Validation of the IRI-2020 topside ionosphere options through in-situ electron density observations by low-Earth-orbit satellites
Bibliographic record
Abstract
The topside ionosphere extends from the F2-layer peak, where the electron density reaches its absolute maximum in the ionosphere, to the overlying plasmasphere and magnetosphere. In the topside ionosphere, the electron density decreases with height with a vertical variation rate strongly dependent on height itself. The last version of the International Reference Ionosphere (IRI) model, i.e., IRI-2020, describes this complex behavior through four topside options based on different sub-models (i.e., options) developed from the 1970s to the present. All these options have in common the F2-layer peak as an anchor point, while they differ in their topside electron density profile and/or plasma effective scale height formulations. In this work, we perform a validation of the accuracy of the four IRI-2020 topside options based on the comparison against in-situ electron density observations by Gravity Recovery and Climate Experiment (GRACE), Ionospheric Connection Explorer (ICON), and Defense Meteorological Satellite Program (DMSP) F15 low-Earth-orbit satellites. Datasets used in this study encompass observations recorded from 1999 to 2022, covering different diurnal, seasonal, and solar activity conditions, on a global basis and for the height range 400−850 km above the ground. The nearly two solar cycles dataset facilitated the evaluation of IRI-2020 topside options ability to reproduce the spatial and time variations of the topside ionosphere for different solar activity conditions. The weaknesses and strengths of each IRI-2020 topside option are highlighted and discussed, and suggestions on how to improve the modeling of the challenging topside ionosphere region within the IRI model are provided for future reference.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".