A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes
Bibliographic record
Abstract
Abstract The coastal ocean contributes to regulating atmospheric greenhouse gas concentrations by taking up carbon dioxide (CO 2 ) and releasing nitrous oxide (N 2 O) and methane (CH 4 ). In this second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP2), we quantify global coastal ocean fluxes of CO 2 , N 2 O and CH 4 using an ensemble of global gap‐filled observation‐based products and ocean biogeochemical models. The global coastal ocean is a net sink of CO 2 in both observational products and models, but the magnitude of the median net global coastal uptake is ∼60% larger in models (−0.72 vs. −0.44 PgC year −1 , 1998–2018, coastal ocean extending to 300 km offshore or 1,000 m isobath with area of 77 million km 2 ). We attribute most of this model‐product difference to the seasonality in sea surface CO 2 partial pressure at mid‐ and high‐latitudes, where models simulate stronger winter CO 2 uptake. The coastal ocean CO 2 sink has increased in the past decades but the available time‐resolving observation‐based products and models show large discrepancies in the magnitude of this increase. The global coastal ocean is a major source of N 2 O (+0.70 PgCO 2 ‐e year −1 in observational product and +0.54 PgCO 2 ‐e year −1 in model median) and CH 4 (+0.21 PgCO 2 ‐e year −1 in observational product), which offsets a substantial proportion of the coastal CO 2 uptake in the net radiative balance (30%–60% in CO 2 ‐equivalents), highlighting the importance of considering the three greenhouse gases when examining the influence of the coastal ocean on climate.
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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 | 0.000 | 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) | 0.001 | 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 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".