Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 23, issue 20
Articles | Volume 23, issue 20
https://doi.org/10.5194/acp-23-13029-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-23-13029-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 23, issue 20
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: 1,906 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,460 384 62 1,906 111 37 50
  • HTML: 1,460
  • PDF: 384
  • XML: 62
  • Total: 1,906
  • Supplement: 111
  • BibTeX: 37
  • EndNote: 50
Views and downloads (calculated since 14 Apr 2023)
Cumulative views and downloads (calculated since 14 Apr 2023)

Viewed (geographical distribution)

Total article views: 1,906 (including HTML, PDF, and XML) Thereof 1,906 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 21 Feb 2025
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.
Read more
Share
Altmetrics
Final-revised paper
Preprint