Modelling high-latitude electron densities with a coupled thermosphere-ionosphere model

• Published in: Annales Geophysicae
• Main Authors: Schoendorf, J., Aylward, A. D., Moffett, R. J.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Springer Verlag 1996
• Subjects: article; Verlagsveröffentlichung; EISCAT
• Online Access: https://doi.org/10.1007/s00585-996-1391-x; https://noa.gwlb.de/receive/cop_mods_00037680; https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00037634/angeo-14-1391-1996.pdf; https://angeo.copernicus.org/articles/14/1391/1996/angeo-14-1391-1996.pdf

A few of the difficulties in accurately modelling high-latitude electron densities with a large-scale numerical model of the thermosphere and ionosphere are addressed by comparing electron densities calculated with the Coupled Thermosphere-Ionosphere Model (CTIM) to EISCAT data. Two types of simulations are presented. The first set of simulations consists of four diurnally reproducible model runs for a Kp index of 4o which differ only in the placement of the energetic-particle distribution and convection pattern input at high latitudes. These simulations predict varying amounts of agreement with the EISCAT data and illustrate that for a given Kp there is no unique solution at high-latitudes. Small changes in the high-latitude inputs cause dramatic changes in the high-latitude modelled densities. The second type of simulation consists of inputting statistical convection and particle precipitation patterns which shrink or grow as a function of Kp throughout a 3-day period 21–23 February 1990. Comparisons with the EISCAT data for the 3 days indicate that equatorward of the particle precipitation the model accurately simulates the data, while in the auroral zone there is more variability in the data than the model. Changing the high-latitude forcing as a function of Kp allows the CTIM to model the average behavior of the electron densities; however at auroral latitudes model spatial and temporal scales are too large to simulate the detailed variation seen in individual nights of data.