The 2022 Tonga Tsunami on the Pacific and Atlantic Coasts of the Americas
Bibliographic record
Abstract
Abstract The Hunga‐Tonga volcano eruption on 15 January 2022 generated tsunami waves that impacted both the Pacific and Atlantic coasts of the Americas. A unique feature of this event was the dual tsunami generation mechanism, which led to motions with long (several days) ringing and slow energy decay. The first ocean waves to reach the coast were “atmospheric tsunamis” generated by atmospheric Lamb waves that propagated with the speed of sound (∼314 m/s) and circled the globe in both directions several times before being fully attenuated. The second type of ocean waves were classical “oceanic tsunami” waves forced directly by the volcanic eruption and which propagated across the Pacific at roughly 2/3 the speed of the atmospheric waves. This study focuses on time series of the Hunga‐Tonga event recorded by tide gauges, microbarographs and Deep‐ocean Assessment and Reporting of Tsunamis on and off the Pacific coasts of North and Central America and in the Gulf of Mexico. Atmospheric tsunami waves only were recorded in the Gulf of Mexico, where the sea level response to the second, westward (shoreward) propagating atmospheric wave was stronger than to the first, eastward (seaward) propagating wave. Along the Pacific coast, the atmospheric tsunami waves were approximately 3–4 times smaller than the oceanic tsunami waves, which at several Mexican stations exceeded 2 m in height. The broad frequency range of 0.2–0.25 to 30 cph spanned by the oceanic tsunami in the Pacific indicates that the “effective” source area for the oceanic waves was more extensive than initially proposed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".