Bayesian inference in geomagnetism

Details Bayesian inference in geomagnetism Bayesian inference in geomagnetism

Jan 1988

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1988geoj...92..125b&link_type=abstract

Geophysical Journal (ISSN 0952-4592), vol. 92, Jan. 1988, p. 125-142.

Computer Science

Numerical Analysis

77

Bayes Theorem, Earth Core, Earth Mantle, Geomagnetism, Heat Transmission, Stochastic Processes, Error Analysis, Numerical Analysis

Scientific paper

The inverse problem in empirical geomagnetic modeling is investigated, with critical examination of recently published studies. Particular attention is given to the use of Bayesian inference (BI) to select the damping parameter lambda in the uniqueness portion of the inverse problem. The mathematical bases of BI and stochastic inversion are explored, with consideration of bound-softening problems and resolution in linear Gaussian BI. The problem of estimating the radial magnetic field B(r) at the earth core-mantle boundary from surface and satellite measurements is then analyzed in detail, with specific attention to the selection of lambda in the studies of Gubbins (1983) and Gubbins and Bloxham (1985). It is argued that the selection method is inappropriate and leads to lambda values much larger than those that would result if a reasonable bound on the heat flow at the CMB were assumed.

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