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.

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.

A document by Song Zhao. Click on the document to view its contents.

Pigmentary hematite carries important signals in paleomagnetic and paleoenvironmental studies. However, weak magnetism and the assumption that it has high magnetic coercivity prevents prevents routine identification of the size distribution of pigmentary hematite, especially for fine particle sizes. We present a strategy for estimating joint hematite particle volume and microcoercivity (f (V, Hk0)) distributions from low-temperature demagnetization curves and thermal fluctuation tomography (TFT) of pigmentary hematite in bulk samples of Triassic-Jurassic Inuyama red chert, Japan. The coercivity of the pigmentary hematite increases exponentially with decreasing temperature, following a modified Kneller’s law, where microcoercivity has a wide but approximately symmetric distribution in logarithmic space from ~1 tesla to tens of tesla. All of the red chert samples contain stable single domain (SSD) hematite with 35 - 160 nm diameter; a significant superparamagnetic (SP) hematite population with sizes down to several nanometers also occurs in Jurassic samples. The SP/SSD threshold size is estimated to be 8 - 18 nm in these samples. The fine particle size of the pigmentary hematite is evident in its low median unblocking temperature (194 °C to 529 °C) and, thus, this hematite may contribute to all four paleomagnetic components identified in published thermal magnetization studies of the Inuyama red chert. In this work, uniaxial anisotropy and magnetization switching via coherent rotation are assumed. Uniaxial anisotropy is often dominant in fine-grained hematite, although the dominant anisotropy type should be evaluated before using TFT. This approach is applicable to studies that require knowledge of coercivity and size distributions of hematite pigments.

Global ice volume (sea level) and deep-sea temperature are key measures of Earth’s climatic state. We synthesize evidence for multi-centennial to millennial ice-volume and deep-sea temperature variations over the past 40 million years, which encompass the early glaciation of Antarctica at ~34 million years ago (Ma), the end of the Middle Miocene Climate Optimum, and the descent into bipolar glaciation from ~3.4 Ma. We compare different sea-level and deep-water temperature reconstructions to build a resource for validating long-term numerical model-based approaches. We present: (a) a new template synthesis of ice-volume and deep-sea temperature variations for the past 5.3 million years; (b) an extended template for the interval between 5.3 and 40 Ma; and (c) a discussion of uncertainties and limitations. We highlight key issues associated with glacial state changes in the geological record from 40 Ma to present that require attention in further research. These include offsets between calibration-sensitive versus thermodynamically guided deep-sea paleothermometry proxy measurements; a conundrum related to the magnitudes of sea-level and deep-sea temperature change at the Eocene-Oligocene transition at 34 Ma; a discrepancy in deep-sea temperature levels during the Middle Miocene; and a hitherto unquantified non-linear reduction of glacial deep-sea temperatures through the past 3.4 million years toward a near-freezing deep-sea temperature asymptote, while sea level stepped down in a more uniform manner. Uncertainties in proxy-based reconstructions hinder further distinction of “reality” among reconstructions. It seems more promising to further narrow this using three-dimensional ice-sheet models with realistic ice-climate-ocean-topography-lithosphere coupling, as computational capacities improve.

Magnetic hysteresis loops are an important tool in theoretical and applied rock magnetism with applications to paleointensities, paleoenvironmental analysis, and tectonic studies, among many others. Hence, information derived from these data is amongst the most ubiquitous rock magnetic data used by the Earth science community. Despite their prevalence, there are no general guidelines to aid scientists in obtaining the best possible data and no widely available software to allow the efficient analysis of hysteresis loop data using the most advanced and appropriate methods. Here we provide an outline of detrimental factors and simple approaches to measuring better hysteresis loops as well as introducing a new MATLAB software package called Hysteresis Loop analysis box (HystLab) for processing and analyzing loop data. This graphical user interface software is capable of reading the wide range of data formats that are generated by the multiple types of equipment typically used to measure hysteresis loops. HystLab provides an easy-to-use interface allowing users to visualize their data and perform advanced processing, including loop centering, drift correction, linear and approach to saturation high-field slope corrections, as well as loop fitting to improve the results from noisy specimens. A large number of hysteresis loop properties and statistics are calculated by HystLab and can be exported to text files for further analysis. All plots generated by HystLab are customizable and user preferences can be saved for future use. In addition, all plots can be exported to encapsulated postscript (EPS) files that are publication ready with little or no adjustment, greatly enhancing workflow productivity when processing and analyzing large data sets. HystLab is freely available for download at https://github.com/greigpaterson/HystLab and in combination with our simple measurement guide should help the paleo- and rock magnetic communities get the most from their hysteresis data.