Near‐surface salinity and stratification in the north Bay of Bengal from moored observations
Bibliographic record
Abstract
Abstract A thin layer of fresh water from summer monsoon rain and river runoff in the Bay of Bengal (BoB) has profound influence on air‐sea interaction across the south Asian region, but the mechanisms that sustain the low‐salinity layer are as yet unknown. Using the first long time series of high‐frequency observations from a mooring in the north BoB and satellite salinity data, we show that fresh water from major rivers is transported by large‐scale flow and eddies, and shallow salinity stratification persists from summer through the following winter. The moored observations show frequent 0.2–1.2 psu salinity jumps with time scales of 10 min to days, due to O(1–10) km submesoscale salinity fronts moving past the mooring. In winter, satellite sea surface temperature shows 10 km wide filaments of cool water, in line with moored data. Rapid salinity and temperature changes at the mooring are highly coherent, suggesting slumping of salinity‐dominated fronts. Based on these observations, we propose that submesoscale fronts may be one of the important drivers for the persistent fresh layer in the north BoB.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".