Testing statistical palaeomagnetic field models against directional data affected by measurement errors

International audienceIn a previous paper, Khokhlov et al. introduced a method to test the compatibility of so-called 'giant Gaussian process' (GGP) statistical models of the palaeomagnetic field against any palaeosecular variation database. This method did not take measurement errors into account. It therefore lacked practical usefulness. In the present paper, we remedy this and generalize the method to account for measurement errors in a way consistent with both the assumptions underlying the GGP approach and the nature of those errors. The method is implemented to test GGP models against any directional data set affected by Fisherian errors. Simulations show that the method can usefully discriminate which GGP model best explains a given data set. Applying the method to test six published GGP models against a test Bruhnes stable polarity data set extracted from the Quidelleur et al. database, it is found that all but one model (that of Quidelleur and Courtillot) should be rejected. Although this result should be taken with care, and does not necessarily imply that this model is superior to other models (Quidelleur and Courtillot precisely used the Quidelleur et al. database to infer their model), it clearly shows that in practice also, and with the databases currently available, the method can discriminate various candidate GGP models. It also shows that the statistical behaviour of the geomagnetic field at times of stable polarity can indeed be described in a consistent way in terms of a GGP model. This 'forward' testing method could ultimately be used to design an 'inverse' approach to GGP modelling of the palaeomagnetic field

Can core-surface flow models be used to improve the forecast of the Earth's main magnetic field?

[1] Geomagnetic main field models used for navigation are updated every 5 years and contain a forecast of the geomagnetic secular variation for the upcoming epoch. Forecasting secular variation is a difficult task. The change of the main magnetic field is thought to be principally due to advection of the field by flow at the surface of the outer core on short timescales and when large length scales are considered. With accurate secular variation (SV) and secular acceleration (SA) models now available from new satellite missions, inverting for the flow and advecting it forward could lead to a more accurate prediction of the main field. However, this scheme faces two significant challenges. The first arises from the truncation of the observable main field at spherical harmonic degree 13. This can however be handled if the true core flow is large scale and has a rapidly decaying energy spectrum. The second is that even at a given single epoch the instantaneous SV and SA cannot simultaneously be explained by a steady flow. Nevertheless, we find that it may be feasible to use flow models for an improved temporal extrapolation of the main field. A medium-term (≈10 years) hindcast of the field using a steady flow model outperforms the usual extrapolation using the presently observed SV and SA. On the other hand, our accelerated, toroidal flow model, which explains a larger portion of the observed average SA over the 2000–2005 period, fails to improve both the short-term and medium-term hindcasts of the field. This somewhat paradoxical result is related to the occurrence of so-called geomagnetic jerks, the still poorly known dynamical nature of which remains the main obstacle to improved geomagnetic field forecasts

Special issue “Swarm science results after 2 years in space”

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Magnetic Schumann Resonances in Swarm ASM Burst Mode, VFM HF and e-POP Data?

The Schumann Resonances (SR) consist of a series of peaks in spectral power in the magnetic and electric field at frequencies of around 8, 14, 22 and 27 Hz. They arise from the continuous occurrence of equatorial lightning strikes [1]. The broadband electromagnetic emission from each lightning strike is contained within a waveguide, bounded by the Earth’s surface and the ionosphere at around 80 km in altitude. The SR are detectable on the ground using sensitive search-coil magnetometers. They have a large Q-factor (i.e. broad peaks) and an obvious diurnal and seasonal variation due to the location of landmasses. Although, the electric field SR have been detected in space using the C/NOFS satellite in 2010/11 at altitudes of 600 km [2], there have been no confirmed measurements using magnetic field instruments. There are theoretical arguments that the ionosphere acts to fully shield the magnetic signal from penetrating out of the atmosphere to Swarm altitudes, though other models suggest some secondary signals occur [3].We examine data from the Swarm Absolute Scalar Magnetometer Burst Mode (250 Hz), the Swarm Vector Field Magnetometer High Resolution (50Hz) and enhanced Polar Outflow Probe (e-POP) Magnetic Field (160 Hz) instruments collected on the 19-Jan-2014 during the commissioning phase of the mission to look for SR signals

A 2015 International Geomagnetic Reference Field (IGRF) candidate model based on <i>Swarm’s</i> experimental absolute magnetometer vector mode data

International audienceEach of the three satellites of the European Space Agency Swarm mission carries an absolute scalar magnetometer (ASM) that provides the nominal 1-Hz scalar data of the mission for both science and calibration purposes. These ASM instruments, however, also deliver autonomous 1-Hz experimental vector data. Here, we report on how ASM-only scalar and vector data from the Alpha and Bravo satellites between November 29, 2013 (a week after launch) and September 25, 2014 (for on-time delivery of the model on October 1, 2014) could be used to build a very valuable candidate model for the 2015.0 International Geomagnetic Reference Field (IGRF). A parent model was first computed, describing the geomagnetic field of internal origin up to degree and order 40 in a spherical harmonic representation and including a constant secular variation up to degree and order 8. This model was next simply forwarded to epoch 2015.0 and truncated at degree and order 13. The resulting ASM-only 2015.0 IGRF candidate model is compared to analogous models derived from the mission's nominal data and to the now-published final 2015.0 IGRF model. Differences among models mainly highlight uncertainties enhanced by the limited geographical distribution of the selected data set (essentially due to a lack of availability of data at high northern latitude satisfying nighttime conditions at the end of the time period considered). These appear to be comparable to differences classically observed among IGRF candidate models. These positive results led the ASM-only 2015.0 IGRF candidate model to contribute to the construction of the final 2015.0 IGRF model