Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/5884
AuthorsSoldati, G.* 
Boschi, L.* 
Deschamps, F.* 
Giardini, D.* 
TitleInferring radial models of mantle viscosity from gravity (GRACE) data and an evolutionary algorithm
Issue DateSep-2009
Series/Report no./176 (2009)
DOI10.1016/j.pepi.2009.03.013
URIhttp://hdl.handle.net/2122/5884
Keywordsmantle rheology
inverse theory
Subject Classification05. General::05.01. Computational geophysics::05.01.03. Inverse methods 
AbstractConvective flow in the mantle can be thought of (and modeled) as exclusively driven by density hetero- geneities in the mantle itself, and the resulting lateral variations in the Earth’s gravity field. With this assumption, and a model of mantle rheology, a theoretical relationship can be found between 3D mantle structure and flow-related quantities that can be measured on the Earth’s surface, like free-air gravity anomalies. This relationship can be used to set up an inverse problem, with 1D mantle viscosity as a solu- tion. In the assumption that seismic velocity anomalies be of purely thermal origin, and related to density anomalies by a simple scaling factor, we invert the large-scale length component of the above-mentioned measurements jointly with seismic observations (waveforms and/or travel times) to derive an accurate 5-layer spherically symmetric model of upper- and lower-mantle viscosity. We attempt to account for non-uniqueness in the inverse problem by exploring the solution space, formed of all possible radial pro- files of Earth viscosity, by means of a non-deterministic global optimization method: the evolutionary algorithm (EA). For each sampled point of the solution space, a forward calculation is conducted to deter- mine a map of gravity anomalies, whose similarity to GRACE (gravity recovery and climate experiment) is then measured; the procedure is iterated to convergence, according to EA criteria. The robustness of the inversion is tested by means of synthetic tests, indicating that our gravity data set is able to constrain less than 6 radial layers, each with uniform viscosity. Independently of the tomographic model or the scaling factor adopted to convert seismic velocity into density structure, the EA optimization method finds viscosity profiles characterized by low-viscosity in a depth range corresponding to the transition zone, and relatively uniform elsewhere.
Appears in Collections:Papers Published / Papers in press

Files in This Item:
File Description SizeFormat 
2009 soldati et al PEPI (mantle viscosity from gravity data).pdfpublished article1.99 MBAdobe PDFView/Open
paper8_fig.pdfnext-to-last manuscript 970.02 kBAdobe PDFView/Open
Show full item record

Page view(s)

75
Last Week
0
Last month
2
checked on Aug 21, 2017

Download(s)

113
checked on Aug 21, 2017

Google ScholarTM

Check

Altmetric