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...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-06-01
|
| Series: | Space Weather |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2021SW002994 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841536463199535104 |
|---|---|
| author | Gregory Starr Sebastijan Mrak Yukitoshi Nishimura Michael Hirsch Prakash Ishwar Joshua Semeter |
| author_facet | Gregory Starr Sebastijan Mrak Yukitoshi Nishimura Michael Hirsch Prakash Ishwar Joshua Semeter |
| author_sort | Gregory Starr |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-1c8878fb598346d9b6390236e04c5f94 |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2022-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-1c8878fb598346d9b6390236e04c5f942025-01-14T16:27:09ZengWileySpace Weather1542-73902022-06-01206n/an/a10.1029/2021SW002994Automatic Identification of the Main Ionospheric Trough in Total Electron Content ImagesGregory Starr0Sebastijan Mrak1Yukitoshi Nishimura2Michael Hirsch3Prakash Ishwar4Joshua Semeter5Department of Electrical and Computer Engineering Boston University Boston MA USADepartment of Electrical and Computer Engineering Boston University Boston MA USADepartment of Electrical and Computer Engineering Boston University Boston MA USADepartment of Electrical and Computer Engineering Boston University Boston MA USADepartment of Electrical and Computer Engineering Boston University Boston MA USADepartment of Electrical and Computer Engineering Boston University Boston MA USAAbstract 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.https://doi.org/10.1029/2021SW002994main ionospheric troughTotal Electron Contentregularized inverse problemmid latitude ionosphereimage processingdata labeling |
| spellingShingle | Gregory Starr Sebastijan Mrak Yukitoshi Nishimura Michael Hirsch Prakash Ishwar Joshua Semeter Automatic Identification of the Main Ionospheric Trough in Total Electron Content Images Space Weather main ionospheric trough Total Electron Content regularized inverse problem mid latitude ionosphere image processing data labeling |
| title | Automatic Identification of the Main Ionospheric Trough in Total Electron Content Images |
| title_full | Automatic Identification of the Main Ionospheric Trough in Total Electron Content Images |
| title_fullStr | Automatic Identification of the Main Ionospheric Trough in Total Electron Content Images |
| title_full_unstemmed | Automatic Identification of the Main Ionospheric Trough in Total Electron Content Images |
| title_short | Automatic Identification of the Main Ionospheric Trough in Total Electron Content Images |
| title_sort | automatic identification of the main ionospheric trough in total electron content images |
| topic | main ionospheric trough Total Electron Content regularized inverse problem mid latitude ionosphere image processing data labeling |
| url | https://doi.org/10.1029/2021SW002994 |
| work_keys_str_mv | AT gregorystarr automaticidentificationofthemainionospherictroughintotalelectroncontentimages AT sebastijanmrak automaticidentificationofthemainionospherictroughintotalelectroncontentimages AT yukitoshinishimura automaticidentificationofthemainionospherictroughintotalelectroncontentimages AT michaelhirsch automaticidentificationofthemainionospherictroughintotalelectroncontentimages AT prakashishwar automaticidentificationofthemainionospherictroughintotalelectroncontentimages AT joshuasemeter automaticidentificationofthemainionospherictroughintotalelectroncontentimages |