An Analysis of the Beaufort Sea Thermohaline Structure and Variability, and Its Effects on Acoustic Propagation
Bibliographic record
Abstract
This thesis provides an analysis of spatial and temporal thermohaline variations of the Canada Basin in the Western Arctic and examines how these variations affect sound speed fields and acoustic propagation. In recent decades, changes in the Arctic water column have been underway as a result of climate change including reduced sea ice and changes in transports between the Pacific and Atlantic oceans. These changes were studied and analyzed using observational data collected from the Canada Basin Acoustic Propagation Experiment (CANAPE) conducted in the summer of 2015. The thermohaline sound speed structure was examined by computing isopycnal displacements, which allowed separation of internal waves and eddies from intrusive thermohaline structure or spice. Temporal structure of these processes was estimated using spectral analysis, and vertical structure was examined by computing the rms variation of the various processes as a function of depth. Observations were compared to climatology. Acoustic propagation simulations using a ray-based model termed Bellhop were used to estimate the acoustic sensitivity to the observed ocean structure. It was found that internal waves were weak compared to the Garret Munk spectrum and that spice is surprisingly strong in the ocean structure with dominance in the upper 100m. The acoustic analysis revealed that a greater variability in transmission loss in the CTD CANAPE data was evident compared to climatology and previous observations, particularly at greater frequencies and range. The presence of a sub-surface sound speed duct existed with an axis at ~120m and accommodated an environment with increased travel distance for acoustic energy and lower transmission loss for depths between 100Ð200m.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".