A normalised framework for the Zero Emissions Commitment
Bibliographic record
Abstract
Abstract. The Zero Emissions Commitment (ZEC) measures the transient climate response after carbon emissions cease, defined by whether there is a continued rise or decrease in global surface temperature. A normalised framework for the ZEC connects the surface temperature response post emissions to carbon, radiative and thermal processes, involving changes in carbon inventories, radiative forcing, planetary heat uptake and climate feedback. The normalised ZEC, defined by the surface temperature change since the pre industrial divided by the temperature change at the time of net zero, is controlled by opposing-signed contributions: (i) a cooling contribution from a weakening in radiative forcing due to a decrease in atmospheric CO2 from carbon uptake by the land and ocean versus (ii) surface warming contributions from a decline in the fraction of radiative forcing used for planetary heat uptake augmented by possible amplification by climate feedbacks. From a set of 9 CMIP6 Earth system models following an idealised atmospheric CO2 scenario, inter-model differences in the post-emission climate response are primarily determined by differences in the ocean heat uptake and the land and ocean uptake of carbon. These inferences as to the controls of the ZEC broadly carry over for diagnostics of a large ensemble, observationally-constrained efficient Earth system model using two different emission scenarios to reach net zero. The large ensembles reveal a partial compensation between the changes in landborne and oceanborne fractions, as well as revealing ensembles with greater range in amplification of warming by climate feedbacks.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".