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: 1,451 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,085 318 48 1,451 89 22 25
  • HTML: 1,085
  • PDF: 318
  • XML: 48
  • Total: 1,451
  • Supplement: 89
  • BibTeX: 22
  • EndNote: 25
Views and downloads (calculated since 14 Apr 2023)
Cumulative views and downloads (calculated since 14 Apr 2023)

Viewed (geographical distribution)

Total article views: 1,451 (including HTML, PDF, and XML) Thereof 1,465 with geography defined and -14 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 08 May 2024
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
Altmetrics
Final-revised paper
Preprint