Dependence of Climate and Carbon Cycle Response in Net Zero Emission Pathways on the Magnitude and Duration of Positive and Negative Emission Pulses
Bibliographic record
Abstract
Abstract Understanding the climate and carbon cycle response to negative CO 2 emissions is important for developing climate mitigation strategies that aim to limit global warming to a specific threshold. In this study, using a coupled climate and carbon cycle model, a novel set of nine stylized simulations are conducted with cumulative emissions of 1,000 GtC, 2,000 GtC, and 5,000 GtC over 150, 250, and 500 years, followed by identical cumulative negative emissions so that the net cumulative emissions are zero. On millennial‐timescales, the climate system returns close to the preindustrial state, independent of the emission and removal pathways. However, the thermal and biogeochemical inertia of the ocean play an important role in determining the climate and carbon cycle response during the emission and removal phases. When zero net emissions are reached, surface air temperature is larger by 0–1°C than the preindustrial state, and the atmospheric CO 2 concentration is less by 12–29 ppm. These changes increase with both the magnitude and duration of the emission and removal pulses. In contrast, hysteresis in the relationship between global mean surface temperature and cumulative carbon emissions increases with the magnitude but decreases with the duration of emission and removal pulses. Our study highlights the role of ocean inertia in the asymmetry in climate response to emissions and removals and indicates that an earlier emission reduction implying emission/removal pathways with smaller magnitudes and shorter durations for the positive and negative emission pulses would avoid larger climate and carbon cycle impacts on centennial‐timescales.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".