Sea–air methane flux estimates derived from marine surface observations and instantaneous atmospheric measurements in the northern Labrador Sea and Baffin Bay
Bibliographic record
Abstract
Abstract. Vast amounts of methane (CH4) stored in submarine sediments are susceptible to release in a warming Arctic, further exacerbating climate change in a positive feedback. It is therefore critical to monitor CH4 over pan-regional scales to detect early signs of CH4 release. However, our ability to monitor CH4 is hampered in remote northern regions by sampling and logistical constraints, and few good baseline data exist in many areas. From high-resolution atmospheric CH4 measurements and discrete surface water samples, we estimated instantaneous sea–air CH4 fluxes at various locations. We also created a baseline study of current background levels of CH4 in North Atlantic waters based on the atmospheric CH4 data over 22 d in summer 2021 on a roughly 5100 km voyage in the northern Labrador Sea and Baffin Bay between 55 and 72∘ N. In addition, we measured CH4 concentrations across the water column at various stations. Measured atmospheric mixing ratios of CH4 ranged from 1944 to 2012 ppbv, with a mean of 1966 ± 8 ppbv and a baseline of 1954–1981 ppbv. Dissolved CH4 concentrations in the near-surface water peaked at 5.3 nmol L−1 within 1 km down-current of a known cold seep at Scott Inlet and were consistently oversaturated throughout the water column in Southwind Fjord, which is an area that has been recently affected by submarine landslides. Local sea–air CH4 fluxes ranged from 0.003–0.119 µmol m−2 d−1, indicating that the ocean released only small amounts of CH4 to the atmosphere at all stations. Atmospheric CH4 levels were also driven by meteorological, spatial, and temporal variations, and both onshore and ocean-based contributions to atmospheric CH4 mixing ratios are likely. Coupled high-resolution measurements of marine and atmospheric CH4 data have the potential to provide ongoing monitoring in a region susceptible to CH4 releases, as well as critical validation data for global-scale measurements and modelling.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".