Articles | Volume 23, issue 20
https://doi.org/10.5194/acp-23-13029-2023
https://doi.org/10.5194/acp-23-13029-2023
Research article
 | 
16 Oct 2023
Research article |  | 16 Oct 2023

Quantifying stratospheric ozone trends over 1984–2020: a comparison of ordinary and regularized multivariate regression models

Yajuan Li, Sandip S. Dhomse, Martyn P. Chipperfield, Wuhu Feng, Jianchun Bian, Yuan Xia, and Dong Guo

Viewed

Total article views: 4,721 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
3,207 1,248 266 4,721 526 324 390
  • HTML: 3,207
  • PDF: 1,248
  • XML: 266
  • Total: 4,721
  • Supplement: 526
  • BibTeX: 324
  • EndNote: 390
Views and downloads (calculated since 14 Apr 2023)
Cumulative views and downloads (calculated since 14 Apr 2023)

Viewed (geographical distribution)

Total article views: 4,721 (including HTML, PDF, and XML) Thereof 4,677 with geography defined and 44 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 16 Sep 2026
Download
Short summary
For the first time a regularized multivariate regression model is used to estimate stratospheric ozone trends. Regularized regression avoids the over-fitting issue due to correlation among explanatory variables. We demonstrate that there are considerable differences in satellite-based and chemical-model-based ozone trends, highlighting large uncertainties in our understanding about ozone variability. We argue that caution is needed when interpreting results with different methods and datasets.
Share
Altmetrics
Final-revised paper
Preprint