A CMIP6 Analysis of Past and Future Arctic Winter Stratospheric Temperature Trends
Bibliographic record
Abstract
Abstract Reanalysis data reveal a weak warming trend in the midwinter Arctic stratosphere, contrary to the cooling expectation based on the greenhouse gas effect. This trend is also influenced by the occurrence of sudden stratospheric warmings (SSWs). Using Phase 6 of the Coupled Model Intercomparison Project (CMIP6) we investigate temperature trends over a similar timescale as ERA5 and find that CMIP6 models can replicate the positive midwinter temperature trend in the mid‐lower stratosphere. However, when considering the multi‐model mean, this positive temperature trend is much weaker than ERA5. Extrapolating to the future, we find that the SSW‐driven positive temperature trend will likely not continue in the future based on the SSP2‐4.5 and SSP5‐8.5 climate scenarios. Instead, the models project there will be widespread cooling throughout the Arctic winter stratosphere regardless of the occurrence of SSWs. Using a subsample of CMIP6 models which replicate the seasonality of the Arctic winter stratosphere most similarly to that of ERA5, we also find that the zonal wind strength during SSWs correlates the most with the temperature trends found there. However, trends in the zonal wind strength alone cannot account for the observed temperature trends among the CMIP6 models.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".