School of Electronic Engineering, Nanjing Xiaozhuang University, Nanjing, China
Dong Guo
Key Laboratory of Meteorological Disaster, Ministry of Education–Joint International Research Laboratory of Climate and Environment Change–Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing, China
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1,752
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521
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Cumulative views and downloads
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Viewed (geographical distribution)
Total article views: 2,909 (including HTML, PDF, and XML)
Thereof 2,909 with geography defined
and 0 with unknown origin.
Total article views: 2,182 (including HTML, PDF, and XML)
Thereof 2,182 with geography defined
and 0 with unknown origin.
Total article views: 727 (including HTML, PDF, and XML)
Thereof 727 with geography defined
and 0 with unknown origin.
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.
For the first time a regularized multivariate regression model is used to estimate stratospheric...
