An Automatic Method for Detection and Naive Classification of the Martian Ionospheric Irregularities

Abstract

The abundant observations and research established a detailed category of the terrestrial ionospheric irregularities, which significantly advanced our understanding of how the Earth system's complicated physical and chemical process generates the intermediate‐scale structures of the charged particles. Motivated by a future attempt at categorizing the Martian ionospheric irregularity, this study designs a method for naive classification of the plasma density depletion, enhancement, and oscillation based on the in situ measurements of the Martian ionosphere. The technique consists of several procedures: trend estimation, detrending and candidate extraction, and parameterization. The classification is achieved through a machine‐learning‐like process using some testing artificial density profiles. A preliminary credence test shows a good performance in separating the terrestrial low‐latitude Equatorial Plasma bubble (depletion) and mid‐latitude Median‐scale Traveling Ionospheric Disturbance (oscillation). Another detection experiment of the Martian plasma depletion events (collected by Basuvaraj et al. (2022a, https://doi.org/10.1029/2022je007302)) showed a recall rate (i.e., true positive) of 38% but with a high precision of 67.8%. Therefore, we believe the proposed method could convincingly extract different Martian ionospheric irregularities and help uncover the climatological characteristics in the future.