Understanding global space weather effects is of great importance to the international scientific community, but more localised space weather predictions are important on a national level. In this study, data from a ground magnetometer at Valentia Observatory is used to characterise space weather effects on the island of Ireland. The horizontal component of magnetometer observations and its time derivative are considered, and extreme values of these are identified. These extremes are fit to a generalised extreme value distribution, and from this model return values (the expected magnitude of an observation within a given time window) are predicted. The causes of extreme values are investigated both in a case study, and also statistically by looking at contributions from geomagnetic storms, substorms, and sudden commencements. This work characterises the extreme part of the distribution of space weather effects on Ireland (and at similar latitudes), and hence examines those space weather observations which are likely to have the greatest impact on susceptible technologies.

Models of the high-latitude ionospheric electric field are commonly used to specify the magnetospheric forcing in thermosphere or whole atmosphere models. The use of decades-old models based on spacecraft data is still widespread. Currently the Heelis and Weimer climatology models are most commonly used but it is possible a more recent electric field model could improve forecasting functionality. Modern electric field models, derived from radar data, have been developed to incorporate advances in data availability. It is expected that climatologies based on this larger and up-to-date dataset will better represent the high latitude ionosphere and improve forecasting abilities. An example of two such models, which have been developed using line-of-sight velocity measurements from the Super Dual Auroral Radar Network (SuperDARN) are the Thomas and Shepherd model (TS18), and the Time-Variable Ionospheric Electric Field model (TiVIE). Here we compare the outputs of these electric field models during the September 2017 storm, covering a range of solar wind and interplanetary magnetic field (IMF) conditions. We explore the relationships between the IMF conditions and the model output parameters such as transpolar voltage, the polar cap size and the lower latitude boundary of convection. We find that the electric potential and field parameters from the spacecraft-based models have a significantly higher magnitude than the SuperDARN-based models. We discuss the similarities and differences in topology and magnitude for each model.

We use a 20 year database of Super Dual Auroral Radar Network (SuperDARN) observations to investigate the two component model of ionospheric convection. A convection pattern is included in the database if it is derived from at least 250 radar vectors and has a distribution of electric potential consistent with Dungey-cycle twin vortex flow (a negative potential peak in the dusk cell and a positive potential peak in the dawn cell). We extract the locations of the foci of the convection cells from the SuperDARN convection patterns, and compare their dependencies on the north-south component of the interplanetary magnetic field, IMF Bz, and the auroral electrojet index, AL. We define a quantity, dMLT, as the hour angle between the dawn and dusk convection cell foci, which we use as a proxy for the extent to which the dayside or nightside component of the convection pattern is dominating. We find that at a fixed level of AL, dMLT decreases with increasingly negative IMF Bz, consistent with an increasing dominance of dayside reconnection. We also find that at a fixed level of IMF Bz, dMLT increases with increasingly negative AL, consistent with an increasing dominance of nightside reconnection, but only up to modest values of AL (to ~ −200 nT). As AL becomes further enhanced dMLT decreases again, which we attribute to an inherent dependence of AL on IMF Bz.

We utilise Principal Component Analysis to identify and quantify the primary electric potential morphologies during geomagnetic storms. Ordering data from the Super Dual Auroral Radar Network (SuperDARN) by geomagnetic storm phase, we are able to discern changes that occur in association with the development of the storm phases. Along with information on the size of the patterns, the first 6 eigenvectors provide over ~80% of the variability in the morphology, providing us with a robust analysis tool to quantify the main changes in the patterns. Studying the first 6 eigenvectors and their eigenvalues with respect to storm phase shows that the primary changes in the morphologies with respect to storm phase are the convection potential enhancing and the dayside throat rotating from pointing towards the early afternoon sector to being more sunward aligned during the main phase of the storm. We find that the ionospheric electric potential increases through the main phase and then decreases after the end of the main phase is reached. The dayside convection throat points towards the afternoon sector before the main phase and then as the potential increases throughout the main phase, the dayside throat rotates towards magnetic noon. Furthermore, we find that a two cell convection pattern is dominant throughout and that the dusk cell is overall stronger than the dawn cell.

