Ciaran Beggan

International Geomagnetic Reference Field: the 12th generation

The 12th generation of the International Geomagnetic Reference Field (IGRF) was adopted in December 2014 by the Working Group V-MOD appointed by the International Association of Geomagnetism and Aeronomy (IAGA). It updates the previous IGRF generation with a definitive main field model for epoch 2010.0, a main field model for epoch 2015.0, and a linear annual predictive secular variation model for 2015.0-2020.0. Here, we present the equations defining the IGRF model, provide the spherical harmonic coefficients, and provide maps of the magnetic declination, inclination, and total intensity for epoch 2015.0 and their predicted rates of change for 2015.0-2020.0. We also update the magnetic pole positions and discuss briefly the latest changes and possible future trends of the Earth’s magnetic field.

Generation of 100‐year geomagnetically induced current scenarios

A series of 100-year extreme geoelectric field and geomagnetically induced current (GIC) scenarios are explored by taking into account the key geophysical factors associated with the geomagnetic induction process. More specifically, we derive explicit geoelectric field temporal profiles as a function of ground conductivity structures and geomagnetic latitudes. We also demonstrate how the extreme geoelectric field scenarios can be mapped into GIC. Generated statistics indicate 20 V/km and 5 V/km 100-year maximum 10-s geoelectric field amplitudes at high-latitude locations with poorly conducting and well-conducting ground structures, respectively. We show that there is an indication that geoelectric field magnitudes may experience a dramatic drop across a boundary at about 40°–60° of geomagnetic latitude. We identify this as a threshold at about 50° of geomagnetic latitude. The sub-threshold geoelectric field magnitudes are about an order of magnitude smaller than those at super-threshold geomagnetic latitudes. Further analyses are required to confirm the existence and location of the possible latitude threshold. The computed extreme GIC scenarios can be used in further engineering analyses that are needed to quantify the geomagnetic storm impact on conductor systems such as high-voltage power transmission systems. To facilitate further work on the topic, the digital data for generated geoelectric field scenarios are made publicly available.

The Swarm Satellite Constellation Application and Research Facility (SCARF) and Swarm data products

Swarm, a three-satellite constellation to study the dynamics of the Earth’s magnetic field and its interactions with the Earth system, is expected to be launched in late 2013. The objective of the Swarm mission is to provide the best ever survey of the geomagnetic field and its temporal evolution, in order to gain new insights into the Earth system by improving our understanding of the Earth’s interior and environment. In order to derive advanced models of the geomagnetic field (and other higher-level data products) it is necessary to take explicit advantage of the constellation aspect of Swarm. The Swarm SCARF (SatelliteConstellationApplication andResearchFacility) has been established with the goal of deriving Level-2 products by combination of data from the three satellites, and of the various instruments. The present paper describes the Swarm input data products (Level-1b and auxiliary data) used by SCARF, the various processing chains of SCARF, and the Level-2 output data products determined by SCARF.

Evaluation of candidate geomagnetic field models for IGRF-12

BackgroundThe 12th revision of the International Geomagnetic Reference Field (IGRF) was issued in December 2014 by the International Association of Geomagnetism and Aeronomy (IAGA) Division V Working Group V-MOD (http://www.ngdc.noaa.gov/IAGA/vmod/igrf.html). This revision comprises new spherical harmonic main field models for epochs 2010.0 (DGRF-2010) and 2015.0 (IGRF-2015) and predictive linear secular variation for the interval 2015.0-2020.0 (SV-2010-2015).FindingsThe models were derived from weighted averages of candidate models submitted by ten international teams. Teams were led by the British Geological Survey (UK), DTU Space (Denmark), ISTerre (France), IZMIRAN (Russia), NOAA/NGDC (USA), GFZ Potsdam (Germany), NASA/GSFC (USA), IPGP (France), LPG Nantes (France), and ETH Zurich (Switzerland). Each candidate model was carefully evaluated and compared to all other models and a mean model using well-defined statistical criteria in the spectral domain and maps in the physical space. These analyses were made to pinpoint both troublesome coefficients and the geographical regions where the candidate models most significantly differ. Some models showed clear deviation from other candidate models. However, a majority of the task force members appointed by IAGA thought that the differences were not sufficient to exclude models that were well documented and based on different techniques.ConclusionsThe task force thus voted for and applied an iterative robust estimation scheme in space. In this paper, we report on the evaluations of the candidate models and provide details of the algorithm that was used to derive the IGRF-12 product.

The Swarm Initial Field Model for the 2014 geomagnetic field

Data from the first year of ESAs Swarm constellation mission are used to derive the Swarm Initial Field Model (SIFM), a new model of the Earths magnetic field and its time variation. In addition to the conventional magnetic field observations provided by each of the three Swarm satellites, explicit advantage is taken of the constellation aspect by including east-west magnetic intensity gradient information from the lower satellite pair. Along-track differences in magnetic intensity provide further information concerning the north-south gradient. The SIFM static field shows excellent agreement (up to at least degree 60) with recent field models derived from CHAMP data, providing an initial validation of the quality of the Swarm magnetic measurements. Use of gradient data improves the determination of both the static field and its secular variation, with the mean misfit for east-west intensity differences between the lower satellite pair being only 0.12 nT.

