Gravity waves generated by the Hunga Tonga–Hunga Ha′apai volcanic eruption and their global propagation in the mesosphere/lower thermosphere observed by meteor radars and modeled with the High-Altitude general Mechanistic Circulation Model
Bibliographic record
Abstract
The Hunga Tonga–Hunga Ha′apai volcano erupted on 15 January 2022, launching Lamb waves and gravity waves into the atmosphere. In this study, we present results using 13 globally distributed meteor radars and identify the volcanogenic gravity waves in the mesospheric/lower thermospheric winds. Leveraging the High-Altitude Mechanistic general Circulation Model (HIAMCM), we compare the global propagation of these gravity waves. We observed an eastward-propagating gravity wave packet with an observed phase speed of 240 ± 5.7 m s −1 and a westward-propagating gravity wave with an observed phase speed of 166.5 ± 6.4 m s −1 . We identified these waves in HIAMCM and obtained very good agreement of the observed phase speeds of 239.5 ± 4.3 and 162.2 ± 6.1 m s −1 for the eastward the westward waves, respectively. Considering that HIAMCM perturbations in the mesosphere/lower thermosphere were the result of the secondary waves generated by the dissipation of the primary gravity waves from the volcanic eruption, this affirms the importance of higher-order wave generation. Furthermore, based on meteor radar observations of the gravity wave propagation around the globe, we estimate the eruption time to be within 6 min of the nominal value of 15 January 2022 04:15 UTC, and we localized the volcanic eruption to be within 78 km relative to the World Geodetic System 84 coordinates of the volcano, confirming our estimates to be realistic.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".