Evolution of stratospheric ozone and water vapour time series studied with satellite measurements
Bibliographic record
Abstract
Abstract. The long term evolution of stratospheric ozone and water vapour has been investigated by extending satellite time series to April 2008. For ozone, we examine monthly average ozone values from various satellite data sets for nine latitude and altitude bins covering 60° S to 60° N and 20–45 km and covering the time period of 1979–2008. Data are from the Stratospheric Aerosol and Gas Experiment (SAGE I+II), the HALogen Occultation Experiment (HALOE), the Solar BackscatterUltraViolet-2 (SBUV/2) instrument, the Sub-Millimetre Radiometer (SMR), the Optical Spectrograph InfraRed Imager System (OSIRIS), and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartograpY (SCIAMACHY). Monthly ozone anomalies are calculated by utilising a linear regression model, which also models the solar, quasi-biennial oscillation (QBO), and seasonal cycle contributions. Individual instrument ozone anomalies are combined producing an all instrument average. Assuming a turning point of 1997 and that the all instrument average is represented by good instrumental long term stability, the largest statistically significant ozone declines (at two sigma) from 1979–1997 are seen at the mid-latitudes between 35 and 45 km, namely −7.2%±0.9%/decade in the Northern Hemisphere and −7.1%±0.9%/in the Southern Hemisphere. Furthermore, for the period 1997 to 2008 we find that the same locations show the largest ozone recovery (+1.4% and +0.8%/decade respectively) compared to other global regions, although the estimated trend model errors indicate that the trend estimates are not significantly different from a zero trend at the 2 sigma level. An all instrument average is also constructed from water vapour anomalies during 1991–2008, using the SAGE II, HALOE, SMR, and the Microwave Limb Sounder (Aura/MLS) measurements. We report that the decrease in water vapour values after 2001 slows down around 2004–2005 in the lower tropical stratosphere (20–25 km) and has even shown signs of increasing until present. We show that a similar correlation is also seen with the temperature measured at 100 hPa during this same period.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".