Spatial probabilistic calibration of a high-resolution Amundsen Sea Embayment ice sheet model with satellite altimeter data
<jats:p>Abstract. Probabilistic predictions of the sea level contribution from Antarctica often have large uncertainty intervals. Calibration of model simulations with observations can reduce uncertainties and improve confidence in projections, particularly if this exploits as much of the avai...
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ftunivliverpool:oai:livrepository.liverpool.ac.uk:3086347 2023-05-15T13:23:57+02:00 Spatial probabilistic calibration of a high-resolution Amundsen Sea Embayment ice sheet model with satellite altimeter data Wernecke, Andreas Edwards, Tamsin L Nias, Isabel Holden, Philip B Edwards, Neil Robert 2020 http://livrepository.liverpool.ac.uk/3086347/ https://doi.org/10.5194/tc-14-1459-2020 en eng Copernicus GmbH Wernecke, Andreas, Edwards, Tamsin L, Nias, Isabel orcid:0000-0002-5657-8691 , Holden, Philip B and Edwards, Neil Robert (2020) Spatial probabilistic calibration of a high-resolution Amundsen Sea Embayment ice sheet model with satellite altimeter data. CRYOSPHERE, 14 (5). pp. 1459-1474. Article NonPeerReviewed 2020 ftunivliverpool https://doi.org/10.5194/tc-14-1459-2020 2023-01-19T23:54:31Z <jats:p>Abstract. Probabilistic predictions of the sea level contribution from Antarctica often have large uncertainty intervals. Calibration of model simulations with observations can reduce uncertainties and improve confidence in projections, particularly if this exploits as much of the available information as possible (such as spatial characteristics), but the necessary statistical treatment is often challenging and can be computationally prohibitive. Ice sheet models with sufficient spatial resolution to resolve grounding line evolution are also computationally expensive. Here we address these challenges by adopting and comparing dimension-reduced calibration approaches based on a principal component decomposition of the adaptive mesh model BISICLES. The effects model parameters have on these principal components are then gathered in statistical emulators to allow for smooth probability density estimates. With the help of a published perturbed parameter ice sheet model ensemble of the Amundsen Sea Embayment (ASE), we show how the use of principal components in combination with spatially resolved observations can improve probabilistic calibrations. In synthetic model experiments (calibrating the model with altered model results) we can identify the correct basal traction and ice viscosity scaling parameters as well as the bedrock map with spatial calibrations. In comparison a simpler calibration against an aggregated observation, the net sea level contribution, imposes only weaker constraints by allowing a wide range of basal traction and viscosity scaling factors. Uncertainties in sea level rise contribution of 50-year simulations from the current state of the ASE can be reduced with satellite observations of recent ice thickness change by nearly 90 %; median and 90 % confidence intervals are 18.9 [13.9, 24.8] mm SLE (sea level equivalent) for the proposed spatial calibration approach, 16.8 [7.7, 25.6] mm SLE for the net sea level calibration and 23.1 [−8.4, 94.5] mm SLE for the uncalibrated ensemble. ... Article in Journal/Newspaper Amundsen Sea Antarc* Antarctica Ice Sheet The University of Liverpool Repository Amundsen Sea The Cryosphere 14 5 1459 1474 |
institution |
Open Polar |
collection |
The University of Liverpool Repository |
op_collection_id |
ftunivliverpool |
language |
English |
description |
<jats:p>Abstract. Probabilistic predictions of the sea level contribution from Antarctica often have large uncertainty intervals. Calibration of model simulations with observations can reduce uncertainties and improve confidence in projections, particularly if this exploits as much of the available information as possible (such as spatial characteristics), but the necessary statistical treatment is often challenging and can be computationally prohibitive. Ice sheet models with sufficient spatial resolution to resolve grounding line evolution are also computationally expensive. Here we address these challenges by adopting and comparing dimension-reduced calibration approaches based on a principal component decomposition of the adaptive mesh model BISICLES. The effects model parameters have on these principal components are then gathered in statistical emulators to allow for smooth probability density estimates. With the help of a published perturbed parameter ice sheet model ensemble of the Amundsen Sea Embayment (ASE), we show how the use of principal components in combination with spatially resolved observations can improve probabilistic calibrations. In synthetic model experiments (calibrating the model with altered model results) we can identify the correct basal traction and ice viscosity scaling parameters as well as the bedrock map with spatial calibrations. In comparison a simpler calibration against an aggregated observation, the net sea level contribution, imposes only weaker constraints by allowing a wide range of basal traction and viscosity scaling factors. Uncertainties in sea level rise contribution of 50-year simulations from the current state of the ASE can be reduced with satellite observations of recent ice thickness change by nearly 90 %; median and 90 % confidence intervals are 18.9 [13.9, 24.8] mm SLE (sea level equivalent) for the proposed spatial calibration approach, 16.8 [7.7, 25.6] mm SLE for the net sea level calibration and 23.1 [−8.4, 94.5] mm SLE for the uncalibrated ensemble. ... |
format |
Article in Journal/Newspaper |
author |
Wernecke, Andreas Edwards, Tamsin L Nias, Isabel Holden, Philip B Edwards, Neil Robert |
spellingShingle |
Wernecke, Andreas Edwards, Tamsin L Nias, Isabel Holden, Philip B Edwards, Neil Robert Spatial probabilistic calibration of a high-resolution Amundsen Sea Embayment ice sheet model with satellite altimeter data |
author_facet |
Wernecke, Andreas Edwards, Tamsin L Nias, Isabel Holden, Philip B Edwards, Neil Robert |
author_sort |
Wernecke, Andreas |
title |
Spatial probabilistic calibration of a high-resolution Amundsen Sea Embayment ice sheet model with satellite altimeter data |
title_short |
Spatial probabilistic calibration of a high-resolution Amundsen Sea Embayment ice sheet model with satellite altimeter data |
title_full |
Spatial probabilistic calibration of a high-resolution Amundsen Sea Embayment ice sheet model with satellite altimeter data |
title_fullStr |
Spatial probabilistic calibration of a high-resolution Amundsen Sea Embayment ice sheet model with satellite altimeter data |
title_full_unstemmed |
Spatial probabilistic calibration of a high-resolution Amundsen Sea Embayment ice sheet model with satellite altimeter data |
title_sort |
spatial probabilistic calibration of a high-resolution amundsen sea embayment ice sheet model with satellite altimeter data |
publisher |
Copernicus GmbH |
publishDate |
2020 |
url |
http://livrepository.liverpool.ac.uk/3086347/ https://doi.org/10.5194/tc-14-1459-2020 |
geographic |
Amundsen Sea |
geographic_facet |
Amundsen Sea |
genre |
Amundsen Sea Antarc* Antarctica Ice Sheet |
genre_facet |
Amundsen Sea Antarc* Antarctica Ice Sheet |
op_relation |
Wernecke, Andreas, Edwards, Tamsin L, Nias, Isabel orcid:0000-0002-5657-8691 , Holden, Philip B and Edwards, Neil Robert (2020) Spatial probabilistic calibration of a high-resolution Amundsen Sea Embayment ice sheet model with satellite altimeter data. CRYOSPHERE, 14 (5). pp. 1459-1474. |
op_doi |
https://doi.org/10.5194/tc-14-1459-2020 |
container_title |
The Cryosphere |
container_volume |
14 |
container_issue |
5 |
container_start_page |
1459 |
op_container_end_page |
1474 |
_version_ |
1766376547940302848 |