G4.3

A gravimetric quasi-geoid model, based on the latest FAMOS database release, has been computed for the Baltic Sea region, aiming for a best-possible model on the sea, while not focusing on the surrounding land.

 The geoid computation is based on the FFT remove-compute-restore method. XGM2019 is used as global reference field, with a Wong-Gore linear tapering from 180 to 200. No terrain corrections are included in the computation, since these are not expected to contribute to the accuracy of the model on the sea.

The gravimetric quasi-geoid model is compared to a GNSS-levelled ITRF2008 zero-tide dataset, the altimetry based DTU21 Mean Sea Surface dataset, and to a few tide gauge stations distributed throughout the region. Some preliminary comparisons to the GNSS-levelling dataset indicates that the gravimetric geoid has an accuracy of ±25 mm in the region surrounding the Baltic Sea.

How to cite: Teitsson, H. and Forsberg, R.: Gravimetric quasi-geoid of the Baltic Sea and comparison to GNSS levelling, DTU21 and tide gauges, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11302, https://doi.org/10.5194/egusphere-egu22-11302, 2022.

How to cite: Krcmaric, J.: Development and evaluation of the xGEOID20 Digital Elevation Model at NGS, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13101, https://doi.org/10.5194/egusphere-egu22-13101, 2022.

With the definition of the International Height Reference System (IHRS) and the development of a roadmap for its implementation through the International Height Reference Frame (IHRF), an analytical evaluation of the various approaches for the practical determination of potential values at IHRF is necessary. In this work we focus on two main approaches to estimate geopotential values at IHRF stations. The first approach resides on the use of either local gravity anomalies and gravity disturbances around each site and the geopotential determination based on Stokes’ and Molodensky’s boundary value problems, respectively. In this scheme, the influence of the classical residual terrain model (RTM) reduction as well as that of RTM effects based on spherical harmonics expansion of the topographic potential are investigated. Furthermore, the introduction of possible biases within the various pre- and post-processing steps are thoroughly investigated, as e.g., during the estimation of station geometric heights, along with the influence of the quasi-geoid to geoid separation estimation. In the second approach, we investigate the determination of geopotential values based on either national and regional geoid models, i.e., resembling the case that access to local gravity data is not available, and the determination has to be based on some available geoid model. In the present work we analyze the theoretical and methodological steps that need to be followed in each approach, identifying the possible sources of biases. Finally, some early results are presented aiming at providing a roadmap and an error assessment for the practical realization of the IHRF.

How to cite: Barzaghi, R. and Vergos, G.: Practical implementation of the IHRF employing local gravity data and geoid models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-927, https://doi.org/10.5194/egusphere-egu22-927, 2022.

In the northeastern Japan arc with the active compressive stress field since ~3 Ma, it is reported that a characteristic relationship between crustal deformation including faulting and short-wavelength (< 160 km) Bouguer anomalies. According to previous studies, active faults tend to be located in negative regions, which are caused by cracks and volumetric strain due to accumulated fault dislocation. Especially, it is shown that in strain concentration zones with active faults and muti folding, the effect of accumulated fault dislocation forms the negative zones of gravity anomaly along the northeastern Japan arc, impacting the pattern of short-wavelength Bouguer anomalies throughout the entire arc. In this presentation, we extend this concept further and discuss the positive and negative zones of gravity zones along the entire northeastern Japan arc from the geometrical viewpoint of folding with one of the defect, disclination. Folding is described by Euler-Schouten curvature tensor, which defines the protrusion of included space (e.g., two-dimensional Riemannian space) from enveloping space (e.g., three-dimensional Euclid space). Based on previous studies, the density of earthquake occurrence is proportional to the curvature of the plastic folding deformation of the crust, which is related to Euler-Schouten curvature, and fault dislocation also accumulates at the regions with its high curvature. The row (accumulation) of fault dislocation can be replaced by the disclination, and Riemann-Christoffel curvature, derived from Euler-Schouten curvature tensor, also expresses disclination density. In particular, angular folding with local curvature accompanied by a pair of disclination is called Kink folding, forming the mass-loss or mass-excess regions around disclination. Since Kink folding can approximately be the same as the undulating region bounded by several faults (fault block) in strain concentration zones, it is expected that the northeastern Japan arc has not only negative zones of gravity anomaly but also positive zones along the arc due to the mass-loss or mass-excess regions around disclination. Therefore, we conclude that the positive and negative zones of gravity anomaly along the northeastern Japan arc reflect the geometric condition of the crust with disclination.

