A document by Brendan Cych. Click on the document to view its contents.

Some rocks contain multiple remanence “components”, each of which preserves a record of a different magnetic field. The temperature ranges over which these remanence components demagnetize can overlap, making it difficult to determine their directions. We present a data analysis tool called Thermal Resolution Of Unblocking Temperatures (TROUT) that treats the process of thermal demagnetization as a function of temperature (or alternating field demagnetization as a function of coercivity). TROUT models the unblocking temperature distributions of components in a demagnetization experiment, allowing these distributions to overlap. TROUT can be used to find the temperatures over which paleomagnetic directions change and when two directional components overlap resulting in curved demagnetization trajectories. When applied to specimens given multi-component Thermoremanent Magnetizations (TRMs) in the laboratory, the TROUT method estimates the temperature at which the partial TRMs were acquired to within one temperature step, even for specimens with significant overlap. TROUT has numerous applications: knowing the temperature at which the direction changes is useful for experiments in which the thermal history of a specimen is of interest (e.g. emplacement temperature of pyroclastic deposits, re-heating of archaeological artifacts, reconstruction of cooling rates of igneous bodies). The ability to determine whether a single component or multiple components are demagnetizing at a given temperature is useful for choosing appropriate ranges of temperatures to use in paleointensity experiments. Finally, the width of the range of temperature overlap may be useful for inferring the domain state of magnetic mineral assemblages.

Micromagnetic modelling allows the systematic study of the effects of particle size and shape on the first-order reversal curve (FORC) magnetic hysteresis response for magnetite particles in the single-domain (SD) and pseudo-single domain (PSD) particle size range. The interpretation of FORCs, though widely used, has been highly subjective.  Here, we use micromagnetics to model randomly oriented distributions of particles to allow more physically meaningful interpretations.  We show that one commonly found type of PSD particle - namely single vortex (SV) particles - has far more complex signals than SD particles, with multiple peaks and troughs in the FORC distribution, where the peaks have higher switching fields for larger SV particles. Particles in the SD to SV transition zone have the lowest switching fields. Symmetrical and prolate particles display similar behavior, with distinctive peaks forming near the vertical axis of the FORC diagram. In contrast, highly oblate particles produce `butterfly' structures, suggesting that these are potentially diagnostic of particle morphology. We also consider FORC diagrams for distributions of particle sizes and shapes and produce an online application that users can use to build their own FORC distributions.  There is good agreement between the model predictions for distributions of particle sizes and shapes, and the published experimental literature.

Magnetic hysteresis measurements are routinely made in the Earth and planetary sciences to identify geologically meaningful  magnetic recorders, and to study variations in present and past environments. Interpreting magnetic hysteresis data in terms of domain state (particle size)  and paleomagnetic stability are major motivations behind undertaking these measurements, but the interpretations remain  fraught with challenges and ambiguities. To shed new light on these ambiguities, we have undertaken a systematic micromagnetic study to quantify the magnetic hysteresis behavior of room-temperature magnetite as a function of particle size (50-195 nm; equivalent spherical volume diameter) and shape (oblate, prolate and equant); our models span uniformly magnetized single domain (SD) to non-uniformly magnetized single vortex (SV) states. Within our models the reduced magnetization  marks a clear boundary between SD (≥0.5) and SV (<0.5) magnetite. We further identify particle sizes and shapes with unexpectedly low coercivity and coercivity of remanence. These low coercivity regions correspond to magnetite particles that typically have multiple possible magnetic domain states, which has been previously linked to a zone of unstable magnetic recorders. Of all hysteresis parameters investigated, transient hysteresis is most sensitive to particles that exhibit such domain state multiplicity, leading us to suggest that transient behavior be more routinely measured during rock magnetic investigations.

