Details

Autor(en) / Beteiligte

• Marignier, Augustin
• Ferreira, Ana M. G.
• Kitching, Thomas

Titel

The Probability of Mantle Plumes in Global Tomographic Models

Ist Teil von

• Geochemistry, geophysics, geosystems : G3, 2020-09, Vol.21 (9), p.n/a

Ort / Verlag

Washington: Blackwell Publishing Ltd

Erscheinungsjahr

2020

Link zum Volltext

Quelle

Wiley Online Library Journals Frontfile Complete

Beschreibungen/Notizen

• While the downward mass flux in the Earth's deep interior is well constrained by seismic tomography, the upward flux is still poorly understood and debated. Recent tomography studies suggest that we are now starting to resolve deep mantle plume structures. However, a lack of uncertainty quantification impedes a full assessment of their significance and whether they are statistically distinct from noise. This work uses a spherical wavelet transform and random noise realizations to quantify the probability of deep plume‐like features in six recent global tomographic models. We find that out of 50 possible mantle deep plumes, 12 are highly likely, with probabilities larger than 80%, and 12 are likely, with probability between 70% and 80%. Objective, quantitative approaches as proposed in this study should be used for model interpretation. The five most likely deep mantle plumes are Tahiti, Macdonald, East Africa, Pitcairn, and Marquesas, which have some of the largest buoyancy fluxes estimated in a previous study that used hotspot swell volumes. This could resolve past discrepancies between deep mantle plumes inferred by visual analysis of tomography models and flux estimations from hotspot swell data. In addition, a notable unlikely deep mantle plume is Yellowstone, with probability lower than 50%. We also identify a likely deep mantle plume associated with the Amsterdam‐St Paul hotspot, a region scarcely discussed in previous studies and that deserves future investigation. Hence, our automated, objective approach is a valuable alternative approach for the quantitative interpretation of tomographic models. Plain Language Summary There are now many seismic images of the Earth's deep interior, but inconsistencies between the images and a lack of error quantification make it difficult to interpret them. We develop a tool to objectively and automatically assess the probabilities of features in the images being real rather than artifacts. Specifically, we investigate narrow upwellings of hot material called mantle plumes. These are connected with areas of surface volcanism that can be challenging to image seismically. We identify the plumes with highest probability and also identify one plume that has been rarely discussed in previous seismic studies. Key Points This is a new technique for interpreting tomographic models numerically and objectively based on a wavelet transform and noise simulations The most likely plumes are at the Tahiti, Macdonald, East Africa, Pitcairn, Marquesas, and Canary Islands hotspots The Amsterdam‐St Paul hotspot is likely to have a deep plume in many models, whereas Yellowstone is unlikely