The Michoacán Tsunami of 19 September 2022 on the Coast of Mexico: Observations, Spectral Properties and Modelling
Bibliographic record
Abstract
The Mw 7.6 earthquake of 19 September 2022 within the coastal zone of Michoacán, Mexico, generated a major tsunami that was recorded by six coastal tide gauges and a single offshore DART station. All seven instruments were located within 250 km of the source. No tsunami was detected at larger distances. Maximum wave heights were observed at Manzanillo (172 cm) and Zihuatanejo (102 cm). Numerical modelling of the event closely reproduced the coastal and offshore tsunami records and shows that the tsunami energy radiated seaward from the source as a narrow “searchlight” beam directed normal to the source and mainland coast. Estimates of the frequency content (“colour”) of the 2022 tsunami event, and that generated in 2017 by the much stronger (Mw 8.2) Chiapas earthquake further up the coast, reveal a marked difference in the tsunamigenic response. Whereas the 2017 tsunami was mostly long-period (“reddish”), with 87% of the total tsunami energy at periods >35 min, the 2022 tsunami was short period (“bluish”) with 91% of energy at periods <35 min. A noteworthy feature of the 2022 event was the seismically generated seiches observed at Puerto Vallarta, which had a recorded period of about 7 min, began immediately after the main earthquake shock, and persisted for about one hour.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".