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Assessing the risk posed by Geomagnetically Induced Currents (GICs) to the regular operation of power grids requires a hazard specification in terms of the induced geoelectric field (GEF). In order to specify the GIC hazard posed to the German high-voltage transmission grid, we model the GEF within Germany for geomagnetically disturbed conditions using magnetic field measurements from INTERMAGNET observatories and a predefined electrical conductivity model of the subsurface as input. This contribution focuses on a comparison of GEFs modeled assuming electromagnetic (EM) induction scenarios of different complexity, which are imposed through the specification of the inducing EM field on the one hand and the dimensionality of the conductivity model on the other. The former is specified either as a plane wave or a laterally varying field obtained by fitting Spherical Elementary Current Systems basis functions to the magnetic field observations. The conductivity distribution is given either by the “EURHOM” model or our new dedicated 3D model for Germany obtained from legacy magnetotelluric data. The latter also includes realistic 3D conductivity variations due to the ocean/sea and marine sediments, which are known to affect magnetotelluric impedance tensors at GIC-relevant frequencies near coastlines. Based on the modeled GEFs, we calculate GICs exemplarily at selected substations and geomagnetic disturbance events. The results indicate the level of complexity needed in the GEF modeling in order to derive meaningful GIC hazard maps for Germany down the line., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

A major source of time-varying magnetic fields are external ionosphere-magnetosphere currents and associated fields induced in subsurface and oceans. Induced fields may bias external and core field models if not accounted for in a physically consistent manner. In addition, induced fields contain unique information on the subsurface conductivity distribution. Yet, induced fields are often considered noise (and neglected) or at best treated peripherally as a nuisance parameter. The outstanding accuracy of Swarm magnetic field data and increasing demand for fast-track magnetic field products has pushed the frontier of the field to a point where sophisticated core and external magnetic field models are hindered by improper modelling of induced fields. We propose a versatile and efficient way of modelling induced fields in ground and satellite measurements, which also enables modelling in near real-time settings as is required by many present Space Weather products. The proposed approach also offers a more consistent way to assimilate geomagnetic data from ground observatories and satellites into physics-based magnetic field models., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Understanding the geological setting of nonvolcanic geothermal systems is vital to explaining the formation of geothermal reservoirs and their observable surface manifestations. The magnetotelluric method, used to determine the subsurface electrical conductivity distribution, is a common tool in geothermal exploration. In this study, we present an integrated interpretation of an electrical conductivity subsurface model, together with geological analyses and geochemical probes from a nonvolcanic, intermediate-temperature geothermal system in Mongolia. We conducted magnetotelluric (MT) and telluric-magnetotelluric (TMT) measurements at the Tsenkher geothermal area in the Mongolian Khangai dome during the summers of 2019 and 2020. The 20km*20km large area is characterized by three major hot springs with water temperatures up to 87°C. From a total of 196 MT and TMT stations, we obtained a 3-D electrical conductivity model of the subsurface. To interpret the data, we used a high-order finite-element electromagnetic modelling code (GOFEM) with locally refined hexahedral meshes that allows including accurate topography while ensuring high numerical accuracy with a sufficiently fine discretization of the inversion domain. The best-fitting model provides essential insights into the subsurface structure of the Tsenkher geothermal area. The model is characterized by a strong vertical crustal conductor that appears south of the hot springs area and rises from depths of more than 10 km to the surface. We interpret this conductor as a remnant of past local volcanism and a zone of former magma ascent, indicating the potential source for the observed enhanced surface heat flow in the hot springs area around Tsenkher. Additionally, the model includes a prominent striking conductor beneath the hot springs at depths down to more than 3 km below the surface. The conductor is spatially aligned with a major fault that intersects the survey area, and is accompanied by several basaltic dyke intrusions. We interpret the fault-aligned conductor as the major area of deep fluid circulation and an accumulation zone for heated fluids. The interpretation agrees with theoretical concepts of topography-driven deep fluid circulation and local fault zones playing a major role in the transport of hot water from a reservoir to the surface. Inferred reservoir temperatures from geochemical fluid analyses are inagreement with interpretations of the maximum depth of fluid circulation inferred from the MT model. Our MT subsurface model serves to better understand the formation of the Tsenkher hot springs in particular and intermediate-temperature geothermal systems in general, 25th EM Induction Workshop

Intraplate processes, such as continental surface uplift and intraplate volcanism, are enigmatic and the underlying mechanisms responsible are not fully understood. Central Mongolia is an ideal natural laboratory for studying such processes because of its location in the continental interior far from tectonic plate boundaries, its high-elevation plateau, and its widespread, low-volume, basaltic volcanism. The processes responsible for developing this region remain largely unexplained — due in part to a lack of high-resolution geophysical studies — and thus are open questions. A recent project undertaken to map the crust and upper mantle structure of central Mongolia has collected a large magnetotelluric array (~700 km x ~450 km).

