A self-consistent estimate of O + + N 2 − rate coefficient and total EUV solar flux with λ < 1050 Å using EISCAT observations

• Published in: Annales Geophysicae
• Main Authors: A. V. Mikhailov, K. Schlegel
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2000
• Subjects: Science; Q; Physics; QC1-999; Geophysics. Cosmic physics; QC801-809; EISCAT
• Online Access: https://doi.org/10.1007/s00585-000-1164-x; https://doaj.org/article/76ef6275c6e64853afbac09e0c6def5d

There are differences between existing models of solar EUV with λ < 1050 Å and between laboratory measurements of the O + + N 2 – reaction rate coefficient, both parameters being crucial for the F2-region modeling. Therefore, indirect aeronomic estimates of these parameters may be useful for qualifying the existing EUV models and the laboratory measured O + + N 2 – rate coefficient. A modified self-consistent method for daytime F2-region modeling developed by Mikhailov and Schlegel was applied to EISCAT observations (32 quiet summer and equinoctial days) to estimate the set of main aeronomic parameters. Three laboratory measured temperature dependencies for the O + + N 2 – rate coefficient were used in our calculations to find self-consistent factors both for this rate coefficient and for the solar EUV flux model from Nusinov. Independent of the rate coefficient used, the calculated values group around the temperature dependence recently measured by Hierl et al. in the 850–1400 K temperature range. Therefore, this rate coefficient may be considered as the most preferable and is recommended for aeronomic calculations. The calculated EUV flux shows a somewhat steeper dependence on solar activity than both, the Nusinov and the EUVAC models predict. In practice both EUV models may be recommended for the F2-region electron density calculations with the total EUV flux shifted by ±25% for the EUVAC and Nusinov models, correspondingly. Key words: Ionosphere (ion chemistry and composition; ionosphere atmosphere interactions; modeling and forecasting)