How to cite: Hirano, M. and Nagahama, H.: Short-wavelength Bouguer anomaly and folding with disclination in the northeastern Japan, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3409, https://doi.org/10.5194/egusphere-egu22-3409, 2022.

Modelling of geophysical data is often subject to choices made by the researcher undertaking the work. The level of structural complexity in the model, the bounds on parameters imposed by a priori knowledge, the thoroughness and efficiency in exploring the parameter space may all lead to bias in determining what the best fitting models can be.

To avoid bias from our own ideas in constraining the subsurface shape of a given density anomaly, we hereby invite anyone interested to create their own models. This is planned by sharing the same gravity data measured in the field, the same digital elevation model, the main features of the local geological maps, and bounds on the encountered rock density values. These data will be shared openly, in the form of a modelling challenge: each participating researcher or group is expected to submit their solution(s). All these will be compared during a dedicated workshop, ultimately resulting in a joint publication.

The target of this modelling challenge is the world-famous Balmuccia peridotite body (45.84°N, 8.16°E) in the Ivrea-Verbano Zone (IVZ). Here mantle rocks are naturally exposed at the surface, in the broader context of the IVZ, a middle- to lower crustal terrain along the Europe-Adria plate boundary’s eastern side. The surface exposure of the Balmuccia peridotite is ~ 4.4 km N-S by 0.6 km E-W, with outcrop elevation changes exceeding 1000 m. About 150 new gravity data points have been measured within a radius of 3 km from the centre of the peridotite body, along more or less accessible paths and slopes. The measurements have been carried out with a Scintrex CG-5 relative gravimeter, tied to a reference point, and all points located via differential GPS with typical vertical precision of a few cm. Farther away regional gravity data is available at few km spacing.

Beyond the modelling challenge, the interest in constraining the subsurface shape of the Balmuccia peridotite body is its future target role in the ICDP DIVE continental drilling project (www.dive2ivrea.org).

How to cite: Hetényi, G., Baron, L., Scarponi, M., Subedi, S., Michailos, K., Dal, F., Gerle, A., Petri, B., Langone, A., Greenwood, A., Ziberna, L., Pistone, M., Zanetti, A., and Müntener, O.: Crowd modelling: Launching an open gravity-modelling call to challenge the Balmuccia peridotite body, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4230, https://doi.org/10.5194/egusphere-egu22-4230, 2022.

The presence of subglacial sediments is important in enabling streaming ice flow and may be a critical controlling factor in determining the onset regions of ice streams. Improving our knowledge of the location of sedimentary basins underlying large ice sheets will improve our understanding of how the substrate influences the ice streams.  Advancing our understanding of the interaction between subglacial sediments and ice flow is critical for predictions of ice sheet behavior and the consequences on future climate change. To date, no comprehensive distribution of onshore and offshore sedimentary basins over Antarctica has been developed. The goal of this project is to use a combination of large-scale datasets to characterize known basins and identify new sedimentary basins to produce a continent-wide mapping of sedimentary basins and provide improved basal parametrizations conditions that have the potential to support more realistic ice sheet models. The proposed work is divided into three main steps. In the first step, the Random Forest (RF), a supervised machine learning algorithm, is used to identify sedimentary basins in Antarctica. In the second step, a regression analyses between aerogravity data and topography is done to evaluate the gravity signal related to superficial heterogeneities (i.e. sediments) and compare the results to the depth of magnetic sources using the Werner deconvolution method. Last, the correlation between sedimentary basins and ice streams is investigated. Here, we will present the preliminary results from Step 1. The Random Forest uses ensemble learning method for classification and regression. The classification rules for this present work are based on the geophysical parameters of major known sedimentary basins. First we classify the known basins with all available geophysical compilations including topography, gravity and magnetic anomalies, sedimentary thickness, crustal thickness, geothermal heat flux, information on the geology, rocky type and bedrock geochemistry, and then use the Random Forest machine learning algorithm to classify the geology underneath the ice into consolidated rock and sediments based on these parameters.

