Automatic Identification of the Main Ionospheric Trough in Total Electron Content Images

Automatic Identification of the Main Ionospheric Trough in Total Electron Content Images

Abstract The main ionospheric trough (MIT) is a salient density feature in the mid‐latitude ionosphere and characterizing its structure is important for understanding Global Positioning System and HF signal propagation, and identifying geospace phenomena such as the plasmapause boundary layer. While...

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Bibliographic Details
Main Authors: Gregory Starr, Sebastijan Mrak, Yukitoshi Nishimura, Michael Hirsch, Prakash Ishwar, Joshua Semeter
Format: Article
Language:English
Published: Wiley 2022-06-01
Series:Space Weather
Subjects:
main ionospheric trough
Total Electron Content
regularized inverse problem
mid latitude ionosphere
image processing
data labeling
Online Access:https://doi.org/10.1029/2021SW002994
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Summary:Abstract The main ionospheric trough (MIT) is a salient density feature in the mid‐latitude ionosphere and characterizing its structure is important for understanding Global Positioning System and HF signal propagation, and identifying geospace phenomena such as the plasmapause boundary layer. While a number of previous studies have statistically investigated the properties of the MIT utilizing low‐altitude satellite observations, they have been limited to latitudinal cross sections, and have not considered the inherent two‐dimensional structure of the MIT. In this work, we develop a regularized inversion method for identifying the two dimensional structure of the MIT in Total Electron Content maps. Because no ground truth labels exist for the MIT, we extensively characterize the behavior of the algorithm by comparing it to the method developed by Aa, Zou, et al. (2020, doi:https://doi.org/10.1029/2019JA027583). We show that statistics computed on the resulting labels are robust to our choice of algorithm parameters and that we are able to match the results of Aa, Zou, et al. (2020, doi:https://doi.org/10.1029/2019JA027583) with a particular selection of the parameters. In addition to enabling fundamentally different studies, our MIT labels are able to provide statistical MIT properties with higher resolution. Code to reproduce our data set is provided in a GitHub repository: https://github.com/gregstarr/trough.
ISSN:1542-7390

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