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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-279
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-279
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: development and technical paper 29 Oct 2019

Submitted as: development and technical paper | 29 Oct 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

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 Shen1, Daniel J. Jacob1, Mauricio Santillana2,3, Xuan Wang1, and Wei Chen4 Lu Shen et al.
  • 1John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
  • 2Computational Health Informatics Program, Boston Children’s Hospital, Boston, MA, USA
  • 3Department of Pediatrics, Harvard Medical School, Boston, MA, USA
  • 4Department of Physics, Harvard University, Cambridge, MA, USA

Abstract. The major computational bottleneck in atmospheric chemistry models is the numerical integration of the stiff coupled system of kinetic equations describing the chemical evolution of the system as defined by the model chemical mechanism (typically over 100 coupled species). We present an adaptive method to greatly reduce the computational cost of that numerical integration in global 3-D models while maintaining high accuracy. Most of the atmosphere does not in fact require solving for the full chemical complexity of the mechanism, so considerable simplification is possible if one can recognize the dynamic continuum of chemical complexity required across the atmospheric domain. We do this by constructing a limited set of reduced chemical mechanisms (chemical regimes) to cover the range of atmospheric conditions, and then pick locally and on the fly which mechanism to use for a given gridbox and time step on the basis of computed production and loss rates for individual species. Application to the GEOS-Chem global 3-D model for oxidant-aerosol chemistry in the troposphere and stratosphere (full mechanism of 228 species) is presented. We show that 20 chemical regimes can largely encompass the range of conditions encountered in the model. Results from a 2-year GEOS-Chem simulation shows that our method can reduce the computational cost of chemical integration by 30–40 % while maintaining accuracy better than 1 % and with no error growth. Our method retains the full complexity of the original chemical mechanism where it is needed, provides the same model output diagnostics (species production and loss rates, reaction rates) as the full mechanism, and can accommodate changes in the chemical mechanism or in model resolution without having to reconstruct the chemical regimes.

Lu Shen et al.
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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 L. Shen, D. J. Jacob, M. Santillana, X. Wang, and W. Chen https://doi.org/10.7910/DVN/IM5TM4

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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 L. Shen, D. J. Jacob, M. Santillana, X. Wang, and W. Chen https://doi.org/10.7910/DVN/IM5TM4

Lu Shen et al.
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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 accuracy better than 1 %. It retains the complexity of the full mechanism where it is needed and preserves full diagnostic information.
Chemical mechanisms in air quality models tend to get more complicated with time, reflecting...
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