The geomagnetic 'solar flare effect' (SFE) results from excess ionization produced by solar X-ray and EUV radiation in the Earth's upper atmosphere. The simultaneous detection of an SFE at the time of the Carrington flare in 1859 allows us to calibrate this event on the (revised) modern GOES X-ray scale. For this purpose, we make a basic correlation analysis of SFEs recorded at 1-min averaging at a single geomagnetic observatory, the Hartland station, as the site closest to London and the two original observing stations (Kew and Greenwich). We find the equivalent GOES magnitude of the Carrington event to have been X105(+ 41 ,) (-24 )based on a sample of 39 X-class flare events observable as SFEs, with the estimate limited by systematic errors in the interpretation of the modern data. This estimate agrees with estimates based on the visual observations of the flare. This suggests that the Carrington flare was not a 'superflare' in the sense that it required physics beyond that needed for ordinary flares.

Ground-based impacts of solar activity through the interaction of the Earth’s magnetic field with the solar wind have been classified as a major natural hazard in many mid-high latitude countries. Effects on the ground are closely coupled to local geology due to varying electrical conductivity of different rock types. The conductivity distribution can be estimated from magnetotelluric (MT) measurements, which then is used for the large-scale modelling of the time-varying ground electric field. This geoelectric field model serves as the input for the impact analysis of Space Weather on ground-based systems such as the high voltage power grid, gas pipelines and railways. Previous efforts in the UK had been based on a thin-sheet approach, but MT data better captures the true conductivity variations in the Earth’s crust and mantle that drive geoelectric fields during space weather activity. Within the UK-funded SWIMMR programme, we collected long-period MT data at 50 sites with site spacing of 50-70 km in Britain during a field campaign in 2021-23, adding to a few existing legacy data sets. Using a frequency-domain approach and geomagnetic field observations from the UK geomagnetic observatories and variometer sites we can derive models of the geoelectric field during geomagnetic active times. Using the new MT data, we revisit GIC estimates for both historic and modern geomagnetic storms, perform extreme value analysis of both geoelectric fields and GICs, and implement a fast now- and forecasting of ground effects within the SWIMMR framework.

Abstract Dedicated scientific measurements of the strength and direction of the Earth's magnetic field began at Greenwich and Kew observatories in London, United Kingdom, in the middle of the nineteenth century. Using advanced techniques for the time, collimated light was focussed onto mirrors mounted on free‐swinging magnetized needles which reflected onto photographic paper, allowing continuous analog magnetograms to be recorded. By good fortune, both observatories were in full operation during the so‐called Carrington storm in early September 1859 and its precursor storm in late August 1859. Based on digital images of the magnetograms and information from the observatory yearbooks and scientific papers, it is possible to scale the measurements to International System of Units (SI units) and extract quasi‐minute cadence spot values. However, due to the magnitude of the storms, the periods of the greatest magnetic field variation were lost as the traces moved off‐page. We present the most complete digitized magnetic records to date of the 10‐day period from 25 August to 5 September 1859 encompassing the Carrington storm and its lesser recognized precursor on 28 August. We demonstrate the good correlation between observatories and estimate the instantaneous rate of change of the magnetic field.

<p>Dedicated scientific measurements of the strength and direction of the Earth's field began at Greenwich and Kew observatories in London, UK, in the middle of the 19th century. Using advanced techniques for the time, light-sensitive photographic paper and light-levered reflections from magnetized needles allowed continuous analogue magnetograms to be recorded. By good fortune, both observatories were in full operation during the so-called Carrington storm in late August/early September 1859 providing as complete a record as possible. Based on digital images of the magnetograms and information from the observatory yearbooks and scientific papers scaling the measurements to SI units is possible at minute-mean cadence. However, due to the magnitude of the storm, periods of the greatest magnetic field variation are lost as the traces moved off-page. We present the most complete digitized magnetic records to date of the ten-day period from 25th August to 5th September 1859 encompassing the Carrington storm and its precursor on the 28<sup>th</sup> August.</p>

<p>Space weather poses a hazard to grounded electrical infrastructure such as power transmission networks, through the induction of geomagnetically induced currents (GIC). Modelling GIC in real-time, as well as historical events and extreme event scenarios is of great importance for understanding and mitigating the effects on power networks. We have constructed a model of the interconnected European power networks using open-source data, to provide estimates of GIC across the whole continent, with the goal of creating a real-time operational warning system.</p><p>In recent years there have also been improvements in forecasting the ground geomagnetic field from L1 solar wind measurements using magnetohydrodynamic (MHD) models, and the development of models which forecast the solar wind itself days ahead of time. As part of the EUHFORIA2.0 Horizon 2020 project we have coupled models for the full Sun-to-Earth system to generate forecasts of geomagnetic fields, geoelectric fields and ultimately GIC across Europe.</p>

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.

