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Changes of the Earth's magnetic field have been observed with varying spatial and temporal resolution since the middle ages by means of compasses, and later by refined mechanical inclination and intensity instruments, until the modern use of quantum mechanical devices and satellite observations. Ancient records, on the other hand, rely on the natural magnetization of archaeological artifacts and other materials, such as rocks and sediments, being therefore indirect, less accurate and sparser. The combination of such heterogeneous records into a single, self-consistent, global model of the geomagnetic field is very challenging: the highly uneven data coverage, both in space and time, requires a careful handling of data uncertainties and error correlations. Previous models dealt with this problem using separated treatments of instrumental data and indirect records, respectively, as well as a different handling of the dipole field component, with respect to non-dipole terms. Here we present a global geomagnetic field model based, for the first time, on the simultaneous inversion of historical, archaeomagnetic, and volcanic records, using a Bayesian approach with minimal-committing time regularization that minimizes the energy of secular variation. A detailed assessment of data uncertainty and error correlation is used to minimize artifacts generated by the appearance of an overwhelming number of incomplete, mostly declination-only records, associated with shipboard measurements in the early colonial period. Our model yields lower dipole energies, which better match modern values, as well as higher non-dipole energies and a stronger secular variation of the dipole moment. Some model artifacts associated with extremely heterogeneous distributions of records in time and space are not completely eliminable and might be caused by incorrect a-priori uncertainty assessments. Alternatively, they might represent an intrinsic limit that can be overcome only by adding new records at critical locations and times.

High-resolution first-order reversal curve (FORC) diagrams are increasingly employed to characterize magnetic minerals in sediments, and especially as a magnetofossil detection tool. Conventional processing protocols, however, are not well suited for this purpose because the opposed needs of high resolution and smoothing of noisy data over different regions of the FORC diagram cannot be reconciled. This problem is particularly severe in samples containing non-interacting single-domain particles, whose FORC signature is described by an infinitely narrow, divergent feature called a central ridge. In this paper, a new FORC processing protocol called VARIFORC (VARIable FORC smoothing) is presented for the analysis of non-regular FORC functions, such as those featuring a central ridge. This protocol is based on weighted polynomial regression of rectangular arrays of measurement points whose size is determined by the local properties of the FORC function (i.e. small arrays where high resolution is needed and vice-versa). The resulting FORC diagram is characterized by improved signal-to-noise ratios that pass significance tests over much larger domains. This enables simultaneous quantitative analysis of FORC signatures corresponding to different magnetization processes (e.g. the central ridge produced by single-domain particles and a weak, extended background due to detrital magnetic minerals). VARIFORC has been successfully tested on a magnetofossil-bearing pelagic carbonate sample that has a non-regular FORC function, and on a volcanic ash sample with a typical pseudo-single-domain signature. An unexpected minor central ridge contribution, which is invisible to traditional processing, has been detected in the volcanic ash sample. This finding demonstrates the effectiveness of the new FORC processing protocol and potential new applications of high-resolution FORC measurements.

Experimental results on the change in the Verwey transition temperature in magnetite under compression exhibit puzzling variability, with slopes ranging from − 6 to + 16 K/GPa. Our thermodynamic analysis of the Verwey transition in magnetite explains much of this variability in terms of the transformation strain as magnetite changes in crystal structure from cubic to monoclinic. Because this strain involves a much larger change in shape than in volume, the change in temperature of the phase boundary ( T v ) can be much more sensitive to nonhydrostatic stress than to hydrostatic pressure. Uniaxial compression and tension both are predicted to increase T v , an effect that is opposite in sign and, for favorable orientations, up to six times greater per gigapascal than for pressure. Moreover, because the monoclinic twin orientation with highest T v is thermodynamically favored, our treatment also shows how any desired twin may be selected uniquely by applying stress of appropriate orientation, thereby removing obstacles to understanding many kinds of low-temperature phenomena in magnetite caused by the presence of multiple twins. A similar analysis for the thermodynamic effects of strong magnetic fields is outlined, predicting that T v will generally be lowered. Again, the twin for which T v is highest (i.e., is lowered the least) will be the most stable. Twin selectivity per gigapascal of stress is up to two to three times stronger than that per Tesla of magnetic field.

