A Global Climatological Model of Extreme Geomagnetic Field Fluctuations

This paper presents a multi-parameter global statistical model of extreme horizontal geomagnetic field fluctuations (dBH/dt), which are a useful input to models assessing the risk of geomagnetically induced currents in ground infrastructure. Generalised Pareto (GP) distributions were fitted to 1-minute measurements of |dBH/dt| from 125 magnetometers (with an average of 28 years of data per site) and return levels (RL) predicted for return periods (RP) between 5 and 500 years. Analytical functions characterise the profiles of maximum-likelihood GP model parameters and the derived RLs as a function of corrected geomagnetic latitude, λ. A sharp peak in both the GP shape parameter and the RLs is observed at |λ|=53° in both hemispheres, indicating a sharp equatorward limit of the auroral electrojet region. RLs also increase strongly in the dayside region poleward of the polar cusp (|λ|>75°) for RPs > 100 years. We describe how the GP model may be further refined by modelling the probability of occurrences of |dBH/dt| exceeding the 99.97th percentile as a function of month, magnetic local time, and the direction of the field fluctuation, dBH , and demonstrate that these patterns of occurrence align closely to known patterns of auroral substorm onsets, ULF Pc5 wave activity, and (storm) sudden commencement impacts. Changes in the occurrence probability profiles with the interplanetary magnetic field (IMF) orientation reveal further details of the nature of the ionospheric currents driving extreme |dBH/dt| fluctuations, such as the changing location of the polar cusp and seasonal variations explained by the Russell-McPherron effect

An empirical orthogonal function reanalysis of the northern polar external and induced magnetic field during solar cycle 23

We apply the method of data-interpolating Empirical Orthogonal Functions (EOFs) to ground-based magnetic vector data from the SuperMAG archive to produce a series of month-length reanalyses of the surface external and induced magnetic field (SEIMF) in 110,000 km2 equal-area bins over the entire northern polar region at 5-minute cadence over solar cycle 23, from 1997.0 to 2009.0. Each EOF re-analysis also decomposes the measured SEIMF variation into a hierarchy of spatio-temporal patterns which are ordered by their contribution to the monthly magnetic field variance. We find that the leading EOF patterns can each be (subjectively) interpreted as well-known SEIMF systems or their equivalent current systems. The relationship of the equivalent currents to the true current flow is not investigated. We track the leading SEIMF or equivalent current systems of similar type by inter-monthly spatial correlation, and apply graph theory to (objectively) group their appearance and relative importance throughout a solar cycle, revealing seasonal and solar cycle variation. In this way, we identify the spatiotemporal patterns which maximally contribute to SEIMF variability over a solar cycle. We propose this combination of EOF and graph theory as a powerful method for objectively defining and investigating the structure and variability of the SEIMF or their equivalent ionospheric currents for use in both geomagnetism and space weather applications. It is demonstrated here on solar cycle 23, but is extendable to any epoch with sufficient data coverage

Spatial variation in the responses of the surface external and induced magnetic field to the solar wind

We analyse the spatial variation in the response of the surface geomagnetic field (or the equivalent ionospheric current) to variations in the solar wind. Specifically, we regress a reanalysis of surface external and induced magnetic field (SEIMF) variations onto measurements of the solar wind. The regression is performed in monthly sets, independently for 559 regularly‐spaced locations covering the entire northern polar region above 50° magnetic latitude. At each location, we find the lag applied to the solar wind data that maximises the correlation with the SEIMF. The resulting spatial maps of these independent lags and regression coefficients provide a model of the localised SEIMF response to variations in the solar wind, which we call ‘Spatial Information from Distributed Exogenous Regression’ (SPIDER). We find that the lag and regression coefficients vary systematically with ionospheric region, season, and solar wind driver. In the polar cap region the SEIMF is best described by the By component of the interplanetary magnetic field (50–75% of total variance explained) at a lag ∼20–25 min. Conversely, in the auroral zone the SEIMF is best described by the solar wind ϵ function (60–80% of total variance explained), with a lag that varies with season and magnetic local time (MLT), from ∼15–20 min for dayside and afternoon MLT (except in Oct‐Dec) to typically 30–40 min for nightside and morning MLT, and even longer (60–65 min) around midnight MLT