Measurements from six longitudinally separated magnetic observatories, all located close to the 53° mid-latitude contour, are analysed. We focus on the large geomagnetic disturbance that occurred during 7 and 8 September 2017. Combined with available geomagnetically induced current (GIC) data from two substations, each located near to a magnetic observatory, we investigate the magnetospheric drivers of the largest events. We analyse solar wind parameters combined with auroral electrojet indices to investigate the driving mechanisms. Six magnetic field disturbance events were observed at mid-latitudes with dH/dt > 60 nT/min. Co-located GIC measurements identified transformer currents >15 A during three of the events. The initial event was caused by a solar wind pressure pulse causing largest effects on the dayside, consistent with the rapid compression of the dayside geomagnetic field. Four of the events were caused by substorms. Variations in the Magnetic Local Time of the maximum effect of each substorm-driven event were apparent, with magnetic midnight, morning-side, and dusk-side events all occurring. The six events occurred over a period of almost 24 h, during which the solar wind remained elevated at >700 km s−1, indicating an extended time scale for potential GIC problems in electrical power networks following a sudden storm commencement. This work demonstrates the challenge of understanding the causes of ground-level magnetic field changes (and hence GIC magnitudes) for the global power industry. It also demonstrates the importance of magnetic local time and differing inner magnetospheric processes when considering the global hazard posed by GIC to power grids.

Abstract Geomagnetically induced currents (GICs) during a space weather event have previously caused transformer damage in New Zealand. During the 2015 St. Patrick's Day Storm, Transpower NZ Ltd has reliable GIC measurements at 23 different transformers across New Zealand's South Island. These observed GICs show large variability, spatially and within a substation. We compare these GICs with those calculated from a modeled geolectric field using a network model of the transmission network with industry‐provided line, earthing, and transformer resistances. We calculate the modeled geoelectric field from the spectra of magnetic field variations interpolated from measurements during this storm and ground conductance using a thin‐sheet model. Modeled and observed GIC spectra are similar, and coherence exceeds the 95% confidence threshold, for most valid frequencies at 18 of the 23 transformers. Sensitivity analysis shows that modeled GICs are most sensitive to variation in magnetic field input, followed by the variation in land conductivity. The assumption that transmission lines follow straight lines or getting the network resistances exactly right is less significant. Comparing modeled and measured GIC time series highlights that this modeling approach is useful for reconstructing the timing, duration, and relative magnitude of GIC peaks during sudden commencement and substorms. However, the model significantly underestimates the magnitude of these peaks, even for a transformer with good spectral match. This is because of the limited range of frequencies for which the thin‐sheet model is valid and severely limits the usefulness of this modeling approach for accurate prediction of peak GICs.

Aims: This paper presents a H2020 project aimed at developing an advanced space weather forecasting tool, combining the MagnetoHydroDynamic (MHD) solar wind and coronal mass ejection (CME) evolution modelling with solar energetic particle (SEP) transport and acceleration model(s). The EUHFORIA 2.0 project will address the geoeffectiveness of impacts and mitigation to avoid (part of the) damage, including that of extreme events, related to solar eruptions, solar wind streams, and SEPs, with particular emphasis on its application to forecast geomagnetically induced currents (GICs) and radiation on geospace.Methods: We will apply innovative methods and state-of-the-art numerical techniques to extend the recent heliospheric solar wind and CME propagation model EUHFORIA with two integrated key facilities that are crucial for improving its predictive power and reliability, namely (1) data-driven flux-rope CME models, and (2) physics-based, self-consistent SEP models for the acceleration and transport of particles along and across the magnetic field lines. This involves the novel coupling of advanced space weather models. In addition, after validating the upgraded EUHFORIA/SEP model, it will be coupled to existing models for GICs and atmospheric radiation transport models. This will result in a reliable prediction tool for radiation hazards from SEP events, affecting astronauts, passengers and crew in high-flying aircraft, and the impact of space weather events on power grid infrastructure, telecommunication, and navigation satellites. Finally, this innovative tool will be integrated into both the Virtual Space Weather Modeling Centre (VSWMC, ESA) and the space weather forecasting procedures at the ESA SSCC in Ukkel (Belgium), so that it will be available to the space weather community and effectively used for improved predictions and forecasts of the evolution of CME magnetic structures and their impact on Earth.Results: The results of the first six months of the EU H2020 project are presented here. These concern alternative coronal models, the application of adaptive mesh refinement techniques in the heliospheric part of EUHFORIA, alternative flux-rope CME models, evaluation of data-assimilation based on Karman filtering for the solar wind modelling, and a feasibility study of the integration of SEP models.