This paper addresses one of the critical questions of scientific inquiry: How do we know when a given data set is representative of the phenomenon being examined? For paleomagnetists, the question is often whether a particular dataset sufficiently averaged paleosecular variation (PSV). To this aim, we updated an existing PSV dataset that now comprises 2441 site mean directions from 94 individual studies (PSV10-24). Minimal filtering for data quality resulted in 1619 sites from 90 publications. Fitting PSV10-24 with three newly defined parameters as well as two existing ones form the basis of a Giant Gaussian Process field model (THG24) consistent with the data. Drawing directions from THG24 yields directional distributions predicted for a given latitude allowing a comparison between empirical distributions and the cumulative distribution function generated by the model. This tests whether the observed data adequately averaged out PSV according to THG24. Sedimentary datasets that may have experienced inclination shallowing can be corrected using an (un)flattening factor that yields directions satisfying THG24 in a newly-defined, four-parameter space. This approach builds on the Elongation-Inclination (E/I) method of Tauxe and Kent (2004), so the approach introduced here is called SVEI. We show examples of the use of SVEI and explain how to use this newly developed python code that is publicly available in the PmagPy GitHub repository.

The ability of rocks to hold a reliable record of the ancient geomagnetic field depends on the structure and stability of magnetic domain-states contained within the rock’s magnetic particles. In paleomagnetic studies, the Day plot is an easily constructed graph of magnetic hysteresis parameters that is frequently used (and mis-used) to estimate the likely magnetic recording stability of samples. Often samples plot in the region of the Day plot attributed to so-called pseudo-single-domain (PSD) particles with little under standing of the implications for domain-states or recording fidelity. Here we use micromagnetic models to explore the hysteresis parameters of magnetite particles with idealized prolate and oblate truncated-octahedral geometries containing single domain (SD), single-vortex (SV) and occasionally multi-vortex (MV) states. We show that these do main states exhibit a well-defined trend in the Day plot that extends from the SD region well into the multi-domain (MD) region, all of which are likely to be stable remanence carriers. We suggest that although the interpretation of the Day plot and its vari33 ants might be subject to ambiguities, if the magnetic mineralogy is known, it can still provide some useful insights about paleomagnetic specimens’ dominant domain state, average particle sizes and, consequently, their paleomagnetic stability.

Twenty-two sites, subjected to an IZZI-modified Thellier-Thellier experiment and strict selection criteria, recover a paleomagnetic axial dipole moment (PADM) of 62.24$\pm$ 30.6 ZAm$^2$ in Northern Israel over the Pleistocene (0.012 - 2.58 Ma). Pleistocene data from comparable studies from Antarctica, Iceland, and Hawaii, re-analyzed using the same criteria and age range, show that the Northern Israeli data are on average slightly higher than those from Iceland (PADM = 53.8 $\pm$ 23 ZAm$^2$, n = 51 sites) and even higher than the Antarctica average %\cite{asefaw21} (PADM = 40.3 $\pm$ 17.3 ZAm$^2$, n = 42 sites). Also, the data from the Hawaiian drill core, HSDP2, spanning the last half million years (PADM = 76.7 $\pm$ 21.3 ZAm$^2$, n = 59 sites) are higher than those from Northern Israel. These results, when compared to Pleistocene results filtered from the PINT database (www.pintdb.org) suggest that data from the Northern hemisphere mid-latitudes are on average higher than those from the southern hemisphere and than those from latitudes higher than 60$^{\circ}$N. The weaker intensities found at high (northern and southern) latitudes therefore, cannot be attributed to inadequate spatio-temporal sampling of a time-varying dipole moment or low quality data. The high fields in mid-latitude Northern hemisphere could result from long-lived non-axial dipole terms in the geomagnetic field with episodes of high field intensities occurring at different times in different longitudes. This hypothesis is supported by an asymmetry predicted from the Holocene, 100 kyr, and five million year time-averaged geomagnetic field models.

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.