The characterization of individual magnetic components in sediments and sedimentary rocks is difficult, as these natural materials are often a complex mixture of magnetic mineral sources. The analysis of magnetization curves with model functions is the only practicable method of unmixing the magnetic components and characterizing their magnetic properties, if a priori information is not available. Unfortunately, such analyses rely on time consuming measurements and on the choice of appropriate model functions. The simplification of the unmixing problem is closely related to the number of parameters required to fully characterize a magnetic component, and the significance of these parameters in rock magnetic terms. A systematic analysis of synthetic and natural samples shows that a combination of four parameters, here called magnetic fingerprints, is sufficient for this purpose. The fingerprints of individual magnetic components isolated from a wide range of natural sediments and sedimentary rocks form well-defined groups with specific properties. These groups reflect common processes of formation, transport and dissolution of magnetic particles. A clear distinction can be made between two sorts of biogenic magnetite, atmospheric dust, urban pollution and ultrafine magnetite produced in soils and lacustrine/marine sediments. � 2004 Elsevier Ltd. All rights reserved.

The analysis of magnetization curves with model functions has been proposed independently in several works as a method to unmix and characterize magnetic minerals assemblages in sediments and sedimentary rocks. Unfortunately, a successful result of such analysis relies on time-consuming measurements and on the choice of appropriate model functions. However, once the magnetic properties of individual magnetic components have been determined on a small set of selected samples, a simpler and faster analysis of similar samples is possible. The fast analysis of a large number of samples allows investigation of the effect of natural processes on the properties of single magnetic components. The simplification of the unmixing problem proposed in this paper is based on an iterative linearization procedure, which considers the variability of magnetic components. Any simplification of the unmixing problem is limited by a minimum number of parameters, which are required to fully characterize a magnetic component. It has been shown that a combination of four parameters, so-called magnetic fingerprints, is sufficient for a complete characterization of the remanent magnetization of a component. The usefulness of magnetic fingerprints in tracking natural processes is demonstrated exemplarily for lake sediments. The response of Baldeggersee (Switzerland) to environmental changes has been investigated, with special regard to the role of bacterial magnetite in the iron cycle and its possible use as a sensitive paleoredox indicator. The relation between the magnetic properties of lake sediments on one hand, and climatic, tectonic- and human-driven environmental changes on the other, is strongly non-linear. Therefore, a classic correlation between so-called magnetic proxies and environmental signals should be considered with care.

We present a quantitative model for the climatic dependence of magnetic enhancement in loessic soils. The model is based on the widely accepted hypothesis that ultrafine magnetite precipitates during alternating wetting and drying cycles in the soil micropores. The rate at which this occurs depends on the frequency of drying/wetting cycles, and on the average moisture of the soil. Both parameters are estimated using a statistical model for the soil water balance that depends on frequency and intensity of rainfall events and on water loss by evapotranspiration. Monthly climatic tables are used to calculate the average soil moisture and the rate of pedogenic magnetite production, which is proportional to a new parameter called magnetite enhancement proxy (MEP). Our model is tested by comparing MEP calculated for known present-day climates with the magnetic enhancement of modern soils. The magnetic enhancement factor, defined as the ratio between a given magnetic enhancement parameter and MEP, is expected to be a site-independent constant. We show that magnetic enhancement differences between soils from the Chinese Loess Plateau and from Midwestern U.S. are explained by our model, which yields similar magnetic enhancement factors for the two regions. Our model is also successful in predicting the mean annual rainfall threshold above which magnetic enhancement declines in a given type of climate.