Contrasting behaviors of the atmospheric CO <sub>2</sub> interannual variability during two types of El Niños
Bibliographic record
Abstract
Abstract. El Niño has two different flavors: eastern Pacific (EP) and central Pacific (CP) El Niños, with different global teleconnections. However, their different impacts on carbon cycle interannual variability remain unclear. We here compared the behaviors of the atmospheric CO2 interannual variability and analyzed their terrestrial mechanisms during these two types of El Niños, based on Mauna Loa (MLO) CO2 growth rate (CGR) and Dynamic Global Vegetation Models (DGVMs) historical simulations. Composite analysis shows that evolutions of MLO CGR anomaly have three clear differences in terms of (1) negative and neutral precursors in boreal spring of El Niño developing years (denoted as “yr0”), (2) strong and weak amplitudes, and (3) durations of peak from December (yr0) to April of El Niño decaying year (denoted as “yr1”) and from October (yr0) to January (yr1) during EP and CP El Niños, respectively. Models simulated global land–atmosphere carbon flux (FTA) is able to capture the essentials of these characteristics. We further find that the gross primary productivity (GPP) over the tropics and extratropical southern hemisphere (Trop+SH) generally dominates the global FTA variations during both El Niño types. Regionally, significant anomalous carbon uptake caused by more precipitation and colder temperature, corresponding to the negative precursor, occurs between 30° S and 20° N from January (yr0) to June (yr0), while the strongest anomalous carbon releases, due largely to the reduced GPP induced by low precipitation and warm temperature, happen between equator and 20° N from February (yr1) to August (yr1) during EP El Niño events. In contrast, during CP El Niño events, clear carbon releases exist between 10° N and 20° S from September (yr0) to September (yr1), resulted from the widespread dry and warm climate conditions. Different spatial patterns of land temperature and precipitation in different seasons associated with EP and CP El Niños account for the characteristics in evolutions of GPP, terrestrial ecosystem respiration (TER), and resultant FTA. Understanding these different behaviors of the atmospheric CO2 interannual variability along with their terrestrial mechanisms during EP and CP El Niños is important because CP El Niño occurrence rate might increase under global warming.
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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".