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

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Latest update: 15 Jul 2024
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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.
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