The volume scattering function of natural bubble populations
Bibliographic record
Abstract
The volume scattering function (VSF) of natural bubble populations is (1) determined from Mie scattering theory, (2) measured by a newly designed volume scattering meter in the laboratory, and (3) inferred from field observations of the VSF. The laboratory measurements have confirmed our theoretical prediction in that (1) bubbles of sizes that have been recorded in situ in the surface ocean (>10 μm) show elevated scattering for angles between 60° and 80° and (2) the organic coatings on the bubble surface will increase the scattering in the backward hemisphere but little change the scattering in the forward directions, including the critical angles. An optimization analysis is applied to the measurement of the VSF in coastal waters, and the results suggest the potential existence of submicron bubbles that are coated with organic film. The bubble population thus determined, which has a negligible contribution to the total scattering (5%), accounts for 40% of the total backscattering that has been observed in situ. The extension of the bubble size distribution to smaller sizes than can presently be measured by direct techniques will alter the shape of derived phase function in general but will result in rather small changes to the backscattering ratio (<20%) as long as the slope of the size distribution is small, because most of the changes are in the forward (<10°) direction. However, the prominent peak in the VSF at the critical angle observed for larger bubbles is strongly reduced by the inclusion of the small sizes, and the backscattering ratio is increased by a factor of two for distributions that varies as the −4 power of size. Because these bubbles contribute strongly to scattering at large angles, these results have significant implications for the remote observation of the color of the sea.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".