Preprints
https://doi.org/10.5194/se-2021-16
https://doi.org/10.5194/se-2021-16

  17 Mar 2021

17 Mar 2021

Review status: this preprint is currently under review for the journal SE.

Comparing global seismic tomography models using the varimax Principal Component Analysis

Olivier de Viron1, Michel Van Camp2, Alexia Grabkowiak3, and Ana M. G. Ferreira4,5 Olivier de Viron et al.
  • 1Littoral, Environnement et Sociétés (LIENSs UMR7266 La Rochelle University – CNRS)
  • 2Royal Observatory of Belgium
  • 3Institut de Physique du Globe de Paris, University Paris Diderot
  • 4University College London
  • 5Instituto Superior Técnico, Universidade de Lisboa

Abstract. Global seismic tomography has greatly progressed in the past decades, with many global Earth models being produced by different research groups. Objective, statistical methods are crucial for the quantitative interpretation of the large amount of information encapsulated by the models as well as for unbiased model comparisons. We propose here to use a rotated version of the Principal Component Analysis (PCA) to compress the information, in order to ease the geological interpretation and model comparison. The method generates between 7 to 15 principal components (PC) for each of the seven tested global tomography models, capturing more than 97 % of the total variance of the model. Each PC consists of a vertical profile, to which a horizontal pattern is associated by projection. The depth profiles and the horizontal patterns enable examining the key characteristics of the main components of the models. Most of the information in the models is associated with a few features: Large Low Shear Velocity Provinces (LLSVPs) in the lowermost mantle, subduction signals and low velocity anomalies likely associated with mantle plumes in the upper and lower mantle, and ridges and cratons in the uppermost mantle. Importantly, all models highlight several independent components in the lower mantle that make between 36 % and 69 % of the total variance, depending on the model, which suggests that the lower mantle is more complex than traditionally assumed. Overall, we find that the varimax PCA is a useful additional tool for the quantitative comparison and interpretation of tomography models.

Olivier de Viron et al.

Status: open (until 28 Apr 2021)

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Olivier de Viron et al.

Olivier de Viron et al.

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Short summary
As the travel time of sismic wave depends on the Earth interior properties, seismic tomography uses it to infer distribution of the velocity anomalies, similarly as what is done in medical tomography. We propose to analyze the outputs of those models using the Varimax Principal Component Analyzis, which results in a compressed objective representation of the model, helping analyzis and comparison.