The theory for recording of thermally blocked remanences predicts a quasi-linear relationship between low fields like the Earth’s in which rocks cool and acquire a magnetization. This serves as the foundation for estimating ancient magnetic field strengths. Addressing long-standing questions concerning Earth’s magnetic field require a global paleointensity dataset, but recovering the ancient field strength is complicated because the theory only pertains to uniformly magnetized particles. A key requirement of a paleointensity experiment is that a magnetization blocked at a given temperature should be unblocked by zero-field reheating to the same temperature. However, failure of this requirement occurs frequently and the causes and consequences of failure are poorly understood. Recent experiments demonstrate that the remanence in many samples typical of those used in paleointensity experiments is unstable, and exhibits an ”aging’ effect in which the unblocking temperature spectrum changes over only a few years resulting in non-ideal experimental behavior. While a fresh remanenence may conform to the requirement of equality of blocking and unblocking temperatures, aged remanences may not. Blocking temperature spectra can be unstable (fragile), which precludes reproduction of the conditions under which the original magnetization was acquired. This limits our ability to acquire accurate and precise ancient magnetic field strength estimates because differences between known and estimated fields can be significant (up to 10 μT) for individual specimens, with a low field bias. Fragility of unblocking temperature spectra appears to be related to grain size and may be related to features observed in first-order reversal curves.

This article is composed of three independent commentaries about the state of ICON principles (Goldman et al., 2021) in the Geomagnetism, Paleomagnetism, and Electromagnetism (GPE) section and discussion on the opportunities and challenges of adopting them. Each commentary focuses on a different topic: Global collaboration, reproducibility, data sharing and infrastructure; Inclusive equitable, and accessible science: Involvement, challenges, and support of early career, BIPOC, women, LGBTQIA+, and/or disabled researchers; Community engagement, citizen science, education, and stakeholder involvement. Data sharing practices and open repository use still varies strongly between GPE communities. Some have a long tradition of data sharing, others are only starting it. Globally, GPE leadership is strongly dominated by white males and diversity may increase through the creation of Science Equality Commissions. Improved global stakeholder involvement can increase research impacts and help fight inequalities. In all investigated topics we see promising beginnings but also recognize obstacles that include a lack of funding, a lack of understanding of diversity, and prioritizing short-term gain over long-term benefit. Nonetheless, we are hopeful that our community will embrace ICON science.

MagIC (earthref.org/MagIC (https://www2.earthref.org/MagIC)) is an organization dedicated to improving research capacity in the Earth and Ocean sciences by maintaining an open community digital data archive for rock and paleomagnetic data with portals that allow scientists and others to access to archive, search, visualize, download, and combine versioned datasets. A recent focus of MagIC has been to make our data more accessible, discoverable, and interoperable to further this goal. In collaboration with the GeoCodes/P418 group, we have continued to add more schema.org metadata fields to our data sets which allows for more detailed and deep automated searches. We are involved with the Earth Science Information Partners (ESIP) schema.org cluster which is working on extending the schema.org schema to the sciences. MagIC has been focusing on geo- science issues such as standards for describing deep time. We are also collaborating with the European Plate Observing System (EPOS)’s Thematic Core Service Multi-scale laboratories (TCS MSL). MagIC is sending its contributions’ metadata to TCS MSL via DataCite records for representation in the EPOS system. This collaboration should allow European scientists to use MagIC as an official repository for European rock and paleomagnetic data and help prevent the fragmenting of the global paleomagnetic and rock data into many separate data repositories. By having our data well described by an EarthCube supported standard (schema.org/JSON-LD), we will be able to more easily share data with other EarthCube projects in the future.

Magnetics Information Consortium (MagIC), hosted at http://earthref.org/MagIC, is a database that serves as a Findable, Accessible, Interoperable, Reusable (FAIR) archive for paleomagnetic and rock magnetic data. It has a flexible, comprehensive data model that can accomodate most kinds of paleomagnetic 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. It is available through github.com/PmagPy. Because PmagPy requires installation of Python and the software package, there is a speed bump for many practitioners on beginning to use the software. In order to make the software and MagIC more accessible to the broad spectrum of scientists interested in paleo and rock magnetism, we have prepared a set of Jupyter notebooks, hosted on jupyterhub.earthref.org which serve a set of purposes. 1) There is a complete course in Python for Earth Scientists, and 2) a set of notebooks that introduce PmagPy (importing the software package from the github repository). These notebooks illustrate how to conduct statistical analyses, synthesize create data and create data visualizations of the type that are typically included in papers in the field. The notebooks also demonstrate how to prepare data from the laboratory for the MagIC database. This pathway gives additional tools to researchers so that they can satisfy data archiving requirements from NSF and publishers such as AGU.