Estimating the 27‐day and 11‐year solar cycle variations in tropical upper stratospheric ozone
Bibliographic record
Abstract
Spectral analysis of the solar backscatter ultraviolet (SBUV) satellite instrument ozone and solar flux time series was used to estimate the ozone response in the tropical upper stratosphere to the solar flux harmonics of the 27‐day Sun rotation cycle with periods of 9, 13.5, and 27 days. Solar UV flux at 205 nm, Mg II index, composite solar Lyman alpha, and 10.7 cm solar flux data sets were tested as proxies for the solar signal. The Mg II index has the highest coherency with tropical ozone in the upper stratosphere among all solar proxies. The analysis shows that during the periods of high solar activity, about half of the ozone variance for periods of 13.5 and 27 days near 40 km can be attributed to the fluctuations of the Mg II index. During the periods of low solar activity, the 27‐day signal is below the 90% statistical significance level, while the 13.5‐day signal is usually significant. Also, a 9‐day period can be seen in ozone data during the time of low solar activity. The ozone response to solar variations with a 27‐day period was used to estimate the 11‐year solar cycle amplitude in tropical ozone. Biases in individual SBUV instrument data were included as a part of the statistical model. In that case, the estimate from the 27‐day period minimum to maximum range of the 11‐year cycle is about 2%. This agrees with the data in layers 8–9 (38–43 km) derived from the SBUV data set. Below these layers, the amplitude of the 11‐year cycle is only about one third of the one estimated from the 27‐day cycle. Above these layers, the amplitude of the 11‐year cycle is larger than that estimated from the 27‐day cycle, but it is primarily due to the high amplitude of the 11‐year cycle in the Nimbus 7 SBUV data.
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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 | 0.000 | 0.000 |
| 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".