Stratospheric temperature trends: our evolving understanding
Bibliographic record
Abstract
Abstract We review the scientific literature since the 1960s to examine the evolution of modeling tools and observations that have advanced understanding of global stratospheric temperature changes. Observations show overall cooling of the stratosphere during the period for which they are available (since the late 1950s and late 1970s from radiosondes and satellites, respectively), interrupted by episodes of warming associated with volcanic eruptions, and superimposed on variations associated with the solar cycle. There has been little global mean temperature change since about 1995. The temporal and vertical structure of these variations are reasonably well explained by models that include changes in greenhouse gases, ozone, volcanic aerosols, and solar output, although there are significant uncertainties in the temperature observations and regarding the nature and influence of past changes in stratospheric water vapor. As a companion to a recent WIREs review of tropospheric temperature trends, this article identifies areas of commonality and contrast between the tropospheric and stratospheric trend literature. For example, the increased attention over time to radiosonde and satellite data quality has contributed to better characterization of uncertainty in observed trends both in the troposphere and in the lower stratosphere, and has highlighted the relative deficiency of attention to observations in the middle and upper stratosphere. In contrast to the relatively unchanging expectations of surface and tropospheric warming primarily induced by greenhouse gas increases, stratospheric temperature change expectations have arisen from experiments with a wider variety of model types, showing more complex trend patterns associated with a greater diversity of forcing agents. WIREs Clim Change 2011 2 592–616 DOI: 10.1002/wcc.125 This article is categorized under: Paleoclimates and Current Trends > Modern Climate Change
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".