An Object‐Oriented Bayesian Gravity Inversion Scheme for Inferring Density Anomalies in Planetary Interiors
Abstract Gravity inversions have contributed greatly to our knowledge of the interior of planetary bodies and the processes that shaped them. However, previous global gravity inversion methods neglect the inference of mantle density anomalies when using techniques to decrease the non‐uniqueness of t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Geophysical Union (AGU)
2023-07-01
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| Series: | Earth and Space Science |
| Online Access: | https://doi.org/10.1029/2023EA002853 |
| _version_ | 1827578960611901440 |
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| author | Kristel Izquierdo Vedran Lekić Laurent G. J. Montési |
| author_facet | Kristel Izquierdo Vedran Lekić Laurent G. J. Montési |
| author_sort | Kristel Izquierdo |
| collection | DOAJ |
| description | Abstract Gravity inversions have contributed greatly to our knowledge of the interior of planetary bodies and the processes that shaped them. However, previous global gravity inversion methods neglect the inference of mantle density anomalies when using techniques to decrease the non‐uniqueness of the inversion. In this work, we present a novel global gravity inversion algorithm, named THeBOOGIe, suited to inferring global‐scale density anomalies within the crust and mantle of planetary bodies. The algorithm embraces the nonuniqueness inherent in gravity inversions by not prescribing at the outset a density interface or depth range of interest. Instead, the method combines a Bayesian approach with a flexible incorporation of prior geological or geophysical information to infer density anomalies at any depth. A validation test using synthetic lunar‐like gravity data shows that THeBOOGIe can constrain the lateral location of crustal density anomalies but tends to overestimate their thicknesses. Importantly, THeBOOGIe can detect deep mantle density anomalies and quantify the level of confidence in the inferred density models. Our results show that THeBOOGIe can provide complementary information to one‐dimensional seismic models of the interior of the terrestrial planets and the Moon by constraining density anomalies that are not spherically symmetric. Additionally, THeBOOGIe is specially suited to constraining the interior of partially differentiated bodies where these large‐scale density anomalies are more likely to exist. Finally, thanks to the flexible use of priors, THeBOOGIe is an essential tool to understand the interior of planetary bodies lacking additional constraints. |
| first_indexed | 2024-03-08T21:55:56Z |
| format | Article |
| id | doaj.art-4f285547de2740b1bf351b0bbb7b4d48 |
| institution | Directory Open Access Journal |
| issn | 2333-5084 |
| language | English |
| last_indexed | 2024-03-08T21:55:56Z |
| publishDate | 2023-07-01 |
| publisher | American Geophysical Union (AGU) |
| record_format | Article |
| series | Earth and Space Science |
| spelling | doaj.art-4f285547de2740b1bf351b0bbb7b4d482023-12-19T22:01:29ZengAmerican Geophysical Union (AGU)Earth and Space Science2333-50842023-07-01107n/an/a10.1029/2023EA002853An Object‐Oriented Bayesian Gravity Inversion Scheme for Inferring Density Anomalies in Planetary InteriorsKristel Izquierdo0Vedran Lekić1Laurent G. J. Montési2University of Maryland College Park MD USAUniversity of Maryland College Park MD USAUniversity of Maryland College Park MD USAAbstract Gravity inversions have contributed greatly to our knowledge of the interior of planetary bodies and the processes that shaped them. However, previous global gravity inversion methods neglect the inference of mantle density anomalies when using techniques to decrease the non‐uniqueness of the inversion. In this work, we present a novel global gravity inversion algorithm, named THeBOOGIe, suited to inferring global‐scale density anomalies within the crust and mantle of planetary bodies. The algorithm embraces the nonuniqueness inherent in gravity inversions by not prescribing at the outset a density interface or depth range of interest. Instead, the method combines a Bayesian approach with a flexible incorporation of prior geological or geophysical information to infer density anomalies at any depth. A validation test using synthetic lunar‐like gravity data shows that THeBOOGIe can constrain the lateral location of crustal density anomalies but tends to overestimate their thicknesses. Importantly, THeBOOGIe can detect deep mantle density anomalies and quantify the level of confidence in the inferred density models. Our results show that THeBOOGIe can provide complementary information to one‐dimensional seismic models of the interior of the terrestrial planets and the Moon by constraining density anomalies that are not spherically symmetric. Additionally, THeBOOGIe is specially suited to constraining the interior of partially differentiated bodies where these large‐scale density anomalies are more likely to exist. Finally, thanks to the flexible use of priors, THeBOOGIe is an essential tool to understand the interior of planetary bodies lacking additional constraints.https://doi.org/10.1029/2023EA002853 |
| spellingShingle | Kristel Izquierdo Vedran Lekić Laurent G. J. Montési An Object‐Oriented Bayesian Gravity Inversion Scheme for Inferring Density Anomalies in Planetary Interiors Earth and Space Science |
| title | An Object‐Oriented Bayesian Gravity Inversion Scheme for Inferring Density Anomalies in Planetary Interiors |
| title_full | An Object‐Oriented Bayesian Gravity Inversion Scheme for Inferring Density Anomalies in Planetary Interiors |
| title_fullStr | An Object‐Oriented Bayesian Gravity Inversion Scheme for Inferring Density Anomalies in Planetary Interiors |
| title_full_unstemmed | An Object‐Oriented Bayesian Gravity Inversion Scheme for Inferring Density Anomalies in Planetary Interiors |
| title_short | An Object‐Oriented Bayesian Gravity Inversion Scheme for Inferring Density Anomalies in Planetary Interiors |
| title_sort | object oriented bayesian gravity inversion scheme for inferring density anomalies in planetary interiors |
| url | https://doi.org/10.1029/2023EA002853 |
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