Atmospheric inversion of the surface CO<sub>2</sub> flux with <sup>13</sup>CO<sub>2</sub> constraint
Bibliographic record
Abstract
Abstract. Observations of 13CO2 at 73 sites compiled in the GLOBALVIEW database are used for an additional constraint in a global atmospheric inversion of the surface CO2 flux using CO2 observations at 210 sites for the 2002–2004 period for 39 land regions and 11 ocean regions. This constraint is implemented using the 13CO2/CO2 flux ratio modeled with a terrestrial ecosystem model and an ocean model. These models simulate 13CO2 discrimination rates of terrestrial photosynthesis and respiration and ocean-atmosphere diffusion processes. In both models, the 13CO2 disequilibrium between fluxes to and from the atmosphere is considered due to the historical change in atmospheric 13CO2 concentration. For the 2002–2004 period, the 13CO2 constraint on the inversion increases the total land carbon sink from 3.40 to 3.70 Pg C yr−1 and decreases the total oceanic carbon sink from 1.48 to 1.12 Pg C yr−1. The largest changes occur in tropical areas: a considerable decrease in the carbon source in the Amazon forest, and this decrease is mostly compensated by increases in the ocean region immediately west of the Amazon and the southeast Asian land region. Our further investigation through different treatments of the 13CO2/CO2 flux ratio used in the inversion suggests that variable spatial distributions of the 13CO2 isotopic discrimination rate simulated by the models over land and ocean have considerable impacts on the spatial distribution of the inverted CO2 flux over land and the inversion results are not sensitive to errors in the estimated disequilibria over land and ocean.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".