We measured the height of green and blue aurorae using thousands of camera images recorded over a 7-year period. Both colours are typically brightest at about 114 km altitude. When they peak at higher altitudes the blue aurora is usually higher than the green aurora. This information will help other studies which need an estimate of the auroral height. We used a computer model to explain our observations and to investigate how the green aurora is produced.

We have examined events during which the measured magnetic field on the ground changes very rapidly, causing a risk to technological conductor networks. According to our results, such events occur when strong electric currents in the ionosphere at 100 km altitude are abruptly modified by sudden compression or expansion of the magnetospheric magnetic field farther in space.

We study how the polar regions of the Earth connect to space along magnetic field lines. While the Earth's magnetic field is mostly the shape of a dipole, at high latitudes the field lines tend to be open and connect to interplanetary space. This area of open field line is called the polar cap, and it is highly dynamic. Through data analysis and computer simulations, we find that the shape of the polar cap is closely controlled by the magnetic field embedded in the solar wind.

The study of some ionospheric events benefit from the knowledge of how the physics varies over a volume and over time. Examples are studies of aurora or energy deposition. With EISCAT3D, measurements of ion velocity vectors in a volume will be possible for the first time. We present a technique that uses a set of such measurements to estimate electric field and neutral wind. The technique relies on adding restrictions to the estimates. We successfully consider restrictions based on physics.

Collisional fragmentation of asteroids, comets and meteoroids is the main source of dust in the solar system. The dust distribution is however uncharted and the role of dust in the solar system is largely unknown. At present, the interplanetary medium is explored by the Solar Orbiter spacecraft. We present a novel method, based on artificial intelligence, that can be used for detecting dust impacts in Solar Orbiter observations with high accuracy, advancing the study of dust in the solar system.

Magnetopause is a shielding boundary of planetary magnetic field. Many mathematical models have been proposed to describe or to reproduce the magnetopause location, but they are restricted to the real-number functions. In this work, we analytically develop a magnetopause model in the complex-number domain, which is advantageous in deforming the magnetopause shape in a conformal (angle-preserving) way, and is suited to compare different models or map one model onto another.