Precipitating Electron Energy Spectra and Auroral Power Estimation by Incoherent Scatter Radar With High Temporal Resolution

Abstract

This study presents an improved method to estimate differential energy flux, auroral power and field‐aligned current of electron precipitation from incoherent scatter radar data. The method is based on a newly developed data analysis technique that uses Bayesian filtering to fit altitude profiles of electron density, electron temperature, and ion temperature to observed incoherent scatter spectra with high time and range resolutions. The electron energy spectra are inverted from the electron density profiles. Previous high‐time resolution fits have relied on the raw electron density, which is calculated from the backscattered power assuming that the ion and electron temperatures are equal. The improved technique is applied to one auroral event measured by the EISCAT UHF radar and it is demonstrated that the effect of electron heating on electron energy spectra, auroral power, and upward field‐aligned current can be significant at times. Using the fitted electron densities instead of the raw ones may lead to wider electron energy spectra and auroral power up to 75% larger. The largest differences take place for precipitation that produces enhanced electron heating in the upper E region, and in this study correspond to fluxes of electrons with peak energies from 3 to 5 keV. Finally, the auroral power estimates are verified by comparison to the 427.8 nm auroral emission intensity, which shows good correlation. The improved method makes it possible to calculate unbiased estimates of electron energy spectra with high time resolution and thereby to study rapidly varying aurora.

Characteristics of Auroral Electron Precipitation at Geomagnetic Latitude 67° Over Tromsø

“…Temporal resolution of our data is close to 1 min which is not sensitive enough for auroral structures that vary in time‐scales of a few seconds (Tesfaw et al., 2022) or down to sub‐second level (Dahlgren et al., 2011). The long integration of the radar data may thus have smoothed out rapid variations and short‐lived maxima in peak energy, auroral power, and number flux.…”

“…The long integration of the radar data may thus have smoothed out rapid variations and short‐lived maxima in peak energy, auroral power, and number flux. A general property of the radar observations is also that auroral power is underestimated when the radar beam is not uniformly filled by the precipitation (Tesfaw et al., 2022). We thus have a reason to believe that our auroral powers and number fluxes may be slightly underestimated, especially in active conditions.…”

“…As Newell et al (2009) showed, this region is dominated by so-called monoenergetic electron fluxes, which are most likely generated in the auroral acceleration region (Aikio et al, 2002;Carlson et al, 1998;Paschmann et al, 2003). Examples of these so called inverted-V electron spectra are shown in Tesfaw et al (2022).…”

“…The energy is deposited in the auroral ionosphere, where the precipitation causes auroral emissions, ionizes the neutral atmosphere, enhances ionospheric conductivity, alters neutral and ion compositions, and heats the ambient electron gas (Palmroth et al., 2021). Auroral electron precipitation is characterized by the global distribution of the auroral power (total energy flux), total number flux and peak energy of the precipitating electrons (Kaeppler et al., 2020; Tesfaw et al., 2022; Virtanen et al., 2018).…”

F1 Region Ion Composition in Svalbard During the International Polar Year 2007–2008

“…The final fit results are plasma parameters x″ and their covariance matrix P″ produced by smoothing in altitude by correlation priors, as explained in (Virtanen et al, 2021). The chemistry modeling together with some technical improvements to control of the correlation lengths allow us to use considerably longer time steps than those used by Virtanen et al (2021) and Tesfaw et al (2022).…”