Correcting ozone biases in a global chemistry–climate model: implications for future ozone
<p>Weaknesses in process representation in chemistry–climate models lead to biases in simulating surface ozone and to uncertainty in projections of future ozone change. We here develop a deep learning model to demonstrate the feasibility of ozone bias correction in a global chemistry–climate m...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2022-09-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://acp.copernicus.org/articles/22/12543/2022/acp-22-12543-2022.pdf |