ABSTRACTProviding an accurate estimate of the magnetic field on the Earth's surface at a location distant from an observatory has useful scientific and commercial applications, such as in repeat station data reduction, space weather nowcasting or aeromagnetic surveying. While the correlation of measurements between nearby magnetic observatories at low and mid‐latitudes is good, at high geomagnetic latitudes () the external field differences between observatories increase rapidly with distance, even during relatively low magnetic activity. Thus, it is of interest to describe how the differences (or errors) in external magnetic field extrapolation from a single observatory grow with distance from its location. These differences are modulated by local time, seasonal and solar cycle variations, as well as geomagnetic activity, giving a complex temporal and spatial relationship. A straightforward way to describe the differences are via confidence intervals for the extrapolated values with respect to distance. To compute the confidence intervals associated with extrapolation of the external field at varying distances from an observatory, we used 695 station‐years of overlapping minute‐mean data from 37 observatories and variometers at high latitudes from which we removed the main and crustal fields to isolate unmodelled signals. From this data set, the pairwise differences were analysed to quantify the variation during a range of time epochs and separation distances. We estimate the 68.3%, 95.4% and 99.7% confidence levels (equivalent to the 1σ, 2σ and 3σ Gaussian error bounds) from these differences for all components. We find that there is always a small non‐zero bias that we ascribe to instrumentation and local crustal field induction effects. The computed confidence intervals are typically twice as large in the north–south direction compared to the east‐west direction and smaller during the solstice months compared to the equinoxes.

Paper 1 (Lockwood et al., 2018) generated annual means of a new version of the aa geomagnetic activity index which includes corrections for secular drift in the geographic coordinates of the auroral oval, thereby resolving the difference between the centennial-scale change in the northern and southern hemisphere indices, aaN and aaS. However, other hemispheric asymmetries in the aa index remain: in particular, the distributions of 3-hourly aaN and aaS values are different and the correlation between them is not high on this timescale (r = 0.66). In the present paper, a location-dependant station sensitivity model is developed using the am index (derived from a much more extensive network of stations in both hemispheres) and used to reduce the difference between the hemispheric aa indices and improve their correlation (to r = 0.79) by generating corrected 3-hourly hemispheric indices, aaHN and aaHS, which also include the secular drift corrections detailed in Paper 1. These are combined into a new, “homogeneous” aa index, aaH. It is shown that aaH, unlike aa, reveals the “equinoctial”-like time-of-day/time-of-year pattern that is found for the am index.

Originally complied for 1868–1967 and subsequently continued so that it now covers 150 years, the aa index has become a vital resource for studying space climate change. However, there have been debates about the inter-calibration of data from the different stations. In addition, the effects of secular change in the geomagnetic field have not previously been allowed for. As a result, the components of the “classical” aa index for the southern and northern hemispheres (aa S and aa N) have drifted apart. We here separately correct both aa S and aa N for both these effects using the same method as used to generate the classic aa values but allowing δ, the minimum angular separation of each station from a nominal auroral oval, to vary as calculated using the IGRF-12 and gufm1 models of the intrinsic geomagnetic field. Our approach is to correct the quantized a K -values for each station, originally scaled on the assumption that δ values are constant, with time-dependent scale factors that allow for the drift in δ. This requires revisiting the intercalibration of successive stations used in making the aa S and aa N composites. These intercalibrations are defined using independent data and daily averages from 11 years before and after each station change and it is shown that they depend on the time of year. This procedure produces new homogenized hemispheric aa indices, aa HS and aa HN, which show centennial-scale changes that are in very close agreement. Calibration problems with the classic aa index are shown to have arisen from drifts in δ combined with simpler corrections which gave an incorrect temporal variation and underestimate the rise in aa during the 20th century by about 15%.

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 analyzes 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 3,000 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 5,000 nT/min, current estimates reach ~755 A (confidence interval range 155–910 A). GIC measurements from the much shorter data set collected at transformer number 4 in Halfway Bush, Dunedin, (HWB T4), found induced currents to be consistently a factor of 3 higher than at Islington, suggesting equivalent extreme storm effects of ~460–1,815 A (100 year return) and ~460–2,720 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 to put this regional analysis into a global context.

