ISR spectral analysis in regions of highly variable ion composition

Incoherent scatter radar (ISR) is a powerful remote sensing tool for probing the high-latitude ionosphere. Spectral analysis of radio waves scattered from the ionosphere allows for the simultaneous determination of several important plasma state parameters as a function of range. In almost all cases, the relative concentrations of molecular and atomic ions must be assumed in order to extract ion and electron temperatures from the spectra. However, theoretical models have shown that strong electric fields change ion composition dramatically in the F-layer due to enhanced frictional heating which affects chemical reaction rates. Thus, assumptions made in ISR spectral analysis are readily violated in regions where electric fields are strong, as is expected in the vicinity of auroral arcs. This study investigates the magnitude and occurrence frequency of inaccuracies in ISR analysis resulting from incorrect assumptions about ion composition. Basic spatial and temporal characteristics of ion composition changes induced by electric fields are first reviewed using a physics-based ionospheric model. This model is then used in tandem with data from the Sondrestrom ISR to infer cases of inconsistency in the observed ion temperature profiles and electric fields. It is demonstrated that this inconsistency may be mostly resolved by adopting the modeled composition in the ISR spectral analysis. A determination of the relative importance of these severe composition changes is evaluated from multiple ISR data sets and model simulations. The significance of this work is that it provides some quantitative information about a systematic source of error in ISR data analysis and provides some initial results towards a solution to the issue of variable ion composition in ISR data analysis.