New image processing software for analyzing object size-frequency distributions, geometry, orientation, and spatial distribution

Geological Image Analysis Software (GIAS) combines basic tools for calculating object area, abundance, radius, perimeter, eccentricity, orientation, and centroid location, with the first automated method for characterizing the aerial distribution of objects using sample-size-dependent nearest neighbor (NN) statistics. The NN analyses include tests for (1) Poisson, (2) Normalized Poisson, (3) Scavenged k=1, and (4) Scavenged k=2 NN distributions. GIAS is implemented in MATLAB with a Graphical User Interface (GUI) that is available as pre-parsed pseudocode for use with MATLAB, or as a stand-alone application that runs on Windows and Unix systems. GIAS can process raster data (e.g., satellite imagery, photomicrographs, etc.) and tables of object coordinates to characterize the size, geometry, orientation, and spatial organization of a wide range of geological features. This information expedites quantitative measurements of 2D object properties, provides criteria for validating the use of stereology to transform 2D object sections into 3D models, and establishes a standardized NN methodology that can be used to compare the results of different geospatial studies and identify objects using non-morphological parameters.

Sensitivity of geomagnetically induced currents to varying auroral electrojet and conductivity models

Geomagnetically induced currents (GIC) are created by the interaction of rapid changes in the magnitude of the magnetic field with the conductive subsurface of the Earth. The changing magnetic field induces electric currents, which are particularly strong along boundaries between regions of contrasting conductivity structure such as the land and sea. A technique known as the ‘thin-sheet approximation’ can be used to determine the electric field at the Earth’s surface, which in turn allows the calculation of GIC in the earthing connections of high-voltage nodes within a power grid. The thin-sheet approximation uses a spatially varying conductance over the region of interest on a 2D surface, combined with a 1D layered model of upper lithosphere conductance. We produce synthetic models of the auroral electrojet in different locations over the United Kingdom (UK) and investigate the effects of varying the 2D thin-sheet model. We assess different two-dimensional surface conductance models and vary the underlying 1D conductivity models to simulate the effects of resistant through to conductive lithosphere. With an advanced network model of high-voltage electrical distribution grid, we compute the expected GIC at each node in the system given the input surface electric fields from the various synthetic electrojets and conductivity models. We find that the electrojet location is the primary control on the size of GIC, with conductivity being a second-order effect in general, though it can be locally important.

Understanding GIC in the UK and French High Voltage Transmission Systems During Severe Magnetic Storms

The measurement and collection of digital magnetic field data in Europe extends back to the 1970s, providing over 30 years of data for the analysis of severe space weather. Although paper records can potentially extend these datasets back by over a century, few digitized records are currently available for use in extreme studies. Therefore we rely on theoretical arguments and modelling to elucidate the largest likely variations of the magnetic field. We assess the relationship, during the three largest storms in the digital era, between variations in the horizontal magnetic field and the largest measured Dst index to estimate likely magnetic variations for more extreme storms in northern and mid-latitude Europe. We examine how Geomagnetically Induced Currents (GIC) flow in the UK and French networks during recent severe storms and analyse the sensitivity of these flows to changes in grid parameters. The maximum GIC computed at any one node in the French and UK grids are 44 A and 208 A respectively. Sensitivity tests show that while gross changes of the whole network structure, such as disconnecting parts of the network, reduces the mean GIC per node, changes in GIC at individual nodes have distinct behaviors implying that local effects are network-dependent and require detailed modelling to sufficiently characterize GIC. In addition, the scale factors we have derived allow GIC results from recent storms to be up-scaled to estimate the potential risk to the system from more extreme events, such as the Carrington storm in 1859.

Derivation and use of core surface flows for forecasting secular variation

Improving forecasts of the temporal and spatial changes of the Earths main magnetic field over periods of less than 5 years has important scientific and economic benefits. Various methods for forecasting the rate of change, or secular variation, have been tried over the past few decades, ranging from the extrapolation of trends in ground observatory measurements to computational geodynamo modeling with data assimilation from historical magnetic field models. We examine the utility of an intermediate approach, using temporally varying core surface flow models derived from relatively short periods of magnetic field data to produce, by advection, secular variation estimates valid for the Earths surface. We describe a new method to compute a core flow changing linearly with time from magnetic secular variation and acceleration data. We invert a combination of data from the CHAMP satellite mission and ground observatories over the period 2001.0 to 2010.0 for a series of such models. We assess their ability to forecast magnetic field changes by comparing them to CHAOS-4, a state-of-the-art model using data from 1997 to 2014.5. We show that the magnetic field predictions tend to have a lower root-mean-square difference from CHAOS-4 than the International Geomagnetic Reference Field or World Magnetic Map series of secular variation models.

Decadal period external magnetic field variations determined via eigenanalysis

We perform a reanalysis of hourly mean magnetic data from ground-based observatories spanning 1997-2009 inclusive, in order to isolate (after removal of core and crustal field estimates) the spatiotemporal morphology of the external fields important to mantle induction, on (long) periods of months to a full solar cycle. Our analysis focuses on geomagnetically quiet days, and mid- to low-latitudes. We use the climatological eigenanalysis technique called Empirical Orthogonal Functions (EOFs), which allows us to identify discrete spatiotemporal patterns with no a priori specification of their geometry – the form of the decomposition is controlled by the data. We apply a spherical harmonic analysis (SHA) to the EOF outputs in a joint inversion for internal and external coefficients. The results justify our assumption that the EOF procedure responds primarily to the long-period external inducing field contributions. Though we cannot determine uniquely the contributory source regions of these inducing fields, we find that they have distinct temporal characteristics which enable some inference of sources. An identified annual-period pattern appears to stem from a north-south seasonal motion of the background mean external field distribution. Separate patterns of semi-annual and solar-cycle-length periods appear to stem from the amplitude modulations of spatially fixed background fields.