Spatial probabilistic calibration of a high-resolution Amundsen Sea Embayment ice sheet model with satellite altimeter data

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 pos...

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Published in:The Cryosphere
Main Authors: Wernecke, Andreas, Edwards, Tamsin L., Nias, Isabel J., Holden, Philip B., Edwards, Neil R.
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2020
Subjects:
Online Access:https://doi.org/10.5194/tc-14-1459-2020
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topic article
Verlagsveröffentlichung
spellingShingle article
Verlagsveröffentlichung
Wernecke, Andreas
Edwards, Tamsin L.
Nias, Isabel J.
Holden, Philip B.
Edwards, Neil R.
Spatial probabilistic calibration of a high-resolution Amundsen Sea Embayment ice sheet model with satellite altimeter data
topic_facet article
Verlagsveröffentlichung
description 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. The spatial model behaviour is much more consistent with observations if, instead of Bedmap2, a modified bedrock topography is used that most notably removes a topographic rise near the initial grounding line of Pine Island Glacier. The ASE dominates the current Antarctic sea level contribution, but other regions have the potential to become more important on centennial scales. These larger spatial and temporal scales would benefit even more from methods of fast but exhaustive model calibration. Applied to projections of the whole Antarctic ice sheet, our approach has therefore the potential to efficiently improve our understanding of model behaviour, as well as substantiating and reducing projection uncertainties.
format Article in Journal/Newspaper
author Wernecke, Andreas
Edwards, Tamsin L.
Nias, Isabel J.
Holden, Philip B.
Edwards, Neil R.
author_facet Wernecke, Andreas
Edwards, Tamsin L.
Nias, Isabel J.
Holden, Philip B.
Edwards, Neil R.
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 Publications
publishDate 2020
url https://doi.org/10.5194/tc-14-1459-2020
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https://tc.copernicus.org/articles/14/1459/2020/tc-14-1459-2020.pdf
long_lat ENVELOPE(-101.000,-101.000,-75.000,-75.000)
geographic Amundsen Sea
Antarctic
Pine Island Glacier
geographic_facet Amundsen Sea
Antarctic
Pine Island Glacier
genre Amundsen Sea
Antarc*
Antarctic
Antarctica
Ice Sheet
Pine Island
Pine Island Glacier
The Cryosphere
genre_facet Amundsen Sea
Antarc*
Antarctic
Antarctica
Ice Sheet
Pine Island
Pine Island Glacier
The Cryosphere
op_relation The Cryosphere -- ˜Theœ Cryosphere -- http://www.bibliothek.uni-regensburg.de/ezeit/?2393169 -- http://www.the-cryosphere.net/ -- 1994-0424
https://doi.org/10.5194/tc-14-1459-2020
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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
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spelling ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00051427 2023-05-15T13:24:04+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 J. Holden, Philip B. Edwards, Neil R. 2020-05 electronic https://doi.org/10.5194/tc-14-1459-2020 https://noa.gwlb.de/receive/cop_mods_00051427 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00051083/tc-14-1459-2020.pdf https://tc.copernicus.org/articles/14/1459/2020/tc-14-1459-2020.pdf eng eng Copernicus Publications The Cryosphere -- ˜Theœ Cryosphere -- http://www.bibliothek.uni-regensburg.de/ezeit/?2393169 -- http://www.the-cryosphere.net/ -- 1994-0424 https://doi.org/10.5194/tc-14-1459-2020 https://noa.gwlb.de/receive/cop_mods_00051427 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00051083/tc-14-1459-2020.pdf https://tc.copernicus.org/articles/14/1459/2020/tc-14-1459-2020.pdf https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess CC-BY article Verlagsveröffentlichung article Text doc-type:article 2020 ftnonlinearchiv https://doi.org/10.5194/tc-14-1459-2020 2022-02-08T22:36:23Z 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. The spatial model behaviour is much more consistent with observations if, instead of Bedmap2, a modified bedrock topography is used that most notably removes a topographic rise near the initial grounding line of Pine Island Glacier. The ASE dominates the current Antarctic sea level contribution, but other regions have the potential to become more important on centennial scales. These larger spatial and temporal scales would benefit even more from methods of fast but exhaustive model calibration. Applied to projections of the whole Antarctic ice sheet, our approach has therefore the potential to efficiently improve our understanding of model behaviour, as well as substantiating and reducing projection uncertainties. Article in Journal/Newspaper Amundsen Sea Antarc* Antarctic Antarctica Ice Sheet Pine Island Pine Island Glacier The Cryosphere Niedersächsisches Online-Archiv NOA Amundsen Sea Antarctic Pine Island Glacier ENVELOPE(-101.000,-101.000,-75.000,-75.000) The Cryosphere 14 5 1459 1474