Analysis of the IMAGE RPI electron density data and CHAMP plasmasphere electron density reconstructions with focus on plasmasphere modelling

Abstract

The electron density of the topside ionosphere and the plasmasphere contributes essentially to the overall Total Electron Content (TEC) budget affecting Global Navigation Satellite Systems (GNSS) signals. The plasmasphere can cause half or even more of the GNSS range error budget due to ionospheric propagation errors. This paper presents a comparative study of different plasmasphere and topside ionosphere data aiming at establishing an appropriate database for plasmasphere modelling. We analyze electron density profiles along the geomagnetic field lines derived from the Imager for Magnetopause-to-Aurora Global Exploration (IMAGE) satellite/Radio Plasma Imager (RPI) records of remote plasma sounding with radio waves. We compare these RPI profiles with 2D reconstructions of the topside ionosphere and plasmasphere electron density derived from GNSS based TEC measurements onboard the Challenging Minisatellite Payload (CHAMP) satellite. Most of the coincidences between IMAGE profiles and CHAMP reconstructions are detected in the region with L-shell between 2 and 5. In general the CHAMP reconstructed electron densities are below the IMAGE profile densities, with median of the CHAMP minus IMAGE residuals around −588cm−3. Additionally, a comparison is made with electron densities derived from passive radio wave RPI measurements onboard the IMAGE satellite. Over the available 2001–2005 period of IMAGE measurements, the considered combined data from the active and passive RPI operations cover the region within a latitude range of ±60°N, all longitudes, and an L-shell ranging from 1.2 to 15. In the coincidence regions (mainly 2⩽L⩽4), we check the agreement between available active and passive RPI data. The comparison shows that the measurements are well correlated, with a median residual of ∼52cm−3. The RMS and STD values of the relative residuals are around 22% and 21% respectively. In summary, the results encourage the application of IMAGE RPI data for plasmasphere and plasmapause modeling.