Shift in cold-point tropopause trends derived from radiosonde, satellite and reanalysis data
Bibliographic record
Abstract
The tropical tropopause layer is the transition region between the well-mixed convective troposphere and the radiatively controlled stratosphere and plays a crucial role in air mass transport between these layers. In this paper, we present updated trends of tropopause and lower stratospheric temperature from radiosondes, GNSS-RO data, and the reanalyses ERA5, JRA-3Q and MERRA-2. Given its importance in determining the concentration of water vapour entering the stratosphere, we focus on temperature trends at the cold-point tropopause (CPT), which we determined from radiosonde observations after correcting for time-varying biases. Radiosonde and GNSS-RO data show a significant shift from strong cold-point cooling for 1980–2001 to warming for 2002–2023. Reanalysis datasets reproduce the robust change in the tropical tropopause temperature trends and furthermore show opposite trends in tropical upwelling for 1980–2001 compared to 2002–2023, consistent with the cold-point and lower stratosphere temperature changes. The shift in cold-point temperature trends around 2000 suggests a regime shift in the dominant mechanism controlling CPT temperatures, from ozone-depleting substance-induced dynamical changes before 2000 to greenhouse-gas-induced radiative warming with some dynamical contributions after 2000. While the role of dynamical changes after 2000 is not completely clear, this regime shift suggests that in the absence of strong dynamically induced cooling trends, radiative warming could dominate the cold-point temperature trends and thus stratospheric water vapour entry values.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".