How to cite: Constantino, R. R., Tinto, K. J., and Bell, R. E.: Using random forest machine learning algorithm to help investigating the relationship between subglacial sediments and ice flow in Antarctica, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2658, https://doi.org/10.5194/egusphere-egu22-2658, 2022.

Sub-ice-bathymetry is an important boundary condition when modelling the evolution of ice shelves and ice sheets. Radar sounding is a proven method to reveal the sub-ice-topography beneath grounded ice. However, it fails to image the bathymetry beneath the floating ice shelves due to the strong radar reflectivity of sea water. As an alternative, the inversion of gravity measurements has been used increasingly frequently in recent years. To overcome the ambiguity of inverse modelling, this method benefits from independent depth constraints derived from direct measurements distributed throughout the model area, such as by active seismic, hydroacoustic, and radar methods.

Here, we present a novel geostatistical approach to gravity inversion and compare it to the classical and more commonly used FFT approach. Instead of only fitting individual points, we also include the spatial continuity of the sub-ice morphology. To do so, we calculate a variogram that fits the available depth measurements and derive a covariance matrix from it. The covariance matrix and an initial bathymetry model obtained by kriging together describe an a-priori probability density. For the inversion, the model bathymetry is related to the measured gravity using a quasi-Newton method, for which the derived probability density serves as the inversion’s regularization term. We successfully apply the algorithm to airborne gravity data across the Ekström ice shelf (Antarctica) and compare our results with those of previous studies based on the classical approach. The simplified addition of constraints both for the geometry and the density structure in our approach proves to be advantageous.

How to cite: Liebsch, J., Ebbing, J., Eisermann, H., and Eagles, G.: Geostatistical Gravity Inversion for Estimating Sub-Ice-Bathymetry, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13231, https://doi.org/10.5194/egusphere-egu22-13231, 2022.

Joint inversion of complementary datasets is an important tool to gather new insights and aid interpretation, especially in regions which show structural complexity. Using the joint inversion framework jif3D [1] with a newly developed coupling for density and resistivity, based on a variation of information approach which is a machine-learning method that constructs a possible relationship between the properties [2], we combine satellite gravity measurements with electromagnetic data, from broadband and long-period magnetotellurics [3,4,5,6].

Central Mongolia is located in the continental interior, far from tectonic plate boundaries, yet has a high-elevation plateau and enigmatic widespread low-volume basaltic volcanism [7,8,9]. The processes responsible for developing this region remain unexplained and there are questions about its tectonic evolution. A recent project employed thermo-mechanical numerical modeling [10] to simulate the temporal evolution of various tectonic scenarios, offering an opportunity to test hypotheses and determine which are physically plausible mechanisms. Constraints on lithospheric properties, e.g., density distribution, are important for evaluating the geodynamic models. Furthermore, they can help shed light on questions regarding the nature of lower crustal electrical conductors [11], which may be related to tectonically-significant low-viscosity zones.

We will present preliminary results that provide new constraints on the 3-D structure of the lithosphere beneath Central Mongolia, as well as a roadmap for moving towards integrating geophysical results into geodynamic modeling to better understand the evolution of the lithosphere.

