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

Author:

Wan Xin12ORCID,Zhong Jiahao12ORCID,Hao Yongqiang12,Cao Yutian1ORCID,Cui Jun1ORCID,Xiong Chao3ORCID,Wang Hui3ORCID,Liu Yiwen4ORCID,Kuai Jiawei5ORCID,Li Qiaoling6ORCID

Affiliation:

1. Planetary Environmental and Astrobiological Research Laboratory (PEARL) School of Atmospheric Sciences Sun Yat‐sen University Zhuhai China

2. Key Laboratory of Tropical Atmosphere‐Ocean System Ministry of Education Zhuhai China

3. Department of Space Physics College of Electronic Information Wuhan University Wuhan China

4. School of Physics and Electronic Information Shangrao Normal University Shangrao China

5. College of Astronautics Nanjing University of Aeronautics and Astronautics Nanjing China

6. School of Petroleum China University of Petroleum‐Beijing at Karamay Karamay China

Abstract

AbstractThe 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.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

American Geophysical Union (AGU)

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