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Title: Capturing the interactions between ice sheets, sea level and the solid Earth on a range of timescales: a new “time window” algorithm
Abstract. Retreat and advance of ice sheets perturb the gravitational field, solidsurface and rotation of the Earth, leading to spatially variable sea-levelchanges over a range of timescales O(100−6 years), which in turn feedback onto ice-sheet dynamics. Coupled ice-sheet–sea-level models havebeen developed to capture the interactive processes between ice sheets, sealevel and the solid Earth, but it is computationally challenging to captureshort-term interactions O(100−2 years) precisely within longer O(103−6 years) simulations. The standard forward sea-level modelling algorithmassigns a uniform temporal resolution in the sea-level model, causing aquadratic increase in total CPU time with the total number of input icehistory steps, which increases with either the length or temporal resolutionof the simulation. In this study, we introduce a new “time window”algorithm for 1D pseudo-spectral sea-level models based on the normal modemethod that enables users to define the temporal resolution at which the iceloading history is captured during different time intervals before thecurrent simulation time. Utilizing the time window, we assign a finetemporal resolution O(100−2 years) for the period of ongoing andrecent history of surface ice and ocean loading changes and a coarsertemporal resolution O(103−6 years) for earlier periods in thesimulation. This reduces the total CPU time and memory required per modeltime step while maintaining the precision of the model results. We explorethe sensitivity of sea-level model results to the model temporal resolutionand show how this sensitivity feeds back onto ice-sheet dynamics in coupledmodelling. We apply the new algorithm to simulate sea-level changes inresponse to global ice-sheet evolution over two glacial cycles and the rapidcollapse of marine sectors of the West Antarctic Ice Sheet in the comingcenturies 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 timeincrease from quadratic to linear. This improvement would increase withlonger simulations than those considered here. Our algorithm also allows for couplingtime intervals of annual temporal scale for coupled ice-sheet–sea-levelmodelling of regions such as West Antarctica that are characterized byrapid solid Earth response to ice changes due to the thin lithosphere andlow mantle viscosities.  more » « less
Award ID(s):
1745074
NSF-PAR ID:
10351122
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Geoscientific Model Development
Volume:
15
Issue:
3
ISSN:
1991-9603
Page Range / eLocation ID:
1355 to 1373
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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