Toward seeing the Earth's interior through unbiased tomographic lenses
Geophysical tomographic studies traditionally exploit linear, damped least-squares inversion methods. We demonstrate that the resulting models can be locally biased toward lower or higher amplitudes in regions of poor data illumination, potentially causing physical misinterpretations. For example, w...
| Main Authors: | , , |
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| Format: | Journal article |
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American Geophysical Union
2017
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| _version_ | 1797065071999844352 |
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| author | Zaroli, C Koelemeijer, P Lambotte, S |
| author_facet | Zaroli, C Koelemeijer, P Lambotte, S |
| author_sort | Zaroli, C |
| collection | OXFORD |
| description | Geophysical tomographic studies traditionally exploit linear, damped least-squares inversion methods. We demonstrate that the resulting models can be locally biased toward lower or higher amplitudes in regions of poor data illumination, potentially causing physical misinterpretations. For example, we show that global model S40RTS is locally biased toward higher amplitudes below isolated receivers where ray paths are quasi vertical, such as on Hawaii. This leads to questions on the apparent low-velocity structure interpreted as the Hawaii hotspot. We prove that a linear Backus–Gilbert inversion scheme can bring the Earth's interior into focus through unbiased tomographic lenses, as its model estimates are constrained to be averages over the true model. It also efficiently computes the full generalized inverse required to infer both model resolution and its covariance, enabling quantitative interpretations of tomographic models. |
| first_indexed | 2024-03-06T21:23:24Z |
| format | Journal article |
| id | oxford-uuid:4241823a-c451-47d5-9afb-fe140b824826 |
| institution | University of Oxford |
| last_indexed | 2024-03-06T21:23:24Z |
| publishDate | 2017 |
| publisher | American Geophysical Union |
| record_format | dspace |
| spelling | oxford-uuid:4241823a-c451-47d5-9afb-fe140b8248262022-03-26T14:48:22ZToward seeing the Earth's interior through unbiased tomographic lensesJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:4241823a-c451-47d5-9afb-fe140b824826Symplectic Elements at OxfordAmerican Geophysical Union2017Zaroli, CKoelemeijer, PLambotte, SGeophysical tomographic studies traditionally exploit linear, damped least-squares inversion methods. We demonstrate that the resulting models can be locally biased toward lower or higher amplitudes in regions of poor data illumination, potentially causing physical misinterpretations. For example, we show that global model S40RTS is locally biased toward higher amplitudes below isolated receivers where ray paths are quasi vertical, such as on Hawaii. This leads to questions on the apparent low-velocity structure interpreted as the Hawaii hotspot. We prove that a linear Backus–Gilbert inversion scheme can bring the Earth's interior into focus through unbiased tomographic lenses, as its model estimates are constrained to be averages over the true model. It also efficiently computes the full generalized inverse required to infer both model resolution and its covariance, enabling quantitative interpretations of tomographic models. |
| spellingShingle | Zaroli, C Koelemeijer, P Lambotte, S Toward seeing the Earth's interior through unbiased tomographic lenses |
| title | Toward seeing the Earth's interior through unbiased tomographic lenses |
| title_full | Toward seeing the Earth's interior through unbiased tomographic lenses |
| title_fullStr | Toward seeing the Earth's interior through unbiased tomographic lenses |
| title_full_unstemmed | Toward seeing the Earth's interior through unbiased tomographic lenses |
| title_short | Toward seeing the Earth's interior through unbiased tomographic lenses |
| title_sort | toward seeing the earth s interior through unbiased tomographic lenses |
| work_keys_str_mv | AT zarolic towardseeingtheearthsinteriorthroughunbiasedtomographiclenses AT koelemeijerp towardseeingtheearthsinteriorthroughunbiasedtomographiclenses AT lambottes towardseeingtheearthsinteriorthroughunbiasedtomographiclenses |