Reductions in atmospheric levels of non-CO2 greenhouse gases explain about a quarter of the 1998-2012 warming slowdown
Bibliographic record
Abstract
The observed global mean surface temperature increase from 1998 to 2012 was slower than that since 1951. The relative contributions of all relevant factors including climate forcers, however, have not been comprehensively analyzed. Using a reduced-complexity climate model and an observationally constrained statistical model, here we find that La Niña cooling and a descending solar cycle contributed approximately 50% and 26% of the total warming slowdown during 1998-2012 compared to 1951-2012. Furthermore, reduced ozone-depleting substances and methane accounted for roughly a quarter of the total warming slowdown, which can be explained by changes in atmospheric concentrations. We identify that non-CO2 greenhouse gases played an important role in slowing global warming during 1998-2012. Together, La Niña cooling and a descending solar cycle can explain about three quarters of the warming slowdown between 1998 and 2012, whereas changes in the atmospheric levels of methane and ozone depleting substances explain the remaining quarter, according to analyses with a reduced-complexity climate model.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".