An adaptive method for speeding up the numerical integration of chemical mechanisms in atmospheric chemistry models: application to GEOS-Chem version 12.0.0

Shen, Lu; Jacob, Daniel J.; Santillana, Mauricio; Wang, Xuan; Chen, Wei

doi:https://doi.org/10.5194/gmd-13-2475-2020

Articles | Volume 13, issue 5

https://doi.org/10.5194/gmd-13-2475-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-13-2475-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 13, issue 5

Development and technical paper

|

28 May 2020

Development and technical paper |

| 28 May 2020

An adaptive method for speeding up the numerical integration of chemical mechanisms in atmospheric chemistry models: application to GEOS-Chem version 12.0.0

Lu Shen, Daniel J. Jacob, Mauricio Santillana, Xuan Wang, and Wei Chen

Supplement

https://doi.org/10.5194/gmd-13-2475-2020-supplement

Data sets

Replication Data for: An adaptive method for speeding up the numerical integration of chemical mechanisms in atmospheric chemistry models: application to GEOS-Chem version 12.0.0 Lu Shen, Daniel J. Jacob, Mauricio Santillana, Xuan Wang, Wei Chen https://doi.org/10.7910/DVN/IM5TM4

Model code and software

GEOS-Chem source code Harvard atmospheric chemistry modeling group https://doi.org/10.5281/zenodo.1343547

Short summary

Chemical mechanisms in air quality models tend to get more complicated with time, reflecting both increasing knowledge and the need for greater scope. This objectively improves the models but increases the computational burden. In this work, we present an approach that can reduce the computational cost of chemical integration by 30–40 % while maintaining an accuracy better than 1 %. It retains the complexity of the full mechanism where it is needed and preserves full diagnostic information.