Error Analysis of Total Field Models Derived from POGS Data

Abstract

Scalar magnetic data from the POGS satellite are analysed for the 1991-1993 period. Models of the main geomagnetic field are computed using an iterative least-squares method. Vector components of the field derived from these models display large errors known as the Backus effect. A method for estimating the noise level in global data in the form of an equivalent gaussian noise is introduced and POGS data are shown to have a standard deviation of about σ = 45 nT. Despite this high noise level, it is shown that POGS data can be used to improve models derived from observatory vector data. It is also shown that the Backus effect can be significantly reduced by using some accurate vector ground-based measurements of the main field at observatories located near the equator. Monthly models are computed using both POGS and observatory data for which monthly mean values are available at POGS period. Local corrections applied to observatory measurements are computed by comparing observatory monthly mean values with Magsat models. The results are shown to be improved when these corrections are applied to the observatory data, confirming that they correspond essentially to stationary short-wavelength crustal anomalies.