Ozone correlation lengths and measurement uncertainties from analysis of historical ozonesonde data in North America and Europe
Bibliographic record
Abstract
A spatial and temporal correlation analysis is performed on the WOUDC (World Ozone and Ultraviolet Radiation Data Centre) ozonesonde data from 13 midlatitude stations in North America and Europe. The data records span more than 40 years at some stations, and a total of more than 27,000 ozonesonde profiles are utilized. The spatial correlation coefficients between pairs of stations decrease with increasing station separation distance, following a power exponential correlation function. The horizontal distance for the correlation coefficient to decrease by a factor of e is about 1000–2000 km in the stratosphere with a peak at around 22‐km altitude, and is about 500–1000 km in the troposphere. The autocorrelation coefficient decreases rapidly with time lag, and the timescale of the autocorrelation varies between about 1.5 and 3.5 days in the troposphere but is generally longer in the stratosphere at 2–6 days. The extrapolation of the correlation functions to zero station distance or zero time lag yields estimates of the intrinsic uncertainty of ozonesonde measurements. The uncertainty is found to be less than 7% for 20–30‐km altitudes in the stratosphere, about 15% in the troposphere, and to have larger values near the tropopause and at the surface. The results are broadly consistent with those from the recent JOSIE and BESOS experiments, and other intercomparisons, with the additional measurement uncertainty probably reflecting changes in ozonesonde type, model, manufacture, and preparation procedure during the period of the record.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 teacher head, 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".