loading page

Bias Corrected Estimation of Paleointensity (BiCEP): An improved methodology for obtaining paleointensity estimates
  • Brendan J Cych,
  • Matthias Morzfeld,
  • Lisa Tauxe
Brendan J Cych
Scripps Institution of Oceanography, Scripps Institution of Oceanography

Corresponding Author:[email protected]

Author Profile
Matthias Morzfeld
Author Profile
Lisa Tauxe
University of California, San Diego, University of California, San Diego
Author Profile


The assumptions of paleointensity experiments are violated in many natural and archaeological materials, leading to Arai plots which do not appear linear and yield inaccurate paleointensity estimates, leading to bias in the result. Recently, paleomagnetists have adopted sets of “selection criteria” that exclude specimens with non linear Arai plots from the analysis, but there is little consensus in the paleomagnetic community on which set to use. In this paper, we present a statistical method we call Bias Corrected Estimation of Paleointensity (BiCEP), which assumes that the paleointensity recorded by each specimen is biased away from a true answer by an amount that is dependent a single metric of nonlinearity (the curvature parameter $\vec{k}$) on the Arai plot. We can use this empirical relationship to estimate the recorded paleointensity for a specimen where $\vec{k}=0$, i.e., a perfectly straight line. We apply the BiCEP method to a collection of 30 sites for which the true value of the original field is well constrained. Our method returns accurate estimates of paleointensity, with similar levels of accuracy and precision to restrictive sets of paleointensity criteria, but accepting as many sites as permissive criteria. The BiCEP method has a significant advantage over using these selection criteria because it achieves these accurate results without excluding large numbers of specimens from the analysis. It yields accurate, albeit imprecise estimates from sites whose specimens all fail traditional criteria. BiCEP combines the accuracy of the strictest selection criteria with the low failure rates of the less reliable ‘loose’ criteria.
Aug 2021Published in Geochemistry, Geophysics, Geosystems volume 22 issue 8. 10.1029/2021GC009755