The Super Dual Auroral Radar Network (SuperDARN) is a collection of radars built to study ionospheric convection. We use a 7-year archive of SuperDARN convection maps, processed in 3 different ways, to build a statistical understanding of dusk-dawn asymmetries in the convection patterns. We find that the dataset processing alone can introduce a bias which manifests itself in dusk-dawn asymmetries. We find that the solar wind clock angle affects the balance in the strength of the convection cells. We further find that the location of the positive potential foci is most likely observed at latitudes of 78◦ for long periods (>300 minutes) of southward IMF, as opposed to 74◦ for short periods (<20 minutes) of steady IMF. For long steady dawnward IMF the median is also at 78◦. For long steady periods of duskward IMF, the positive potential foci tends to be at lower latitudes than the negative potential and vice versa during dawnward IMF. For long periods of steady Northward IMF, the positive and negative cells can swap sides in the convection pattern.We find that they move from ~0-9 MLT to 15 MLT or ~15-23 MLT to 10 MLT, which reduces asymmetry in the average convection cell locations for Northward IMF. We also investigate the width of the region in which the convection returns to the dayside, the return flow width. Asymmetries in this are not obvious, until we select by solar wind conditions, when the return flow region is widest for the negative convection cell during Southward IMF.

The Super Dual Auroral Radar Network (SuperDARN) was built to study ionospheric convection and has in recent years been expanded geographically. Alongside software developments, this has resulted in many different versions of the convection maps dataset being available. Using data from 2012 to 2018, we produce five different versions of the widely used convection maps, using limited backscatter ranges, background models and the exclusion/inclusion of data from specific radar groups such as the mid-latitude radars. This enables us to simulate how much information was missing from previous decades of SuperDARN research. We study changes in the Heppner-Maynard boundary, the cross polar cap potential (CPCP), the number of backscatter echoes (n) and the χ-squared/n statistic which is a measure of the global agreement between the measured and fitted velocities. We find that the CPCP is reduced when the polar cap radars are introduced, but then increases again when the mid-latitude radars are added. When the background model is changed from the RG96 model, to the most recent TS18 model, the CPCP tends to decrease for lower values, but tends to increase for higher values. When comparing to geomagnetic indices, we find that there is on average a linear relationship between the Heppner-Maynard boundary and the geomagnetic indices, as well as n, which breaks at high values (e.g. HMB ~50 degrees) due to the low observational density. We find that whilst n is important in constraining the maps (maps with n>400 are unlikely to change), is insufficient as the sole measure of quality.

We examine the average evolution of precipitation-induced height-integrated conductances, along with field-aligned currents, in the nightside sector of the polar cap over the course of a substorm. Conductances are estimated from the average energy flux and mean energies derived from auroral emission data. Data are binned using a superposed epoch analysis on a normalised time grid based on the time between onset and recovery phase ($\delta$t) of each contributing substorm. We also examine conductances using a fixed time binning of width 0.25 hr. We split the data set by magnetic latitude of onset. We find that the highest conductances are observed for substorms with onsets that occur between 63 and 65 degrees magnetic latitude, peaking at around 11 mho (Hall) and 4.8 mho (Pedersen). Substorms with onsets at higher magnetic latitudes show lower conductances and less variability. Changes in conductance over the course of a substorm appear primarily driven by changes (about 40% at onset) in the average energy flux, rather than the average energy of the precipitation. Average energies increase after onset slower than energy flux, later these energies decrease slowly for the lowest latitude onsets. No clear expansion of the main region 1 and region 2 field-aligned currents is observed. However, we do see an ordering of the current magnitudes with magnetic latitude of onset, particularly for region 1 downwards FAC in the morning sector. Peak current magnitudes occur slightly after or before the start of the recovery phase for the normalised and fixed-time grids.