Quantifying the sources of increasing stratospheric water vapour concentrations
Bibliographic record
Abstract
According to satellite measurements from multiple instruments, water vapour (H 2 O) concentrations, in most regions of the stratosphere, have been increasing at a statistically significant rate of ∼1 %–5 % per decade since the early 2000s. Previous studies have estimated stratospheric H 2 O trends, but none have simultaneously quantified the contributions from all main sources (temperature variations in the tropical tropopause region, changes in the Brewer–Dobson circulation, and changes in methane (CH 4 ) concentrations and oxidation) at all latitudes. Atmospheric Chemistry Experiment–Fourier Transform Spectrometer (ACE-FTS) measurements are used to estimate altitude-/latitude-dependent stratospheric H 2 O trends from 2004–2021 due to these sources. Results indicate that rising temperatures in the tropical tropopause region play a significant role in the increases, accounting for ∼1 %–4 % per decade in the tropical lower mid-stratosphere and in the mid-latitudes below ∼20 km. By regressing to ACE-FTS N 2 O concentrations, it is found that, in the lower mid-stratosphere, general circulation changes have led to both significant H 2 O increases and significant H 2 O decreases on the order of 1 %–2 % per decade depending on the altitude/latitude region. Making use of measured and modelled CH 4 concentrations, the increase in H 2 O due to CH 4 oxidation is calculated to be ∼1 %–2 % per decade above ∼30 km in the Northern Hemisphere and throughout the stratosphere in the Southern Hemisphere. After accounting for these sources, there are still regions of the mid-latitude lower mid-stratosphere that exhibit significant residual H 2 O trends increasing at 1 %–2 % per decade. Results indicate that these unaccounted-for increases could potentially be explained by increases in upper-tropospheric molecular hydrogen.
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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 | 0.001 | 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) | 0.000 | 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".