Antarctic Geothermal Heat Flow: Investigations by Geophysical and Statistical Analyses
Antarctica’s contribution to past and future sea level changes is highly uncertain given the poor understanding of ice sheet dynamics in which solid Earth interactions play an important role. Geothermal heat flow (GHF) is one of the least constrained solid Earth components but has a significant infl...
Main Author: | |
---|---|
Other Authors: | , |
Format: | Doctoral or Postdoctoral Thesis |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | https://nbn-resolving.org/urn:nbn:de:gbv:8:3-2022-00820-3 https://macau.uni-kiel.de/receive/macau_mods_00003271 https://macau.uni-kiel.de/servlets/MCRFileNodeServlet/macau_derivate_00004439/Thesis_Loesing.pdf |
id |
ftunivkiel:oai:macau.uni-kiel.de:macau_mods_00003271 |
---|---|
record_format |
openpolar |
spelling |
ftunivkiel:oai:macau.uni-kiel.de:macau_mods_00003271 2024-06-23T07:46:39+00:00 Antarctic Geothermal Heat Flow: Investigations by Geophysical and Statistical Analyses Lösing, Mareen Isabell Susanne Ebbing, Jörg Moorkamp, Max 2022 https://nbn-resolving.org/urn:nbn:de:gbv:8:3-2022-00820-3 https://macau.uni-kiel.de/receive/macau_mods_00003271 https://macau.uni-kiel.de/servlets/MCRFileNodeServlet/macau_derivate_00004439/Thesis_Loesing.pdf eng eng https://nbn-resolving.org/urn:nbn:de:gbv:8:3-2022-00820-3 https://macau.uni-kiel.de/receive/macau_mods_00003271 https://macau.uni-kiel.de/servlets/MCRFileNodeServlet/macau_derivate_00004439/Thesis_Loesing.pdf https://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess thesis ddc:550 Antarctica heat flow Bayesian inversion machine learning joint inversion Gondwana dissertation Text doc-type:PhDThesis 2022 ftunivkiel 2024-06-12T14:18:24Z Antarctica’s contribution to past and future sea level changes is highly uncertain given the poor understanding of ice sheet dynamics in which solid Earth interactions play an important role. Geothermal heat flow (GHF) is one of the least constrained solid Earth components but has a significant influence on the visco-elastic behavior of the lithosphere and the thermal state at the base of the ice sheet. Estimations of Antarctic GHF seldom come from direct measurements and rely on indirect methods based on geophysical observations. Forward models using constraints on lithospheric isotherms and assumptions on uniform thermal parameters exhibit large differences, both in amplitude and spatial distribution of the calculated heat flow. The consistency of such models is explored using a Bayesian inversion approach in an effort to reconcile different modeled lithospheric structures. Further, a machine learning approach is adopted that enables a statistical derivation of GHF incorporating multiple global geophysical data sets and in situ heat flow measurements. Lastly, a novel joint inversion approach is applied to magnetic and gravity data to invert for the crustal structure of the Wilkes Land region in East Antarctica and South Australia. This improves the understanding of the subglacial geology and small-scale GHF contributions. The methods and results presented in this thesis are relevant for the thermal modeling of ice sheets and the lithosphere, especially with regard to understanding the coupling between ice and solid Earth. Doctoral or Postdoctoral Thesis Antarc* Antarctic Antarctica East Antarctica Ice Sheet Wilkes Land MACAU: Open Access Repository of Kiel University Antarctic East Antarctica Wilkes Land ENVELOPE(120.000,120.000,-69.000,-69.000) |
institution |
Open Polar |
collection |
MACAU: Open Access Repository of Kiel University |
op_collection_id |
ftunivkiel |
language |
English |
topic |
thesis ddc:550 Antarctica heat flow Bayesian inversion machine learning joint inversion Gondwana |
spellingShingle |
thesis ddc:550 Antarctica heat flow Bayesian inversion machine learning joint inversion Gondwana Lösing, Mareen Isabell Susanne Antarctic Geothermal Heat Flow: Investigations by Geophysical and Statistical Analyses |
topic_facet |
thesis ddc:550 Antarctica heat flow Bayesian inversion machine learning joint inversion Gondwana |
description |
Antarctica’s contribution to past and future sea level changes is highly uncertain given the poor understanding of ice sheet dynamics in which solid Earth interactions play an important role. Geothermal heat flow (GHF) is one of the least constrained solid Earth components but has a significant influence on the visco-elastic behavior of the lithosphere and the thermal state at the base of the ice sheet. Estimations of Antarctic GHF seldom come from direct measurements and rely on indirect methods based on geophysical observations. Forward models using constraints on lithospheric isotherms and assumptions on uniform thermal parameters exhibit large differences, both in amplitude and spatial distribution of the calculated heat flow. The consistency of such models is explored using a Bayesian inversion approach in an effort to reconcile different modeled lithospheric structures. Further, a machine learning approach is adopted that enables a statistical derivation of GHF incorporating multiple global geophysical data sets and in situ heat flow measurements. Lastly, a novel joint inversion approach is applied to magnetic and gravity data to invert for the crustal structure of the Wilkes Land region in East Antarctica and South Australia. This improves the understanding of the subglacial geology and small-scale GHF contributions. The methods and results presented in this thesis are relevant for the thermal modeling of ice sheets and the lithosphere, especially with regard to understanding the coupling between ice and solid Earth. |
author2 |
Ebbing, Jörg Moorkamp, Max |
format |
Doctoral or Postdoctoral Thesis |
author |
Lösing, Mareen Isabell Susanne |
author_facet |
Lösing, Mareen Isabell Susanne |
author_sort |
Lösing, Mareen Isabell Susanne |
title |
Antarctic Geothermal Heat Flow: Investigations by Geophysical and Statistical Analyses |
title_short |
Antarctic Geothermal Heat Flow: Investigations by Geophysical and Statistical Analyses |
title_full |
Antarctic Geothermal Heat Flow: Investigations by Geophysical and Statistical Analyses |
title_fullStr |
Antarctic Geothermal Heat Flow: Investigations by Geophysical and Statistical Analyses |
title_full_unstemmed |
Antarctic Geothermal Heat Flow: Investigations by Geophysical and Statistical Analyses |
title_sort |
antarctic geothermal heat flow: investigations by geophysical and statistical analyses |
publishDate |
2022 |
url |
https://nbn-resolving.org/urn:nbn:de:gbv:8:3-2022-00820-3 https://macau.uni-kiel.de/receive/macau_mods_00003271 https://macau.uni-kiel.de/servlets/MCRFileNodeServlet/macau_derivate_00004439/Thesis_Loesing.pdf |
long_lat |
ENVELOPE(120.000,120.000,-69.000,-69.000) |
geographic |
Antarctic East Antarctica Wilkes Land |
geographic_facet |
Antarctic East Antarctica Wilkes Land |
genre |
Antarc* Antarctic Antarctica East Antarctica Ice Sheet Wilkes Land |
genre_facet |
Antarc* Antarctic Antarctica East Antarctica Ice Sheet Wilkes Land |
op_relation |
https://nbn-resolving.org/urn:nbn:de:gbv:8:3-2022-00820-3 https://macau.uni-kiel.de/receive/macau_mods_00003271 https://macau.uni-kiel.de/servlets/MCRFileNodeServlet/macau_derivate_00004439/Thesis_Loesing.pdf |
op_rights |
https://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
_version_ |
1802647272476901376 |