Triple jeopardy: The Tonga tsunami, a storm surge, and a meteotsunami simultaneously hit the US East Coast on 16-17 January 2022
Bibliographic record
Abstract
The eruption of the Tonga–Hunga underwater volcano in the Central Pacific on 15 January 2022 generated pronounced atmospheric pressure waves that circumvented the globe several times during the next five days. Propagating with a sound speed of ~10 spherical degrees/hour, the pressure waves forced substantial tsunami waves in the Atlantic Ocean that impacted the East Coast of the United States. Almost simultaneously, on 16-17 January 2022, a deep midlatitude cyclone crossed the East Coast. The cyclone, which formed over the northern part of the Gulf of Mexico, began to rapidly intensify as it moved northward. When it reached 40° N, the system produced a pressure change of 36 hPa/24 hours, classifying the cyclone as a “bomb cyclone”. Strong high-frequency (period <4 h) atmospheric pressure disturbances accompanied the cyclone. Both the large-scale atmospheric low and the markedly enhanced pressure disturbance reached their full strengths during the early morning of 17 January 2022 in the proximity of Atlantic City. As a consequence, three hazardous events - storm surge caused by the midlatitude cyclone, a tsunami caused by the Tonga air pressure waves and a meteotsunami caused by the HF atmospheric pressure disturbance struck the US East Coast on 16-17 January 2022, producing cumulative devastating effects in the coastal zone. Severe coastal flooding affected the Atlantic City region, where sea level heights were increased by as much as 150 cm. This unique joint event is examined in detail and the properties of the atmospheric processes and associated sea level response are thoroughly analysed. The contributions from the various sea level components are assessed and their interaction evaluated.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".