Global variations of HDO and HDO/H<sub>2</sub>O ratios in the upper troposphere and lower stratosphere derived from ACE‐FTS satellite measurements
Bibliographic record
Abstract
High‐quality satellite observations of water and deuterated water in the upper troposphere and lower stratosphere (UTLS) from the Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE‐FTS) are used to map global climatological behavior. Spatial and temporal variability in these data suggest that convection plays a significant role in setting water vapor isotopic composition in these regions. In many instances, enhancements in HDO/H2O (i.e., δD) are closely tied to patterns of climatological deep convection and uncorrelated with water vapor, although convection appears to have different isotopic effects in different locations. The ACE‐FTS data reveal seasonal variations in the tropics and allow mapping of climatological regional structure. These data reveal strong regional isotopic enhancement associated with the North American summer monsoon but not the Asian monsoon or the western Pacific warm pool. We suggest that the isotopic effects of deep convection near the tropopause are moderated by the ambient relative humidity, which controls the amount of convective ice that evaporates. Local convective signals can in turn affect global behavior: the North America monsoon influence introduces a Northern Hemisphere–Southern Hemisphere asymmetry in water isotopic composition in the lower stratosphere that extends into the tropics and influences the apparent seasonal cycle in averaged tropical UTLS data. Seasonal variation in tropical lower stratospheric water isotopic composition extends up to ∼20 km in ACE retrievals, but in contrast to previous reports, there is no clear evidence of propagation beyond the lowermost stratosphere. The reliability of these observations is supported by the broad consistency of ACE‐FTS averaged tropical profiles with previous remote and in situ δD measurements.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".