Muted Radiative Feedback of Stratospheric Water Vapor Found in a Multimodel Assessment
Bibliographic record
Abstract
Abstract The strength of stratospheric water vapor (SWV) radiative feedback has been debated, primarily due to the compensating radiative effects of the associated stratospheric and tropospheric temperature adjustments, which are primarily triggered by radiation process. In this study, we calculate the SWV radiative feedback in the CMIP6 model ensemble in a quadrupling CO 2 experiment. Specifically, we compare the results of two quantifications: one accounting for the radiatively driven temperature adjustment in the stratosphere only and the other in the entire atmospheric column including both the stratosphere and the troposphere. The stratosphere‐adjusted feedback is found to be , but it reduces to with the full atmosphere adjustment, indicating the radiation process alone may lead to a muted overall SWV radiative effect, due to the stratospheric cooling and tropospheric warming simultaneously driven by the SWV radiative perturbation. This suggests that the radiative forcing of SWV is subject to an intrinsic and robust limiting effect. In addition, we analyze the intermodel spreads in the temperature adjustment and its radiative effect, and find the spreads primarily arise from the differences in SWV responses projected by GCMs, rather than the differences in their climatological states.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".