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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ftdatacite:10.48550/arxiv.1501.01937 2023-05-15T13:23:51+02:00 Calibrating an ice sheet model using high-dimensional binary spatial data Chang, Won Haran, Murali Applegate, Patrick Pollard, David 2015 https://dx.doi.org/10.48550/arxiv.1501.01937 https://arxiv.org/abs/1501.01937 unknown arXiv https://dx.doi.org/10.1080/01621459.2015.1108199 arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ Applications stat.AP Methodology stat.ME FOS Computer and information sciences article-journal Article ScholarlyArticle Text 2015 ftdatacite https://doi.org/10.48550/arxiv.1501.01937 https://doi.org/10.1080/01621459.2015.1108199 2022-04-01T12:34:28Z 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. Text Amundsen Sea Antarc* Antarctic Antarctica Ice Sheet West Antarctica DataCite Metadata Store (German National Library of Science and Technology) Antarctic West Antarctica Amundsen Sea West Antarctic Ice Sheet |
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Applications stat.AP Methodology stat.ME FOS Computer and information sciences |
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Applications stat.AP Methodology stat.ME FOS Computer and information sciences Chang, Won Haran, Murali Applegate, Patrick Pollard, David Calibrating an ice sheet model using high-dimensional binary spatial data |
topic_facet |
Applications stat.AP Methodology stat.ME FOS Computer and information sciences |
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. |
format |
Text |
author |
Chang, Won Haran, Murali Applegate, Patrick Pollard, David |
author_facet |
Chang, Won Haran, Murali Applegate, Patrick Pollard, David |
author_sort |
Chang, Won |
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 |
publisher |
arXiv |
publishDate |
2015 |
url |
https://dx.doi.org/10.48550/arxiv.1501.01937 https://arxiv.org/abs/1501.01937 |
geographic |
Antarctic West Antarctica Amundsen Sea West Antarctic Ice Sheet |
geographic_facet |
Antarctic West Antarctica Amundsen Sea West Antarctic Ice Sheet |
genre |
Amundsen Sea Antarc* Antarctic Antarctica Ice Sheet West Antarctica |
genre_facet |
Amundsen Sea Antarc* Antarctic Antarctica Ice Sheet West Antarctica |
op_relation |
https://dx.doi.org/10.1080/01621459.2015.1108199 |
op_rights |
arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ |
op_doi |
https://doi.org/10.48550/arxiv.1501.01937 https://doi.org/10.1080/01621459.2015.1108199 |
_version_ |
1766375902070964224 |