Spatial and temporal variability of the surface water pCO<sub>2</sub> and air‐sea CO<sub>2</sub> flux in the equatorial Pacific during 1980–2003: A basin‐scale carbon cycle model
Bibliographic record
Abstract
The surface water pCO2 data from the past two decades indicate significant seasonal to interannual variability, and the size of the equatorial Pacific CO2 source is strongly influenced by El Niño and La Niña events. A basin‐scale ocean circulation‐biogeochemistry model is developed to study the carbon cycle in the equatorial Pacific for the period of 1980–2003. The model produces strong spatial and temporal variability in sea minus air pCO2 (50–170 μatm) and sea‐to‐air CO2 flux (1–5 mol C m−2 yr−1). The magnitude, spatial pattern, and seasonal to interannual variability in the model fields are in general agreement with the observations. Our analyses have demonstrated that dissolved inorganic carbon (DIC) plays a dominant role in determining the interannual variability of the sea surface pCO2 in the equatorial Pacific. However, sea surface temperature (SST) also has significant influence on the spatial and temporal variability of the sea surface pCO2 in particular during warm periods. At seasonal timescales, the sea surface pCO2 is relatively high both in boreal spring and fall, but low in boreal summer in the eastern equatorial Pacific. While the high sea surface pCO2 in boreal fall is associated with the seasonal upwelling of carbon‐rich water, the high sea surface pCO2 in boreal spring results mainly from the seasonal warming (e.g., high SST). At interannual timescales, the sea surface pCO2 is largely associated with the El Niño–Southern Oscillation (ENSO) phenomenon, showing high values during cold ENSO phase but low ones during warm ENSO phase. The overall spatial and temporal variations of the sea surface pCO2 are dominated by physical processes (e.g., seasonal upwelling and the ENSO cycle). However, biological uptake also plays an important role in modulating the variability of the sea surface pCO2, and determining the strength of the equatorial Pacific CO2 source. On an annual basis, the integrated DIC over the top 50 m of the equatorial Pacific is approximately balanced between the supply due to physical processes (1.47 Pg C) and removal due to the biological activity (0.87 Pg C) and outgassing (0.6 Pg C).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".