Fine scale variability of greenhouse gases in polar and subpolar ocean waters : insights from high resolution sampling and numerical models
Bibliographic record
Abstract
We present high resolution surface water measurements and discrete water column profiles of nitrous oxide (N₂O) and methane (CH₄) saturations in two distinct oceanographic regions, the Canadian Arctic Archipelago, and the Northeast Subarctic Pacific. Utilizing a high frequency, automated measurement system, we were able to reveal fine-scale variability in surface water N₂O and CH₄ saturations not previously captured using discrete sampling in earlier studies. We combine these high frequency observations with depth profile measurements and numerical model output to better understand how vertical mixing influences gas concentrations on small scales. In doing so, we found that elevated gas supersaturation in both study regions was associated with strong vertical mixing, as indicated by increased vertical eddy diffusivity (κ𝚣) values. In the Eastern Canadian Arctic, we observed CH₄ saturations 300% larger than previously reported, based on existing measurements mostly conducted in summertime. We suggest that these summer measurements may have failed to capture elevated surface water concentrations associated with weakened stratification and increased mixing during early autumn. In the Northeast Subarctic Pacific, the range of N₂O and CH₄ saturations we measured was consistent with prior observations, although our high-resolution measurements provided greater detail on the spatial and temporal variability of these gases. In particular, we were able to identify new regions of elevated N₂O and CH₄, associated with regions of strong tidal mixing around the west coast of Vancouver Island and Salish Sea. Time-series observations conducted along the west coast of Vancouver Island revealed strong temporal variability in N₂O and CH₄ saturations associated with a combination of wind-driven and tidal mixing. Our work highlights the utility of high frequency measurements, combined with numerical model output, to provide insight into the oceanographic processes affecting surface water N₂O and CH₄ distributions in dynamic marine systems.
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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 | 0.000 |
| 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) | 0.000 | 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 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".