The Predictive Capabilities of the Auroral Electrojet Index for Medium Energy Electron Precipitation
Tyssøy, Hilde Nesse; Partamies, Noora; Babu, Eldho Midhun; Smith-Johnsen, Christine; Salice, Josephine Alessandra
Journal article, Peer reviewed
Published version
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https://hdl.handle.net/11250/2979653Utgivelsesdato
2021Metadata
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Originalversjon
Frontiers in Astronomy and Space Sciences. 2021, 8, 714146. 10.3389/fspas.2021.714146Sammendrag
The chemical imprint of the energetic electron precipitation on the atmosphere is now acknowledged as a part of the natural forcing of the climate system. It has, however, been questioned to which degree current proxies are able to quantify the medium energy electron (MEE) (≳30 keV) precipitation and the associated daily and decadal variability. It is particularly challenging to model the high energy tail (≳300 keV) of MEE, both in terms of the intensity as well as the timing. This study explores the predictive capabilities of the AE index for the MEE precipitation. MEE measurements from the NOAA/POES over a full solar cycle from 2004 to 2014 are applied. We combine observations from the MEPED 0° and 90° detectors together with theory of pitch angle diffusion by wave-particle interaction to estimate the precipitating fluxes. To explore the energy dependent time scales, each of the MEPED energy channels, > 43, >114, and >292 keV are evaluated independently. While there is a strong correlation between the daily resolved AE index and >43 keV fluxes, it is a poor predictor for the >292 keV fluxes. We create new AE based MEE proxies by accumulating the AE activity over multiple days, including terms counting for the associated lifetimes. The results indicate that AE based proxies can predict at least 70% of the observed MEE precipitation variance at all energies. The potential link between the AE index, substorms and the MEE precipitation is discussed.