A method for improving plasma temperature estimates from incoherent scatter analysis during artificial ionospheric modification experiments

• Main Authors: H. Vickers, T. Robinson, I. W. McCrea
• Format: Other Non-Article Part of Journal/Newspaper
• Language: unknown
• Published: 2010
• Subjects: Uncategorized; IR content; Tromsø
• Online Access: https://figshare.com/articles/journal_contribution/A_method_for_improving_plasma_temperature_estimates_from_incoherent_scatter_analysis_during_artificial_ionospheric_modification_experiments/10117325

[1] Spectral features in incoherent scatter data, such as those caused by the purely growing mode (PGM), can often be strongly enhanced during the first few seconds of artificial ionospheric heating experiments, such as those carried out using the high-power European Incoherent Scatter HF heater at Tromsø. These features, often referred to as “overshoot” effects, are indicators of turbulent non-Maxwellian plasma, and the analysis of these spectra using standard incoherent scatter data analysis software leads to a poor estimation of the plasma parameters (particularly electron and ion temperature) during RF heating experiments. In this study, a procedure is developed to derive a more reliable estimate of plasma temperature during periods when the incoherent scatter spectrum is affected by contamination from the PGM. This is achieved by removing the PGM from the measured spectrum and then analyzing the modified spectrum using standard software. The results are compared to those obtained from the analysis of the original, contaminated spectra. It is found that the differences between the results obtained from the corrected and uncorrected spectra are strongly proportional to the magnitude of the PGM feature. We also show that the bulk temperatures during the remainder of the “heater on” period after the overshoot can generally be estimated reliably by the standard analysis software, though with some important exceptions. These results are important since the plasma temperatures play a crucial role in governing thermal conduction processes, and their correct estimation is thus very important to understanding the underlying physical processes which occur during ionospheric heating.