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:10.6084/m9.figshare.1629327.v2 2023-05-15T13:23:56+02:00 Calibrating an Ice Sheet Model Using High-Dimensional Binary Spatial Data Chang, Won Murali Haran Applegate, Patrick Pollard, David 2016 https://dx.doi.org/10.6084/m9.figshare.1629327.v2 https://figshare.com/articles/Calibrating_an_Ice_Sheet_Model_using_High_dimensional_Binary_Spatial_Data/1629327/2 unknown Taylor & Francis https://dx.doi.org/10.1080/01621459.2015.1108199 https://dx.doi.org/10.6084/m9.figshare.1629327 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY Medicine Genetics FOS Biological sciences Neuroscience Biotechnology 59999 Environmental Sciences not elsewhere classified FOS Earth and related environmental sciences Immunology FOS Clinical medicine 69999 Biological Sciences not elsewhere classified 80699 Information Systems not elsewhere classified FOS Computer and information sciences 19999 Mathematical Sciences not elsewhere classified FOS Mathematics Inorganic Chemistry FOS Chemical sciences Text article-journal Journal contribution ScholarlyArticle 2016 ftdatacite https://doi.org/10.6084/m9.figshare.1629327.v2 https://doi.org/10.1080/01621459.2015.1108199 https://doi.org/10.6084/m9.figshare.1629327 2021-11-05T12:55:41Z 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. Text Amundsen Sea Antarc* Antarctic Antarctica Ice Sheet West Antarctica DataCite Metadata Store (German National Library of Science and Technology) Amundsen Sea Antarctic West Antarctic Ice Sheet West Antarctica |
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DataCite Metadata Store (German National Library of Science and Technology) |
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topic |
Medicine Genetics FOS Biological sciences Neuroscience Biotechnology 59999 Environmental Sciences not elsewhere classified FOS Earth and related environmental sciences Immunology FOS Clinical medicine 69999 Biological Sciences not elsewhere classified 80699 Information Systems not elsewhere classified FOS Computer and information sciences 19999 Mathematical Sciences not elsewhere classified FOS Mathematics Inorganic Chemistry FOS Chemical sciences |
spellingShingle |
Medicine Genetics FOS Biological sciences Neuroscience Biotechnology 59999 Environmental Sciences not elsewhere classified FOS Earth and related environmental sciences Immunology FOS Clinical medicine 69999 Biological Sciences not elsewhere classified 80699 Information Systems not elsewhere classified FOS Computer and information sciences 19999 Mathematical Sciences not elsewhere classified FOS Mathematics Inorganic Chemistry FOS Chemical sciences Chang, Won Murali Haran Applegate, Patrick Pollard, David Calibrating an Ice Sheet Model Using High-Dimensional Binary Spatial Data |
topic_facet |
Medicine Genetics FOS Biological sciences Neuroscience Biotechnology 59999 Environmental Sciences not elsewhere classified FOS Earth and related environmental sciences Immunology FOS Clinical medicine 69999 Biological Sciences not elsewhere classified 80699 Information Systems not elsewhere classified FOS Computer and information sciences 19999 Mathematical Sciences not elsewhere classified FOS Mathematics Inorganic Chemistry FOS Chemical 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. Supplementary materials for this article are available online. |
format |
Text |
author |
Chang, Won Murali Haran Applegate, Patrick Pollard, David |
author_facet |
Chang, Won Murali Haran 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 |
Taylor & Francis |
publishDate |
2016 |
url |
https://dx.doi.org/10.6084/m9.figshare.1629327.v2 https://figshare.com/articles/Calibrating_an_Ice_Sheet_Model_using_High_dimensional_Binary_Spatial_Data/1629327/2 |
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 |
https://dx.doi.org/10.1080/01621459.2015.1108199 https://dx.doi.org/10.6084/m9.figshare.1629327 |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.6084/m9.figshare.1629327.v2 https://doi.org/10.1080/01621459.2015.1108199 https://doi.org/10.6084/m9.figshare.1629327 |
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