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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 unblock 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/coercivity distributions of components in a demagnetization experiment, allowing these distributions to overlap. TROUT can be used to find the temperatures/coercivities 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 paleodirection/intensity experiments. Finally, the width of the range of temperature overlap may be useful for inferring the composition, grain size and domain state of magnetic mineral assemblages.

 

The assumptions of paleointensity experiments are violated in many natural and archeological 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 nonlinear Arai plots from the analysis, but there is little consensus in the paleomagnetic community on which set to use. In this study, 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) on the Arai plot. We can use this empirical relationship to estimate the recorded paleointensity for a specimen where, that is, 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 Southern San Andreas Fault (SSAF) in California is one of the most thoroughly studied faults in the world, but its configuration at seismogenic depths remains enigmatic in the Coachella Valley. We use a combination of space geodetic and seismic observations to demonstrate that the relatively straight southernmost section of the SSAF, between Thousand Palms and Bombay Beach, is dipping to the northeast at 60–80° throughout the upper crust (<10 km), including the shallow aseismic layer. We constrain the fault attitude in the top 2–3 km using inversions of surface displacements associated with shallow creep, and seismic data from a dense nodal array crossing the fault trace near Thousand Palms. The data inversions show that the shallow dipping structure connects with clusters of seismicity at depth, indicating a continuous throughgoing fault surface. The dipping fault geometry has important implications for the long‐term fault slip rate, the intensity of ground shaking during future large earthquakes, and the effective strength of the southern SAF.

 

We consider a stochastic differential equation model for Earth's axial magnetic dipole field. The model's parameters are estimated using diverse and independent data sources that had previously been treated separately. The result is a numerical model that is informed by the full paleomagnetic record on kyr to Myr time scales and whose outputs match data of Earth's dipole in a precisely defined feature-based sense. Specifically, we compute model parameters and associated uncertainties that lead to model outputs that match spectral data of Earth's axial magnetic dipole field but our approach also reveals difficulties with simultaneously matching spectral data and reversal rates. This could be due to model deficiencies or inaccuracies in the limited amount of data. More generally, the approach we describe can be seen as an example of an effective strategy for combining diverse data sets that is particularly useful when the amount of data is limited. 

Abstract. We consider a stochastic differential equation modelfor Earth's axial magnetic dipole field.Our goal is to estimate the model's parametersusing diverse and independent data sources that had previously been treated separately,so that the model is a valid representation of an expanded paleomagnetic recordon kyr to Myr timescales.We formulate the estimation problem within the Bayesian frameworkand define a feature-based posterior distributionthat describes probabilities of model parameters givena set of features derived from the data.Numerically, we use Markov chain Monte Carlo (MCMC)to obtain a sample-based representation of the posterior distribution.The Bayesian problem formulation and its MCMC solutionallow us to study the model's limitations and remaining posterior uncertainties.Another important aspect of our overall approach is thatit reveals inconsistencies between model and data or within the various data sets.Identifying these shortcomings is a first and necessary step towards building more sophisticated models or towards resolving inconsistencies within the data.The stochastic model we derive representsselected aspects of the long-term behavior of the geomagnetic dipole fieldwith limitations and errors that are well defined.We believe that such a model is useful (besides its limitations) for hypothesis testing and give a few examples of how the model can be used in this context. 

Simulations of the Argentine Basin have large uncertainties associated with quantities such as air‐sea exchanges of heat and carbon in current generation climate models and ocean reanalysis products. This is due to the complex topography, profound undersampling until recent years, and strong currents and mixing of subpolar and subtropical water masses in the basin. Because mixing of water masses is important here, model resolution is hypothesized to play an important role in estimating ocean quantities and determining overall budgets. We construct three regional ocean models with biogeochemistry at 1/3°, 1/6°, and 1/12° resolutions for the year 2017 to investigate heat and carbon dynamics in the region and determine the effect of model resolution on these dynamics. Initial conditions and boundary forcing from BSOSE (the Biogeochemical Southern Ocean State Estimate (Verdy & Mazloff, 2017),https://doi.org/10.1002/2016JC012650) and atmospheric forcing from ERA5 are used. The models are evaluated for accuracy by comparing output to Argo and BGC‐Argo float profiles, BSOSE, and other reanalyses and mapped products. We then quantify the effect of resolution on model upper ocean heat and carbon transport and the associated air‐sea exchanges. We determine that increasing the resolution from 1/3° to 1/12° enhances the upward vertical transport and surface exchanges of heat but causes no significant effect on surface carbon fluxes despite enhancing downward transport of anomalous DIC.