Reciprocity and sensitivity kernels for sea level fingerprints

<jats:title>SUMMARY</jats:title><jats:p>Reciprocity theorems are established for the elastic sea level fingerprint problem including rotational feedbacks. In their simplest form, these results show that the sea level change at a location x due to melting a unit point mass of ice at...

Full description

Bibliographic Details
Main Authors: Al-Attar, D, Syvret, F, Crawford, O, Mitrovica, JX, Lloyd, AJ
Format: Article in Journal/Newspaper
Language:English
Published: Oxford University Press (OUP) 2023
Subjects:
Online Access:https://www.repository.cam.ac.uk/handle/1810/361501
id ftunivcam:oai:www.repository.cam.ac.uk:1810/361501
record_format openpolar
spelling ftunivcam:oai:www.repository.cam.ac.uk:1810/361501 2024-01-28T10:06:32+01:00 Reciprocity and sensitivity kernels for sea level fingerprints Al-Attar, D Syvret, F Crawford, O Mitrovica, JX Lloyd, AJ 2023-11-03 application/pdf https://www.repository.cam.ac.uk/handle/1810/361501 eng eng Oxford University Press (OUP) Department of Earth Sciences http://dx.doi.org/10.1093/gji/ggad434 Geophysical Journal International https://www.repository.cam.ac.uk/handle/1810/361501 Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/ 37 Earth Sciences 3709 Physical Geography and Environmental Geoscience 3705 Geology 13 Climate Action Article 2023 ftunivcam 2024-01-04T23:19:24Z <jats:title>SUMMARY</jats:title><jats:p>Reciprocity theorems are established for the elastic sea level fingerprint problem including rotational feedbacks. In their simplest form, these results show that the sea level change at a location x due to melting a unit point mass of ice at x′ is equal to the sea level change at x′ due to melting a unit point mass of ice at x. This identity holds irrespective of the shoreline geometry or of lateral variations in elastic Earth structure. Using the reciprocity theorems, sensitivity kernels for sea level and related observables with respect to the ice load can be readily derived. It is notable that calculation of the sensitivity kernels is possible using standard fingerprint codes, though for some types of observable a slight generalization to the fingerprint problem must be considered. These results are of use within coastal hazard assessment and have a range of applications within studies of modern-day sea level change. To illustrate the latter point, we use sensitivity kernels to investigate two widely used methods for estimating, respectively, ice sheet mass loss from satellite gravity, and rates of global mean sea level rise from satellite altimetry. Though our analysis is idealized in some respects, we identify systematic errors of order 5 per cent due to the use of simplified sea level physics. Crucially, calculation of the relevant sensitivity kernels provides not only a means for understanding sources of bias in existing methods, but will aid in the design of new and improved data-assimilation techniques.</jats:p> Article in Journal/Newspaper Ice Sheet Apollo - University of Cambridge Repository
institution Open Polar
collection Apollo - University of Cambridge Repository
op_collection_id ftunivcam
language English
topic 37 Earth Sciences
3709 Physical Geography and Environmental Geoscience
3705 Geology
13 Climate Action
spellingShingle 37 Earth Sciences
3709 Physical Geography and Environmental Geoscience
3705 Geology
13 Climate Action
Al-Attar, D
Syvret, F
Crawford, O
Mitrovica, JX
Lloyd, AJ
Reciprocity and sensitivity kernels for sea level fingerprints
topic_facet 37 Earth Sciences
3709 Physical Geography and Environmental Geoscience
3705 Geology
13 Climate Action
description <jats:title>SUMMARY</jats:title><jats:p>Reciprocity theorems are established for the elastic sea level fingerprint problem including rotational feedbacks. In their simplest form, these results show that the sea level change at a location x due to melting a unit point mass of ice at x′ is equal to the sea level change at x′ due to melting a unit point mass of ice at x. This identity holds irrespective of the shoreline geometry or of lateral variations in elastic Earth structure. Using the reciprocity theorems, sensitivity kernels for sea level and related observables with respect to the ice load can be readily derived. It is notable that calculation of the sensitivity kernels is possible using standard fingerprint codes, though for some types of observable a slight generalization to the fingerprint problem must be considered. These results are of use within coastal hazard assessment and have a range of applications within studies of modern-day sea level change. To illustrate the latter point, we use sensitivity kernels to investigate two widely used methods for estimating, respectively, ice sheet mass loss from satellite gravity, and rates of global mean sea level rise from satellite altimetry. Though our analysis is idealized in some respects, we identify systematic errors of order 5 per cent due to the use of simplified sea level physics. Crucially, calculation of the relevant sensitivity kernels provides not only a means for understanding sources of bias in existing methods, but will aid in the design of new and improved data-assimilation techniques.</jats:p>
format Article in Journal/Newspaper
author Al-Attar, D
Syvret, F
Crawford, O
Mitrovica, JX
Lloyd, AJ
author_facet Al-Attar, D
Syvret, F
Crawford, O
Mitrovica, JX
Lloyd, AJ
author_sort Al-Attar, D
title Reciprocity and sensitivity kernels for sea level fingerprints
title_short Reciprocity and sensitivity kernels for sea level fingerprints
title_full Reciprocity and sensitivity kernels for sea level fingerprints
title_fullStr Reciprocity and sensitivity kernels for sea level fingerprints
title_full_unstemmed Reciprocity and sensitivity kernels for sea level fingerprints
title_sort reciprocity and sensitivity kernels for sea level fingerprints
publisher Oxford University Press (OUP)
publishDate 2023
url https://www.repository.cam.ac.uk/handle/1810/361501
genre Ice Sheet
genre_facet Ice Sheet
op_relation https://www.repository.cam.ac.uk/handle/1810/361501
op_rights Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/
_version_ 1789333478638092288