Decrease of emissions required to stabilize atmospheric CO<sub>2</sub> due to positive carbon cycle–climate feedbacks
Bibliographic record
Abstract
Positive feedbacks between the carbon cycle and climate have the potential to accelerate the accumulation of atmospheric CO2 over the next century. Here, I address the question of how climate‐induced carbon cycle changes could affect the emissions required to stabilize atmospheric CO2 at 1000 ppmv. From a coupled climate‐carbon cycle simulation, I calculated emissions that are consistent with a prescribed CO2 stabilization pathway. By comparing a coupled simulation with a second constant‐climate simulation, I show that carbon cycle‐climate feedbacks lead to large decreases in allowable emissions. Cumulative emissions are reduced by 94, 230 and 754 GtC between 2005 and years 2050, 2100 and 2350 respectively. Annual differences are largest at 2080, where emissions are reduced by 2.8 GtC/year. Further, while terrestrial feedbacks dominate for the next two centuries, the effect of ocean feedbacks on allowable emissions begin to exceed that of terrestrial feedbacks around the year 2250.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".