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: A. Wernecke, T. L. Edwards, I. J. Nias, P. B. Holden, N. R. Edwards
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2020
Subjects:
geo
Online Access:https://doi.org/10.5194/tc-14-1459-2020
https://www.the-cryosphere.net/14/1459/2020/tc-14-1459-2020.pdf
https://doaj.org/article/e9892cc212334400bd02b5b77f4def84
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spelling fttriple:oai:gotriple.eu:oai:doaj.org/article:e9892cc212334400bd02b5b77f4def84 2023-05-15T13:23:59+02:00 Spatial probabilistic calibration of a high-resolution Amundsen Sea Embayment ice sheet model with satellite altimeter data A. Wernecke T. L. Edwards I. J. Nias P. B. Holden N. R. Edwards 2020-05-01 https://doi.org/10.5194/tc-14-1459-2020 https://www.the-cryosphere.net/14/1459/2020/tc-14-1459-2020.pdf https://doaj.org/article/e9892cc212334400bd02b5b77f4def84 en eng Copernicus Publications doi:10.5194/tc-14-1459-2020 1994-0416 1994-0424 https://www.the-cryosphere.net/14/1459/2020/tc-14-1459-2020.pdf https://doaj.org/article/e9892cc212334400bd02b5b77f4def84 undefined The Cryosphere, Vol 14, Pp 1459-1474 (2020) geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2020 fttriple https://doi.org/10.5194/tc-14-1459-2020 2023-01-22T17:49:51Z 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 ... Article in Journal/Newspaper Amundsen Sea Antarc* Antarctica Ice Sheet The Cryosphere Unknown Amundsen Sea The Cryosphere 14 5 1459 1474
institution Open Polar
collection Unknown
op_collection_id fttriple
language English
topic geo
envir
spellingShingle geo
envir
A. Wernecke
T. L. Edwards
I. J. Nias
P. B. Holden
N. R. Edwards
Spatial probabilistic calibration of a high-resolution Amundsen Sea Embayment ice sheet model with satellite altimeter data
topic_facet geo
envir
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 ...
format Article in Journal/Newspaper
author A. Wernecke
T. L. Edwards
I. J. Nias
P. B. Holden
N. R. Edwards
author_facet A. Wernecke
T. L. Edwards
I. J. Nias
P. B. Holden
N. R. Edwards
author_sort A. Wernecke
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
https://www.the-cryosphere.net/14/1459/2020/tc-14-1459-2020.pdf
https://doaj.org/article/e9892cc212334400bd02b5b77f4def84
geographic Amundsen Sea
geographic_facet Amundsen Sea
genre Amundsen Sea
Antarc*
Antarctica
Ice Sheet
The Cryosphere
genre_facet Amundsen Sea
Antarc*
Antarctica
Ice Sheet
The Cryosphere
op_source The Cryosphere, Vol 14, Pp 1459-1474 (2020)
op_relation doi:10.5194/tc-14-1459-2020
1994-0416
1994-0424
https://www.the-cryosphere.net/14/1459/2020/tc-14-1459-2020.pdf
https://doaj.org/article/e9892cc212334400bd02b5b77f4def84
op_rights undefined
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
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