Global Atmospheric OCS Trend Analysis from 22 NDACC Stations
Bibliographic record
Abstract
Carbonyl sulfide (OCS) is a non-hygroscopic trace species in the free troposphere and the primary sulfur reservoir maintained by direct oceanic, geologic, biogenic and anthropogenic emissions and the oxidation of other sulfur-containing source species. It’s the largest source of sulfur transported to the stratosphere during volcanically quiescent periods. Data from 22 ground-based globally dispersed stations are used to derive trends in total and partial column OCS. Middle infrared spectral data are recorded by solar-viewing Fourier transform interferometers that are operated as part of the Network for the Detection of Atmospheric Composition Change between 1986 and 2020. Vertical information in the retrieved profiles provides analysis of discreet altitudinal regions. Trends are found to have well-defined inflection points. In two linear trend time periods ~2002 - 2008 and ~2008 - 2016, tropospheric trends range from ~0.0 to (1.55 ± 0.30 %/y) in contrast to the prior period where all tropospheric trends are negative. Regression analyses show strongest correlation in the free troposphere with anthropogenic emissions. Stratospheric trends in the period ~2008 - 2016 are positive up to (1.93 ± 0.26 %/y) except notably low latitude stations that have negative stratospheric trends. Since ~2016, all stations show a free tropospheric decrease to 2020. Stratospheric OCS is regressed with simultaneously measured N$_2$O to derive a trend accounting for dynamical variability. Stratospheric lifetimes are derived and range from (54.1 ± 9.7)y in the sub-tropics to (103.4 ± 18.3)y in Antarctica. These unique long-term measurements provide new and critical constraints on the global OCS budget.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| 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) | 0.002 | 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".