References:

[1]  Moorkamp, M. et al. 2011. A framework for 3-D joint inversion of MT, gravity and seismic refraction data. Geophysical Journal International, 184(1). https://doi.org/10.1111/j.1365-246X.2010.04856.x 

[2]  Moorkamp, M., 2021. Deciphering the state of the lower crust and upper mantle with multi-physics inversion. ESSOAr. https://doi.org/10.1002/essoar.10508095.1 

[3]  Comeau, M.J., et al., 2018. Evidence for fluid and melt generation in response to an asthenospheric upwelling beneath the Hangai Dome, Mongolia. Earth and Planetary Science Letters, 487. https://doi.org/10.1016/j.epsl.2018.02.007 

[4]  Käufl, J.S., et al., 2020. Magnetotelluric multiscale 3-D inversion reveals crustal and upper mantle structure beneath the Hangai and Gobi-Altai region in Mongolia. Geophysical Journal International, 221(2). https://doi.org/10.1093/gji/ggaa039 

[5]  Becken, M., et al., 2021a. Magnetotelluric Study of the Hangai Dome, Mongolia. GFZ Data Services. https://doi.org/10.5880/GIPP-MT.201613.1 

[6]  Becken, M., et al., 2021b. Magnetotelluric Study of the Hangai Dome, Mongolia: Phase II. GFZ Data Services. https://doi.org/10.5880/GIPP-MT.201706.1 

[7]  Comeau, M.J., et al., 2021a. Images of a continental intraplate volcanic system: from surface to mantle source. Earth and Planetary Science Letters, 587. https://doi.org/10.1016/j.epsl.2021.117307 

[8]  Papadopoulou, M., et al., 2020. Unravelling intraplate Cenozoic magmatism in Mongolia: Reflections from the present-day mantle or a legacy from the past? Proceedings of the EGU. https://doi.org/10.5194/egusphere-egu2020-12002 

[9]  Ancuta, L.D., et al., 2018. Whole-rock 40Ar/39Ar geochronology, geochemistry, and stratigraphy of intraplate Cenozoic volcanic rocks, central Mongolia. Geological Society of America Bulletin, 130. https://doi.org/10.1130/b31788.1 

[10]  Comeau, M.J., et al., 2021b. Geodynamic modeling of lithospheric removal and surface deformation: Application to intraplate uplift in Central Mongolia. Journal of Geophysical Research: Solid Earth, 126(5). https://doi.org/10.1029/2020JB021304

[11]  Comeau, M.J., et al., 2020. Compaction driven fluid localization as an explanation for lower crustal electrical conductors in an intracontinental setting. Geophysical Research Letters, 47(19). https://doi.org/10.1029/2020gl088455 

How to cite: Comeau, M. J., Moorkamp, M., Becken, M., and Kuvshinov, A.: Joint inversion of gravity and electromagnetic data — New constraints on the 3-D structure of the lithosphere beneath Central Mongolia, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12704, https://doi.org/10.5194/egusphere-egu22-12704, 2022.

Investigating the crustal architecture, specifically the discontinuity interface between the upper mantle and lower crust of the Earth, so-called Moho, can be done in three prevailing techniques, namely lithology, seismicity, and gravity. In contrast to using the information from analyzing the characteristics of rocks and seismic waves, which are sparsed and expensive, inverting gravity data of satellite missions such as GOCE and GRACE is a suitable alternative for such purposes.

The present paper attempts to map the Moho surface using the gravity data as we considered a simplified Earth model based on three shells including the core, mantle and crust with a potential T on a given sphere outside this body. In this notation, by subtracting the topographic effects, compensating for density anomalies in the crust, and other known constants from the observation that are given on and outside the mean Earth radius, one is left with the potential of a single layer on the mean Moho sphere by taking into consideration the Helmert condensation approach. In planar approximation, this is to say that the topography is formally referred to an xy plane and also the condensation surface which is a plane, situated at a depth D below the previous one. Therefore, relating the topographic load of a mass column with height h over the same elementary area element at depth d, the measure of how deep the crust is sinking into the mantle material as a consequence of the load, we can interpret the Moho variations with respect to some mean crustal thickness.

