Incoherent scatter (IS) radars are high-power, large-aperture radars that detect radio wave scattering from thermal fluctuations in the ionospheric plasma. Power spectral density of the scattered signal is a function of number density, temperature, bulk velocity, and ion-neutral collision frequency of a number of ion species and electrons (for example Swartz & Farley, 1979, and references therein). All these parameters cannot be fitted to the spectrum, and a commonly used approximation is the four-parameter fit of N e , T e , T i and V i. Equal temperatures and bulk velocities are assumed for all ion species, and the ion-neutral collision frequency and ion composition are taken from ionospheric models. In the F 1 region the four-parameter fit often produces incorrect temperatures (for example Blelly et al., 2010), because ion composition models are unreliable in the transition region from the E region molecular NO + and  2 O ions to the F 2 region atomic O +. Incorrect compositions bias the temperatures, because the IS spectrum is sensitive to the ratio T i /m i , where m i is the mean ion mass. This is known as the "temperature-ion composition ambiguity" (TICA; Martínez-Ledesma et al., 2019). Several authors have addressed the TICA problem by means of modeling the F 1 region temperature and ion composition profiles (

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.

<p>Electron precipitation and ion frictional heating events cause rapid variations in electron temperature, ion temperature and F1 region ion composition of the high-latitude ionosphere. Four plasma parameters: electron density, electron temperature, ion temperature, and plasma bulk velocity, are typically fitted to incoherent scatter radar (ISR) data.</p><p>Many ISR data analysis tools extract the plasma parameters using an ion composition profile from an empirical model. The modeled ion composition profile may cause bias in the estimated ion and electron temperature profiles in the F1 region, where both atomic and molecular ions exist with a temporally varying proportion.</p><p>In addition, plasma parameter estimation from ISR measurements requires integrating the scattered signal typically for tens of seconds. As a result, the standard ISR observations have not been able to follow the rapid variations in plasma parameters caused by small scale auroral activity.</p><p>In this project, we implemented Bayesian filtering technique to the EISCAT’s standard ISR data analysis package, GUISDAP. The technique allows us to control plasma parameter gradients in altitude and time.</p><p>The Bayesian filtering implementation enabled us to fit electron density, ion and electron temperatures, ion velocity and ion composition to ISR data with high time resolution. The fitted ion composition removes observed artifacts in ion and electron temperature estimates and the plasma parameters are calculated with 5 s time resolution which was previously unattainable.</p><p>Energy spectra of precipitating electrons can be calculated from electron density and electron temperature profiles observed with ISR. We used the unbiased high time-resolved electron density and temperature estimates to improve the accuracy of the estimated energy spectra. The result shows a significant difference compared to previously published results, which were based on the raw electron density (backscattered power) and electron temperature estimates calculated with coarser time resolution.</p><p> </p>

Electron precipitation to the high-latitude ionosphere is a key process in magnetosphere-ionosphere coupling and in the physics of the mesosphere-lower thermosphere region, because the precipitating electrons carry electric current, transfer energy from the magnetosphere to the ionosphere, ionize neutral atoms and molecules, cause optical auroral emissions, heat the electron gas, and change the ion composition. High-resolution observations are needed in studies of these phenomena, as the processes often take place in small spatial and temporal scales.Electron precipitation is quantitatively characterized by the energy distribution of the primary electrons. Electron acceleration processes in the magnetosphere that lead to different energy spectral shapes are discussed by Dombeck et al. (2018) andNewell et al. (2009). For a known differential energy flux, altitude profiles of ion production rate and auroral emission rates can be determined if the neutral atmospheric parameters are known (Fang et al., 2010;Rees, 1963).Indirect estimation of the differential energy flux from electron density altitude profiles observed with an incoherent scatter radar (ISR) is an efficient way to observe electron precipitation from ground (

We use EISCAT UHF ISR data to study the 1-100 keV electron precipitation at 66.7°MLAT observed during 21 years• Large auroral powers (≥60 mWm −2 ) are observed in the 18-02 MLT sector, and mainly in the main auroral oval• Peak energies higher than 50 keV are observed only after 22 MLT and preferentially in the 06-11 MLT sector of the diffuse auroral oval