Ions in the F region ionosphere at 150-400 km altitude consist mainly of molecular NO+ and O2+, and atomic O+. Incoherent scatter (IS) radars are sensitive to the molecular-to-atomic ion density ratio, but its effect to the observed incoherent scatter spectra is almost identical with that of the ion temperature. It is thus very difficult to fit both the ion temperature and the fraction of O+ ions to the observed spectra. In this paper, we introduce a novel combination of Bayesian filtering, smoothness priors, and chemistry modeling to solve for F1 region O+ ion fraction from EISCAT Svalbard IS radar (75.43° corrected geomagnetic latitude) data during the international polar year (IPY) 2007-2008. We find that the fraction of O+ ions in the F1 region ionosphere is controlled by ion temperature and electron production. The median value of the molecular-to-atomic ion transition altitude during IPY varies from 187 km at 16-17 MLT to 208 km at 04-05 MLT. The ion temperature has maxima at 05-06 MLT and 15-16 MLT, but the transition altitude does not follow the ion temperature, because photoionization lowers the transition altitude. A daytime transition altitude maximum is observed in winter, when lack of photoionization leads to very low daytime electron densities. Both ion temperature and the molecular-to-atomic ion transition altitude correlate with the Polar Cap North geomagnetic index. The annual medians of the fitted transition altitudes are 14-32 km lower than those predicted by the International Reference Ionosphere.

Key Points: • We use EISCAT UHF ISR data to study the 1-100 keV electron precipitation at 6 66.7° MLAT observed during 21 years. • The auroral electron precipitation occurrence rate as observed by the radar reaches70% in the 05–06 MLT sector of the main auroral oval.• Electron precipitation with 50–100 keV peak energies is more common than with 30–50 keV peak energies after 06 MLT

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 show 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.

Incoherent scatter (IS) radars are invaluable instruments for ionospheric physics, since they observe altitude profiles of electron density (Ne), electron temperature (Te), ion temperature (Ti) and line-of-sight plasma velocity (Vi) from ground. However, the temperatures can be fitted to the observed IS spectra only when the ion composition is known, and resolutions of the fitted plasma parameters are often insufficient for auroral electron precipitation, which requires high resolutions in both range and time. The problem of unknown ion composition has been addressed by means of the full-profile analysis, which assumes that the plasma parameter profiles are smooth in altitude, or follow some predefined shape. In a similar manner, one could assume smooth time variations, but this option has not been used in IS analysis. We propose a plasma parameter fit technique based on Bayesian filtering, which we have implemented as an additional Bayesian Filtering Module (BAFIM) in the GUISDAP analysis package. BAFIM allows us to control gradients in both time and range directions for each plasma parameter separately. With BAFIM we can fit F1 region ion composition together with Ne, Te, Ti, and Vi, and we have reached 4 s/900 m time/range steps in four-parameter fits of Ne, Te, Ti and Vi in E region observations of auroral electron precipitation.