Articles | Volume 15, issue 16
https://doi.org/10.5194/gmd-15-6341-2022
https://doi.org/10.5194/gmd-15-6341-2022
Model description paper
 | 
17 Aug 2022
Model description paper |  | 17 Aug 2022

A machine learning methodology for the generation of a parameterization of the hydroxyl radical

Daniel C. Anderson, Melanie B. Follette-Cook, Sarah A. Strode, Julie M. Nicely, Junhua Liu, Peter D. Ivatt, and Bryan N. Duncan

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Cited articles

Anderson, D. C., Duncan, B. N., Fiore, A. M., Baublitz, C. B., Follette-Cook, M. B., Nicely, J. M., and Wolfe, G. M.: Spatial and temporal variability in the hydroxyl (OH) radical: understanding the role of large-scale climate features and their influence on OH through its dynamical and photochemical drivers, Atmos. Chem. Phys., 21, 6481–6508, https://doi.org/10.5194/acp-21-6481-2021, 2021. 
Anderson, D. C., Follette-Cook, M. B., Strode, S. A., Nicely, J. M., Liu, J., Ivatt, P. D., and Duncan, B. N.: Code for the development of a parameterization of OH for CCMs, Zenodo [code], https://doi.org/10.5281/zenodo.6046037, 2022a. 
Anderson, D. C., Follette-Cook, M. B., Strode, S. A., Nicely, J .M., Liu, J., Ivatt, P. D., and Duncan, B. N.: Sample ECCOH OH Parameterization (1.0), Zenodo [code and data set], https://doi.org/10.5281/zenodo.6604130, 2022b. 
CEDA Archive: CCMI-1 Data Archive, CEDA Archive [data set], http://data.ceda.ac.uk/badc/wcrp-ccmi/data/CCMI-1/output, last access: 4 Aug. 2022. 
Chen, T. and Guestrin, C.: XGBoost: A Scalable Tree Boosting System, KDD '16: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA, 13–17 August 2016, 785–794, https://doi.org/10.1145/2939672.2939785, 2016. 
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Short summary
The hydroxyl radical (OH) is the most important chemical in the atmosphere for removing certain pollutants, including methane, the second-most-important greenhouse gas. We present a methodology to create an easily modifiable parameterization that can calculate OH concentrations in a computationally efficient way. The parameterization, which predicts OH within 5 %, can be integrated into larger climate models to allow for calculation of the interactions between OH, methane, and other chemicals.