEc:taf:jnlasa:v:111:y:2016:i:513:p:57-72
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spelling ftrepec:oai:RePEc:taf:jnlasa:v:111:y:2016:i:513:p:57-72 2023-05-15T13:23:51+02:00 Calibrating an Ice Sheet Model Using High-Dimensional Binary Spatial Data Won Chang Murali Haran Patrick Applegate David Pollard http://hdl.handle.net/10.1080/01621459.2015.1108199 unknown http://hdl.handle.net/10.1080/01621459.2015.1108199 article ftrepec 2020-12-04T13:33:11Z Rapid retreat of ice in the Amundsen Sea sector of West Antarctica may cause drastic sea level rise, posing significant risks to populations in low-lying coastal regions. Calibration of computer models representing the behavior of the West Antarctic Ice Sheet is key for informative projections of future sea level rise. However, both the relevant observations and the model output are high-dimensional binary spatial data; existing computer model calibration methods are unable to handle such data. Here we present a novel calibration method for computer models whose output is in the form of binary spatial data. To mitigate the computational and inferential challenges posed by our approach, we apply a generalized principal component based dimension reduction method. To demonstrate the utility of our method, we calibrate the PSU3D-ICE model by comparing the output from a 499-member perturbed-parameter ensemble with observations from the Amundsen Sea sector of the ice sheet. Our methods help rigorously characterize the parameter uncertainty even in the presence of systematic data-model discrepancies and dependence in the errors. Our method also helps inform environmental risk analyses by contributing to improved projections of sea level rise from the ice sheets. Supplementary materials for this article are available online. Article in Journal/Newspaper Amundsen Sea Antarc* Antarctic Antarctica Ice Sheet West Antarctica RePEc (Research Papers in Economics) Amundsen Sea Antarctic West Antarctic Ice Sheet West Antarctica
institution Open Polar
collection RePEc (Research Papers in Economics)
op_collection_id ftrepec
language unknown
description Rapid retreat of ice in the Amundsen Sea sector of West Antarctica may cause drastic sea level rise, posing significant risks to populations in low-lying coastal regions. Calibration of computer models representing the behavior of the West Antarctic Ice Sheet is key for informative projections of future sea level rise. However, both the relevant observations and the model output are high-dimensional binary spatial data; existing computer model calibration methods are unable to handle such data. Here we present a novel calibration method for computer models whose output is in the form of binary spatial data. To mitigate the computational and inferential challenges posed by our approach, we apply a generalized principal component based dimension reduction method. To demonstrate the utility of our method, we calibrate the PSU3D-ICE model by comparing the output from a 499-member perturbed-parameter ensemble with observations from the Amundsen Sea sector of the ice sheet. Our methods help rigorously characterize the parameter uncertainty even in the presence of systematic data-model discrepancies and dependence in the errors. Our method also helps inform environmental risk analyses by contributing to improved projections of sea level rise from the ice sheets. Supplementary materials for this article are available online.
format Article in Journal/Newspaper
author Won Chang
Murali Haran
Patrick Applegate
David Pollard
spellingShingle Won Chang
Murali Haran
Patrick Applegate
David Pollard
Calibrating an Ice Sheet Model Using High-Dimensional Binary Spatial Data
author_facet Won Chang
Murali Haran
Patrick Applegate
David Pollard
author_sort Won Chang
title Calibrating an Ice Sheet Model Using High-Dimensional Binary Spatial Data
title_short Calibrating an Ice Sheet Model Using High-Dimensional Binary Spatial Data
title_full Calibrating an Ice Sheet Model Using High-Dimensional Binary Spatial Data
title_fullStr Calibrating an Ice Sheet Model Using High-Dimensional Binary Spatial Data
title_full_unstemmed Calibrating an Ice Sheet Model Using High-Dimensional Binary Spatial Data
title_sort calibrating an ice sheet model using high-dimensional binary spatial data
url http://hdl.handle.net/10.1080/01621459.2015.1108199
geographic Amundsen Sea
Antarctic
West Antarctic Ice Sheet
West Antarctica
geographic_facet Amundsen Sea
Antarctic
West Antarctic Ice Sheet
West Antarctica
genre Amundsen Sea
Antarc*
Antarctic
Antarctica
Ice Sheet
West Antarctica
genre_facet Amundsen Sea
Antarc*
Antarctic
Antarctica
Ice Sheet
West Antarctica
op_relation http://hdl.handle.net/10.1080/01621459.2015.1108199
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