Mechanisms for synoptic transport of atmospheric CO <sub>2</sub> in the midlatitudes and tropics
Bibliographic record
Abstract
Abstract. Synoptic variations of CO2 mixing ratio produced by interactions between weather and surface fluxes are investigated mechanistically and quantitatively in midlatitude and tropical regions using continuous in-situ CO2 observations in North America, South America and Europe and forward chemical transport model simulations with the Parameterized Chemistry Transport Model. Frontal CO2 climatologies show consistently strong, characteristic frontal CO2 signals throughout the midlatitudes of North America and Europe. Transitions between synoptically identifiable CO2 air masses or transient spikes along the frontal boundary typically characterize these signals. One case study of a summer cold front shows that CO2 gradients organize with deformational flow along weather fronts producing strong and spatially coherent variations. A boundary layer budget equation is constructed in order to determine contributions to boundary layer CO2 tendencies by horizontal and vertical advection, moist convection, and biological and anthropogenic surface fluxes. Analysis of this equation suggests that, in midlatitudes, advection is responsible for 50–90% of the amplitude of frontal variations in the summer, depending on upstream influences, and 50% of all day-to-day variations throughout the year. Simulations testing sensitivity to local cloud and surface fluxes further suggest that horizontal advection is a major source of CO2 variability in midlatitudes. In the tropics, coupling between convective transport and surface CO2 flux is most important. Due to the scarcity of tropical observations available at the time of this study, future work should extend such mechanistic analysis to additional tropical locations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".