Performance Analysis of NeQuick-G, IRI-2016, IRI-Plas 2017 and AfriTEC Models over the African Region during the Geomagnetic Storm of March 2015
Bibliographic record
Abstract
Abstract This paper investigates the diurnal variations of modelled and observed vertical total electron content (VTEC) over the African region (40° N to +40° S, 25° W to 65° E) obtained from ground-based global navigation satellite system (GNSS) receivers. The investigations on ionospheric response during the super geomagnetic storm time (March 17 2015) are crucial, especially over African low latitudes. Hence, the performance of ionospheric models has been evaluated in this paper. The VTEC predictability by regional/global ionospheric models (AfriTEC, IRI-2016, IRI-Plas 2017, GIM-CODE, and Nequick-G) is assessed by using root mean square error (RMSE) method and percentage deviation by comparing the GPS/GNSS-VTEC obtained from 10 IGS (International GNSS Service) stations with the modelled-VTEC values over the African region. The peculiarity in VTEC values is evident during the superstorm’s sudden commencement compared to the pre- and post-storm periods. Northern hemisphere GPS station TEC data showed a twin peak in the daily VTEC patterns. The enhanced VTEC values were observed over all the selected 10 IGS stations on the storm day than on other quiet days. Moreover, during the post-storm days (March 18–20, 2015), these VTEC values decreased more than on quiet days over the IGS stations in the southern hemisphere (MBAR, MAYG, HARB, SBOK). On the other hand, during the post-storm days (March 18–20, 2015), the VTEC values remained high over the geomagnetic northern hemisphere (NOT1, SFER, MAS1, CPVG, NKLG). It is worth mentioning that three northern IGS stations (NOT1, SFER, and MAS1) displayed a VTEC increase record of approximately 75–90% due to the extension of equatorial ionization anomaly (EIA) during the geomagnetic storm. In contrast, the other northern stations at the EIA trough region (CPVG, BJCO, NKLG) registered a VTEC increment of 7, 26, and 25%, respectively. Southern IGS stations registered an enhancement in VTEC of about 5%. The VTEC maps from AfriTEC, IRI-2016, and Nequick-G were able to predict the feature of EIA at around 20° N/15° S. The GPS-VTEC values at IGS stations located on the geomagnetic EIA crests (in both northern and southern hemispheres) and in the trough (equatorial stations) are higher than those of the IGS stations situated at mid-latitudes. AfriTEC, a regional model, recorded the lowest RMSE values over all the stations. The prediction results show that the regional model performance is better than the global ionospheric models (IRI-2016 and Nequick-G models), especially over EIA latitudes of the African region.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".