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

Data sets

The Stratospheric Water and Ozone Satellite Homogenized (SWOOSH) database: a long-term database for climate studies ( S. M. Davis, K. H. Rosenlof, B. Hassler, D. F. Hurst, W. G. Read, H. Vömel, H. Selkirk, M. Fujiwara, and R. Damadeo

ML-TOMCAT V1.0: Machine-Learning-Based Satellite-Corrected Global Stratospheric Ozone Profile Dataset S. S. Dhomse, M. P. Chipperfield, W. Feng, C. Arosio, M. Weber, and A. Rozanov

Effects of Reanalysis Forcing Fields on Ozone Trends and Age of Air from a Chemical Transport Model Y. Li, S. Dhomse, M. Chipperfield, W. Feng, A. Chrysanthou, Y. Xia, and D. Guo

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.
Final-revised paper