Separating GIA signal from surface mass change using GPS and GRACE data
The visco-elastic response of the solid Earth to the past glacial cycles and the present-day surface mass change (PDSMC) are detected by the geodetic observation systems such as global navigation satellite system and satellite gravimetry. Majority of the contemporary PDSMC is driven by climate chang...
Published in: | Geophysical Journal International |
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Online Access: | https://hdl.handle.net/1983/4a8935d6-4f1a-43cd-9cf0-c812ecaa7a4c https://research-information.bris.ac.uk/en/publications/4a8935d6-4f1a-43cd-9cf0-c812ecaa7a4c https://doi.org/10.1093/gji/ggac336 |
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ftubristolcris:oai:research-information.bris.ac.uk:publications/4a8935d6-4f1a-43cd-9cf0-c812ecaa7a4c 2024-02-04T10:00:51+01:00 Separating GIA signal from surface mass change using GPS and GRACE data Vishwakarma, Bramha Dutt Ziegler, Yann Bamber, Jonathan L Royston, Sam J 2022-09-23 https://hdl.handle.net/1983/4a8935d6-4f1a-43cd-9cf0-c812ecaa7a4c https://research-information.bris.ac.uk/en/publications/4a8935d6-4f1a-43cd-9cf0-c812ecaa7a4c https://doi.org/10.1093/gji/ggac336 eng eng info:eu-repo/grantAgreement/EC/H2020/694188 info:eu-repo/semantics/openAccess Vishwakarma , B D , Ziegler , Y , Bamber , J L & Royston , S J 2022 , ' Separating GIA signal from surface mass change using GPS and GRACE data ' , Geophysical Journal International , vol. 232 , no. 1 , pp. 537-547 . https://doi.org/10.1093/gji/ggac336 /dk/atira/pure/core/keywords/globalmass GlobalMass article 2022 ftubristolcris https://doi.org/10.1093/gji/ggac336 2024-01-11T23:48:34Z The visco-elastic response of the solid Earth to the past glacial cycles and the present-day surface mass change (PDSMC) are detected by the geodetic observation systems such as global navigation satellite system and satellite gravimetry. Majority of the contemporary PDSMC is driven by climate change and in order to better understand them using the aforementioned geodetic observations, glacial isostatic adjustment (GIA) signal should be accounted first. The default approach is to use forward GIA models that use uncertain ice-load history and approximate Earth rheology to predict GIA, yielding large uncertainties. The proliferation of contemporary, global, geodetic observations and their coverage have therefore enabled estimation of data-driven GIA solutions. A novel framework is presented that uses geophysical relations between the vertical land motion (VLM) and geopotential anomaly due to GIA and PDSMC to express GPS VLM trends and GRACE geopotential trends as a function of either GIA or PDSMC, which can be easily solved using least-squares regression. The GIA estimates are data-driven and differ significantly from forward models over Alaska and Greenland. Article in Journal/Newspaper Greenland Alaska University of Bristol: Bristol Research Greenland Geophysical Journal International 232 1 537 547 |
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Open Polar |
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University of Bristol: Bristol Research |
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ftubristolcris |
language |
English |
topic |
/dk/atira/pure/core/keywords/globalmass GlobalMass |
spellingShingle |
/dk/atira/pure/core/keywords/globalmass GlobalMass Vishwakarma, Bramha Dutt Ziegler, Yann Bamber, Jonathan L Royston, Sam J Separating GIA signal from surface mass change using GPS and GRACE data |
topic_facet |
/dk/atira/pure/core/keywords/globalmass GlobalMass |
description |
The visco-elastic response of the solid Earth to the past glacial cycles and the present-day surface mass change (PDSMC) are detected by the geodetic observation systems such as global navigation satellite system and satellite gravimetry. Majority of the contemporary PDSMC is driven by climate change and in order to better understand them using the aforementioned geodetic observations, glacial isostatic adjustment (GIA) signal should be accounted first. The default approach is to use forward GIA models that use uncertain ice-load history and approximate Earth rheology to predict GIA, yielding large uncertainties. The proliferation of contemporary, global, geodetic observations and their coverage have therefore enabled estimation of data-driven GIA solutions. A novel framework is presented that uses geophysical relations between the vertical land motion (VLM) and geopotential anomaly due to GIA and PDSMC to express GPS VLM trends and GRACE geopotential trends as a function of either GIA or PDSMC, which can be easily solved using least-squares regression. The GIA estimates are data-driven and differ significantly from forward models over Alaska and Greenland. |
format |
Article in Journal/Newspaper |
author |
Vishwakarma, Bramha Dutt Ziegler, Yann Bamber, Jonathan L Royston, Sam J |
author_facet |
Vishwakarma, Bramha Dutt Ziegler, Yann Bamber, Jonathan L Royston, Sam J |
author_sort |
Vishwakarma, Bramha Dutt |
title |
Separating GIA signal from surface mass change using GPS and GRACE data |
title_short |
Separating GIA signal from surface mass change using GPS and GRACE data |
title_full |
Separating GIA signal from surface mass change using GPS and GRACE data |
title_fullStr |
Separating GIA signal from surface mass change using GPS and GRACE data |
title_full_unstemmed |
Separating GIA signal from surface mass change using GPS and GRACE data |
title_sort |
separating gia signal from surface mass change using gps and grace data |
publishDate |
2022 |
url |
https://hdl.handle.net/1983/4a8935d6-4f1a-43cd-9cf0-c812ecaa7a4c https://research-information.bris.ac.uk/en/publications/4a8935d6-4f1a-43cd-9cf0-c812ecaa7a4c https://doi.org/10.1093/gji/ggac336 |
geographic |
Greenland |
geographic_facet |
Greenland |
genre |
Greenland Alaska |
genre_facet |
Greenland Alaska |
op_source |
Vishwakarma , B D , Ziegler , Y , Bamber , J L & Royston , S J 2022 , ' Separating GIA signal from surface mass change using GPS and GRACE data ' , Geophysical Journal International , vol. 232 , no. 1 , pp. 537-547 . https://doi.org/10.1093/gji/ggac336 |
op_relation |
info:eu-repo/grantAgreement/EC/H2020/694188 |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1093/gji/ggac336 |
container_title |
Geophysical Journal International |
container_volume |
232 |
container_issue |
1 |
container_start_page |
537 |
op_container_end_page |
547 |
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1789966359012048896 |