Computer model calibration based on image warping metrics: an application for sea ice deformation
Arctic sea ice plays an important role in the global climate. Sea ice models governed by physical equations have been used to simulate the state of the ice including characteristics such as ice thickness, concentration, and motion. More recent models also attempt to capture features such as fracture...
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ftdatacite:10.48550/arxiv.1810.06608 2023-05-15T15:05:28+02:00 Computer model calibration based on image warping metrics: an application for sea ice deformation Guan, Yawen Sampson, Christian Tucker, J. Derek Chang, Won Mondal, Anirban Haran, Murali Sulsky, Deborah 2018 https://dx.doi.org/10.48550/arxiv.1810.06608 https://arxiv.org/abs/1810.06608 unknown arXiv 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 Preprint Article article CreativeWork 2018 ftdatacite https://doi.org/10.48550/arxiv.1810.06608 2022-04-01T09:01:11Z Arctic sea ice plays an important role in the global climate. Sea ice models governed by physical equations have been used to simulate the state of the ice including characteristics such as ice thickness, concentration, and motion. More recent models also attempt to capture features such as fractures or leads in the ice. These simulated features can be partially misaligned or misshapen when compared to observational data, whether due to numerical approximation or incomplete physics. In order to make realistic forecasts and improve understanding of the underlying processes, it is necessary to calibrate the numerical model to field data. Traditional calibration methods based on generalized least-square metrics are flawed for linear features such as sea ice cracks. We develop a statistical emulation and calibration framework that accounts for feature misalignment and misshapenness, which involves optimally aligning model output with observed features using cutting edge image registration techniques. This work can also have application to other physical models which produce coherent structures. Report Arctic Sea ice DataCite Metadata Store (German National Library of Science and Technology) Arctic |
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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 Guan, Yawen Sampson, Christian Tucker, J. Derek Chang, Won Mondal, Anirban Haran, Murali Sulsky, Deborah Computer model calibration based on image warping metrics: an application for sea ice deformation |
topic_facet |
Applications stat.AP Methodology stat.ME FOS Computer and information sciences |
description |
Arctic sea ice plays an important role in the global climate. Sea ice models governed by physical equations have been used to simulate the state of the ice including characteristics such as ice thickness, concentration, and motion. More recent models also attempt to capture features such as fractures or leads in the ice. These simulated features can be partially misaligned or misshapen when compared to observational data, whether due to numerical approximation or incomplete physics. In order to make realistic forecasts and improve understanding of the underlying processes, it is necessary to calibrate the numerical model to field data. Traditional calibration methods based on generalized least-square metrics are flawed for linear features such as sea ice cracks. We develop a statistical emulation and calibration framework that accounts for feature misalignment and misshapenness, which involves optimally aligning model output with observed features using cutting edge image registration techniques. This work can also have application to other physical models which produce coherent structures. |
format |
Report |
author |
Guan, Yawen Sampson, Christian Tucker, J. Derek Chang, Won Mondal, Anirban Haran, Murali Sulsky, Deborah |
author_facet |
Guan, Yawen Sampson, Christian Tucker, J. Derek Chang, Won Mondal, Anirban Haran, Murali Sulsky, Deborah |
author_sort |
Guan, Yawen |
title |
Computer model calibration based on image warping metrics: an application for sea ice deformation |
title_short |
Computer model calibration based on image warping metrics: an application for sea ice deformation |
title_full |
Computer model calibration based on image warping metrics: an application for sea ice deformation |
title_fullStr |
Computer model calibration based on image warping metrics: an application for sea ice deformation |
title_full_unstemmed |
Computer model calibration based on image warping metrics: an application for sea ice deformation |
title_sort |
computer model calibration based on image warping metrics: an application for sea ice deformation |
publisher |
arXiv |
publishDate |
2018 |
url |
https://dx.doi.org/10.48550/arxiv.1810.06608 https://arxiv.org/abs/1810.06608 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_rights |
arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ |
op_doi |
https://doi.org/10.48550/arxiv.1810.06608 |
_version_ |
1766337163339759616 |