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Glacial isostatic adjustment modelling: historical perspectives, recent advances, and future directions
Glacial isostatic adjustment (GIA) describes the response of the solid Earth, the gravitational field, and the oceans to the growth and decay of the global ice sheets. A commonly studied component of GIA is “postglacial rebound”, which specifically relates to uplift of the land surface following ice...
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Published in: | Earth surface dynamics 2018-05, Vol.6 (2), p.401-429 |
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Main Author: | |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Glacial isostatic adjustment (GIA) describes the response of the solid Earth, the gravitational field, and the oceans to the growth and decay of the global ice sheets. A commonly studied component of GIA is “postglacial rebound”, which specifically relates to uplift of the land surface following ice melt. GIA is a relatively rapid process, triggering 100 m scale changes in sea level and solid Earth deformation over just a few tens of thousands of years. Indeed, the first-order effects of GIA could already be quantified several hundred years ago without reliance on precise measurement techniques and scientists have been developing a unifying theory for the observations for over 200 years. Progress towards this goal required a number of significant breakthroughs to be made, including the recognition that ice sheets were once more extensive, the solid Earth changes shape over time, and gravity plays a central role in determining the pattern of sea-level change. This article describes the historical development of the field of GIA and provides an overview of the processes involved. Significant recent progress has been made as concepts associated with GIA have begun to be incorporated into parallel fields of research; these advances are discussed, along with the role that GIA is likely to play in addressing outstanding research questions within the field of Earth system modelling. |
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ISSN: | 2196-632X 2196-6311 2196-632X |
DOI: | 10.5194/esurf-6-401-2018 |