An examination of convective moistening of the lower stratosphere using satellite data
Bibliographic record
Abstract
Abstract In this paper, we use satellite data to test the hypothesis that deep convection moistens the lower stratosphere. Water vapor measurements from Earth Observing System‐Microwave Limb Sounder and Atmospheric Chemistry Experiment‐Fourier Transform Spectrometer over North America are binned according to the International Satellite Cloud Climatology Project deep convection indices. The results show that in the North American region (50–112°W, 10–50°N) the convection‐impacted samples are significantly moister than the nonimpact samples in the lowermost stratospheric layer right above the tropopause, and a drier tendency is also noticed right above this moistened layer. Trajectory modeling is used to aid the identification of deep convection‐impacted water vapor samples. However, we find that a substantial fraction of high‐concentration (>8 ppmv) samples at 100 hPa cannot be attributed to nearby deep convections.
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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".