To do this inversion, we applied the Least Square Collocation (LSC) approach which uses the functional relationships between the quantities, the auto-covariance and cross-covariance matrices based on a covariance function between observations and the unknowns. Practically, after constructing the required residual data, an empirical covariance is estimated, then fitted to analytical one to define the required covariance models.

Finally, the Moho variations has been estimated in an active tectonic zone created by the continental collision of the Arabian plate from South-West and Turan shield from North-East with respect to a mean Moho depth equal to 45 km. Results of this study are comparable and much the same with other studies so that different rheological zones of Iranian plateau can be seen in this estimated map of Moho. For instance, a maximum depth is estimated for Sanandaj-Sirjan zones in South-East and minimum depth for Caspian Sea in North.

How to cite: De Gaetani, C. I., Heydarizadeh Shali, H., Ramouz, S., Safari, A., and Barzaghi, R.: Moho depth evaluation using GOCE gradient data and Least Square Collocation over Iran, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3615, https://doi.org/10.5194/egusphere-egu22-3615, 2022.

The objective of this work is to investigate the geologic and tectonic units in the Iranian plateau in relation to the information that can be obtained from the gravity field observed from space. The objective requires to collect seismologic tomography, seismicity, geodetic observations of crustal movements, a database of active faults, active seismic investigations of sediment depths, heat flow measurements and to use this information as a constraint for gravity inversion with the present available satellite-derived gravity field. The gravity field correlated to the topography defines blocks of the plateau, which indicates varying crustal rigidity (Pivetta and Braitenberg, 2020). We find that mechanisms of vertical growth are tied to crustal thickening, coherently identified from the gravity field, seismic tomography and isostasy. Persistent high density crustal blocks are identified for instance SE of Isfahan, which require further investigation and validation, also in relation to magmatism. The study is embedded in a major project addressing the “Intraplate deformation, magmatism and topographic evolution of a diffuse collisional belt: Insights into the geodynamics of the Arabia-Eurasia collisional zones” financed by the Italian Ministry (PRIN 2017). When defining the density structure and its uncertainties, the question appears, what improvements on the knowledge of the structure, seismic faults, and on the block-structure can be expected from future gravity missions, with a payload of quantum gradiometers and atom-clocks in a multi satellite configuration. The geophysical sensitivity to quantum gravimetry in space is of interest to the MOCAST+ ASI project, a follower project of the MOCASS ASI project, in which the geophysical sensitivity of the quantum gradiometer payload has been studied (Pivetta et al., 2021).

Pivetta, T., & Braitenberg, C. (2020). Sensitivity of gravity and topography regressions to earth and planetary structures. Tectonophysics, 774, 228299. https://doi.org/10.1016/j.tecto.2019.228299

Pivetta, T., Braitenberg, C. & Barbolla, D.F. (2021) Geophysical Challenges for Future Satellite Gravity Missions: Assessing the Impact of MOCASS Mission. Pure Appl. Geophys. https://doi.org/10.1007/s00024-021-02774-3

How to cite: Braitenberg, C., Pivetta, T., Pastorutti, A., and Tesauro, M.: Geologic and Tectonic units in the Iranian Plateau from present and future satellite missions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12459, https://doi.org/10.5194/egusphere-egu22-12459, 2022.

The famous circular structure of Richat, sometimes referred to as “the eye of Africa”, is located in the northwestern part of the Taoudeni basin, in the central part of the Mauritanian Adrar plateaus. It is expressed at the surface as a slightly elliptical depression, about 40 kilometers in diameter, marked by concentric ridges of Proterozoic-Lower Paleozoic sediments. Its origin as resulting from either a meteorite impact or a deep magmatic intrusion, has been long debated. Modelling of high-resolution airborne magnetic data as well as satellite gravity data reinforces the intrusion hypothesis. Geophysical modelling has been calibrated by determinations of rock properties from various types of magmatic lithologies sampled in the field. The three complementary types of geophysical data allow us to image at various scales and depths the buried structures of the Richat magmatic complex, to determine the areas most affected by hydrothermal alteration and finally to elaborate a kinematic model for its emplacement. We emphasize that : (1) the Richat intrusion is characterized by the presence of two important circular magnetic signals that coincide with gabbroic ring dykes partly exposed at the surface, (2) its overall circular structure rests above a deep mafic (gabbroic) body, (3) the upwelling of magma at the surface has been facilitated by the presence of concentric faults and (4) the central zone of the complex recorded intense hydrothermal alteration. This case study aims to provide insights for similar types of magma-induced ring structures observed worldwide.

