A normalised framework for the Zero Emissions Commitment
Bibliographic record
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. This delayed climate response affects the maximum cumulative carbon emission to avoid exceeding a warming target. In a set of 9 Earth system models following an idealised atmospheric CO 2 scenario with a cumulative emission of 1000 Pg C, the ZEC after 50 years ranges from −0.3 to 0.28 °C with a model mean of −0.11 °C and standard deviation of 0.19 °C. In order to understand these different climate responses, a normalised framework is introduced that quantifies the relative importance of carbon, radiative and thermal drivers of the ZEC. Inter-model differences in the ZEC are primarily due to differences in the radiative response, planetary heat uptake and the land carbon sink, with more minor contributions from differences in the ocean carbon sink and climate feedback. The ZEC response is controlled by opposing-signed contributions: (i) cooling from a decrease in radiative forcing from a carbon contribution due to increasing land and ocean carbon uptake, versus (ii) surface warming from a thermal contribution involving a decline in the fraction of radiative forcing used for planetary heat uptake plus possible amplification by climate feedback. The carbon contribution to the ZEC depends on the increase in the ocean carbon sink and whether the land carbon sink either increases or saturates in time. The thermal contribution to the ZEC depends upon how radiative forcing is partitioned between planetary heat uptake and radiative response with the radiative response either declining in time or remaining constant. These inferences as to the controls of the ZEC broadly carry over for diagnostics for a large ensemble, observationally-constrained, efficient Earth system model using two different emission scenarios to reach net zero. The large set of ensembles reveal a partial compensation between the changes in landborne and oceanborne fractions, as well as including ensembles with a 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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 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".