Equivalent Kernel Method for FUV Inversion Problems: Applications to NASA GOLD Disk Emission Data

Le résumé fourni par la source

Over the past decades far-ultraviolet (FUV) remote sensing has played a key role in advancing heliophysics by providing valuable measurements of space plasmas and neutral species. However, current inversion techniques for retrieval of physical parameters such as neutral composition and temperature and plasma density from FUV emission data do not consider the Poisson nature of the data or incorporate spatial information. This leads to loss of information that can be leveraged to more accurately retrieve fields of physical parameters with spatial structure and quantify uncertainty. We propose here that by modeling the received photon counts as a permanental process and applying reproducing kernel Hilbert space techniques, we are better able to uncover structure in fields and reduce the effects of shot noise, allowing for more reliable estimates and accurate uncertainty quantification. We demonstrate the method by estimating thermospheric neutral temperature from FUV disk emission data from the NASA Global Observation of the Limb and Disk (GOLD) mission. Case studies with both simulated data during a geomagnetic storm in early November 2018 and actual GOLD L1C data products are presented.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.