The British Geological Survey (BGS) operate seven magnetic observatories; three in the United Kingdom and four at remote locations worldwide. All seven are now INTERMAGNET Magnetic Observatories or IMOs. BGS also help to operate two other worldwide observatories on behalf of a directional drilling company. The processing of all nine observatories is carried out in the BGS office in Edinburgh, where rigorous quality-control operations are in place to ensure the quality of data and products. This is considered in relation to the real-time supply as well as next day delivery of quasi-definitive and longer term definitive data products. The data processing operations carried out on daily, weekly and annual time-scales are described, and the current practice is demonstrated. A single observatory system includes a fluxgate magnetometer - to measure variations in two perpendicular horizontal components and in the vertical component - and a proton precession magnetometer to measure absolute total field values. A fluxgate-theodolite is also required to enable weekly manual observations of declination and inclination, which supplement the other continuous and automatic measurements as per standard observatory operations. We compare processing techniques used for single-system observatories, which are in place at the seven remote locations, with those possible at the three UK observatories, where three systems are run in parallel. We describe the data correction processes that are used and the differences between those applied to one-second and one-minute values. Various sets of results are presented and some examples of their usefulness for scientific research discussed.

Over the past 20 years, directional borehole drilling has become increasingly important for improving the optimal extrac­tion of reserves from challenging targets and for reducing wellbore collisions. Very long wells drilled using borehole steering methods can take weeks to months to complete and rely on accurate models of the Earth’s magnetic field which necessarily include a parameterization of its time variation. Magnetic field models used in the hydrocarbon industry, such as the BGS Global Geomagnetic Model (BGGM), are computed from data collected by a network of ground-based magnetic observato­ries and from low Earth-orbiting satellites. Magnetic field models provide snapshots looking back in time, but to be useful to industry, they also need to predict how the field will change in the future. Previously, predictions of magnetic variation have been based on relatively simple extrapolation of the observed changes. We introduce a physics-based technique to forecast the changes in the field by deducing large-scale flow of the iron-rich liquid at the top of the outer core and use this to advect the present magnetic field forwards in time. We demonstrate that this method produces valuable improvements in the accuracy of magnetic field models and hence an improved tool for directional drilling.

“How far south will the aurora borealis be seen?” is a common question asked when a geomagnetic storm forecast is issued. It is not a straightforward answer; and current projections based, for example, on Kp do not always match sighting reports received after a display. Citizen science – engaging the general public to aid scientific research - may be one way of tackling this issue. By using social media, such as Twitter, a new source of data can be mined for scientific analysis. We present a new interactive web application to gather relevant tweets about the aurora and display these on a map. This tool has been created in JavaScript using the Twitter API and a customised application template from ESRI. We use both active and passive means to gather data. We actively encourage users to tweet using a known hashtag (#BGSaurora) with their location in a prescribed format. This will geo-locate the tweet and place a marker on the map reporting the sighting. We can also passively search tweets for more general hashtags such as #aurora or #northernlights. If these are geo-tagged they again can be mapped. Other relevant data layers, such as cloud cover and geomagnetic activity levels, can also be displayed. We present the aurora sightings map and discuss the benefits of it both as an application to engage the general public, helping them to see when and where aurora are visible, and as a potential tool for gathering useful data for scientific analysis. If a better indicator of geomagnetic activity levels relevant for aurora viewing can be determined from these then this in turn will improve future predictions for aurora enthusiasts.

The ultimate goal of cognitive enhancement as an intervention for age-related cognitive decline is transfer to everyday cognitive functioning. Development of training methods that transfer broadly to untrained cognitive tasks (far transfer) requires understanding of the neural bases of training and far transfer effects. We used cognitive training to test the hypothesis that far transfer is associated with altered attentional control demands mediated by the dorsal attention network and trained sensory cortex. In an exploratory study, we randomly assigned 42 healthy older adults to six weeks of training on Brain Fitness (BF—auditory perception), Space Fortress (SF—visuomotor/working memory), or Rise of Nations (RON—strategic reasoning). Before and after training, cognitive performance, diffusion-derived white matter integrity, and functional connectivity of the superior parietal cortex (SPC) were assessed. We found the strongest effects from BF training, which transferred to everyday problem solving and reasoning and selectively changed integrity of occipito-temporal white matter associated with improvement on untrained everyday problem solving. These results show that cognitive gain from auditory perception training depends on heightened white matter integrity in the ventral attention network. In BF and SF (which also transferred positively), a decrease in functional connectivity between SPC and inferior temporal lobe (ITL) was observed compared to RON—which did not transfer to untrained cognitive function. These findings highlight the importance for cognitive training of top–down control of sensory processing by the dorsal attention network. Altered brain connectivity – observed in the two training tasks that showed far transfer effects – may be a marker for training success.