Beamforming of Rayleigh and Love Waves in the Course of Atlantic Cyclones
Bibliographic record
Abstract
Abstract The main sources of the ambient seismic wavefield in the microseismic frequency band (peaking in the ∼0.04–0.5 Hz range) are earth's oceans, namely the wind‐driven surface gravity waves (SGW) that couple oscillations into the seafloor and the upper crust underneath. Cyclones (e.g., hurricanes, typhoons) and other atmospheric storms are efficient generators of high ocean waves that in turn generate distinct microseismic signatures. In this study, we perform a polarization (i.e., three‐component) beamforming analysis of microseismic (0.05–0.16 Hz) retrograde Rayleigh and Love waves during major Atlantic hurricanes using a virtual array of seismometers in Eastern Canada. Oceanic hindcasts and meteorological data are used for comparison. No continuous generation of microseism along the hurricane track is observed but rather an intermittent signal generation. Both seismic surface wave types show clear cyclone‐related microseismic signatures that are consistent with a colocated generation at near‐coastal or shallow regions, however the Love wavefield is comparatively less coherent. We identify two different kinds of intermittent signals: (a) azimuthally progressive signals that originate with a nearly constant spatial lag pointing toward the trail of the hurricanes and (b) azimuthally steady signals remaining nearly constant in direction of arrival even days after the hurricane significantly changed its azimuth. This high complexity highlights the need for further studies to unravel the interplay between site‐dependent geophysical parameters, SGW forcing at depth and microseismic wavefield radiation and propagation, as well as the potential use of cyclone microseisms as passive natural sources.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".