Forecast Global Ionospheric TEC: Apply Modified U‐Net on VISTA TEC Data Set
Abstract This work developed a modified U‐Net model (a convolutional network architecture) to predict global Total Electron Content (TEC) maps. The input includes the current global TEC map, the current F10.7, the time history of the Interplanetary Magnetic Field Bz and SYM‐H in the previous 4 days,...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-08-01
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| Series: | Space Weather |
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| Online Access: | https://doi.org/10.1029/2023SW003494 |
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| _version_ | 1841536324465590272 |
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| author | Zihan Wang Shasha Zou Hu Sun Yang Chen |
| author_facet | Zihan Wang Shasha Zou Hu Sun Yang Chen |
| author_sort | Zihan Wang |
| collection | DOAJ |
| description | Abstract This work developed a modified U‐Net model (a convolutional network architecture) to predict global Total Electron Content (TEC) maps. The input includes the current global TEC map, the current F10.7, the time history of the Interplanetary Magnetic Field Bz and SYM‐H in the previous 4 days, the Hour of Day, and the Day of Year. The output is the global TEC map several hours or several days ahead. The modified U‐Net was trained and validated on a brand new TEC database, the VISTA (Video Imputation with SoftImpute, Temporal smoothing and Auxiliary data) TEC database. The VISTA TEC maps can reveal important large‐scale TEC structures and preserve mesoscale structures simultaneously. Taking advantage of the new neural network and the new database, our model achieves an root of the mean squared error from 1.2 TECU to 2.4 TECU as the prediction horizon increases from 1 hr to 7 days. In addition, the model could reveal multiscale structures in the predicted TEC maps. |
| format | Article |
| id | doaj-art-41a5a827fe2d4541a50f98f9ce27a26c |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2023-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-41a5a827fe2d4541a50f98f9ce27a26c2025-01-14T16:31:19ZengWileySpace Weather1542-73902023-08-01218n/an/a10.1029/2023SW003494Forecast Global Ionospheric TEC: Apply Modified U‐Net on VISTA TEC Data SetZihan Wang0Shasha Zou1Hu Sun2Yang Chen3Department of Climate and Space Sciences and Engineering University of Michigan Ann Arbor MI USADepartment of Climate and Space Sciences and Engineering University of Michigan Ann Arbor MI USADepartment of Statistics University of Michigan Ann Arbor MI USADepartment of Statistics University of Michigan Ann Arbor MI USAAbstract This work developed a modified U‐Net model (a convolutional network architecture) to predict global Total Electron Content (TEC) maps. The input includes the current global TEC map, the current F10.7, the time history of the Interplanetary Magnetic Field Bz and SYM‐H in the previous 4 days, the Hour of Day, and the Day of Year. The output is the global TEC map several hours or several days ahead. The modified U‐Net was trained and validated on a brand new TEC database, the VISTA (Video Imputation with SoftImpute, Temporal smoothing and Auxiliary data) TEC database. The VISTA TEC maps can reveal important large‐scale TEC structures and preserve mesoscale structures simultaneously. Taking advantage of the new neural network and the new database, our model achieves an root of the mean squared error from 1.2 TECU to 2.4 TECU as the prediction horizon increases from 1 hr to 7 days. In addition, the model could reveal multiscale structures in the predicted TEC maps.https://doi.org/10.1029/2023SW003494TECionospheremachine learningspace weather |
| spellingShingle | Zihan Wang Shasha Zou Hu Sun Yang Chen Forecast Global Ionospheric TEC: Apply Modified U‐Net on VISTA TEC Data Set Space Weather TEC ionosphere machine learning space weather |
| title | Forecast Global Ionospheric TEC: Apply Modified U‐Net on VISTA TEC Data Set |
| title_full | Forecast Global Ionospheric TEC: Apply Modified U‐Net on VISTA TEC Data Set |
| title_fullStr | Forecast Global Ionospheric TEC: Apply Modified U‐Net on VISTA TEC Data Set |
| title_full_unstemmed | Forecast Global Ionospheric TEC: Apply Modified U‐Net on VISTA TEC Data Set |
| title_short | Forecast Global Ionospheric TEC: Apply Modified U‐Net on VISTA TEC Data Set |
| title_sort | forecast global ionospheric tec apply modified u net on vista tec data set |
| topic | TEC ionosphere machine learning space weather |
| url | https://doi.org/10.1029/2023SW003494 |
| work_keys_str_mv | AT zihanwang forecastglobalionospherictecapplymodifiedunetonvistatecdataset AT shashazou forecastglobalionospherictecapplymodifiedunetonvistatecdataset AT husun forecastglobalionospherictecapplymodifiedunetonvistatecdataset AT yangchen forecastglobalionospherictecapplymodifiedunetonvistatecdataset |