Capturing the interactions between ice sheets, sea level and the solid Earth on a range of timescales: a new “time window” algorithm

Retreat and advance of ice sheets perturb the gravitational field, solid surface and rotation of the Earth, leading to spatially variable sea-level changes over a range of timescales O (10 0−6 years), which in turn feed back onto ice-sheet dynamics. Coupled ice-sheet–sea-level models have been devel...

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Published in:Geoscientific Model Development
Main Authors: Han, Holly Kyeore, Gomez, Natalya, Wan, Jeannette Xiu Wen
Format: Text
Language:English
Published: 2022
Subjects:
Online Access:https://doi.org/10.5194/gmd-15-1355-2022
https://gmd.copernicus.org/articles/15/1355/2022/
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spelling ftcopernicus:oai:publications.copernicus.org:gmd94178 2023-05-15T14:02:17+02:00 Capturing the interactions between ice sheets, sea level and the solid Earth on a range of timescales: a new “time window” algorithm Han, Holly Kyeore Gomez, Natalya Wan, Jeannette Xiu Wen 2022-02-16 application/pdf https://doi.org/10.5194/gmd-15-1355-2022 https://gmd.copernicus.org/articles/15/1355/2022/ eng eng doi:10.5194/gmd-15-1355-2022 https://gmd.copernicus.org/articles/15/1355/2022/ eISSN: 1991-9603 Text 2022 ftcopernicus https://doi.org/10.5194/gmd-15-1355-2022 2022-02-21T17:22:15Z Retreat and advance of ice sheets perturb the gravitational field, solid surface and rotation of the Earth, leading to spatially variable sea-level changes over a range of timescales O (10 0−6 years), which in turn feed back onto ice-sheet dynamics. Coupled ice-sheet–sea-level models have been developed to capture the interactive processes between ice sheets, sea level and the solid Earth, but it is computationally challenging to capture short-term interactions O (10 0−2 years) precisely within longer O (10 3−6 years) simulations. The standard forward sea-level modelling algorithm assigns a uniform temporal resolution in the sea-level model, causing a quadratic increase in total CPU time with the total number of input ice history steps, which increases with either the length or temporal resolution of the simulation. In this study, we introduce a new “time window” algorithm for 1D pseudo-spectral sea-level models based on the normal mode method that enables users to define the temporal resolution at which the ice loading history is captured during different time intervals before the current simulation time. Utilizing the time window, we assign a fine temporal resolution O (10 0−2 years) for the period of ongoing and recent history of surface ice and ocean loading changes and a coarser temporal resolution O (10 3−6 years) for earlier periods in the simulation. This reduces the total CPU time and memory required per model time step while maintaining the precision of the model results. We explore the sensitivity of sea-level model results to the model temporal resolution and show how this sensitivity feeds back onto ice-sheet dynamics in coupled modelling. We apply the new algorithm to simulate sea-level changes in response to global ice-sheet evolution over two glacial cycles and the rapid collapse of marine sectors of the West Antarctic Ice Sheet in the coming centuries and provide appropriate time window profiles for each application. The time window algorithm reduces the total CPU time by ∼ 50 % in each of these examples and changes the trend of the total CPU time increase from quadratic to linear. This improvement would increase with longer simulations than those considered here. Our algorithm also allows for coupling time intervals of annual temporal scale for coupled ice-sheet–sea-level modelling of regions such as West Antarctica that are characterized by rapid solid Earth response to ice changes due to the thin lithosphere and low mantle viscosities. Text Antarc* Antarctic Antarctica Ice Sheet West Antarctica Copernicus Publications: E-Journals Antarctic West Antarctic Ice Sheet West Antarctica Geoscientific Model Development 15 3 1355 1373
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language English
description Retreat and advance of ice sheets perturb the gravitational field, solid surface and rotation of the Earth, leading to spatially variable sea-level changes over a range of timescales O (10 0−6 years), which in turn feed back onto ice-sheet dynamics. Coupled ice-sheet–sea-level models have been developed to capture the interactive processes between ice sheets, sea level and the solid Earth, but it is computationally challenging to capture short-term interactions O (10 0−2 years) precisely within longer O (10 3−6 years) simulations. The standard forward sea-level modelling algorithm assigns a uniform temporal resolution in the sea-level model, causing a quadratic increase in total CPU time with the total number of input ice history steps, which increases with either the length or temporal resolution of the simulation. In this study, we introduce a new “time window” algorithm for 1D pseudo-spectral sea-level models based on the normal mode method that enables users to define the temporal resolution at which the ice loading history is captured during different time intervals before the current simulation time. Utilizing the time window, we assign a fine temporal resolution O (10 0−2 years) for the period of ongoing and recent history of surface ice and ocean loading changes and a coarser temporal resolution O (10 3−6 years) for earlier periods in the simulation. This reduces the total CPU time and memory required per model time step while maintaining the precision of the model results. We explore the sensitivity of sea-level model results to the model temporal resolution and show how this sensitivity feeds back onto ice-sheet dynamics in coupled modelling. We apply the new algorithm to simulate sea-level changes in response to global ice-sheet evolution over two glacial cycles and the rapid collapse of marine sectors of the West Antarctic Ice Sheet in the coming centuries and provide appropriate time window profiles for each application. The time window algorithm reduces the total CPU time by ∼ 50 % in each of these examples and changes the trend of the total CPU time increase from quadratic to linear. This improvement would increase with longer simulations than those considered here. Our algorithm also allows for coupling time intervals of annual temporal scale for coupled ice-sheet–sea-level modelling of regions such as West Antarctica that are characterized by rapid solid Earth response to ice changes due to the thin lithosphere and low mantle viscosities.
format Text
author Han, Holly Kyeore
Gomez, Natalya
Wan, Jeannette Xiu Wen
spellingShingle Han, Holly Kyeore
Gomez, Natalya
Wan, Jeannette Xiu Wen
Capturing the interactions between ice sheets, sea level and the solid Earth on a range of timescales: a new “time window” algorithm
author_facet Han, Holly Kyeore
Gomez, Natalya
Wan, Jeannette Xiu Wen
author_sort Han, Holly Kyeore
title Capturing the interactions between ice sheets, sea level and the solid Earth on a range of timescales: a new “time window” algorithm
title_short Capturing the interactions between ice sheets, sea level and the solid Earth on a range of timescales: a new “time window” algorithm
title_full Capturing the interactions between ice sheets, sea level and the solid Earth on a range of timescales: a new “time window” algorithm
title_fullStr Capturing the interactions between ice sheets, sea level and the solid Earth on a range of timescales: a new “time window” algorithm
title_full_unstemmed Capturing the interactions between ice sheets, sea level and the solid Earth on a range of timescales: a new “time window” algorithm
title_sort capturing the interactions between ice sheets, sea level and the solid earth on a range of timescales: a new “time window” algorithm
publishDate 2022
url https://doi.org/10.5194/gmd-15-1355-2022
https://gmd.copernicus.org/articles/15/1355/2022/
geographic Antarctic
West Antarctic Ice Sheet
West Antarctica
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West Antarctic Ice Sheet
West Antarctica
genre Antarc*
Antarctic
Antarctica
Ice Sheet
West Antarctica
genre_facet Antarc*
Antarctic
Antarctica
Ice Sheet
West Antarctica
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op_relation doi:10.5194/gmd-15-1355-2022
https://gmd.copernicus.org/articles/15/1355/2022/
op_doi https://doi.org/10.5194/gmd-15-1355-2022
container_title Geoscientific Model Development
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