How to cite: Abdeina, E. H., Bazin, S., Chazot, G., Bertrand, H., Le Gall, B., Youbi, N., Sabar, M. S., Bensalah, M. K., and Boumehdi, M. A.: The deep structure of the Richat magmatic intrusion (northern Mauritania) from geophysical modelling. Insights into its kinematics of emplacement, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-711, https://doi.org/10.5194/egusphere-egu22-711, 2022.

The Monchique alkaline complex (MAC) crops out in southern Portugal with a roughly elliptical shape of about 80 km² elongated along ENE-WSW direction. The MAC dates to Late Cretaceous (69-72 Ma) and intrudes the Carboniferous Flysh formation of the South Portuguese Zone. At the surface, it comprises two main types of syenites: a central homogeneous nepheline syenite surrounded by a heterogeneous syenite unit, and some less expressive outcrops of mafic rocks (gabbros, hornfels, breccia and basalts). This igneous complex belongs to the Upper Cretaceous West Iberia alkaline magmatic event, characterized by alkaline magmatism of sublithospheric origin and active from approximately 100 Ma to 69 Ma.

The Monchique region hosts the most active seismic cluster of mainland Portugal, with low magnitude earthquakes (M < 4) that occur along lineations with NNE–SSW and WNW–ESE preferred orientation.

In this work we study the Monchique region through gravimetric and magnetic methods in order to: 1) better understand how the MAC influences the geomagnetic and gravimetric field in the region; 2) to create a new and consistent 2D and 3D model for the intrusion; and 3) to help constraining the origin of the observed seismicity and its possible relation with the existence of subcropping magmatic bodies.

We process recently acquired data - ground gravity survey (49 points) and drone-borne aeromagnetic survey – and integrate it with existing data. The interpretation of gravimetric results is complemented by density analysis of magmatic and host rocks. We perform 3D magnetic and gravity inversion to model the geometry of gravity and magnetic sources, and 2D magnetic forward modeling along a representative profile.

The calculated Bouguer gravity anomaly shows a positive gradient towards the southwest with a negative peak in the center of the Monchique mountain. However, when applied the terrain correction (complete Bouguer anomaly), this peak vanishes. This is justified by the similar mean density values for the syenite and host rocks, respectively 2560 kg/m³ and 2529 kg/m³.

The new aeromagnetic data allows for mapping the Monchique magnetic anomaly with unprecedented detail and reveal a 10 km elongated anomaly with 30 m wavelength with maximum 1707 nT amplitude. 3D susceptibility inversion models show a 15km long body with maximum depth between 5-10km, and susceptibility >0.02 SI, in agreement with previous susceptibility analysis in the region. The highest magnetic signal is found at Picota hill (east), but the deepest parts of the intrusion seem to be bellow Foia hill (west). It is noteworthy that earthquake hypocenters concentrate at depths of 5-20 km, thus below most of the modeled magmatic intrusion.  

This work was developed for the MSc thesis of GCC, in the frame of ATLAS project (PTDC/CTA-GEF/31272/2017), POCI-01-0145-FEDER-031272, FEDER-COMPETE/POCI 2020) partly funded by FCT. FCT is further acknowledged for support through projects UIDB/50019/2020-IDL, PTDC/CTA-GEF/1666/2020 and PTDC/CTA-GEF/6674/2020.

