Understanding the Atmospheric Temperature Adjustment to CO2 Perturbation at the Process Level
Bibliographic record
Abstract
Abstract Climate model comparisons show that there is considerable uncertainty in the atmospheric temperature response to CO 2 perturbation. The uncertainty results from both the rapid adjustment that occurs before SST changes and the slow feedbacks that occur after SST changes. The analysis in this paper focuses on the rapid adjustment. We use a novel method to decompose the temperature change in AMIP-type climate simulation in order to understand the adjustment at the process level. We isolate the effects of different processes, including radiation, convection, and large-scale circulation in the temperature adjustment, through a set of numerical experiments using a hierarchy of climate models. We find that radiative adjustment triggers and largely controls the zonal mean atmospheric temperature response pattern. This pattern is characterized by stratospheric cooling, lower-tropospheric warming, and a warming center near the tropical tropopause. In contrast to conventional views, the warming center near the tropopause is found to be critically dependent on the shortwave absorption of CO 2 . The dynamical processes largely counteract the effect of the radiative process that increases the vertical temperature gradient in the free troposphere. The effect of local convection is to move atmospheric energy vertically, which cools the lower troposphere and warms the upper troposphere. The adjustment due to large-scale circulation further redistributes energy along the isentropic surfaces across the latitudes, which cools the low-latitude lower troposphere and warms the midlatitude upper troposphere and stratosphere. Our results highlight the importance of the radiative adjustment in the overall adjustment and provide a potential method to understand the spread in the models.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".