A joint global carbon inversion system using both CO <sub>2</sub> and <sup>13</sup> CO <sub>2</sub> atmospheric concentration data
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 (62 collocated with 13CO2 sites) for the 2002–2004 period for 39 land regions and 11 ocean regions. This constraint is implemented using prior CO2 fluxes estimated with a terrestrial ecosystem model and an ocean model. These models simulate 13CO2 discrimination rates of terrestrial photosynthesis 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. This joint inversion system using both13CO2 and CO2 observations is effectively a double deconvolution system with consideration of the spatial variations of isotopic discrimination and disequilibrium. Compared to the CO2-only inversion, this 13CO2 constraint on the inversion considerably reduces the total land carbon sink from 3.40 ± 0.84 to 2.53 ± 0.93 Pg C year−1 but increases the total oceanic carbon sink from 1.48 ± 0.40 to 2.36 ± 0.49 Pg C year−1. This constraint also changes the spatial distribution of the carbon sink. The largest sink increase occurs in the Amazon, while the largest source increases are in southern Africa, and Asia, where CO2 data are sparse. Through a case study, in which the spatial distribution of the annual 13CO2 discrimination rate over land is ignored by treating it as a constant at the global average of −14. 1 ‰, the spatial distribution of the inverted CO2 flux over land was found to be significantly modified (up to 15 % for some regions). The uncertainties in our disequilibrium flux estimation are 8.0 and 12.7 Pg C year−1 ‰ for land and ocean, respectively. These uncertainties induced the unpredictability of 0.47 and 0.54 Pg C year−1 in the inverted CO2 fluxes for land and ocean, respectively. Our joint inversion system is therefore useful for improving the partitioning between ocean and land sinks and the spatial distribution of the inverted carbon flux.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".