Interannual variability in atmospheric CO<sub>2</sub> uptake on the northeast U.S. continental shelf
Bibliographic record
Abstract
Continental shelf systems are thought to play an important role in the exchange of carbon dioxide (CO2) between the atmosphere and ocean. Currently, our ability to quantify the air‐sea flux of CO2 on continental shelves is limited due to large spatial and temporal variability coupled with historically sparse oceanographic measurements (e.g., of surface water pCO2). Here we use the Regional Ocean Modeling System (ROMS) to quantify the air‐sea flux of CO2 and its interannual variability on the northeast U.S. continental shelf, which includes the Middle Atlantic Bight (MAB) and Gulf of Maine (GOM). Two years marked by opposite phases of the North Atlantic Oscillation (NAO) are considered in the study. A novel analysis method, second‐order Taylor series decomposition, is used to identify the important processes responsible for producing NAO‐related changes in the CO2 air‐sea flux. On the northeast U.S. shelf, atmospheric CO2 uptake as simulated by ROMS decreases from 2.4 Mt C yr−1 in 1985 (low NAO) to 1.8 Mt C yr−1 in 1990 (high NAO), with most of this decrease (0.5 Mt C yr−1) occurring in the MAB. In the MAB the difference in annual air‐sea flux of CO2 is due mainly to changes in near‐surface wind speed, while the flux difference in the GOM is controlled primarily by surface water pCO2 (CO2 partial pressure) changes resulting from changes in sea surface temperature and new production. The large magnitude of interannual variability in the air‐sea flux of CO2 simulated here suggests the potential for even more significant flux changes in the future as climate change accelerates.
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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 | 0.000 | 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 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".