Meteotsunamis: atmospherically induced destructive ocean waves in the tsunami frequency band
Bibliographic record
Abstract
Abstract. In light of the recent enhanced activity in the study of tsunami waves and their source mechanisms, we consider tsunami-like waves that are induced by atmospheric processes rather than by seismic sources. These waves are mainly associated with atmospheric gravity waves, pressure jumps, frontal passages, squalls and other types of atmospheric disturbances, which normally generate barotropic ocean waves in the open ocean and amplify them near the coast through specific resonance mechanisms (Proudman, Greenspan, shelf, harbour). The main purpose of the present study is to describe this hazardous phenomenon, to show similarities and differences between seismic and meteorological tsunamis and to provide an overview of meteorological tsunamis in the World Ocean. It is shown that tsunamis and meteotsunamis have the same periods, same spatial scales, similar physical properties and affect the coast in a comparably destructive way. Some specific features of meteotsunamis make them akin to landslide-generated tsunamis. The generation efficiency of both phenomena depend on the Froude number (Fr), with resonance taking place when Fr~1.0. Meteotsunamis are much less energetic than seismic tsunamis and that is why they are always local, while seismic tsunamis can have globally destructive effects. Destructive meteotsunamis are always the result of a combination of several resonant factors; the low probability of such a combination is the main reason why major meteotsunamis are infrequent and observed only at some specific locations in the ocean.
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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 | 0.001 |
| 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".