Geomagnetism : review 2009

The Geomagnetism team measures, records, models and interprets variations in the Earth’s natural magnetic fields, across the world and over time. Our data and expertise help to develop scientific understanding of the evolution of the solid Earth and its atmospheric, ocean and space environments. We also provide geomagnetic products and services to industry and academics and we use our knowledge to inform and educate the public, government and the private sector

Geomagnetism review 2014

The Geomagnetism team measures, records, models and interprets variations in the Earth’s magnetic field. Our data and research help to develop scientific understanding of the evolution of the solid Earth and its atmospheric, ocean and space environments, and help develop our understanding of the geomagnetic hazard and its impact. We also provide geomagnetic products and services to industry and academics and we use our knowledge to inform the public, government and industry

Geomagnetic observatories: monitoring the Earth’s magnetic and space weather environment

Geomagnetism research provides insight into the Earth’s properties and processes, from the core out to space. For this reason continuous geomagnetic field observations have been carried out in the UK for more than 170 years. Geomagnetism also has diverse applications, in navigation, maps, even smart phone apps, and in the monitoring and prediction of space weather impacts on technology. Modern instruments, together with digital sampling, real-time data processing and product dissemination, support global space weather monitoring and modelling activities. In this review we describe the role of the UK geomagnetic observatory network in Earth and space weather science and applications

A novel weighting method for satellite magnetic data and a new global magnetic field model

A new data weighting scheme is introduced for satellite geomagnetic survey data. Data weights for individual satellite samples at 20-s spacing are derived from two ‘noise’ (or unmodelled signal) estimators for the sample. First, the standard deviation along the 20 s of satellite track, centred on each sample, is computed as a measure of local magnetic activity. Second a larger-scale noise estimator is defined in terms of a ‘local area vector activity’ (LAVA) index for the sample. This is derived from activity measured at the geographically nearest magnetic observatories to the sample point. Weighting of the satellite data by the inverse-sum-of-squares of these noise estimators then leads to a robust model of the field, the ‘Model of Earth’s Magnetic Environment 2008’, or MEME08, to about spherical harmonic degree 60. Our approach allows vector samples of the field to be used at all magnetic latitudes and, for example, results in a lithospheric magnetic field model with low spectral noise, comparable with other recent global models. We also do not require a particularly complex model parametrization, regularization, or prior data correction to remove estimates of unmodelled source fields

Probabilistic hazard assessment: application to geomagnetic activity

Probabilistic Hazard Assessment (PHA) provides an appropriate methodology for assessing space weather hazards and their impact on technology. PHA is widely used in geosciences to determine the probability of exceedance of critical thresholds, caused by one or more hazard sources. PHA has proved useful with limited historical data to estimate the likelihood of specific impacts. PHA has also driven the development of empirical and physical models, or ensembles of models, to replace measured data. Here we aim to highlight the PHA method to the space weather community and provide an example of how it could be used. In terms of space weather impact, the critical hazard thresholds might include the Geomagnetically Induced Current in a specific high voltage power transformer neutral, or the local pipe-to-soil potential in a particular metal pipe. We illustrate PHA in the space weather context by applying it to a twelve-year dataset of Earth-directed solar Coronal Mass Ejections (CME), which we relate to the probability that the global three-hourly geomagnetic activity index Kp exceeds specific thresholds. We call this a “Probabilistic Geomagnetic Hazard Assessment”, or PGHA. This provides a simple but concrete example of the method. We find that the cumulative probability of Kp > 6−, > 7−, > 8− and Kp = 9o is 0.359, 0.227, 0.090, 0.011, respectively, following observation of an Earth-directed CME, summed over all CME launch speeds and solar source locations. According to the historical Kp distribution, this represents an order of magnitude increase in the a priori probability of exceeding these thresholds. For the lower Kp thresholds, the results are somewhat distorted by our exclusion of coronal hole high-speed stream effects. The PHGA also reveals useful probabilistic associations between solar source location and subsequent maximum Kp for operational forecasters

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-min 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

Geoelectric field measurement, modelling and validation during geomagnetic storms in the UK

Significant geoelectric fields are produced by the interaction of rapidly varying magnetic fields with the conductive Earth, particularly during intense geomagnetic activity. Though usually harmless, large or sustained geoelectric fields can damage grounded infrastructure such as high-voltage transformers and pipelines via Geomagnetically Induced Currents (GICs). A key aspect of understanding the effects of space weather on grounded infrastructure is through the spatial and temporal variation of the geoelectric field. Globally, there are few long-term monitoring sites of the geoelectric field, so in 2012 measurements of the horizontal surface field were started at Lerwick, Eskdalemuir and Hartland observatories in the UK. Between 2012 and 2020, the maximum value of the geoelectric field observed was around 1 V/km in Lerwick, 0.5 V/km in Eskdalemuir and 0.1 V/km in Hartland during the March 2015 storm. These long-term observations also allow comparisons with models of the geoelectric field to be made. We use the measurements to compute magnetotelluric impedance transfer functions at each observatory for periods from 20 to 30,000 seconds. These are then used to predict the geoelectric field at the observatory sites during selected storm times that match the recorded fields very well (correlation around 0.9). We also compute geoelectric field values from a thin-sheet model of Britain, accounting for the diverse geological and bathymetric island setting. We find the thin-sheet model captures the peak and phase of the band-passed geoelectric field reasonably well, with linear correlation of around 0.4 in general. From these two modelling approaches, we generate geoelectric field values for historic storms (March 1989 and October 2003) and find the estimates of past peak geoelectric fields of up to 1.75 V/km in Eskdalemuir. However, evidence from high voltage transformer GIC measurements during these storms suggests these estimates are likely to represent an underestimate of the true value

