RESUMEN
Space weather has the potential to impact ground-based technologies on Earth, affecting many systems including railway signalling. This study uses a recently developed model to analyse the impact of geomagnetically induced currents on railway signalling systems in the United Kingdom during the March 1989 and October 2003 geomagnetic storms. The March 1989 storm is also scaled to estimate a 1-in-100 year and a 1-in-200 year extreme storm. Both the Glasgow to Edinburgh line, and the Preston to Lancaster section of the West Coast Main Line are modelled. No "right side" failures (when unoccupied sections appear occupied) are suggested to have occurred during either storm, and the total number of potential "wrong side" failures (when occupied sections appear clear) is low. However, the modelling indicates "right side" and "wrong side" failures are possible on both routes during the 1-in-100 year and 1-in-200 year extreme storms, with the Glasgow to Edinburgh line showing more total misoperations than the Preston to Lancaster section of the West Coast Main Line. A 1-in-100 year or 1-in-200 year extreme storm would result in misoperations over an extended period of time, with most occurring over a duration of 2-3 h either side of the peak of the storm.
RESUMEN
Continuous geomagnetic records of the strength and direction of the Earth's field at the surface extend back to the 1840s. Over the past two centuries, eight observatories have existed in the United Kingdom, which measured the daily field variations using light-sensitive photographic paper to produce analogue magnetograms. Around 350,000 magnetograms have been digitally photographed at high resolution. However, converting the traces to digital values is difficult and time consuming as the magnetograms can have over-lapping lines, low quality recordings and obscure metadata for conversion to SI units. We discuss our approach to digitizing the traces from large geomagnetic storms and highlight some of the issues to be aware of when capturing magnetic information from analogue measurements. These include cross-checking the final digitized values with the recorded hourly mean values from observatory year books and comparing several observatory records for the same storm to catch errors such as sign inversions or incorrect 'wrap-around' of data on the paper records.
RESUMEN
BACKGROUND: Migratory animals use information from the Earth's magnetic field on their journeys. Geomagnetic navigation has been observed across many taxa, but how animals use geomagnetic information to find their way is still relatively unknown. Most migration studies use a static representation of geomagnetic field and do not consider its temporal variation. However, short-term temporal perturbations may affect how animals respond - to understand this phenomenon, we need to obtain fine resolution accurate geomagnetic measurements at the location and time of the animal. Satellite geomagnetic measurements provide a potential to create such accurate measurements, yet have not been used yet for exploration of animal migration. METHODS: We develop a new tool for data fusion of satellite geomagnetic data (from the European Space Agency's Swarm constellation) with animal tracking data using a spatio-temporal interpolation approach. We assess accuracy of the fusion through a comparison with calibrated terrestrial measurements from the International Real-time Magnetic Observatory Network (INTERMAGNET). We fit a generalized linear model (GLM) to assess how the absolute error of annotated geomagnetic intensity varies with interpolation parameters and with the local geomagnetic disturbance. RESULTS: We find that the average absolute error of intensity is - 21.6 nT (95% CI [- 22.26555, - 20.96664]), which is at the lower range of the intensity that animals can sense. The main predictor of error is the level of geomagnetic disturbance, given by the Kp index (indicating the presence of a geomagnetic storm). Since storm level disturbances are rare, this means that our tool is suitable for studies of animal geomagnetic navigation. Caution should be taken with data obtained during geomagnetically disturbed days due to rapid and localised changes of the field which may not be adequately captured. CONCLUSIONS: By using our new tool, ecologists will be able to, for the first time, access accurate real-time satellite geomagnetic data at the location and time of each tracked animal, without having to start new tracking studies with specialised magnetic sensors. This opens a new and exciting possibility for large multi-species studies that will search for general migratory responses to geomagnetic cues. The tool therefore has a potential to uncover new knowledge about geomagnetic navigation and help resolve long-standing debates.
RESUMEN
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.