DOI

Studying the episodes with the most elevated electron density (Ne) values provides valuable information about spatial distribution and drivers of intense energetic electron (EE) precipitation, which has important space weather implications. By combining EISCAT-Tromso UHF observations in different modes made in 2001–2021, we survey Ne occurrences and study statistical properties of EE precipitation, producing the highest 10% and 1% of Ne values at the altitudes between 100 and 75 km (corresponding to EE energies of ∼20–∼200 keV). We found that the highest Ne values occur in the nightside-morning local time sector at the altitudes 90–100 km and in the morning-noon sector at low altitudes (75–85 km). Although this bimodal pattern could partly be contributed by the suppressed Ne in the dark ionosphere, by analyzing measurements in the twilight conditions at all MLTs together with published patterns of EE precipitation, we argue that a dominance of pre-noon maximum at low altitudes reflects the enhanced precipitation of >100 keV electrons in this local time sector. At all altitudes (especially below 90 km), the appearance of the highest Ne values favors enhanced auroral activity and shows a strong correlation with fast solar wind (V > 550 km/s) events. These properties mimic the well-known driving characteristics of energetic electrons. From the correlation of Ne with integral magnetic activity indexes we found that the memory of preceding magnetic activity increases with decreasing altitude, reaching roughly one day at H = 75 km. We discuss the advantages of exploring Ne data at specific altitudes (compared to direct measurements of EE precipitation) to investigate statistically the effects of specific precipitated energy components and the evolution of EE energy spectra.
Original languageEnglish
Article numbere2024JA032913
JournalJournal of Geophysical Research: Space Physics
Volume129
Issue number10
DOIs
StatePublished - 27 Sep 2024

    Research areas

  • activity dependence, d-region, energetic electrons, precipitation, spatial patterns

ID: 125308861