A novel weighting method for satellite magnetic data and a new global magnetic field model

Abstract

A new data weighting scheme is introduced for satellite geomagnetic survey data. Data weights for individual satellite samples at 20-s spacing are derived from two ‘noise’ (or unmodelled signal) estimators for the sample. First, the standard deviation along the 20 s of satellite track, centred on each sample, is computed as a measure of local magnetic activity. Second a larger-scale noise estimator is defined in terms of a ‘local area vector activity’ (LAVA) index for the sample. This is derived from activity measured at the geographically nearest magnetic observatories to the sample point. Weighting of the satellite data by the inverse-sum-of-squares of these noise estimators then leads to a robust model of the field, the ‘Model of Earth’s Magnetic Environment 2008’, or MEME08, to about spherical harmonic degree 60. Our approach allows vector samples of the field to be used at all magnetic latitudes and, for example, results in a lithospheric magnetic field model with low spectral noise, comparable with other recent global models. We also do not require a particularly complex model parametrization, regularization, or prior data correction to remove estimates of unmodelled source fields