The Heliospheric Imagers on board NASAs twin STEREO spacecraft show that coronal mass ejections (CMEs) can be visually complex structures. To explore this complexity, we created a web-based citizen science project in collaboration with the UK Science Museum, in which participants were shown pairs of differenced CME images, taken by the inner cameras of the Heliospheric Imagers (HI-1) on board the twin NASA STEREO spacecraft between 2008 and 2016. Participants were asked to decide which image in each pair appeared the most complicated. 4,028 volunteers conducted 246,692 comparisons of 20,190 image pairs, with each pair being classified by 12 independent users. A Bradley-Terry model was then applied to these data to rank the CMEs by their visual complexity. This complexity ranking revealed that the annual average visual complexity values follow the solar activity cycle, with a higher level of complexity being observed at the peak of the cycle, and the average complexity of CMEs observed by HI1-A was significantly higher than the complexity of CMEs observed by HI1-B. Visual complexity was found to be associated with CME size and brightness, but the differences between HI1-A and HI1-B images suggest that complexity may be influenced by the scale-sizes of structure in the CMEs. Whilst it might not be surprising that the complexity observed in these CME images follows the trend observed in sunspots and the solar cycle; these results demonstrate that there is a quantifiable change in the structure of CMEs seen in the inner heliosphere.

Accurately forecasting the arrival of coronal mass ejections (CMEs) at Earth is important to enabling mitigation of the associated space weather risks to society. This is only possible with accurate modelling of the event. To do so, we must understand the propagation of a CME through the heliosphere and quantify the performance of models through comparison with spacecraft observations. For the December 12th 2008 Earth-directed CME event, we compute ensembles using the HUXt solar wind model to analyse CME distortion with a structured solar wind and explore hindcast arrival time error (ATE). By highlighting the impact CME shape has on Root-Mean-Square-Error (RMSE) values, we show that time-elongation profiles of fronts captured by the Heliospheric Imager (HI) instruments onboard NASA’s STEREO mission match those of the modelled CME nose and flank and can therefore be used to infer details of the longitudinal extent of the CME. We then show that accounting for CME distortion is important to enable accurate estimates of the CME arrival at Earth. This can be achieved by either using observations of multiple features in HI data to infer CME evolution or mapping the solar wind back to a lower inner boundary to allow CMEs to be distorted close to the Sun. For the event studied we show that these approaches resulted in reduced RMSEs of 0.726˚and 0.638˚ with an ATE of one hour and three hours respectively.

Geometric modelling of Coronal Mass Ejections (CMEs) is a widely used tool for assessing their kinematic evolution. Furthermore, techniques based on geometric modelling, such as ELEvoHI, are being developed into forecast tools for space weather prediction. These models assume that solar wind structure does not affect the evolution of the CME, which is an unquantified source of uncertainty. We use a large number of Cone CME simulations with the HUXt solar wind model to quantify the scale of uncertainty introduced into geometric modelling and the ELEvoHI CME arrival times by solar wind structure. We produce a database of simulations, representing an average, a fast, and an extreme CME scenario, each independently propagating through 100 different ambient solar wind environments. Synthetic heliospheric imager observations of these simulations are then used with a range of geometric models to estimate the CME kinematics. The errors of geometric modelling depend on the location of the observer, but do not seem to depend on the CME scenario. In general, geometric models are biased towards predicting CME apex distances that are larger than the true value. For these CME scenarios, geometric modelling errors are minimised for an observer in the L5 region. Furthermore, geometric modelling errors increase with the level of solar wind structure in the path of the CME. The ELEvoHI arrival time errors are minimised for an observer in the L5 region, with mean absolute arrival time errors of 8.2±1.2h, 8.3±1.0h, and 5.8±0.9h for the average, fast, and extreme CME scenarios

We introduce the inductive effects of polar cap motions towards and way from the Sun into magnetospheric electrodynamics and show how this explains observed Universal Time variations in hemispheric geomagnetic indices. The large (and growing) hemispheric asymmetry in the offsets of the geomagnetic (dip or eccentric dipole) poles from Earth’s rotational axis means that the effect is not cancelled out in global indices. By adding this effect to that of the Russell-McPherron effect on solar wind-magnetosphere coupling, that of ionospheric conductivities, and that of the solar wind dynamic pressure and dipole tilt on the near-Earth tail lobe field and cross-tail current sheet, we are able to model the persistent “equinoctial” time-of-day/time-of-year pattern (with additional net Universal time variations) observed in the an, as and am geomagnetic indices since 1959. We discuss the implications for the longitudinal dependence of the effects of extreme space weather events