Long term geomagnetically induced current observations from New Zealand: peak current estimates for extreme geomagnetic storms

Geomagnetically Induced Current (GIC) observations made in New Zealand over 14 years show induction effects associated with a rapidly varying horizontal magnetic field (dBH/dt) during geomagnetic storms. This study analyses the GIC observations in order to estimate the impact of extreme storms as a hazard to the power system in New Zealand. Analysis is undertaken of GIC in transformer number six in Islington, Christchurch (ISL M6), which had the highest observed currents during the 6 November 2001 storm. Using previously published values of 3000 nT/min as a representation of an extreme storm with 100 year return period, induced currents of ~455 A were estimated for Islington (with the 95% confidence interval range being ~155-605 A). For 200 year return periods using 5000 nT/min, current estimates reach ~755 A (confidence interval range 155-910 A). GIC measurements from the much shorter dataset collected at transformer number 4 in Halfway Bush, Dunedin, (HWB T4), found induced currents to be consistently a factor of three higher than at Islington, suggesting equivalent extreme storm effects of ~460-1815 A (100 year return) and ~460-2720 A (200 year return). An estimate was undertaken of likely failure levels for single phase transformers, such as HWB T4 when it failed during the 6 November 2001 geomagnetic storm, identifying that induced currents of ~100 A can put such transformer types at risk of damage. Detailed modeling of the New Zealand power system is therefore required put this regional analysis into a global context

A detailed model of the Irish High Voltage Power Network for simulating GICs

Constructing a power network model for geomagnetically induced current (GIC) calculations requires information on the DC resistances of elements within a network. This information is often not known, and power network models are simplified as a result, with assumptions used for network element resistances. Ireland's relatively small, isolated network presents an opportunity to model a complete power network in detail, using as much real‐world information as possible. A complete model of the Irish 400, 275, 220, and 110 kV network was made for GIC calculations, with detailed information on the number, type, and DC resistances of transformers. The measured grounding resistances at a number of substations were also included in the model, which represents a considerable improvement on previous models of the Irish power network for GIC calculations. Sensitivity tests were performed to show how calculated GIC amplitudes are affected by different aspects of the model. These tests investigated: (1) How the orientation of a uniform electric field affects GICs. (2) The effect of including/omitting lower voltage elements of the power network. (3) How the substation grounding resistances assumptions affected GIC values. It was found that changing the grounding resistance value had a considerable effect on calculated GICs at some substations and no discernible effect at others. Finally, five recent geomagnetic storm events were simulated in the network. It was found that heavy rainfall prior to the 26–28 August 2015 geomagnetic storm event may have had a measurable impact on measured GIC amplitudes at a 400/220 kV transformer ground

A risk assessment framework for the socio-economic impacts of electricity transmission infrastructure failure due to space weather: an application to the United Kingdom

Space weather phenomena have been studied in detail in the peer‐reviewed scientific literature. However, there has arguably been scant analysis of the potential socioeconomic impacts of space weather, despite a growing gray literature from different national studies, of varying degrees of methodological rigor. In this analysis, we therefore provide a general framework for assessing the potential socioeconomic impacts of critical infrastructure failure resulting from geomagnetic disturbances, applying it to the British high‐voltage electricity transmission network. Socioeconomic analysis of this threat has hitherto failed to address the general geophysical risk, asset vulnerability, and the network structure of critical infrastructure systems. We overcome this by using a three‐part method that includes (i) estimating the probability of intense magnetospheric substorms, (ii) exploring the vulnerability of electricity transmission assets to geomagnetically induced currents, and (iii) testing the socioeconomic impacts under different levels of space weather forecasting. This has required a multidisciplinary approach, providing a step toward the standardization of space weather risk assessment. We find that for a Carrington‐sized 1‐in‐100‐year event with no space weather forecasting capability, the gross domestic product loss to the United Kingdom could be as high as £15.9 billion, with this figure dropping to £2.9 billion based on current forecasting capability. However, with existing satellites nearing the end of their life, current forecasting capability will decrease in coming years. Therefore, if no further investment takes place, critical infrastructure will become more vulnerable to space weather. Additional investment could provide enhanced forecasting, reducing the economic loss for a Carrington‐sized 1‐in‐100‐year event to £0.9 billion