The selection of paleointensity data is a challenging, but essential step for establishing data reliability. There is, however, no consensus as to how best to quantify paleointensity data and which data selection processes are most effective. To address these issues, we begin to lay the foundations for a more unified and theoretically justified approach to the selection of paleointensity data. We present a new compilation of standard definitions for paleointensity statistics to help remove ambiguities in their calculation. We also compile the largest-to-date data set of raw paleointensity data from historical locations and laboratory control experiments with which to test the effectiveness of commonly used sets of selection criteria. Although most currently used criteria are capable of increasing the proportion of accurate results accepted, criteria that are better at excluding inaccurate results tend to perform poorly at including accurate results and vice versa. In the extreme case, one widely used set of criteria, which is used by default in the ThellierTool software (v4.22), excludes so many accurate results that it is often statistically indistinguishable from randomly selecting data. We demonstrate that, when modified according to recent single domain paleointensity predictions, criteria sets that are no better than a random selector can produce statistically significant increases in the acceptance of accurate results and represent effective selection criteria. The use of such theoretically derived modifications places the selection of paleointensity data on a more justifiable theoretical foundation and we encourage the use of the modified criteria over their original forms. © 2014. American Geophysical Union. All Rights Reserved.

© 2015. American Geophysical Union. All Rights Reserved. Geomagnetic models based on direct observations since the 1830s show that the averaged relative change in field intensity on Earth's surface over the past 170 years is less than 4.8% per decade. It is unknown if these rates represent the typical behavior of secular variations due to insufficient temporal resolution of archaeomagnetic records from earlier periods. To address this question, we investigate two ancient slag mounds in Cyprus-Skouriotissa Vouppes (SU1, fourth to fifth centuries CE, 21 m in height), and Mitsero Kokkinoyia (MK1, seventh to fifth centuries BCE, 8 m in height). The mounds are multilayered sequences of slag and charcoals that accumulated near ancient copper production sites. We modeled the age-height relation of the mounds using radiocarbon dates, and estimated paleointensities using Thellier-type IZZI experiments with additional anisotropy, cooling rate, and nonlinear TRM assessments. To screen out ambiguous paleointensity interpretations, we applied strict selection criteria at the specimen/sample levels. To ensure objectivity, consistency, and robust error estimation, we employed an automatic interpretation technique and put the data available in the MagIC database. The analyses yielded two independent subcentury-scale paleointensity time series. The MK1 data indicate relatively stable field at the time the mound accumulated. In contrast, the SU1 data demonstrate changes that are comparable in magnitude to the fastest changes inferred from geomagnetic models. We suggest that fast changes observed in the published archaeomagnetic data from the Levant are driven by two longitudinally paired regions, the Middle East and South Africa, that show unusual activity in geomagnetic models.

© 2015. American Geophysical Union. All Rights Reserved. Geomagnetic models based on direct observations since the 1830s show that the averaged relative change in field intensity on Earth's surface over the past 170 years is less than 4.8% per decade. It is unknown if these rates represent the typical behavior of secular variations due to insufficient temporal resolution of archaeomagnetic records from earlier periods. To address this question, we investigate two ancient slag mounds in Cyprus-Skouriotissa Vouppes (SU1, fourth to fifth centuries CE, 21 m in height), and Mitsero Kokkinoyia (MK1, seventh to fifth centuries BCE, 8 m in height). The mounds are multilayered sequences of slag and charcoals that accumulated near ancient copper production sites. We modeled the age-height relation of the mounds using radiocarbon dates, and estimated paleointensities using Thellier-type IZZI experiments with additional anisotropy, cooling rate, and nonlinear TRM assessments. To screen out ambiguous paleointensity interpretations, we applied strict selection criteria at the specimen/sample levels. To ensure objectivity, consistency, and robust error estimation, we employed an automatic interpretation technique and put the data available in the MagIC database. The analyses yielded two independent subcentury-scale paleointensity time series. The MK1 data indicate relatively stable field at the time the mound accumulated. In contrast, the SU1 data demonstrate changes that are comparable in magnitude to the fastest changes inferred from geomagnetic models. We suggest that fast changes observed in the published archaeomagnetic data from the Levant are driven by two longitudinally paired regions, the Middle East and South Africa, that show unusual activity in geomagnetic models.

The Magnetics Information Consortium (MagIC) database provides an archive with a flexible data model for paleomagnetic and rock magnetic data. The PmagPy software package is a cross-platform and open-source set of tools written in Python for the analysis of paleomagnetic data that serves as one interface to MagIC, accommodating various levels of user expertise. PmagPy facilitates thorough documentation of sampling, measurements, data sets, visualization, and interpretation of paleomagnetic and rock magnetic experimental data. Although not the only route into the MagIC database, PmagPy makes preparation of newly published data sets for contribution to MagIC as a byproduct of normal data analysis and allows manipulation as well as reanalysis of data sets downloaded from MagIC with a single software package. The graphical user interface (GUI), Pmag GUI enables use of much of PmagPy's functionality, but the full capabilities of PmagPy extend well beyond that. Over 400 programs and functions can be called from the command line interface mode, or from within the interactive Jupyter notebooks. Use of PmagPy within a notebook allows for documentation of the workflow from the laboratory to the production of each published figure or data table, making research results fully reproducible. The PmagPy design and its development using GitHub accommodates extensions to its capabilities through development of new tools by the user community. Here we describe the PmagPy software package and illustrate the power of data discovery and reuse through a reanalysis of published paleointensity data which illustrates how the effectiveness of selection criteria can be tested.