Analysis of a newly homogenised ozonesonde dataset from Lauder, New Zealand
Bibliographic record
Abstract
Abstract. This study presents an updated and homogenised ozone time series covering 34 years (1987–2020) of ozonesonde measurements at Lauder, New Zealand, and derived vertically resolved ozone trends. Over the period of 1987–1999, the ozone trends in the homogenised ozone data are predominantly negative from the surface to ∼30 km, ranging from −2 to −10 % decade−1, maximising at around 12–13 km. These negative trends are statistically significant at 95 % confidence level below 5 km and above 17 km. For the post-2000 period, ozone at Lauder shows negative trends in the stratosphere (but the trends are only statistically significant above 17 km), maximising just below 20 km (∼ −5 % decade−1), despite stratospheric chlorine and bromine from ozone-depleting substances (ODSs) both declining in this period. In the troposphere, the ozone trends change from negative for 1987–1999 to positive in the post-2000 period. The post-2000 ozone trends from the ozonesonde measurements compare well with those from a low-vertical resolution Fourier-transform infrared spectroscopy (FTIR) ozone time series. A multiple-linear regression analysis indicates that anthropogenic forcing plays a significant role in driving the significant negative trend in the stratospheric ozone at Lauder, in which the effect of greenhouse gas (GHG)-driven dynamical and chemical changes is reflected in the significant positive trends in tropopause height and tropospheric temperature, and significant negative trends of stratospheric temperature observed at Lauder. The interannual variation in lower stratospheric ozone is largely explained by the variation in tropopause height at Lauder, which is highly anti-correlated with stratospheric temperature and correlated with tropospheric temperature. Furthermore, the impact of ODSs and GHGs on ozone over Lauder is assessed in a chemistry-climate model using a series of single forcing simulations. The model simulations show that the predominantly negative modelled trend in ozone for the 1987–1999 period is driven not only by ODSs, but also by increases in GHGs with large but opposing impacts from methane (positive) and CO2 (negative), respectively. Over the 2000–2020 period, although the model underestimates the observed negative ozone trend in the lower stratosphere but clearly shows that CO2-driven dynamical changes have had an increasingly important role in driving ozone trends in this region.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".