Influence of Data Filters on the Position and Precision of Paleomagnetic Poles: What Is the Optimal Sampling Strategy?

To determine a paleopole, the paleomagnetic community commonly applies a loosely defined set of quantitative data filters that were established for studies of geomagnetic field behavior. These filters require costly and time-consuming sampling procedures, but whether they improve the precision and influence the position of paleopoles has not yet been systematically analyzed. In this study, we performed a series of experiments on four datasets which consist of 73–125 lava sites with 6–7 samples per lava. The datasets are from different regions and ages, and are large enough to represent paleosecular variation, yet include demonstrably unreliable paleomagnetic directions. We show that the systematic application of data filters based on within-site scatter (a maximum angular deviation filter on individual directions, a k-cutoff, a minimum number of samples per site, and eliminating the farthest outliers per site) cannot identify unreliable directions. We find instead that excluding unreliable directions relies on the subjective interpretation of the expert, highlighting the importance of making all data available following the FAIR principles. In addition, data filters that decrease the number of sites even have an adverse effect; they decrease the precision of the paleopole. Between-site scatter often outweighs within-site scatter, and when collecting paleomagnetic poles, the extra efforts put into collecting multiple samples per site are more effectively spent on collecting more single-sample sites