The Magnetic Sun: Reversals and Long-Term Variations

A didactic introduction to current thinking on some aspects of the solar dynamo is given for geophysicists and planetary scientists.Comment: 17 pages, 9 figures; Space Science Rev., in pres

On the usage of geomagnetic indices for data selection in internal field modelling

We present a review on geomagnetic indices describing global geomagnetic storm activity (Kp, am, Dst and dDst/dt) and on indices designed to characterize high latitude currents and substorms (PC and AE-indices and their variants). The focus in our discussion is in main field modelling, where indices are primarily used in data selection criteria for weak magnetic activity. The publicly available extensive data bases of index values are used to derive joint conditional Probability Distribution Functions (PDFs) for different pairs of indices in order to investigate their mutual consistency in describing quiet conditions. This exercise reveals that Dst and its time derivative yield a similar picture as Kp on quiet conditions as determined with the conditions typically used in internal field modelling. Magnetic quiescence at high latitudes is typically searched with the help of Merging Electric Field (MEF) as derived from solar wind observations. We use in our PDF analysis the PC-index as a proxy for MEF and estimate the magnetic activity level at auroral latitudes with the AL-index. With these boundary conditions we conclude that the quiet time conditions that are typically used in main field modelling (, and ) correspond to weak auroral electrojet activity quite well: Standard size substorms are unlikely to happen, but other types of activations (e.g. pseudo breakups ) can take place, when these criteria prevail. Although AE-indices have been designed to probe electrojet activity only in average conditions and thus their performance is not optimal during weak activity, we note that careful data selection with advanced AE-variants may appear to be the most practical way to lower the elevated RMS-values which still exist in the residuals between modeled and observed values at high latitudes. Recent initiatives to upgrade the AE-indices, either with a better coverage of observing stations and improved baseline corrections (the SuperMAG concept) or with higher accuracy in pinpointing substorm activity (the Midlatitude Positive Bay-index) will most likely be helpful in these efforts.</p

Quality of life in hidradenitis suppurativa: An update

Knowledge on hidradenitis suppurativa/acne inversa (HS) is rapidly increasing. HS has a profound impact on patients and their family life. Several factors, such as comorbidities, unemployment and HS severity, make this impact even more severe. The most widely used instrument to measure this impact is the dermatology-specific DLQI. We also identified six HS-specific healthrelated quality of life (HRQoL) instruments. Of them, HIDRAdisk, HSIA, HiSQOL and HSQoL-24 are better validated but there is still lack of experience of its use. Several treatment methods showed positive effect on patients’ HRQoL. Surgery remains a method with a substantial positive effect on HRQoL. Several studies confirming a positive effect of adalimumab on the HRQoL of patients with HS were published during the last three years. Data on the influence of several other biologics on HRQoL of HS patients are controversial or based on studies with a small number of patients

Local flow estimation at the top of the Earth’s core using Physics Informed Neural Networks

The Earth’s main geomagnetic field arises from the constant motion of the fluid outer core. By assuming that the field changes are advection-dominated, and that diffusion only plays a minor role, the fluid motion at the core surface can be related to the secular variation of the geomagnetic field, providing an observational approach to understanding the motions in the deep Earth. The majority of existing core flow models are global, showing features such as an eccentric planetary gyre, with some evidence of rapid regional changes. By construction, the flow defined at any location by such a model depends on all magnetic field variations across the entire core–mantle boundary: because of this nonlocal dependence of the flow on the magnetic field, it is very challenging to interpret local structures in the flow as due to specific local changes in magnetic field. Here we present an alternative strategy in which we construct regional flow models that rely only on local secular changes. We use a novel technique based on machine learning termed Physics-Informed Neural Networks (PINNs), in which we seek a regional flow model that simultaneously fits both the local magnetic field variation and dynamical conditions assumed satisfied by the flow. Although we present results using the Tangentially Geostrophic flow constraint, we set out a modelling framework for which the physics constraint can be easily changed by altering a single line of code. After validating the PINN-based method on synthetic flows, we apply our method to the CHAOS-8.1 geomagnetic field model, itself based on data from Swarm. Constructing a global mosaic of regional flows, we reproduce the planetary gyre, providing independent evidence that the strong secular changes at high latitude and in equatorial regions are part of the same global feature. Our models also corroborate regional changes in core flows over the last decade. In our models, we find that the azimuthal flow under South America has changed sign quasi-periodically, with a recent sign change in 2022. Furthermore, our models endorse the existence of a dynamic high latitude jet, which began accelerating around 2005 but has been weakening since 2017