How to cite: Camargo, G., Neres, M., Bos, M., Martins, B., Custódio, S., and Terrinha, P.: Magnetic and gravimetric modeling of the Monchique magmatic intrusion in south Portugal, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2625, https://doi.org/10.5194/egusphere-egu22-2625, 2022.

How to cite: Capponi, M. and Sampietro, D.: eXperimental jOint inveRsioN (XORN) project: first results of a 3D joint gravity and magnetic inversion, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12321, https://doi.org/10.5194/egusphere-egu22-12321, 2022.

How to cite: Rodrigues, D., Neres, M., Terrinha, P., Bos, M., and Martins, B.: Drone-magnetic survey along the Alentejo coast (SW Portugal): a quest for the intruded Messejana fault, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6489, https://doi.org/10.5194/egusphere-egu22-6489, 2022.

Magnetic surveys employing Uncrewed Aerial Systems (UAS) allow a fast and affordable acquisition of high-resolution data. We developed a self-built carbon-fiber frame which can be used to attach magnetometers 0.5 m below an UAS. In order to remove undesired signals from the magnetic recordings that originate from the aircraft and that can cause strong heading errors, we apply calibration processes often referred to as magnetic compensation. These processes are usually applied for manned aerial surveys for both scalar and vector magnetometer data and require flying a calibration pattern prior to a survey. We recently published open-source software written in Python to process data and compute compensations for both scalar and vector magnetometers. We tested our method with two commercially available magnetometer systems (scalar and vector) by flying dense grid patterns over a test site using different suspension methods (magnetometer system attached to 2.8 m long tethers, fixed on the landing gear of the UAS, and fixed on our frame configuration). The accuracy of the magnetic recordings was assessed using both standard deviations of the calibration pattern and tie-line cross-over differences from the grid survey. Our frame configuration resulted after magnetic compensation in the highest accuracy of all configurations tested. The frame also allows for the acquisition of aeromagnetic data under a wide range of flight conditions. This is of great advantage compared to the often-used tethered solutions to avoid recording the aircraft’s signals. Since tethered payloads are prone to rotations and swing motions, they require skilled pilots and can be difficult to fly safely. In contrast to that, our system is easy to use and due to its high in-flight stability, even fully autonomous flights are possible. Since the calibration flights that are required for magnetic compensation need to be collected in areas with low magnetic gradients, it can be difficult to find suitable locations in areas with strong magnetic gradients – such as in volcanic and geothermally active regions. However, a survey collected at the location of the calibration site can be used to evaluate the geological magnetic signal. The compensation process involves then two successive evaluations of the compensation parameters. First, an approximate evaluation of the compensation parameters is done assuming a constant value of the magnetic field at the calibration site. The resulting compensation parameters are then used to compensate the survey data collected over the calibration site and evaluate the magnetic field along the calibration pattern trajectory. Second, the compensation parameters are reevaluated taking the magnetic field variations into account. We tested this double calibration scheme on recordings that were collected over the Krafla geothermal area in the Northern Volcanic Zone of Iceland. The double calibrated data resulted in higher accuracy than a single calibration showing that this method can improve magnetic compensation in magnetically high-gradient areas.

How to cite: Kaub, L., Bouligand, C., and Glen, J. M. G.: Collecting and calibrating magnetic data from surveys with Uncrewed Aerial Systems (UAS) and an approach for regions with strong magnetic gradients, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11258, https://doi.org/10.5194/egusphere-egu22-11258, 2022.

We compare marine magnetic measurements simultaneously acquired with absolute and three-component fluxgate sensors to evaluate their respective benefits for marine geophysical mapping and detection surveys.

