Two major near-field tsunamis (2017 and 2022) on the coast of Mexico: Observations, spectral properties and numerical modelling
Bibliographic record
Abstract
Two prominent near-field tsunamis impacted the nearby coasts of Mexico. The first tsunami was generated by a major (Mw 8.2) intraplate normal-fault earthquake on 8 September 2017 in the Gulf of Tehuantepec (Chiapas, Mexico). Tsunami waves from this event were measured by a large number of high-resolution coastal tide gauges located along the coasts of California, Mexico and Central America, by three open-ocean DART stations anchored offshore from the affected region and by several distant DARTs. The second tsunami was produced by a thrust fault Mw 7.6 earthquake on 19 September 2022 within the coastal zone of Michoacán, Mexico. The 2022 tsunami 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 along the coasts of North and Central America, but the tsunami signal was detected at the Hawaii and Samoa islands. All available coastal and open-ocean data were used for comprehensive analyses of these two events. Maximum trough-to-crest wave heights for the 2017 tsunami were recorded at Puerto Chiapas (351 cm), Salina Cruz (209 cm), Acapulco (160 cm) and Huatulco (137 cm), while for the 2022 tsunami they were observed at Manzanillo (172 cm) and Zihuatanejo (102 cm). For both events, the “strengths” of the recorded tsunami waves were mostly determined by distance from the source rather than by the specific resonant characteristics of individual sites. Estimates of the frequency content (“colour”) of the two tsunami events revealed that the 2017 tsunami was mostly long-period (“reddish”), with 87% of the total tsunami energy at periods >35 min, while 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 7 min period seiche observed at Puerto Vallarta that began immediately after the main earthquake shock and persisted for about one hour. Numerical modelling of the events closely reproduced the coastal and offshore tsunami records and demonstrated the markedly different character of the tsunami energy radiation patterns: the 2017 tsunami spread energy widely in a semicircular pattern emanating from the source whereas the main beam of offshore energy radiating outward from the 2022 event was directed like a “searchlight” oriented normally to the mainland coast.
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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 | 0.001 | 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".