PROSERPINA: An Automated Pipeline for Martian Ionospheric Radio-occultation Retrievals with Probabilistic Uncertainty and Spherical-symmetry Bias Quantification

Spacecraft-to-Earth radio occultation (RO) experiments are a powerful tool for probing planetary atmospheres and ionospheres. However, standard processing typically requires manual intervention and assumes spherical symmetry. This assumption is rarely tested, and its impact on retrieved electron density profiles is not often quantified. Here we present Processing Radio Occultations System for Examining and Reconstructing Planetary Ionised and Neutral Atmospheres (PROSERPINA), a fully automated Python pipeline designed to retrieve electron density profiles from one-way radio occultation observations at Mars. The pipeline also introduces Forward–Backward Ionospheric Density Estimation System (FIDES), a module that quantifies the bias introduced by the spherical-symmetry assumption in Abel inversion. FIDES generates synthetic two-dimensional ionospheres anchored to the retrieved Abel peak and analyzes the difference between FIDES and Abel results. This difference is decomposed into amplitude, peak-altitude, and width components, producing a structured model-error covariance for each profile. The Abel-retrieved profile remains the primary estimate. The reported 95% credible intervals incorporate contributions from thermal noise, uncertainty in the baseline slope, and the model uncertainty derived from FIDES. We validate PROSERPINA using Mars Global Surveyor (MGS) electron density profiles archived and processed independently in the NASA Planetary Data System and apply it to 100 previously unprocessed MGS profiles, of which 20 are fully shown here. Across these cases, the uncertainty associated with the spherical-symmetry assumption dominates over baseline-slope uncertainty and thermal noise for high solar zenith angle dayside M2 peaks, contributing a median uncertainty of about 30% of the peak density.