Articles | Volume 11, issue 10
https://doi.org/10.5194/gmd-11-4155-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-4155-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
16 Oct 2018
Model evaluation paper |
| 16 Oct 2018
| 16 Oct 2018
Evaluating simplified chemical mechanisms within present-day simulations of the Community Earth System Model version 1.2 with CAM4 (CESM1.2 CAM-chem): MOZART-4 vs. Reduced Hydrocarbon vs. Super-Fast chemistry
Benjamin Brown-Steiner
CORRESPONDING AUTHOR
now at: Atmospheric and Environmental Research, 131 Hartwell Avenue, Lexington, MA 02421-3126, USA
Center for Global Change Science, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139, USA
Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139, USA
Noelle E. Selin
Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139, USA
Institute for Data, Systems, and Society, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139, USA
Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139, USA
Ronald Prinn
Center for Global Change Science, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139, USA
Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139, USA
Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139, USA
Simone Tilmes
Atmospheric Chemistry Observations and Modeling Lab, National Center for Atmospheric Research, 3450 Mitchell Lane, Boulder, CO 80301, USA
Louisa Emmons
Atmospheric Chemistry Observations and Modeling Lab, National Center for Atmospheric Research, 3450 Mitchell Lane, Boulder, CO 80301, USA
Jean-François Lamarque
Atmospheric Chemistry Observations and Modeling Lab, National Center for Atmospheric Research, 3450 Mitchell Lane, Boulder, CO 80301, USA
Philip Cameron-Smith
Lawrence Livermore National Laboratory, 7000 East Ave, Livermore, CA 94550, USA
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Cited
12 citations as recorded by crossref.
- Graph characterization of higher-order structure in atmospheric chemical reaction mechanisms S. Silva & M. Halappanavar 10.1017/eds.2024.30
- Development and evaluation of a new compact mechanism for aromatic oxidation in atmospheric models K. Bates et al. 10.5194/acp-21-18351-2021
- Improvement of the ozone forecast over Beijing through combining the chemical transport model with multiple machine learning methods J. Xie et al. 10.1016/j.apr.2024.102184
- A machine-learning-guided adaptive algorithm to reduce the computational cost of integrating kinetics in global atmospheric chemistry models: application to GEOS-Chem versions 12.0.0 and 12.9.1 L. Shen et al. 10.5194/gmd-15-1677-2022
- Progress in modeling dynamic systems for sustainable development N. Selin et al. 10.1073/pnas.2216656120
- An Adaptive Auto‐Reduction Solver for Speeding Up Integration of Chemical Kinetics in Atmospheric Chemistry Models: Implementation and Evaluation in the Kinetic Pre‐Processor (KPP) Version 3.0.0 H. Lin et al. 10.1029/2022MS003293
- A Graph Theoretical Intercomparison of Atmospheric Chemical Mechanisms S. Silva et al. 10.1029/2020GL090481
- An adaptive method for speeding up the numerical integration of chemical mechanisms in atmospheric chemistry models: application to GEOS-Chem version 12.0.0 L. Shen et al. 10.5194/gmd-13-2475-2020
- Dimensionality-reduction techniques for complex mass spectrometric datasets: application to laboratory atmospheric organic oxidation experiments A. Koss et al. 10.5194/acp-20-1021-2020
- An Online‐Learned Neural Network Chemical Solver for Stable Long‐Term Global Simulations of Atmospheric Chemistry M. Kelp et al. 10.1029/2021MS002926
- Diagnosing uncertainties in global biomass burning emission inventories and their impact on modeled air pollutants W. Hua et al. 10.5194/acp-24-6787-2024
- Evaluating simplified chemical mechanisms within present-day simulations of the Community Earth System Model version 1.2 with CAM4 (CESM1.2 CAM-chem): MOZART-4 vs. Reduced Hydrocarbon vs. Super-Fast chemistry B. Brown-Steiner et al. 10.5194/gmd-11-4155-2018
11 citations as recorded by crossref.
- Graph characterization of higher-order structure in atmospheric chemical reaction mechanisms S. Silva & M. Halappanavar 10.1017/eds.2024.30
- Development and evaluation of a new compact mechanism for aromatic oxidation in atmospheric models K. Bates et al. 10.5194/acp-21-18351-2021
- Improvement of the ozone forecast over Beijing through combining the chemical transport model with multiple machine learning methods J. Xie et al. 10.1016/j.apr.2024.102184
- A machine-learning-guided adaptive algorithm to reduce the computational cost of integrating kinetics in global atmospheric chemistry models: application to GEOS-Chem versions 12.0.0 and 12.9.1 L. Shen et al. 10.5194/gmd-15-1677-2022
- Progress in modeling dynamic systems for sustainable development N. Selin et al. 10.1073/pnas.2216656120
- An Adaptive Auto‐Reduction Solver for Speeding Up Integration of Chemical Kinetics in Atmospheric Chemistry Models: Implementation and Evaluation in the Kinetic Pre‐Processor (KPP) Version 3.0.0 H. Lin et al. 10.1029/2022MS003293
- A Graph Theoretical Intercomparison of Atmospheric Chemical Mechanisms S. Silva et al. 10.1029/2020GL090481
- An adaptive method for speeding up the numerical integration of chemical mechanisms in atmospheric chemistry models: application to GEOS-Chem version 12.0.0 L. Shen et al. 10.5194/gmd-13-2475-2020
- Dimensionality-reduction techniques for complex mass spectrometric datasets: application to laboratory atmospheric organic oxidation experiments A. Koss et al. 10.5194/acp-20-1021-2020
- An Online‐Learned Neural Network Chemical Solver for Stable Long‐Term Global Simulations of Atmospheric Chemistry M. Kelp et al. 10.1029/2021MS002926
- Diagnosing uncertainties in global biomass burning emission inventories and their impact on modeled air pollutants W. Hua et al. 10.5194/acp-24-6787-2024
Discussed (final revised paper)
Latest update: 07 Jun 2025
Short summary
We conduct three simulations of atmospheric chemistry using chemical mechanisms of different levels of complexity and compare their results to observations. We explore situations in which the simplified mechanisms match the output of the most complex mechanism, as well as when they diverge. We investigate how concurrent utilization of chemical mechanisms of different complexities can further our atmospheric-chemistry understanding at various scales and give some strategies for future research.
We conduct three simulations of atmospheric chemistry using chemical mechanisms of different...