Shom collected the data in shallow waters, in the Bay of Brest (France) and in the Iroise Sea, during two cruises in the Fall 2021. As per standard practice, an absolute Overhauser magnetometer was towed 180 m behind the 60 m-long Laplace and Lapérouse hydrographic vessels. In addition, two vector magnetometers were temporarily installed at the top of the ship’s mast and on the roof of a 10 m-long launch. Scalar data were processed following Shom’s standards: shift to sensor position, layback adjustments, removal of gyrations and spikes, filtering and calculation of magnetic anomalies by removing the IGRF model (Alken et al., 2021) and reducing external variations measured at a local reference station. Vector data were corrected for the strong magnetic fields generated by the hull and other steel components of the ship by the application of a “scalar compensation” using a least-squares regression analysis (Leliak, 1961) on data from figures of merit. The compensated vector data then need to be low-pass filtered to remove uncorrected variations of attitude and heading. Magnetic anomalies were finally computed by removing the median value for each profile and reducing external variations from the same local reference station.

Our first results show that maps of total-field anomalies derived from vector data acquired on the ship are very close to those of the absolute data upward-continued to the altitude of the mast. This similarity suggests that it is possible to perform good-quality magnetic surveys without the constraint of having to tow an instrument. The different processing steps however raise the detection threshold for anthropogenic objects lying on the seafloor or partially buried. Vector data acquired on smaller launchs are much more complicated to compensate as ranges of pitch, roll and heading variations are greater than for a large ship and potentially imperfectly sampled by the figures of merit.

How to cite: Reiller, H., Oehler, J.-F., Lucas, S., Marquis, G., Rouxel, D., and Munschy, M.: Comparison between towed absolute and shipborne 3C fluxgate magnetic measurements in shallow water. Applications for marine geophysical surveys., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1602, https://doi.org/10.5194/egusphere-egu22-1602, 2022.

To paraphrase a common model aphorism: “all magnetic maps are wrong, some are useful”. In other words, all maps of the Earth’s magnetic field are subject to uncertainty, both observationally and dynamically. Depending on the intended use of the map, this uncertainty will have varying implications. For those of us who build and use magnetic maps it is important to gain understanding of the uncertainty in these maps to ensure that they are clearly presented and suitable for a given use.

Uncertainty evaluation is a general challenge that affects all magnetic maps and models, but here we concentrate on maps of magnetic anomalies (i.e., perturbations of the Earth’s main field primarily due to variations in magnetic minerals in the crust and shallow mantle) in oceanic areas.

Magnetic anomaly maps for oceanic regions are typically representations of gridded data. The grids are built from available data which generally consists of marine trackline data with a range of ages, collection parameters and uncertainty in original observations. Data coverage and trackline geometries are highly variable around the world. For example, near-shore regions in the Northern Hemisphere tend to be well sampled, whereas open ocean portions of the Southern Hemisphere are poorly sampled.

Quantification of cell by cell uncertainty for magnetic anomaly grids can be subdivided into two regimes: cells containing data and cells without data. For cells containing data, factors such as point-wise observation uncertainty, number of observations, and spatial distribution of data, can be analysed to estimate grid value uncertainty. For interpolated cells, factors such as distance to nearest data cells, local field behavior, and uncertainty in surrounding cells are relevant.

Using NOAA/NCEI trackline marine data for portions of the Caribbean Sea and North Atlantic we are constructing and testing uncertainty models and methods for representing this uncertainty for a variety of magnetic map uses. For a marine magnetic anomaly grid of a portion of the North Atlantic at a 4 km grid interval (the same grid interval used by our global EMAG2 magnetic anomaly compilation), the calculated cell level uncertainty ranges from 20 nT to 150 nT with a mean value of 90 nT. This mean value is similar to the average grid uncertainty of 100 nT/cell that we estimated for marine areas of EMAG2v3. Different gridding approaches, including kriging or minimum curvature algorithms, yield variations in individual cell values, but these variations fall within our estimated uncertainty ranges. 

How to cite: Saltus, R., Chulliat, A., Meyer, B., and Bates, M.: Examination of magnetic map variability and uncertainty: crustal magnetic anomalies in oceanic areas, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6615, https://doi.org/10.5194/egusphere-egu22-6615, 2022.