View graph of relations

Livia Kathleen Kother - Lecturer

We present a technique for modelling the lithospheric magnetic field based on estimation of equivalent
potential field sources. As a first demonstration we present an application to magnetic field
measurements made by the CHAMP satellite during the period 2009-2010. Three component vector
field data are utilized at all latitudes. Estimates of core and large-scale magnetospheric sources are
removed from the satellite measurements using the CHAOS-4 model. Quiet-time and night-side data
selection criteria are also employed to minimize the influence of the ionospheric field. The model for the
remaining lithospheric magnetic field consists of magnetic point sources (monopoles) arranged in an
icosahedron grid with an increasing grid resolution towards the airborne survey area. The
corresponding source values are estimated using an iteratively reweighted least squares algorithm that
includes model regularization (either quadratic or maximum entropy) and Huber weighting. Data error
covariance matrices are implemented, accounting for the dependence of data error variances on quasidipole
latitudes. Results show good consistency with the CM5 and MF7 models for spherical harmonic
degrees up to n = 95. Advantages of the equivalent source method include its local nature and the
ease of transforming to spherical harmonics when needed. The method can also be applied in local,
high resolution, investigations of the lithospheric magnetic field, for example where suitable
aeromagnetic data is available. To illustrate this possibility, we present preliminary results from a case
study combining satellite measurements and local airborne scalar magnetic measurements of the
Norwegian coastline.
17 Dec 2014

Event (Conference)

Title2014 AGU Fall Meeting
CitySan Francisco, CA
CountryUnited States


  • LIthospheric Field, Monopoles


Download as:
Download as PDF
Select render style:
Download as HTML
Select render style:
Download as Word
Select render style:

Download statistics

No data available

ID: 105039600