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  5. Statistical assessment of predictive modelling uncertainty: a geophysical case study
 
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Statistical assessment of predictive modelling uncertainty: a geophysical case study

Author(s)
Barzaghi, Riccardo 
Marotta, Anna Maria 
Splendore, Raffaele 
De Gaetani, Carlo 
Borghi, Alessandra 
Language
English
Obiettivo Specifico
1T. Struttura della Terra
Status
Published
JCR Journal
JCR Journal
Peer review journal
Yes
Title of the book
Geophysical Journal International 
Issue/vol(year)
/197 (2014)
Pages (printed)
22-32
Issued date
2014
DOI
10.1093/gji/ggt510
URI
https://www.earth-prints.org/handle/2122/12922
Keywords
  • Numerical solutions

  • Numerical approximati...

Abstract
When the results of geophysical models are compared with data, the uncertainties of the model are typically disregarded. This paper proposes a method for defining the uncertainty of a geophysical model based on a numerical procedure that estimates the empirical auto- and cross-covariances of model-estimated quantities. These empirical values are then fitted by proper covariance functions and used to compute the covariance matrix associated with the model predictions. The method is tested using a geophysical, spherical, thin-sheet finite element model of the Mediterranean region. Using a χ2 analysis, the model's estimated horizontal velocities are compared with the velocities estimated from permanent GPS stations while taking into account the model uncertainty through its covariance structure and the covariance of the GPS estimates. The results indicate that including the estimated model covariance in the testing procedure leads to lower observed χ2 values and might help a sharper identification of the best-fitting geophysical models.
Type
article
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[41]_Geophys. J. Int.-2014-Barzaghi-gji_ggt510.pdf

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3.24 MB

Format

Adobe PDF

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