A Vertical Diffusion Scheme to estimate the atmospheric rectifier effect
Bibliographic record
Abstract
The magnitude and spatial distribution of the carbon sink in the extratropical Northern Hemisphere remain uncertain in spite of much progress made in recent decades. Vertical CO2 diffusion in the planetary boundary layer (PBL) is an integral part of atmospheric CO2 transport and is important in understanding the global CO2 distribution pattern, in particular, the rectifier effect on the distribution [ Keeling et al., 1989 ; Denning et al., 1995 ]. Attempts to constrain carbon fluxes using surface measurements and inversion models are limited by large uncertainties in this effect governed by different processes. In this study, we developed a Vertical Diffusion Scheme (VDS) to investigate the vertical CO2 transport in the PBL and to evaluate CO2 vertical rectification. The VDS was driven by the net ecosystem carbon flux and the surface sensible heat flux, simulated using the Boreal Ecosystem Productivity Simulator (BEPS) and a land surface scheme. The VDS model was validated against half‐hourly CO2 concentration measurements at 20 m and 40 m heights above a boreal forest, at Fraserdale (49°52′29.9″N, 81°34′12.3″W), Ontario, Canada. The amplitude and phase of the diurnal/seasonal cycles of simulated CO2 concentration during the growing season agreed closely with the measurements (linear correlation coefficient (R) equals 0.81). Simulated vertical and temporal distribution patterns of CO2 concentration were comparable to those measured at the North Carolina tower. The rectifier effect, in terms of an annual‐mean vertical gradient of CO2 concentration in the atmosphere that decreases from the surface to the top of PBL, was found at Fraserdale to be about 3.56 ppmv. Positive covariance between the seasonal cycles of plant growth and PBL vertical diffusion was responsible for about 75% of the effect, and the rest was caused by covariance between their diurnal cycles. The rectifier effect exhibited strong seasonal variations, and the contribution from the diurnal cycle was mostly confined to the surface layer (less than 300 m).
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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 | 0.000 | 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 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".