Magnetotelluric measurements are a powerful tool to image the subsurface under active volcanic regions. 3-D models, computed from magnetotelluric data, nowadays provide detailed multi-scale images of the electrical conductivity distribution. Since electrical conductivity is predominantly controlled by the presence of melt and fluid phases, conductivity models proved to be highly suitable for mapping the distribution of melt and for constraining melt fractions. Melt fractions can be estimated by combining laboratory models for melt electrical conductivity and mixing laws to derive the bulk electrical conductivity of multiphase systems. Melt electrical conductivity depends on the composition of the melt, the amount of dissolved water as well as temperature and pressure conditions. However, estimates of melt fractions are often based on arbitrary combinations of these parameters, and they do not consider the dependance of melt interconnectedness on melt fraction. Here we present an interdisciplinary approach to interpret electric conductivity models from three volcanoes in the Main Ethiopian Rift. We use rhyolite-MELTS to model magma crystallization and storage conditions constrained by petrological analyses of on-site erupted products. To derive the electrical conductivity of melt during fractional crystallization we derive an expanded melt electrical conductivity model by interpolating between existing models for rhyolite, dacite and andesite melt. Thereby we obtain a generalized model that describes the electrical conductivity of melt in dependence on the SiO2 and H2O content, pressure and temperature. These parameters are given by rhyolite-MELTS. Decreasing melt connectedness with diminishing melt fraction is considered by varying the cementation exponent, m, in the generalized Archie’s law whilst taking into account conservation of connectedness. Furthermore, we describe the magma reservoirs as three-phase systems consisting of crystals, melt and magmatic volatiles. The results show that this approach enables us to constrain the current state of magma reservoirs in terms of melt fraction, temperature and free volatile abundance. The latter is of eminent importance when discriminating between the two major mechanisms that drive volcanic unrest: magma on the move or increased degassing of a crystallizing magmatic system, so-called second boiling. With this study we demonstrate the great capability of the presented interdisciplinary solution approach that combines geophysical observations, petrological probes and laboratory models to capture the current state of volcanoes. The outcome is of major importance when it comes to realistic volcanic hazard assessment and geothermal energy applications that require a detailed understanding of magmatic heat sources that sustain geothermal reservoirs., 25th EM Induction Workshop

Galvanic distortions represent one of the greatest challenges when dealing with magnetotelluric datasets. Several methods exist that try to mitigate the effect of distortions on inversion. One solution to avoid this major issue was provided with the introduction of the phase tensor, a transfer function that is free of galvanic distortion. However, the nature of the phase tensor makes it predominantly sensitive to relative changes of resistivity and its ability to constrain absolute resistivities is still under debate. So far, case studies have shown that phase tensor inversion works effectively if (i) the subsurface resistivity distribution has significant 3-D heterogeneities, (ii) MT site spacing is sufficiently dense, and (iii) data-constrained starting models are employed. There is presently a lack of systematic investigations to what extent phase tensors constrain absolute resistivity values in 3-D subsurface models. To shed light on this discussion we systematically analyse to what degree variations of absolute resistivities influence the fit of phase tensor data. We use a dataset with measurements from 127 MT stations in an area of about 340 km2 covering a volcanic geothermal field in the Main Ethiopian Rift. To ensure the eligibility of the dataset for 3-D phase tensor inversion we introduce a quantitative criterion for “sufficiently” dense station spacing. Using a homogenous starting model derived from the average apparent resistivity we retrieve a model with a good data fit, that acts as a reference model. In a first test the fit of the reference model is compared to models obtained from inversion using arbitrary (i.e. not data-constrained) starting models consisting of homogenous halfspace models of 20, 50, 100 and 1000 Wm. This results in poorer data fit and less geologically plausible models, thereby demonstrating the importance of using starting models that are constrained by data. In a second test we use the reference model and vary the resistivity values using algorithms from image processing such as contrast adjustment and linear stretching. Detailed analysis of the modelled responses and residuals reveals significant changes in the misfit relative to the reference model. We conclude that in a realistic 3-D settings with sufficiently dense MT site spacing phase tensor inversion can be considered as a reliable method to recover true subsurface resistivities. If performed properly, phase tensor inversion is an elegant and straight-forward method to obtain models not affected by galvanic distortion., 25th EM Induction Workshop

International audience; The geomagnetic field has been continuously monitored from low-Earth orbit (LEO) since 1999, complementing ground-based observatory data by providing calibrated scalar and vector measurements with global coverage. The successful three-satellite ESA Swarm constellation is expected to remain in operation up to at least 2025. Further monitoring the field from space with high-precision absolute magnetometry beyond that date is of critical importance for improving our understanding of dynamics of the multiple components of this field, as well as that of the ionospheric environment. Here, we will report on the latest status of the NanoMagSat project, which aims to deploy and operate a new constellation concept of three identical 16U nanosatellites, using two inclined (approximately 60°) and one polar LEO, as well as an innovative payload including an advanced Miniaturized Absolute scalar and self-calibrated vector Magnetometer (MAM) combined with a set of precise star trackers (STR), a compact High-frequency Field Magnetometer (HFM, sharing subsystems with the MAM), a multi-needle Langmuir Probe (m-NLP) and dual frequency GNSS receivers. The data to be produced will at least include 1 Hz absolutely calibrated and oriented magnetic vector field (using the MAM and STR), 2 kHz very low noise magnetic scalar (using the MAM) and vector (using the HFM) field, 2 kHz local electron density (using the m-NLP) as well as precise timing, location and TEC products. In addition to briefly presenting the nanosatellite and constellation concepts, as well as the evolving programmatic status of the mission (which already underwent a consolidation study funded by the ESA Scout programme), this presentation will illustrate through a number of E2E simulations the ability of NanoMagSat to complement and improve on many of the science goals of the Swarm mission at a much lower cost, and to bring innovative science capabilities for ionospheric investigations. NanoMagSat could form the basis of a permanent collaborative constellation of nanosatellites for low-cost long-term monitoring of the geomagnetic field and ionospheric environment from space.