On the Measurement of Ocean Acidity With Ambient Sound
Bibliographic record
Abstract
Abstract The volume‐integrated pH of seawater can be determined from the frequency and depth dependence of wind‐generated ambient noise in the ocean. Over the 1–10 kHz frequency band, three main processes contribute to the acoustic attenuation in seawater: the chemical relaxation of boric acid and magnesium carbonate (<3 kHz, related to pH) and of magnesium sulfate (>3 kHz, unrelated to pH). When local winds are strong (>10 m/s), the ambient noise is dominated by locally generated surface noise, which exhibits a depth‐independent directionality and weak frequency and depth‐dependent intensity. By measuring the depth dependence of the spectral slope, the pH may be estimated from a comparison of the experimental data with an analytical model of ambient noise. Wideband (5 Hz–30 kHz) vertical ambient sound profiles were recorded using two‐ and four‐channel free‐falling acoustic profilers at depths ranging from 500 m to 10 km during nine deployments in the Philippine Sea, Mariana Trench, and Tonga Trench from 2009 to 2021. Two analytical models of the depth dependence of ambient noise were developed: a simplified linear model valid at depths <1,500 m and a full nonlinear model valid for the deep ocean. Estimates of pH were found by minimizing the mean absolute percent error between the measurements and the models. This method of passive acoustic absorption spectroscopy demonstrates the potential and sources of uncertainty in determining the depth‐averaged value of pH. The method could be suitable for the long‐term passive acoustic monitoring of ocean acidity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".