Abstract:
Magnetospheric images are constructed from resonant scattering of emissions by He$\sp+$ 30.4-nm and O$\sp+$ 83.4-nm ions from different spatial locations to study the structure of the intensities and its relation to the distribution of He$\sp+$ and O$\sp+$ ions around the Earth. The image intensities at these EUV wavelengths were obtained from a knowledge of ion scattering rates and available data on ion densities. This particular approach is called forward modelling and consists of the calculation of simulated EUV images of the magnetosphere. Different regions in the magnetosphere have been considered in this study to determine the dependence of the image intensities on ion energies and ion drift speeds with respect to the Sun-Earth line. Hot O$\sp+$ ions in the energy range from 1 keV to 50 keV are present in the plasma sheet with typical densities of the order of 0.1 ions cm$\sp{-3}$ arising during disturbed times. Image intensities of the order of a few millirayleighs were obtained in our simulations for these densities. During quiet times the densities are of the order of 0.05 ions cm$\sp{-3}.$ The reduction of the image intensities as a result of Doppler shifts caused by ion motion relative to the Sun-Earth line is discussed in detail and the effects of ion dynamics (particle acceleration) in the polar cap on the image intensities have also been analyzed for both He$\sp+$ and O$\sp+$ ions. The possibility of detecting polar outflows may also depend on the location of the imager. Simulated images of the plasmasphere and trough regions in both 30.4-nm and 83.4-nm wavelengths have been obtained to reflect the relative abundance of the ions in these regions. Photometric intensities of He$\sp+$ at 30.4 nm were obtained from a spinning rocket at an altitude of 435 km. The different viewing angles covered a wide range of regions in the magnetosphere, and this particular rocket geometry offered the possibility of obtaining the He$\sp+$ ion distribution from the measured intensities. This method (forward inversion) can be applied to 2-D images and it is shown that it is possible to extract 3-D ion distributions from the images.
