A new method to determine paleosecular variation

Abstract

This study is based on synthetic virtual geomagnetic pole distributions simulated by the sum of a Fisherian distribution characteristic of paleosecular variation (PSV) and a uniform distribution representing transitional data resulting from reversals and excursions of the geomagnetic field. Using such simulations, the optimum cutoff angle to apply to estimate the most precise value of the angular standard deviation (ASD) characteristic of PSV is determined for variable ASD and random data percentage. A relation between this optimum cutoff angle ( A) and the expected ASD is deduced: A(°) = 1.8 ASD(°) + 5°. A recursive method for determining the characteristic ASD using this relation is proposed. It is compared with the classical selection method using a constant cutoff angle equal to 40°. The method proposed in the present paper gives much more regular results and especially corrects bias on low and high ASD values obtained with the classical method. The proposed method should be important for PSV modeling because the lowest and highest ASD are the most constraining. The relation cited above could also be used in magnetostratigraphy to limit the domain of transitional geomagnetic poles.