High-resolution physical–biogeochemical structure of a filament and an eddy of upwelled water off northwest Africa
Bibliographic record
Abstract
Abstract. Nutrient-rich water upwells offshore of northwest Africa and is subsequently advected westwards. There it forms eddies and filaments with a rich spatial structure of physical and biological/biogeochemical properties. Here we present a high-resolution (2.5 km) section through upwelling filaments and an eddy obtained in May 2018 with a TRIAXUS towed vehicle equipped with various oceanographic sensors. Physical processes at the mesoscale and submesoscale such as symmetric instability, trapping of fluid in eddies, and subduction of low potential vorticity (which we use as a water mass tracer) water can explain the observed distribution of biological production and export. We found a nitrate excess (higher concentrations of nitrate than expected from oxygen values if only influenced by production and remineralization processes) core of an anticyclonic mode water eddy. We also found a high nitrate concentration region of ≈5 km width in the mixed layer where symmetric instability appears to have injected nutrients from below into the euphotic zone. Similarly, further south high chlorophyll-a concentrations suggest that nutrients had been injected there a few days earlier. Considering that such interactions of physics and biology are ubiquitous in the upwelling regions of the world, we assume that they strongly influence the productivity of such systems and their role in CO2 uptake. The intricate interplay of different parameters at the kilometer scale needs to be taken into account when interpreting single-profile and/or bottle data in dynamically active regions of the ocean.
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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 | 0.000 | 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".