Decadal variability in core surface flows deduced from geomagnetic observatory monthly means

Monthly means of the magnetic field measurements at ground observatories are a key data source for studying temporal changes of the core magnetic field. However, when they are calculated in the usual way, contributions of external (magnetospheric and ionospheric) origin may remain, which make them less favourable for studying the field generated by dynamo action in the core. We remove external field predictions, including a new way of characterizing the magnetospheric ring current, from the data and then calculate revised monthly means using robust methods. The geomagnetic secular variation (SV) is calculated as the first annual differences of these monthly means, which also removes the static crustal field. SV time-series based on revised monthly means are much less scattered than those calculated from ordinary monthly means, and their variances and correlations between components are smaller. On the annual to decadal timescale, the SV is generated primarily by advection in the fluid outer core. We demonstrate the utility of the revised monthly means by calculating models of the core surface advective flow between 1997 and 2013 directly from the SV data. One set of models assumes flow that is constant over three months; such models exhibit large and rapid temporal variations. For models of this type, less complex flows achieve the same fit to the SV derived from revised monthly means than those from ordinary monthly means. However, those obtained from ordinary monthly means are able to follow excursions in SV that are likely to be external field contamination rather than core signals. Having established that we can find models that fit the data adequately, we then assess how much temporal variability is required. Previous studies have suggested that the flow is consistent with torsional oscillations (TO), solid body-like oscillations of fluid on concentric cylinders with axes aligned along the Earth's rotation axis. TO have been proposed to explain decadal timescale changes in the length-of-day. We invert for flow models where the only temporal changes are consistent with TO, but such models have an unacceptably large data misfit. However, if we relax the TO constraint to allow a little more temporal variability, we can fit the data as well as with flows assumed constant over three months, demonstrating that rapid SV changes can be reproduced by rather small flow changes. Although the flow itself changes slowly, its time derivative can be locally (temporally and spatially) large, in particular when and where core surface secular acceleration peaks. Spherical harmonic expansion coefficients of the flows are not well resolved, and many of them are strongly correlated. Averaging functions, a measure of our ability to determine the flow at a given location from the data distribution available, are poor approximations to the ideal, even when centred on points of the core surface below areas of high observatory density. Both resolution and averaging functions are noticeably worse for the toroidal flow component, which dominates the flow, than the poloidal flow component, except around the magnetic equator where averaging functions for both components are poor.<br/

Independent validation of Swarm Level2 magnetic field products and 'Quick Look' for Level 1b data

Magnetic field models are produced on behalf of the European Space Agency (ESA) by an independent scientific consortium known as the Swarm Satellite Constellation Application and Research Facility (SCARF), through the Level 2 Processor (L2PS). The consortium primarily produces magnetic field models for the core, lithosphere, ionosphere and magnetosphere. Typically, for each magnetic product, two magnetic field models are produced in separate chains using complementary data selection and processing techniques. Hence, the magnetic field models from the complementary processing chains will be similar but not identical. The final step in the overall L2PS therefore involves inspection and validation of the magnetic field models against each other and against data from (semi-) independent sources (e.g. ground observatories). We describe the validation steps for each magnetic field product and the comparison against independent datasets, and we show examples of the output of the validation. In addition, the L2PS also produces a daily set of `Quick Look' output graphics and statistics to monitor the overall quality of Level 1b data issued by ESA. We describe the outputs of the `Quick Look' chain