Influence of atmospheric transport on the inter‐annual variation of the CO<sub>2</sub> seasonal cycle downward zero‐crossing
Bibliographic record
Abstract
Using a 3‐dimensional atmospheric transport model driven by the ECMWF winds and the non‐interannually varying seasonal biospheric flux from the CASA global ecosystem model, we show that a significant change in the downward‐zero crossing day (DZCD) of the atmospheric CO2 seasonal cycle in the Northern Hemisphere above 30°N latitude can be obtained by year‐to‐year changes in the atmospheric transport alone. The transport model is able to reproduce both the trend and standard deviation of DZCD observed at Pt. Barrow. With only atmospheric transport changing from year to year, eastern North Atlantic, Europe, southern Eurasia, southeastern United States and western North America show DZCD starting earlier by 5–10 days after 21 years of model integration. If DZCD obtained from CO2 monitoring stations is going to be used as a proxy for determining the growing season length, then it is important to take into account of that portion caused by the atmospheric transport.
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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 | 0.001 |
| 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 | 0.001 | 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 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".