Complex systems methods characterizing nonlinear processes in the near-Earth electromagnetic environment: recent advances and open challenges

Learning from successful applications of methods originating in statistical mechanics, complex systems science, or information theory in one scientific field (e.g., atmospheric physics or climatology) can provide important insights or conceptual ideas for other areas (e.g., space sciences) or even stimulate new research questions and approaches. For instance, quantification and attribution of dynamical complexity in output time series of nonlinear dynamical systems is a key challenge across scientific disciplines. Especially in the field of space physics, an early and accurate detection of characteristic dissimilarity between normal and abnormal states (e.g., pre-storm activity vs. magnetic storms) has the potential to vastly improve space weather diagnosis and, consequently, the mitigation of space weather hazards. This review provides a systematic overview on existing nonlinear dynamical systems-based methodologies along with key results of their previous applications in a space physics context, which particularly illustrates how complementary modern complex systems approaches have recently shaped our understanding of nonlinear magnetospheric variability. The rising number of corresponding studies demonstrates that the multiplicity of nonlinear time series analysis methods developed during the last decades offers great potentials for uncovering relevant yet complex processes interlinking different geospace subsystems, variables and spatiotemporal scales

Spatial variation in the responses of the surface external and induced magnetic field to the solar wind

We analyze the spatial variation in the response of the surface geomagnetic field (or the equivalent ionospheric current) to variations in the solar wind. Specifically, we regress a reanalysis of surface external and induced magnetic field (SEIMF) variations onto measurements of the solar wind. The regression is performed in monthly sets, independently for 559 regularly spaced locations covering the entire northern polar region above 50° magnetic latitude. At each location, we find the lag applied to the solar wind data that maximizes the correlation with the SEIMF. The resulting spatial maps of these independent lags and regression coefficients provide a model of the localized SEIMF response to variations in the solar wind, which we call “Spatial Information from Distributed Exogenous Regression.” We find that the lag and regression coefficients vary systematically with ionospheric region, season, and solar wind driver. In the polar cap region the SEIMF is best described by the By component of the interplanetary magnetic field (50–75% of total variance explained) at a lag ~20–25 min. Conversely, in the auroral zone the SEIMF is best described by the solar wind ϵ function (60–80% of total variance explained), with a lag that varies with season and magnetic local time (MLT), from ~15–20 min for dayside and afternoon MLT (except in Oct–Dec) to typically 30–40 min for nightside and morning MLT and even longer (60–65 min) around midnight MLT

Distribution and Occurrence Frequency of dB/dt Spikes During Magnetic Storms 1980–2020

The physical magnetospheric cause for geomagnetically induced currents (GICs) are rapid time-varying magnetic fields (dB/dt), which occur mainly during magnetic substorms and storms. When, where and why exactly such rapid dB/dt may occur is insufficiently understood. We investigated all storms since 1980 and analyzed the negative and positive dB/dt spikes (>|500| nT/min) in the north and east component using a worldwide coverage (SuperMAG). Our analysis confirmed the existence of two dB/dt spikes "hotspots" located in the pre-midnight and in the morning magnetic local time sector, independently of the geographic location of the stations. The associated physical phenomena are probably substorm current wedge onsets and westward traveling surges (WTS) in the evening sector, and wave- or vortex-like current flows in the morning sector known as Omega bands. We observed a spatiotemporal evolution of the negative northern dB/dt spikes. The spikes initially occur in the pre-midnight sector, and then develop in time toward the morning sector. This spatiotemporal sequence is correlated with bursts in the AE index, and can be repeated several times throughout a storm. Finally, we investigated the peak value of Dst and AE during the storm period in comparison with the dB/dt spike occurrence frequency, we did not find any correlation. This result implies that a moderate storm with many spikes can be as (or more) dangerous for ground-based infrastructures than a major storm with fewer dB/dt spikes. Our findings regarding the physical causes and characteristics of dB/dt spikes may help to improve the GIC forecast for the affected regions