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ACP | Articles | Volume 18, issue 21
Atmos. Chem. Phys., 18, 16155-16172, 2018
https://doi.org/10.5194/acp-18-16155-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue: Chemistry–Climate Modelling Initiative (CCMI) (ACP/AMT/ESSD/GMD...

Atmos. Chem. Phys., 18, 16155-16172, 2018
https://doi.org/10.5194/acp-18-16155-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 13 Nov 2018

Research article | 13 Nov 2018

Tropospheric ozone in CCMI models and Gaussian process emulation to understand biases in the SOCOLv3 chemistry–climate model

Laura E. Revell et al.
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BADC data access IGAC/SPARC Chemistry-Climate Model Initiative http://blogs.reading.ac.uk/ccmi/badc-data-access

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Short summary
Global models such as those participating in the Chemistry-Climate Model Initiative (CCMI) consistently simulate biases in tropospheric ozone compared with observations. We performed an advanced statistical analysis with one of the CCMI models to understand the cause of the bias. We found that emissions of ozone precursor gases are the dominant driver of the bias, implying either that the emissions are too large, or that the way in which the model handles emissions needs to be improved.
Global models such as those participating in the Chemistry-Climate Model Initiative (CCMI)...
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