Citizen scientists, along with satellite and ground-based sensors, have revealed a new arc boundary at subauroral latitudes.

Under periods of strong solar wind driving, the magnetopause can become compressed, playing a significant role in draining electrons from the outer radiation belt. Also termed "magnetopause shadowing," this loss process has traditionally been attributed to a combination of magnetospheric compression and outward radial diffusion of electrons. However, the drift paths of relativistic electrons and the location of the magnetopause are usually calculated from statistical models and, as such, may not represent the time-varying nature of this highly dynamic process. In this study, we construct a database ∼20,000 spacecraft crossings of the dayside magnetopause to quantify the accuracy of the commonly used Shue et al. (1998, https://doi.org/10.1029/98JA01103) model. We find that, for the majority of events (74%), the magnetopause model can be used to estimate magnetopause location to within ±1 R E . However, if the magnetopause is compressed below 8 R E , the observed magnetopause is greater than 1 R E inside of the model location on average. The observed magnetopause is also significantly displaced from the model location during storm sudden commencements, when measurements are on average 6% closer to the radiation belts, with a maximum of 42%. We find that the magnetopause is rarely close enough to the outer radiation belt to cause direct magnetopause shadowing, and hence rapid outward radial transport of electrons is also required. We conclude that statistical magnetopause parameterizations may not be appropriate during dynamic compressions. We suggest that statistical models should only be used during quiescent solar wind conditions and supplemented by magnetopause observations wherever possible.

A new, citizen science‐based, aurora observing and reporting platform has been developed with the primary aim of collecting auroral observations made by the general public to further improve the modeling of the aurora. In addition, the real‐time ability of this platform facilitates the combination of citizen science observations with auroral oval models to improve auroral visibility nowcasting. Aurorasaurus provides easily understandable aurora information, basic gamification, and real‐time location‐based notification of verified aurora activity to engage citizen scientists. The Aurorasaurus project is one of only a handful of space weather citizen science projects and can provide useful results for the space weather and citizen science communities. Early results are promising with over 2000 registered users submitting over 1000 aurora observations and verifying over 1700 aurora sightings posted on Twitter.

[1] Exploiting 8 years of magnetic field data from the Cluster mission, we employ an automated magnetopause crossing detection routine to determine the magnetopause location over varying magnetic latitudes and local times. For a period spanning nearly one solar cycle we build a database of 2709 magnetopause crossings and compare these locations to the magnetopause models of Petrinec and Russell (1996), Shue et al. (1998), Dmitriev and Suvorova (2000), and Lin et al. (2010). We compare our detected locations with the predicted locations for a variety of solar wind conditions and positions on the magnetopause. We find that, on average, the Petrinec and Russell (1996) and Shue et al.(1998) models overestimate the radial distance to the magnetopause by 1 R E (9%), while the Dmitriev and Suvorova (2000) and Lin et al. (2010) models underestimate it by 0.5 R E (4.5%) and 0.25 R E (2.3%), respectively. Some varying degree of control on the differences between the predicted and encountered locations, by the solar wind and location parameters, are found.