Estimating ionospheric currents by inversion from ground-based geomagnetic data and calculating geoelectric fields for studies of geomagnetically induced currents

This research focuses on the inversion of geomagnetic variation field measurements to obtain the source currents in the ionosphere and magnetosphere, and to determine the geoelectric fields at the Earth’s surface. During geomagnetic storms, the geoelectric fields create geomagnetically induced currents (GIC) in power networks. These GIC may disturb the operation of power systems, cause damage to power transformers, and even result in power blackouts. In this model, line currents running east–west along given latitudes are postulated to exist at a certain height above the Earth’s surface. This physical arrangement results in the fields on the ground being composed of a zero magnetic east component and a nonzero electric east component. The line current parameters are estimated by inverting Fourier integrals (over wavenumber) of elementary geomagnetic fields using the Levenberg–Marquardt technique. The output parameters of the model are the ionospheric current strength and the geoelectric east component at the Earth’s surface. A conductivity profile of the Earth is adapted from a shallow layered-Earth model for one observatory, together with a deep-layer model derived from satellite observations. This profile is used to obtain the ground surface impedance and therefore the reflection coefficient in the integrals. The inputs for the model are a spectrum of the geomagnetic data for 31 May 2013. The output parameters of the model are spectrums of the ionospheric current strength and of the surface geoelectric field. The inverse Fourier transforms of these spectra provide the time variations on the same day. The geoelectric field data can be used as a proxy for GIC in the prediction of GIC for power utilities. The current strength data can assist in the interpretation of upstream solar wind behaviour

Fast computation of the geoelectric field using the method of elementary current systems and planar Earth models

International audienceThe method of spherical elementary current systems provides an accurate modelling of the horizontal component of the geomagnetic variation field. The interpolated magnetic field is used as input to calculate the horizontal geoelectric field. We use planar layered (1-D) models of the Earth's conductivity, and assume that the electric field is related to the local magnetic field by the plane wave surface impedance. There are locations in which the conductivity structure can be approximated by a 1-D model, as demonstrated with the measurements of the Baltic Electromagnetic Array Research project. To calculate geomagnetically induced currents (GIC), we need the spatially integrated electric field typically in a length scale of 100km. We show that then the spatial variation of the electric field can be neglected if we use the measured or interpolated magnetic field at the site of interest. In other words, even the simple plane wave model is fairly accurate for GIC purposes. Investigating GIC in the Finnish high-voltage power system and in the natural gas pipeline, we find a good agreement between modelled and measured values, with relative errors less than 30% for large GIC values. Key words. Geomagnetism and paleomagnetism (geomagnetic induction; rapid time variations) ? Ionosphere (electric field and currents

Quantifying extreme behaviour in geomagnetic activity

Understanding the extremes in geomagnetic activity is an important component in understanding just how severe conditions can become in the terrestrial space environment. Extreme activity also has consequences for technological systems. On the ground, extreme geomagnetic behavior has an impact on navigation and position accuracy and the operation of power grids and pipeline networks. We therefore use a number of decades of one-minute mean magnetic data from magnetic observatories in Europe, together with the technique of extreme value statistics, to provide a preliminary exploration of the extremes in magnetic field variations and their one-minute rates of change. These extremes are expressed in terms of the variations that might be observed every 100 and 200 years in the horizontal strength and in the declination of the field. We find that both measured and extrapolated extreme values generally increase with geomagnetic latitude (as might be expected), though there is a marked maximum in estimated extreme levels between about 53 and 62 degrees north. At typical midlatitude European observatories (55–60 degrees geomagnetic latitude), compass variations may reach approximately 3–8 degrees/minute, and horizontal field changes may reach 1000–4000 nT/minute, in one magnetic storm once every 100 years. For storm return periods of 200 years the equivalent figures are 4–11 degrees/minute and 1000–6000 nT/minute

Seasonal and Diurnal Variation of Geomagnetic Activity: Revised \u3cem\u3eDst\u3c/em\u3e Versus External Drivers

Daily and seasonal variability of long time series of magnetometer data from Dst stations is examined. Each station separately shows a local minimum of horizontal magnetic component near 18 local time (LT) and weakest activity near 06 LT. The stations were found to have different baselines such that the average levels of activity differed by about 10 nT. This effect was corrected for by introducing a new “base method” for the elimination of the secular variation. This changed the seasonal variability of the Dst index by about 3 nT. The hemispheric differences between the annual variation (larger activity during local winter and autumn solstice) were demonstrated and eliminated from the Dst index by addition of two Southern Hemisphere stations to a new index termed Dst6. Three external drivers of geomagnetic activity were considered: the heliographic latitude, the equinoctial effect, and the Russell–McPherron effect. Using the newly created Dst6 index, it is demonstrated that these three effects account for only about 50% of the daily and seasonal variability of the index. It is not clear what drives the other 50% of the daily and seasonal variability, but it is suggested that the station distribution may play a role