UNIVERSITY OF ALBERTA (CA)
Electromagnetic Ion Cyclotron (EMIC) waves are electromagnetic plasma waves in near-Earth space, which play an important role in outer radiation belt dynamics. Specifically, these waves remove electrons from the outer radiation belt by scattering them into the Earth’s atmosphere. Energetic so-called “killer” electrons trapped in the outer belt pose dangers to satellites. Understanding the processes responsible for the loss of such “killer electrons” is therefore important for developing improved space weather forecasts, and for determining when harsh space radiation returns to more benign levels. Ultimately a better understanding of the dynamics of space radiation leads to improved protections for satellites from adverse effects through appropriate shielding design and on-orbit operations procedures. It is therefore important for radiation belt models to include EMIC wave driven loss. However, EMIC waves can be highly localized in both space and time and are therefore difficult to detect using data from typical slow-moving high altitude magnetospheric satellites, which are often in the wrong place at the wrong time to observe the wave. EMIC waves can be observed by ground magnetometer arrays, but these observations have their own problems, as EMIC waves observed from the ground undergo various ducting effects, meaning that a wave observed on the ground often does not match the location of the wave in space. Since it is challenging to accurately know when and where EMIC wave loss processes should be applied, a number of radiation belt simulations invoke EMIC wave scattering without direct observational evidence.
The constellation of Swarm satellites in Low-Earth Orbit (LEO) can observe EMIC waves much more frequently than magnetospheric satellites, due to their shorter orbital period. The challenge with using Swarm is distinguishing EMIC waves from nearby field-aligned currents, which can look electromagnetically very similar from LEO. This project builds upon previous work to use a range of techniques, including multi-point observations and frequency domain analysis, to solve this problem. The various techniques form a single EMIC wave detection algorithm, with machine learning used to assign probabilities to detected events based on a set of criteria. The algorithm output is an EMIC wave database comprising 10 years of Swarm data (2014-2024) for all 3 spacecraft, which has been published on Zenodo. The database was cross-referenced with observations of energetic electron precipitation (EEP), determining that EMIC waves correspond to EEP at energies as low as >100 keV, rather than multi-MeV scattering generally assumed. Statistics performed on detected EMIC waves reveal their localized nature and show the existence of a high-wave-amplitude tail; while typical amplitudes are ~0.2 nT, some EMIC waves reach tens/hundreds of nT. Event-specific modelling shows that these extremely large EMIC waves occur exactly during times of rapid intense radiation belt loss during extreme storms. In summary, Swarm was successfully used as an EMIC wave monitor, providing significant EEP results and filling a major capability gap in radiation belt modelling and providing the possibility of near-real time EMIC wave forecasting, opening an important new capability for Swarm to be used to monitor space weather.
Publications:
Pakhotin, I., Mann, I., & Ozeke, L. (2025). Swarm-EMIC Research Project – EMIC database [Data set]. Zenodo. https://doi.org/10.5281/zenodo.17752572
